This document describes a training module on the role of digital water level recorder (DWLR) data in groundwater resource estimation. It discusses how DWLR data, which provides high frequency water level measurements, can help improve water balance computations and recharge estimation. Specifically, it allows identifying effective rainfall events, estimating recharge parameters like the rainfall threshold and time lag to recharge, and selecting optimal time periods for water balance studies. The module aims to help hydrogeologists better understand the recharge process and more accurately assess groundwater resources using lumped water balance approaches.
Gw01 understanding conventional and dwlr assisted water level monitoringhydrologyproject0
The document describes a training module on conventional and high frequency water level monitoring. It was funded by the World Bank and Government of the Netherlands.
The module aims to help participants differentiate between conventional water level monitoring methods, which typically take place 4 times per year in dug wells, and high frequency monitoring using dedicated piezometers and digital recorders.
Conventional monitoring provides an incomplete picture of water levels and hydrographs. High frequency monitoring using piezometers and data loggers can generate near-continuous hydrographs and provide more accurate data to help understand aquifers and estimate recharge. The detailed hydrographs may inspire new analyses to enhance water resource management.
This document outlines a training module on other applications of data from Digital Water Level Recorders (DWLRs). The module aims to help participants appreciate the utility of high frequency water level monitoring data beyond groundwater resource assessment. It discusses how DWLR data can be used for conjunctive use planning, identifying over-exploited areas, scheduling pumpages, calibrating aquifer response models, and identifying cycles in water level fluctuations. The module includes session plans, presentation materials, and handouts to support a 60-minute training session on these topics.
This document provides guidance on how to carry out secondary validation of water level data. It discusses comparing hydrographs between adjacent monitoring stations to identify suspect values or timing errors. Graphical inspection of hydrographs is the primary validation method. Peaks and troughs should generally match between stations, with earlier occurrences upstream. Examples demonstrate identifying anomalies by comparing multiple station hydrographs and examining lag times between peaks. Combined hydrograph and rainfall plots can further assess timing errors and intervening rainfall effects. The overall goal is to flag potential errors for further investigation while transforming data to discharge where possible for more robust comparisons.
This document provides guidance on how to carry out primary validation of water level data. It discusses validating data from staff gauges, automatic water level recorders, and digital water level recorders by checking for errors and inconsistencies in single time series, and by comparing data between instruments. Methods include examining data graphically and against physical limits, and viewing hydrographs from adjacent stations. The goal is to flag potentially incorrect values for further validation while replacing others with corrected values based on these initial checks.
The document provides guidance on conducting pumping tests for water wells. It discusses the importance of pumping tests for determining a well's sustainable yield and performance. The document outlines the basic preparations needed for pumping tests, including gathering information on the well and acquiring basic monitoring equipment to measure water levels and pumping rates. It describes the main types of pumping tests as step tests, constant-rate tests, and recovery tests. The document is intended as a practical guide for water and habitat engineers working in remote areas to help evaluate wells and aquifers under field conditions.
DSD-INT 2015 - Coastal ecological and geomorphologic analysis and prediction ...Deltares
The document describes the Coastal Ecological and Geomorphologic Analysis and Prediction System (CEGAPS), a real-time forecasting system developed by The Water Institute of Gulf to predict water levels, salinity, temperature and other variables in coastal Louisiana. The system incorporates atmospheric forecasts, river forecasts, and 3D hydrodynamic models to generate 7-day forecasts on a gridded and time-series basis to help with adaptive management of freshwater diversions. It is currently being used and improved to better inform operational plans for diversions on the Mississippi River.
This document is a thesis submitted by Niraj Lamichhane to Youngstown State University in partial fulfillment of the requirements for a Master of Science degree in engineering. The thesis investigates the prediction of travel time and development of flood inundation maps for a flood warning system on the Grand River in Ohio, including scenarios involving ice jams. Hydraulic modeling was performed using HEC-RAS and HEC-GeoRAS to simulate floods, generate inundation maps, and assess the impacts of different elevation data resolutions and Manning's roughness values. The study found that coarser elevation data led to overprediction of travel time and inundated areas compared to LiDAR data integrated with field surveys.
The document provides guidance on sampling surface waters for water quality analysis. It discusses selecting sampling sites that are representative of the waterbody and safely accessible. It describes three types of samples - grab samples, composite samples, and integrated samples - and when each would be used. It also outlines appropriate sampling devices and containers for different analyses, as well as procedures for sample handling, preservation, and identification. The overall aim is to collect samples that accurately represent water quality without significant changes prior to analysis.
Gw01 understanding conventional and dwlr assisted water level monitoringhydrologyproject0
The document describes a training module on conventional and high frequency water level monitoring. It was funded by the World Bank and Government of the Netherlands.
The module aims to help participants differentiate between conventional water level monitoring methods, which typically take place 4 times per year in dug wells, and high frequency monitoring using dedicated piezometers and digital recorders.
Conventional monitoring provides an incomplete picture of water levels and hydrographs. High frequency monitoring using piezometers and data loggers can generate near-continuous hydrographs and provide more accurate data to help understand aquifers and estimate recharge. The detailed hydrographs may inspire new analyses to enhance water resource management.
This document outlines a training module on other applications of data from Digital Water Level Recorders (DWLRs). The module aims to help participants appreciate the utility of high frequency water level monitoring data beyond groundwater resource assessment. It discusses how DWLR data can be used for conjunctive use planning, identifying over-exploited areas, scheduling pumpages, calibrating aquifer response models, and identifying cycles in water level fluctuations. The module includes session plans, presentation materials, and handouts to support a 60-minute training session on these topics.
This document provides guidance on how to carry out secondary validation of water level data. It discusses comparing hydrographs between adjacent monitoring stations to identify suspect values or timing errors. Graphical inspection of hydrographs is the primary validation method. Peaks and troughs should generally match between stations, with earlier occurrences upstream. Examples demonstrate identifying anomalies by comparing multiple station hydrographs and examining lag times between peaks. Combined hydrograph and rainfall plots can further assess timing errors and intervening rainfall effects. The overall goal is to flag potential errors for further investigation while transforming data to discharge where possible for more robust comparisons.
This document provides guidance on how to carry out primary validation of water level data. It discusses validating data from staff gauges, automatic water level recorders, and digital water level recorders by checking for errors and inconsistencies in single time series, and by comparing data between instruments. Methods include examining data graphically and against physical limits, and viewing hydrographs from adjacent stations. The goal is to flag potentially incorrect values for further validation while replacing others with corrected values based on these initial checks.
The document provides guidance on conducting pumping tests for water wells. It discusses the importance of pumping tests for determining a well's sustainable yield and performance. The document outlines the basic preparations needed for pumping tests, including gathering information on the well and acquiring basic monitoring equipment to measure water levels and pumping rates. It describes the main types of pumping tests as step tests, constant-rate tests, and recovery tests. The document is intended as a practical guide for water and habitat engineers working in remote areas to help evaluate wells and aquifers under field conditions.
DSD-INT 2015 - Coastal ecological and geomorphologic analysis and prediction ...Deltares
The document describes the Coastal Ecological and Geomorphologic Analysis and Prediction System (CEGAPS), a real-time forecasting system developed by The Water Institute of Gulf to predict water levels, salinity, temperature and other variables in coastal Louisiana. The system incorporates atmospheric forecasts, river forecasts, and 3D hydrodynamic models to generate 7-day forecasts on a gridded and time-series basis to help with adaptive management of freshwater diversions. It is currently being used and improved to better inform operational plans for diversions on the Mississippi River.
This document is a thesis submitted by Niraj Lamichhane to Youngstown State University in partial fulfillment of the requirements for a Master of Science degree in engineering. The thesis investigates the prediction of travel time and development of flood inundation maps for a flood warning system on the Grand River in Ohio, including scenarios involving ice jams. Hydraulic modeling was performed using HEC-RAS and HEC-GeoRAS to simulate floods, generate inundation maps, and assess the impacts of different elevation data resolutions and Manning's roughness values. The study found that coarser elevation data led to overprediction of travel time and inundated areas compared to LiDAR data integrated with field surveys.
The document provides guidance on sampling surface waters for water quality analysis. It discusses selecting sampling sites that are representative of the waterbody and safely accessible. It describes three types of samples - grab samples, composite samples, and integrated samples - and when each would be used. It also outlines appropriate sampling devices and containers for different analyses, as well as procedures for sample handling, preservation, and identification. The overall aim is to collect samples that accurately represent water quality without significant changes prior to analysis.
This document summarizes a study that coupled a participatory system dynamics model with the Soil and Water Assessment Tool model to support water quality management in the Du Chêne basin in Quebec. A qualitative system dynamics model was developed with stakeholders then converted to a quantitative model in Simile software. This was coupled with a SWAT model of the basin using an interface from the PEST parameter estimation software. The coupled models were used to discuss scenarios with stakeholders and test management options, though they are not suited for operational use due to uncertainty. Future work will test other coupling methods and apply the approach to soil salinity issues in Pakistan.
This document outlines the stages of surface water data processing under the Hydrological Information System (HIS) in India. It discusses: 1) Receipt of data from field stations and storage of raw records; 2) Data entry at sub-divisional offices; 3) Validation of data through primary, secondary, and hydrological checks; 4) Completion and correction of missing or erroneous data; 5) Compilation, analysis, and reporting of validated data; 6) Transfer of data between processing levels from sub-division to division to state centers. The overall goal is to process field data in a systematic series of steps to produce quality-controlled hydrological information.
February 2022 TAGD Business Meeting
Study Results: Delineating Injection Well Buffer Zones in Brackish Aquifers
Juan Acevedo, BRACS Hydrologist, TWDB Jack Sharp, Professor Emeritus in Geology, UT- Austin
Reservoir Water Supply Planning for an Uncertain FutureDave Campbell
1) Reservoir water supply planning involves projecting future water demand over a 50-year planning period, which involves significant uncertainty. Factors like population growth, climate change, and regulatory requirements are difficult to predict that far in advance.
2) Reservoir projects take 10-20 years to plan, permit, design, and construct, so planning must start well in advance of anticipated need. However, deferring planning can significantly increase costs due to escalation rates for reservoir projects that exceed general inflation rates.
3) Reservoir configurations include on-stream reservoirs supplied by their own watershed, and pumped storage reservoirs that receive diverted flows from other streams to supplement their smaller watershed yield. Operating a reservoir for downstream flow augmentation
D5.3 Integrated water resource sustainability and vulnerability assessmentenvirogrids-blacksee
This document proposes a framework for assessing the sustainability and vulnerability of water resources in the Black Sea catchment. It reviews existing assessment frameworks like the DPSIR and vulnerability models. It also examines integrated water resource management in the region, including organizations like the Black Sea Commission. The proposed assessment combines the DPSIR and vulnerability concepts. It identifies indicators for evaluation and potential data sources. The assessment aims to evaluate the current state of water resources sustainability and identify key challenges in the Black Sea catchment region.
This document summarizes a study on brackish groundwater comingling in Texas aquifers. It reviewed applicable statutes finding no clear definition of comingling. Factors like water quality stratification, hydraulic gradients, and well construction can enable comingling. Assessments of the Gulf Coast, Eagle Ford Region, and Trans Pecos aquifers found potential for comingling due to multi-aquifer wells and water quality variability. Case studies provided evidence of comingling. A statewide ranking identified 10 high-risk aquifers based on cross-formation completions. Future policy guidance on assessing comingling potential in brackish settings was recommended.
The document outlines the design of an active control outlet for a stormwater drainage basin in Pelzer, South Carolina. It discusses the background and rationale for the project, which is to improve stormwater management through an adjustable outlet that can be opened, partially opened, or closed based on weather forecasts and pond water levels. This aims to maximize pollutant retention time and better mimic pre-development flow conditions. The document reviews programming approaches to retrieve weather forecast data and integrate it into the control logic to adjust the outlet in real-time.
Nov. 7, 2018- The Tennessee Department of Environment and Conservation (TDEC) is currently in the process of developing a Total Maximum Daily Load (TMDL) for the Harpeth River.
A TMDL is a pollution reduction study and plan that puts a waterbody on the path to restoration. In the case of the Harpeth River, TDEC is engaging stakeholders to help develop limits for phosphorus pollution.
Presentation Table of Contents:
• Why Are We Doing a TMDL? Why are We Here? • The Over-Riding Goal of a TMDL
• Where Are We Now?
• Elements of a TMDL
• Issues with Most TMDLs?
• Solutions? Stakeholder-led TMDL – “Privatize” the TMDL Process • Examples & Similar Structures
• Requirements & Interim Measures
• Potential for Legislative Involvement / Encouragement
• Similarity to USEPA Region 4’s 5R Approach
• Conclusion
DSD-INT 2015 - The future of computer modeling of coastal wetland, estuarine,...Deltares
The document summarizes a modeling project to simulate coastal wetland, estuarine, and riverine systems in Louisiana. It involved a team effort between multiple organizations. The goal was to develop a validated model to simulate morphological processes during new delta and wetland creation, as well as nutrient effects on vegetation and primary producers. The modeling approach coupled hydrodynamic, morphodynamic, and nutrient dynamic modules. Nine production runs were planned using different scenarios of sediment diversion operations and environmental conditions over 50 years. Model calibration and validation showed good performance in simulating river hydrology and morphology change. The scenarios suggested that operating multiple sediment diversions could significantly build land compared to no diversions.
This document outlines the design of an active control outlet for a stormwater drainage basin in Pelzer, SC. It discusses the background and rationale for using an active control outlet, which can adjust based on weather forecasts and pond water levels, compared to a static outlet. The objectives are to design and evaluate the impact of the active control outlet on water quality and quantity. Approaches include literature review, data collection, modeling, and design of the control structure. Instrumentation options and programming logic for integrating weather forecasts from NOAA into controlling the outlet are also covered.
This document is a project report submitted by students to Reliance Industries Limited on developing techniques for subsea flow measurement in deepwater fields. It evaluates using blockage factor and virtual metering to detect blockages in subsea pipelines and estimate water-gas ratio trends. Blockage factor relates the excess pressure drop across a pipeline blockage to the blockage size. Virtual metering determines well flow rates using existing well instrumentation when direct meters are absent. The techniques were tested on the KG D6 gas and oil fields offshore India and can help optimize production and reservoir monitoring in deepwater fields.
DSD-INT 2021 wflow User Day - Introduction - RussellDeltares
The document outlines the schedule and topics for the wflow User Day 2021 conference. The schedule includes sessions on wflow developments in Julia, large-sample evaluations of the wflow_sbm model, catchment erosion modelling using wflow sediment, and effects of groundwater conceptualization in wflow models. It also provides an introduction to wflow as an open source hydrological modeling framework approach developed by Deltares for distributed hydrological modeling from precipitation to groundwater.
Modern oil and gas field management is increasingly reliant on detailed and precise 3D reservoir characterisation, and timely areal monitoring. Borehole seismic techniques bridge the gap between remote surface-seismic observations and downhole reservoir evaluation: Borehole seismic data provide intrinsically higher-resolution, higher-fidelity images than surface-seismic data in the vicinity of the wellbore, and unique access to properties of seismic wavefields to enhance surface-seismic imaging. With the advent of new, operationally-efficient very large wireline receiver arrays; fiber-optic recording using Distributed Acoustic Sensing (DAS); the crosswell seismic reflection technique, and advanced seismic imaging algorithms such as Reverse Time Migration, a new wave of borehole seismic technologies is revolutionizing 3D seismic reservoir characterization and on-demand reservoir surveillance. New borehole seismic technologies are providing deeper insights into static reservoir architecture and properties, and into dynamic reservoir performance for conventional water-flood production, EOR, and CO2 sequestration – in deepwater, unconventional, full-field, and low-footprint environments. This lecture will begin by illustrating the wide range of borehole seismic solutions for reservoir characterization and monitoring, using a diverse set of current- and recent case study examples – through which the audience will gain an understanding of the appropriate use of borehole seismic techniques for field development and management. The lecture will then focus on DAS, explaining how the technique works; its capability to deliver conventional borehole seismic solutions (with key advantages over geophones); then describing DAS’s dramatic impact on field monitoring applications and business-critical decisions. New and enhanced borehole seismic techniques – especially with DAS time-lapse monitoring – are ready to deliver critical reservoir management solutions for your fields.
DSD-INT 2021 Webinar 3D water quality modelling using Delft3D FM Suite - VilminDeltares
The document discusses 3D water quality modeling using Delft3D FM Suite. It provides the following key points:
1. Delft3D FM allows for flexible mesh grids that can increase resolution in areas of interest while modeling large domains with reduced computation times. It integrates waves, water quality, and other modules.
2. The North Sea is intensely used with increasing pressures on space and ecology from energy transition, sustainable food, and nature conservation. Integrated modeling tools are needed to assess combined effects of large-scale changes.
3. The 3D DCSM-FM model is used to study effects of offshore wind farms and seaweed cultivation on hydrodynamics, nutrients, primary production and higher
DSD-INT 2015 - Addressing high resolution modelling over different computing ...Deltares
This document discusses using high performance computing resources to model water quality and hydrodynamics in reservoirs. It summarizes work using the Delft3D model on the Cuerda del Pozo reservoir, which experiences eutrophication issues. The modeling aims to reproduce conditions like algae blooms and alert authorities before water quality deteriorates. While hydrodynamics modeling was successful, water quality modeling had issues to be addressed. The document also discusses using cloud resources through the EGI FedCloud to run the high resolution models, as well as potential applications of this use case for biodiversity infrastructure projects like LifeWatch and INDIGO-DataCloud.
DSD-INT 2019 Emission and water quality modelling with wflow and D-Water Qual...Deltares
Presentation by Hélène Boisgontier, Deltares, at the wflow - User Day (Developments in distributed hydrological modelling), during Delft Software Days - Edition 2019. Friday, 08 November 2019, Delft.
This document outlines remedies to improve the water supply advisory committee's (WSAC) process for evaluating ideas and proposals. It suggests:
1) Ensuring judges have adequate information before rating proposals through answering "guidance questions";
2) Developing a list of guidance questions to be answered by experts on technical issues across many proposals;
3) Obtaining answers to these questions will allow for more informed, consistent ratings and prevent wasting time and misdirecting the process.
Integration of the MODFLOW Lak7 package in the FREEWAT GIS modelling environmentMassimiliano Cannata
The MODFLOW Lake Package is integrated into the FREEWAT GIS environment in order to simulate surface water - groundwater interaction using state of the art techniques for numerical simulations, thus allowing the improved consideration of surface water bodies for water resources management. Surface water bodies, both stationary and flowing, can strongly affect groundwater elevations and flow patterns which in turn may affect the qualitative and quantitative state of groundwater resources. With the advancement of numerical simulation techniques and increased model complexity, FREEWAT facilitates the usage of the lake package through existing QGIS tools to edit model layer geometry as well as an intuitive and simple user interface for the specification of constant and time variable lake properties as defined through MODFLOW.
This document provides guidance on using hydrological models to validate hydrological data and fill in missing data. It describes a training module on hydrological data validation using the Sacramento hydrological rainfall-runoff model. The module includes an introduction to hydrological models, the conceptualization and components of the Sacramento model, and case studies of applying the model. The overall aim is to teach participants how to carry out hydrological data validation and fill in missing data by calibrating the Sacramento model using measured rainfall, evapotranspiration, and runoff time series from catchments.
Floodplain Modelling Materials and MethodologyIDES Editor
A floodplain is the normally dry land area adjoining
river or stream that is inundated during flood events. The
most common reason for flooding could be overtopping of river
or stream due to heavy downfall. The floodplain carries flow
in excess of the river or stream capacity. Flood frequency and
flood water-surface elevations are the crucial components for
the evaluation of flood hazard. This paper presents the
methodology that incorporates advanced technologies for
hydrologic and hydraulic analyses that are needed to be carried
out to predict the flood water-surface elevations for any
ungaged watershed.
This document provides guidance on secondary validation and processing of hydro-meteorological and surface water quantity and quality data for a hydrological information system in India. It describes various procedures for validating rainfall, climatic, water level, discharge, and sediment data through time series analysis, comparison between stations, and relationship curves. It also provides methods for correcting errors and completing missing data through interpolation, rating curves, and areal estimation techniques. The overall goal is to develop a sustainable hydrological information system with standardized, computerized data to support water resources planning and management.
Nattai River : eWater Source Catchments Model Case StudyeWater
The Source Catchments model has been developed and calibrated to represent hydrological processes in the Nattai River catchment. The model is configured to represent the catchment as 29 sub-catchments comprised of 27 functional units, derived from land use and soil facet spatial information.
The Nattai River Source Catchments model requires additional water quality data and further development to ensure its reliability as a predictor of constituent loads generated in the catchment and delivered to its receiving waters. The model, however, has been configured to represent catchment hydrology and predicts discharge volumes to satisfactory accuracy, and could be considered as a flow yields model.
This document summarizes a study that coupled a participatory system dynamics model with the Soil and Water Assessment Tool model to support water quality management in the Du Chêne basin in Quebec. A qualitative system dynamics model was developed with stakeholders then converted to a quantitative model in Simile software. This was coupled with a SWAT model of the basin using an interface from the PEST parameter estimation software. The coupled models were used to discuss scenarios with stakeholders and test management options, though they are not suited for operational use due to uncertainty. Future work will test other coupling methods and apply the approach to soil salinity issues in Pakistan.
This document outlines the stages of surface water data processing under the Hydrological Information System (HIS) in India. It discusses: 1) Receipt of data from field stations and storage of raw records; 2) Data entry at sub-divisional offices; 3) Validation of data through primary, secondary, and hydrological checks; 4) Completion and correction of missing or erroneous data; 5) Compilation, analysis, and reporting of validated data; 6) Transfer of data between processing levels from sub-division to division to state centers. The overall goal is to process field data in a systematic series of steps to produce quality-controlled hydrological information.
February 2022 TAGD Business Meeting
Study Results: Delineating Injection Well Buffer Zones in Brackish Aquifers
Juan Acevedo, BRACS Hydrologist, TWDB Jack Sharp, Professor Emeritus in Geology, UT- Austin
Reservoir Water Supply Planning for an Uncertain FutureDave Campbell
1) Reservoir water supply planning involves projecting future water demand over a 50-year planning period, which involves significant uncertainty. Factors like population growth, climate change, and regulatory requirements are difficult to predict that far in advance.
2) Reservoir projects take 10-20 years to plan, permit, design, and construct, so planning must start well in advance of anticipated need. However, deferring planning can significantly increase costs due to escalation rates for reservoir projects that exceed general inflation rates.
3) Reservoir configurations include on-stream reservoirs supplied by their own watershed, and pumped storage reservoirs that receive diverted flows from other streams to supplement their smaller watershed yield. Operating a reservoir for downstream flow augmentation
D5.3 Integrated water resource sustainability and vulnerability assessmentenvirogrids-blacksee
This document proposes a framework for assessing the sustainability and vulnerability of water resources in the Black Sea catchment. It reviews existing assessment frameworks like the DPSIR and vulnerability models. It also examines integrated water resource management in the region, including organizations like the Black Sea Commission. The proposed assessment combines the DPSIR and vulnerability concepts. It identifies indicators for evaluation and potential data sources. The assessment aims to evaluate the current state of water resources sustainability and identify key challenges in the Black Sea catchment region.
This document summarizes a study on brackish groundwater comingling in Texas aquifers. It reviewed applicable statutes finding no clear definition of comingling. Factors like water quality stratification, hydraulic gradients, and well construction can enable comingling. Assessments of the Gulf Coast, Eagle Ford Region, and Trans Pecos aquifers found potential for comingling due to multi-aquifer wells and water quality variability. Case studies provided evidence of comingling. A statewide ranking identified 10 high-risk aquifers based on cross-formation completions. Future policy guidance on assessing comingling potential in brackish settings was recommended.
The document outlines the design of an active control outlet for a stormwater drainage basin in Pelzer, South Carolina. It discusses the background and rationale for the project, which is to improve stormwater management through an adjustable outlet that can be opened, partially opened, or closed based on weather forecasts and pond water levels. This aims to maximize pollutant retention time and better mimic pre-development flow conditions. The document reviews programming approaches to retrieve weather forecast data and integrate it into the control logic to adjust the outlet in real-time.
Nov. 7, 2018- The Tennessee Department of Environment and Conservation (TDEC) is currently in the process of developing a Total Maximum Daily Load (TMDL) for the Harpeth River.
A TMDL is a pollution reduction study and plan that puts a waterbody on the path to restoration. In the case of the Harpeth River, TDEC is engaging stakeholders to help develop limits for phosphorus pollution.
Presentation Table of Contents:
• Why Are We Doing a TMDL? Why are We Here? • The Over-Riding Goal of a TMDL
• Where Are We Now?
• Elements of a TMDL
• Issues with Most TMDLs?
• Solutions? Stakeholder-led TMDL – “Privatize” the TMDL Process • Examples & Similar Structures
• Requirements & Interim Measures
• Potential for Legislative Involvement / Encouragement
• Similarity to USEPA Region 4’s 5R Approach
• Conclusion
DSD-INT 2015 - The future of computer modeling of coastal wetland, estuarine,...Deltares
The document summarizes a modeling project to simulate coastal wetland, estuarine, and riverine systems in Louisiana. It involved a team effort between multiple organizations. The goal was to develop a validated model to simulate morphological processes during new delta and wetland creation, as well as nutrient effects on vegetation and primary producers. The modeling approach coupled hydrodynamic, morphodynamic, and nutrient dynamic modules. Nine production runs were planned using different scenarios of sediment diversion operations and environmental conditions over 50 years. Model calibration and validation showed good performance in simulating river hydrology and morphology change. The scenarios suggested that operating multiple sediment diversions could significantly build land compared to no diversions.
This document outlines the design of an active control outlet for a stormwater drainage basin in Pelzer, SC. It discusses the background and rationale for using an active control outlet, which can adjust based on weather forecasts and pond water levels, compared to a static outlet. The objectives are to design and evaluate the impact of the active control outlet on water quality and quantity. Approaches include literature review, data collection, modeling, and design of the control structure. Instrumentation options and programming logic for integrating weather forecasts from NOAA into controlling the outlet are also covered.
This document is a project report submitted by students to Reliance Industries Limited on developing techniques for subsea flow measurement in deepwater fields. It evaluates using blockage factor and virtual metering to detect blockages in subsea pipelines and estimate water-gas ratio trends. Blockage factor relates the excess pressure drop across a pipeline blockage to the blockage size. Virtual metering determines well flow rates using existing well instrumentation when direct meters are absent. The techniques were tested on the KG D6 gas and oil fields offshore India and can help optimize production and reservoir monitoring in deepwater fields.
DSD-INT 2021 wflow User Day - Introduction - RussellDeltares
The document outlines the schedule and topics for the wflow User Day 2021 conference. The schedule includes sessions on wflow developments in Julia, large-sample evaluations of the wflow_sbm model, catchment erosion modelling using wflow sediment, and effects of groundwater conceptualization in wflow models. It also provides an introduction to wflow as an open source hydrological modeling framework approach developed by Deltares for distributed hydrological modeling from precipitation to groundwater.
Modern oil and gas field management is increasingly reliant on detailed and precise 3D reservoir characterisation, and timely areal monitoring. Borehole seismic techniques bridge the gap between remote surface-seismic observations and downhole reservoir evaluation: Borehole seismic data provide intrinsically higher-resolution, higher-fidelity images than surface-seismic data in the vicinity of the wellbore, and unique access to properties of seismic wavefields to enhance surface-seismic imaging. With the advent of new, operationally-efficient very large wireline receiver arrays; fiber-optic recording using Distributed Acoustic Sensing (DAS); the crosswell seismic reflection technique, and advanced seismic imaging algorithms such as Reverse Time Migration, a new wave of borehole seismic technologies is revolutionizing 3D seismic reservoir characterization and on-demand reservoir surveillance. New borehole seismic technologies are providing deeper insights into static reservoir architecture and properties, and into dynamic reservoir performance for conventional water-flood production, EOR, and CO2 sequestration – in deepwater, unconventional, full-field, and low-footprint environments. This lecture will begin by illustrating the wide range of borehole seismic solutions for reservoir characterization and monitoring, using a diverse set of current- and recent case study examples – through which the audience will gain an understanding of the appropriate use of borehole seismic techniques for field development and management. The lecture will then focus on DAS, explaining how the technique works; its capability to deliver conventional borehole seismic solutions (with key advantages over geophones); then describing DAS’s dramatic impact on field monitoring applications and business-critical decisions. New and enhanced borehole seismic techniques – especially with DAS time-lapse monitoring – are ready to deliver critical reservoir management solutions for your fields.
DSD-INT 2021 Webinar 3D water quality modelling using Delft3D FM Suite - VilminDeltares
The document discusses 3D water quality modeling using Delft3D FM Suite. It provides the following key points:
1. Delft3D FM allows for flexible mesh grids that can increase resolution in areas of interest while modeling large domains with reduced computation times. It integrates waves, water quality, and other modules.
2. The North Sea is intensely used with increasing pressures on space and ecology from energy transition, sustainable food, and nature conservation. Integrated modeling tools are needed to assess combined effects of large-scale changes.
3. The 3D DCSM-FM model is used to study effects of offshore wind farms and seaweed cultivation on hydrodynamics, nutrients, primary production and higher
DSD-INT 2015 - Addressing high resolution modelling over different computing ...Deltares
This document discusses using high performance computing resources to model water quality and hydrodynamics in reservoirs. It summarizes work using the Delft3D model on the Cuerda del Pozo reservoir, which experiences eutrophication issues. The modeling aims to reproduce conditions like algae blooms and alert authorities before water quality deteriorates. While hydrodynamics modeling was successful, water quality modeling had issues to be addressed. The document also discusses using cloud resources through the EGI FedCloud to run the high resolution models, as well as potential applications of this use case for biodiversity infrastructure projects like LifeWatch and INDIGO-DataCloud.
DSD-INT 2019 Emission and water quality modelling with wflow and D-Water Qual...Deltares
Presentation by Hélène Boisgontier, Deltares, at the wflow - User Day (Developments in distributed hydrological modelling), during Delft Software Days - Edition 2019. Friday, 08 November 2019, Delft.
This document outlines remedies to improve the water supply advisory committee's (WSAC) process for evaluating ideas and proposals. It suggests:
1) Ensuring judges have adequate information before rating proposals through answering "guidance questions";
2) Developing a list of guidance questions to be answered by experts on technical issues across many proposals;
3) Obtaining answers to these questions will allow for more informed, consistent ratings and prevent wasting time and misdirecting the process.
Integration of the MODFLOW Lak7 package in the FREEWAT GIS modelling environmentMassimiliano Cannata
The MODFLOW Lake Package is integrated into the FREEWAT GIS environment in order to simulate surface water - groundwater interaction using state of the art techniques for numerical simulations, thus allowing the improved consideration of surface water bodies for water resources management. Surface water bodies, both stationary and flowing, can strongly affect groundwater elevations and flow patterns which in turn may affect the qualitative and quantitative state of groundwater resources. With the advancement of numerical simulation techniques and increased model complexity, FREEWAT facilitates the usage of the lake package through existing QGIS tools to edit model layer geometry as well as an intuitive and simple user interface for the specification of constant and time variable lake properties as defined through MODFLOW.
This document provides guidance on using hydrological models to validate hydrological data and fill in missing data. It describes a training module on hydrological data validation using the Sacramento hydrological rainfall-runoff model. The module includes an introduction to hydrological models, the conceptualization and components of the Sacramento model, and case studies of applying the model. The overall aim is to teach participants how to carry out hydrological data validation and fill in missing data by calibrating the Sacramento model using measured rainfall, evapotranspiration, and runoff time series from catchments.
Floodplain Modelling Materials and MethodologyIDES Editor
A floodplain is the normally dry land area adjoining
river or stream that is inundated during flood events. The
most common reason for flooding could be overtopping of river
or stream due to heavy downfall. The floodplain carries flow
in excess of the river or stream capacity. Flood frequency and
flood water-surface elevations are the crucial components for
the evaluation of flood hazard. This paper presents the
methodology that incorporates advanced technologies for
hydrologic and hydraulic analyses that are needed to be carried
out to predict the flood water-surface elevations for any
ungaged watershed.
This document provides guidance on secondary validation and processing of hydro-meteorological and surface water quantity and quality data for a hydrological information system in India. It describes various procedures for validating rainfall, climatic, water level, discharge, and sediment data through time series analysis, comparison between stations, and relationship curves. It also provides methods for correcting errors and completing missing data through interpolation, rating curves, and areal estimation techniques. The overall goal is to develop a sustainable hydrological information system with standardized, computerized data to support water resources planning and management.
Nattai River : eWater Source Catchments Model Case StudyeWater
The Source Catchments model has been developed and calibrated to represent hydrological processes in the Nattai River catchment. The model is configured to represent the catchment as 29 sub-catchments comprised of 27 functional units, derived from land use and soil facet spatial information.
The Nattai River Source Catchments model requires additional water quality data and further development to ensure its reliability as a predictor of constituent loads generated in the catchment and delivered to its receiving waters. The model, however, has been configured to represent catchment hydrology and predicts discharge volumes to satisfactory accuracy, and could be considered as a flow yields model.
This document provides training materials for a module on understanding conventional and DWLR assisted water level monitoring. It includes an introduction explaining the context and relationship to other modules. The module profile outlines the target group, duration, objectives and key concepts to be covered. A session plan details the activities and time allotted. The main text then provides content on prevalent water level monitoring, high frequency monitoring using DWLRs, and how true hydrographs can be obtained and used. Additional materials include overhead masters, handouts and references. The overall purpose is to train participants on differentiating between conventional and high frequency water level monitoring techniques and the benefits of obtaining true hydrographs from DWLR data.
This document provides guidance on secondary validation procedures for hydro-meteorological and surface water quantity and quality data as part of a hydrological information system for 9 states in India. It describes various validation checks that can be performed on rainfall, climatic, water level, discharge, and sediment data including time series analysis, comparison against data limits, double mass curves, and spatial analysis techniques. The document also outlines procedures for correcting and completing data using neighboring station information, interpolation, and rating curves. The overall goal is to ensure standardized and high quality data processing.
This document provides guidance on secondary validation and processing of hydro-meteorological and surface water quantity and quality data for a hydrological information system in India. It describes various procedures for validating rainfall, climatic, water level, discharge, and sediment data through time series analysis, comparison between stations, and relationship curves. It also provides methods for correcting errors and completing missing data through interpolation, rating curves, and areal estimation techniques. The overall goal is to develop a sustainable hydrological information system that meets user needs through standardized data collection and computerized databases.
The document summarizes an awareness workshop on integrated water resources management applications developed under a hydrology project. It describes the objectives of developing standardized hydrological design practices and tools. It outlines the main components of the Hydrological Design Aids software, including modules for water availability assessment, design flood estimation, and sedimentation rate estimation. It provides an overview of the software architecture and features for entering project details, station data, and performing analyses like unit hydrograph development and peak flood estimation. Regional models are being developed for four river systems to enable computation of monthly water yields for ungauged sub-basins.
This document outlines a training module on other applications of data from Digital Water Level Recorders (DWLRs). The module aims to help participants appreciate the utility of high frequency water level monitoring data beyond groundwater resource assessment. It discusses how DWLR data can be used for conjunctive use planning, identifying over-exploited areas, scheduling pumpages, calibrating aquifer response models, and identifying cycles in water level fluctuations. The module includes session plans, presentation materials, and handouts to support a 60-minute training session on these topics.
This document provides guidance on analyzing discharge data. It discusses computing basic statistics, constructing flow duration curves to analyze variability, fitting theoretical frequency distributions, and other time series analysis techniques like moving averages and mass curves. The main text provides detailed explanations of these methods and their uses in hydrological analysis, data validation, and reporting. It is intended to train hydrologists and data managers on effectively analyzing discharge data.
This document provides guidance on correcting and completing water level data. It discusses using staff gauge records, autographic records, and digital records to identify errors such as observer errors, recorder timing errors, pen level errors, and errors from stilling wells or intakes. It also describes techniques for correcting errors, such as linear interpolation for short gaps and using relation curves between adjacent stations. The overall aim is to replace incorrect values and fill in missing values to complete the water level records.
This document provides guidance for managing sediment and water quality data within India's Hydrological Information System (HIS). It summarizes the key HIS manuals that provide procedures for monitoring, data collection, validation, analysis, dissemination and publication of sediment and water quality data. Specifically, it outlines the multi-volume HIS Manuals for Surface Water and Groundwater, which describe the lifecycle of sediment and water quality data within the HIS. It also lists some additional HPI documentation and training modules that are relevant to sediment and water quality monitoring and analysis. The overall aim is to help users navigate and understand the various documents within the HIS library to properly manage sediment and water quality data.
This document provides guidance on how to carry out primary validation of rainfall data. It discusses comparing daily rainfall measurements from a standard raingauge to those from an autographic or digital raingauge. Differences greater than 5% between the two measurements would be further investigated. Likely sources of error are outlined for each type of raingauge. The validation can be done graphically or tabularly by aggregating hourly rainfall data to daily totals and comparing. Actions are suggested based on the patterns of discrepancies found.
This document provides guidance on validating rainfall data from different measurement instruments. It describes common rainfall measurement tools like daily rain gauges, autographic rain gauges, and tipping bucket rain gauges. It outlines potential errors from each tool and recommends comparing daily time series between tools to identify discrepancies. Discrepancies over 5% should be investigated further. Likely error sources are diagnosed based on patterns of discrepancies. The guidance aims to help validate rainfall data and make corrections to measurement tools or recorded values when necessary.
The document provides guidance on reporting stage discharge data from hydrological monitoring stations. It recommends including a table with summary information for each station such as maximum/minimum observed stages and flows, the number of discharge measurements and ratings developed in the current and previous years, and the standard error of ratings. The purpose is to evaluate monitoring efforts and provide information for planning while avoiding reporting all raw data. Stage discharge relationships and time series data should be made available upon request.
The document describes a training module on analyzing rainfall data. It includes sessions on checking data homogeneity, computing basic statistics, fitting frequency distributions, and deriving frequency-duration and intensity-duration-frequency curves. Exercises are provided for trainees to practice analyzing monthly and daily rainfall series, fitting distributions, and deriving curves for different durations and return periods. Case studies from India are referenced as examples throughout the training material.
This document provides guidance on analyzing rainfall data. It discusses checking data homogeneity, computing basic statistics, developing annual exceedance rainfall series, fitting frequency distributions, and deriving frequency-duration and intensity-duration-frequency curves. The document includes examples demonstrating how to calculate statistics for a monthly rainfall series and develop frequency curves. It also outlines computational procedures and examples for depth-area-duration analysis. Key steps in the rainfall data analysis process are presented along with example results and figures.
Gw02 role of dwlr data in groundwater resource estimationhydrologyproject0
This document discusses the role of data from Deep Well Logging Recorders (DWLRs) in estimating groundwater resources. DWLRs provide high-frequency water level data that can help understand recharge processes and parameters. Their data allows identifying accurate peaks and troughs in the water table to define optimal periods for water balance studies estimating specific yield and rainfall recharge. DWLR hydrographs also aid in determining rainfall amounts needed to initiate recharge, lag times between rainfall and recharge, effective rainfall events, and periods of evapotranspiration loss - all improving the accuracy of water balance assessments and groundwater resource estimation.
This document provides guidance on reporting discharge data from hydrological monitoring stations. It outlines the contents and purpose of yearly reports, including descriptive summaries of streamflow patterns, basic statistics for selected stations, and comparisons to long-term averages. Periodic long-term reports every 5-10 years are also recommended to analyze trends over longer time periods. The reports aim to inform water resource planning and make hydrological data more accessible and understandable for users.
This document outlines the need for establishing operation and maintenance procedures for groundwater monitoring networks in India. It discusses how piezometers and observation wells can decline in performance over time if not properly maintained. Factors like siltation, drying up, damage, and influence from nearby pumping can affect data reliability. The document emphasizes that preventative maintenance is crucial to ensure monitoring structures continue generating accurate data to inform groundwater management policies. A well-defined maintenance program is needed to systematically inspect equipment and address any issues identified.
This document provides an overview of a Hydrological Information System (HIS) being developed for 9 states in India. It discusses the key components and activities of the HIS, which include: assessing user needs, establishing observation networks, managing historical data, collecting field data, processing and analyzing data, exchanging and reporting data, storing and disseminating data, and developing institutional and human resources. The overall goal of the HIS is to provide reliable hydrological data and information to support long-term water resources planning and management decisions in India.
This document provides guidance on reporting climatic data in India. It discusses the purpose and contents of annual reports on climatic data, including evaporation data. Key points covered include:
- Annual reports summarize evaporation data for the reporting year and compare to long-term statistics.
- Reports include details on the observational network, basic evaporation statistics, data validation processes.
- Network maps and station listings provide details of monitoring locations. Statistics include monthly and annual evaporation amounts for the current year and historical averages.
- Reports aim to inform water resource planning, acknowledge data collection efforts, and provide access to climatic data records.
This document provides guidance on reporting climatic data in India. It discusses the purpose and contents of annual reports on climatic data, including evaporation data. Key points covered include:
- Annual reports summarize evaporation data for the reporting year and compare to long-term statistics.
- Reports include details on the observational network, basic evaporation statistics, data validation processes.
- Network maps and station listings provide details on locations and recorded variables. Statistics include monthly and annual summaries for the current year and historical averages.
- Reports aim to inform users and support planning, while also recognizing data producers and maintaining the climatic observation system.
This document provides guidance on correcting and completing rainfall data. It discusses using autographic rain gauge (ARG) and standard rain gauge (SRG) data to correct errors. When the SRG is faulty but ARG is available, the SRG can be corrected to match the ARG totals. When the ARG is faulty but SRG is available, hourly distributions from neighboring stations can be used to estimate hourly totals for the station based on its daily SRG total. The document also discusses correcting time shifts, apportioning partial daily accumulations, adjusting for systematic shifts using double mass analysis, and using spatial interpolation methods to estimate missing values. Examples are provided to demonstrate each technique.
This document provides guidance on correcting and completing rainfall data. It discusses using autographic rain gauge (ARG) and standard rain gauge (SRG) data to correct errors when one instrument fails. When the SRG fails but ARG data is available, the SRG data can be replaced with totals from the ARG record. When the ARG fails, hourly distributions from neighboring stations can be used to estimate missing hourly values based on the daily total from the station's SRG. The document also discusses correcting errors like wrong dates and apportioning partial daily accumulations. It describes using double mass analysis to adjust for systematic shifts and spatial interpolation methods to estimate missing values using data from surrounding stations. Examples are provided to demonstrate the techniques.
This document provides guidance on managing groundwater data within India's Hydrological Information System (HIS). It discusses the lifecycle of hydrometric data from collection to dissemination. The document directs the user to relevant manuals within HIS, particularly the Groundwater manual, for guidance on groundwater level monitoring networks, data collection, processing, analysis and publication. It describes the various types of manuals within HIS - design, field operation, and reference - and lists the specific volumes and parts most pertinent to groundwater level data. The overall aim is to help users locate and understand documentation to standardize high quality groundwater data management and inform water resource planning.
Gw05 understanding the concept of optimal monitoring frequency of dwlrhydrologyproject0
This document discusses strategies for determining the optimal monitoring frequency for water level data from digital water level recorders (DWLRs). It states that the optimal frequency depends on the intended use of the data and describes some key criteria: 1) Ensuring derived attributes like peaks and troughs are credible, 2) Preserving the shape of the hydrograph, and 3) Being able to identify cycles of a desired period. It proposes simulating hydrographs with increasing intervals and analyzing attributes, correlation to the true hydrograph, and ability to identify cycles to determine the optimal interval that meets acceptance thresholds for these criteria. Correlation is described as a measure of the linear relationship between two time series.
This document provides information on a training module for understanding hydrological information system (HIS) concepts and setup. It includes an introduction to HIS, why they are needed, how they are set up under the Hydrology Project. It also discusses who the key users of hydrological data are and how computers are used in hydrological data processing. The training module contains session plans, presentations, handouts, and text to educate participants on HIS objectives, components, and how they provide reliable hydrological data to various end users.
Similar to Download-manuals-ground water-training-dwlrg-wdatahandling (20)
This document provides guidance on working with map layers and network layers in HYMOS, a hydrological modeling software. It describes how to obtain map layers from digitized topographic maps and remotely sensed data. It also explains how to create network layers by manually adding observation stations or importing them from another database. The document outlines how to manage and set properties for map layers and network layers within HYMOS to control visibility, styling, and other display options.
This document contains information about receiving hydrological data at different levels in India, including:
1. Data is transferred from field stations to subdivisional offices, then to divisional offices and state/regional data processing centers in stages. Target dates are set for receipt and transmission at each level to ensure smooth processing.
2. Records of receipt are maintained at each office to track data and identify delays, with feedback provided if data is not received by targets.
3. Original paper records are filed by station for easy retrieval, while digital copies are stored for long-term archiving.
The document describes a training module on understanding different types and forms of data in hydrological information systems (HIS). It was developed with funding from the World Bank and Government of the Netherlands. The module provides an overview of the session plan and covers various types of data in HIS, including space-oriented data like catchment maps, time-oriented data such as meteorological observations, and relation-oriented data like stage-discharge relationships. The goal is for participants to learn about all the different types and forms of data managed in HIS.
The document provides details on a surface water data processing plan for India. It discusses distributing data processing activities across three levels - sub-divisional, divisional, and state data processing centers. It outlines the activities, computing facilities, staffing, and time schedules needed at each level to efficiently manage the large volume of hydrological data. The plan aims to ensure data is properly validated and processed within time limits while not overwhelming staff.
This document provides information and guidance on analyzing climatic data to estimate evaporation and evapotranspiration rates. It discusses the use of evaporation pans and appropriate pan coefficients to estimate open water evaporation from lakes and reservoirs. It also describes the Penman method for estimating potential evapotranspiration using standard climatological measurements. The Penman method combines the energy budget and mass transfer approaches and provides formulas for calculating evapotranspiration based on climatic variables like temperature, humidity, wind speed, and solar radiation. Substitutions are suggested when some climatic variables are not directly measured.
This document provides guidance on how to carry out secondary validation of climatic data. It describes various methods for validating data spatially using multiple station comparisons, including comparison plots, balance series, regression analysis, and double mass curves. It also describes single station validation tests for homogeneity, including mass curves and tests of differences in means. The document is part of a training module on secondary validation of climatic data funded by the World Bank and Government of the Netherlands. It provides context for the training and outlines the session plan, materials, and main validation methods to be covered.
This document provides guidance on how to carry out primary validation of climatic data. It discusses validating temperature, humidity, wind speed, atmospheric pressure, sunshine duration, and pan evaporation data. For each variable, it describes typical variations and measurement methods, potential errors, and approaches to error detection such as setting maximum/minimum limits. The goal of primary validation is to check for errors by comparing individual observations to physical limits and sequential observations for unacceptable changes.
This document provides guidance on entering climatic data into a hydrological data processing software called SWDES. It describes the various types of climatic data that can be entered, including daily, twice daily, hourly, and sunshine duration data. Instructions are provided on inspecting paper records, setting up data entry screens, entering values, and performing basic data validation checks. The overall aim is to make climatic data available electronically using SWDES in order to facilitate validation, processing, and reporting of the data.
This document provides guidance on how to report rainfall data in yearly and periodic reports. It outlines the typical contents and structure of annual reports including descriptive summaries of rainfall patterns, comparisons to long-term averages, basic statistics, and descriptions of major storms. Periodic reports produced every 10 years would include long-term statistics updated over the previous decade as well as frequency analysis of rainfall data. The reports aim to inform stakeholders of rainfall patterns and data availability as well as validate and improve the quality of data collection.
This document provides guidance on compiling rainfall data from various time intervals into longer standardized durations. It discusses aggregating hourly data into daily totals, daily data into weekly, ten-daily, monthly, and yearly totals. Methods are presented for arithmetic averaging and Thiessen polygons to estimate areal rainfall from point measurements. Guidance is also given on transforming non-equidistant time series into equidistant series and compiling extreme rainfall statistics. Examples demonstrate compiling hourly rainfall from an autographic rain gauge into daily totals and further aggregating daily point rainfall into areal averages and statistics for various durations.
This document describes a training module on how to carry out secondary validation of rainfall data. It includes the following key points:
1. Secondary validation involves comparing rainfall data to neighboring stations to identify suspect values, taking into account spatial correlation which depends on duration, distance, precipitation type, and physiography.
2. Validation methods described include screening data against limits, scrutinizing multiple time series graphs and tabulations, checking against data limits for longer durations, spatial homogeneity testing, and double mass analysis.
3. Examples demonstrate how spatial correlation varies with duration and distance, and how physiography affects correlation. Screening listings with basic statistics are used to flag suspect data values.
This document provides guidance on entering rainfall data into a dedicated hydrological data processing software (SWDES). It discusses entering daily rainfall data, twice daily rainfall data, and hourly rainfall data from manual records or digital loggers. The key steps are:
1. Manually inspecting field records for completeness and errors before data entry.
2. Entering data into customized SWDES forms that match field observation sheets. This allows direct data transfer with minimal risk of errors.
3. Performing automated checks of the entered data against limits and computed totals to ensure accuracy. Any errors are flagged for further inspection.
4. Graphing the entered time series data during the entry process as an additional validation check.
The document describes methods for hydrological observations including rainfall, water level, discharge, and inspection of observation stations. It contains sections on ordinary and recording rainfall observation, ordinary and recording water level observation, observation of discharge using current meters and floats, and inspection of rainfall and water level observation stations. The document was produced by the Ministry of Construction in Japan.
This document provides guidance on how to review monitoring networks. It begins with an introduction on the objectives and physical characteristics that networks are based on. It then discusses the types of networks, including basic, secondary, dedicated, and representative networks. The document outlines the steps in network design, which include assessing data needs, setting objectives, determining required network density, reviewing the existing network, and conducting a cost-effectiveness analysis. Specific guidance is given on reviewing rainfall and hydrometric networks.
This document provides information on how to carry out correlation and spectral analysis. It discusses autocovariance and autocorrelation functions, cross-covariance and cross-correlation functions, and various spectrum and spectral density functions. The document includes examples and explanations of how to estimate these functions from time series data and interpret the results. It also discusses how these analysis techniques can be used to identify periodicities and correlations in hydrological time series data.
This document provides guidance on statistical analysis of rainfall and discharge data. It discusses graphical representation of data including histograms, line diagrams, and cumulative frequency diagrams. It also covers measures of central tendency, dispersion, skewness, kurtosis, and percentiles. The document emphasizes that hydrological time series must meet stationarity conditions to be suitable for statistical analysis and discusses evaluating and accounting for trends and periodic components when analyzing rainfall and discharge data.
This document provides guidance on how to compile discharge data, including:
1. Aggregating data to longer time intervals through arithmetic averaging or summation.
2. Calculating volumes in cubic meters and runoff depth in millimeters from discharge data and catchment area.
3. Extracting maximum and minimum values over various time periods like days, months, or years for analyses.
This document provides guidance on how to correct and complete discharge data records. It discusses several methods for estimating missing or incorrect discharge values, including interpolation during short gaps or recessions, regression analysis using data from neighboring stations, flow routing to ensure water balance, and rainfall-runoff simulation with a calibrated hydrologic model. The Muskingum method for flow routing between stations is presented as an example. The key is to select the most appropriate technique depending on the type, duration and location of the missing data, while ensuring continuity and physical realism in the corrected or completed record.
This document provides guidance on using regression analysis to validate hydrological data. It discusses using simple linear regression to establish relationships between variables like rainfall and runoff. Key steps covered include estimating regression coefficients to minimize the error variance, measuring the goodness of fit using the coefficient of determination, and examining residuals over time and versus other variables to evaluate changes in the rainfall-runoff relationship. The overall aim is to detect errors in discharge data by comparing observed and computed runoff derived from regression models.
This document provides guidance on how to carry out secondary validation of discharge data. It discusses validating a single station's data against limits and expected behavior through graphical inspection. It also describes validating multiple stations by comparing their time series plots and residual series, as well as comparing streamflow and rainfall data. The overall goal of secondary validation is to identify potential errors or anomalies in discharge data for further investigation and correction.
Webinar: Designing a schema for a Data WarehouseFederico Razzoli
Are you new to data warehouses (DWH)? Do you need to check whether your data warehouse follows the best practices for a good design? In both cases, this webinar is for you.
A data warehouse is a central relational database that contains all measurements about a business or an organisation. This data comes from a variety of heterogeneous data sources, which includes databases of any type that back the applications used by the company, data files exported by some applications, or APIs provided by internal or external services.
But designing a data warehouse correctly is a hard task, which requires gathering information about the business processes that need to be analysed in the first place. These processes must be translated into so-called star schemas, which means, denormalised databases where each table represents a dimension or facts.
We will discuss these topics:
- How to gather information about a business;
- Understanding dictionaries and how to identify business entities;
- Dimensions and facts;
- Setting a table granularity;
- Types of facts;
- Types of dimensions;
- Snowflakes and how to avoid them;
- Expanding existing dimensions and facts.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Digital Marketing Trends in 2024 | Guide for Staying AheadWask
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
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UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
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Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
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During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
1. World Bank & Government of The Netherlands funded
Training module # 1
Understanding Conventional
and DWLR Assisted Water
Level Monitoring
New Delhi, March 2000
CSMRS Building, 4th Floor, Olof Palme Marg, Hauz Khas,
New Delhi – 11 00 16 India
Tel: 68 61 681 / 84 Fax: (+ 91 11) 68 61 685
E-Mail: dhvdelft@del2.vsnl.net.in
DHV Consultants BV & DELFT HYDRAULICS
with
HALCROW, TAHAL, CES, ORG & JPS
2. HP Trng Module File: “ 1 Conventional and DWLR assisted water level monitoring.doc” Version 10/10/02 Page 1
Table of contents
Page
1. Module context 2
2. Module profile 3
3. Session plan 4
4. Main text 5
5. Overhead/flipchart master 6
6. Handout 7
7. Additional handout 8
3. HP Trng Module File: “ 1 Conventional and DWLR assisted water level monitoring.doc” Version 10/10/02 Page 2
1. Module context
While designing a training course, the relationship between this module and the others,
would be maintained by keeping them close together in the syllabus and place them in a
logical sequence. The actual selection of the topics and the depth of training would, of
course, depend on the training needs of the participants, i.e. their knowledge level and skills
performance upon the start of the course. This is an independent module.
4. HP Trng Module File: “ 1 Conventional and DWLR assisted water level monitoring.doc” Version 10/10/02 Page 3
2. Module profile
Title : Understanding Conventional and DWLR Assisted Water
Level Monitoring
Target group : Hydrogeologists, Asst-Hydrogeologists, Senior Technical Assistant
Duration : One Session of 30 minutes
Objectives : After the training the participants will be able to:
• Differentiate between conventional water level monitoring and
high frequency level monitoring.
Key concepts : • Prevalent water level monitoring
• High Frequency water level Monitoring
• True hydrographs
Training methods : Lecture
Training tools
required
: OHS
Handouts : As provided in this module
Further reading
and references
:
5. HP Trng Module File: “ 1 Conventional and DWLR assisted water level monitoring.doc” Version 10/10/02 Page 4
3. Session plan
No Activities Time Tools
1 • Discuss the prevailing water level monitoring,
• Show the nature of the hydrograph emerging from
conventional monitoring
• Discuss the nature of aquifers being monitored,
• List the deficiencies of the conventional monitoring,
• Describe the advantages of dedicated piezometers over
hand dug wells
• Explain the need for high frequency monitoring and role of
DWLR,
• Explain a true hydrograph
15 min OHS
2 • Illustration 5 min OHS
3 Feedback 5 min
4 Wrap up 5 min
6. HP Trng Module File: “ 1 Conventional and DWLR assisted water level monitoring.doc” Version 10/10/02 Page 5
4. Main text
Contents
1. Prevalent Monitoring 1
2. High Frequency Monitoring 2
3. True Hydrograph – What to do with it? 2
7. HP Trng Module File: “ 1 Conventional and DWLR assisted water level monitoring.doc” Version 10/10/02 Page 1
Understanding Conventional and DWLR Assisted Water Level Monitoring
1. Prevalent Monitoring
Conventionally the groundwater monitoring in India has been conducted on the following
lines:
• Water levels are usually monitored in privately owned open dug wells tapping the upper
unconfined aquifers. These levels reveal the piezometric head/water table elevation of
the semi-confined/unconfined aquifers. However, the necessary well-aquifer hydraulic
connection is not always beyond suspicion.
• The frequency of monitoring has generally been restricted to four times in a year. These
times are rather arbitrarily selected during pre-monsoon, monsoon, post-monsoon and
winter seasons. It is presumed that these water levels represent the troughs and peaks
of the water table hydrograph. However, many a time these data may be too sparse to
yield reliable and credible water table hydrograph, as illustrated in figure 1. The figure
shows the true hydrograph (derived from high frequency DWLR data) superposed over
the corresponding hydrograph based upon four annual observations.
Fig 1: True Hydrograph from phreatic aquifer (Granitic rock), in Kattangur
Village, Nalgonda District Andhra Pradesh
8. HP Trng Module File: “ 1 Conventional and DWLR assisted water level monitoring.doc” Version 10/10/02 Page 2
• Limited monitoring of the piezometric head of the deeper confined/leaky confined
aquifers has been carried out by some agencies, usually by observing the water level in
the deep production tube wells. The tube wells, many a time may not be adequately
isolated from (or worse, may even be tapping) the unconfined aquifer. Dedicated
piezometers tapping only the deeper aquifers and duly isolated from the unconfined
aquifer are almost non-existent.
The historical monitoring programmes though quite extensive and commendable in many
ways, have been deficit in several respects. The practising hydrogeologists have been
conducting the resource evaluations quite credibly in spite of these deficits. They have been
circumventing the problem by certain subjective practices based upon norms/past
experience or intuitive reasoning. Nevertheless, this has restricted their practice in many
ways. For example, no norms have been developed for estimating resource of the deeper
aquifers. (This estimation is no doubt difficult due to uncertainties regarding the recharge
zone, but lack of the piezometric head data has pre-empted its solution.) Similarly, since the
practitioners have never been able to view a true water table hydrograph, recharge
estimation by water balance of the unconfined aquifer gets uncertain in many ways. Further,
time series analysis of the water level data is not routinely done because the data at
necessary frequency are usually not available.
2. High Frequency Monitoring
The Hydrology Project has enabled construction of a large number of scientifically designed
piezometers tapping unconfined and the deeper aquifers. These piezometers have the
necessary hydraulic connection with the targeted aquifers and are suitably isolated from
overlying/underlying aquifers. Further, digital automatic water level recorders (DWLRs) are
installed in these piezometers. This ensures measurement of undistorted piezometric head
at the desired frequency, which may be much larger than the present frequency. In fact, the
frequency may be so high that the resulting piezometric hydrograph may almost be
continuous.
3. True Hydrograph – What to do with it?
With the high frequency and credible piezometric head data emanating from the
DWLRs, the groundwater practitioners in India shall have an access to true
piezometric head hydrographs, possibly for the first time. This is bound to inspire the
practitioners to enhance the scientific/technical content of their prevailing practice
and also to incorporate in it many new analyses. Some of the possibilities shall be
discussed subsequently.
9. HP Trng Module File: “ 1 Conventional and DWLR assisted water level monitoring.doc” Version 10/10/02 Page 6
5. Overhead/flipchart master
10. HP Trng Module File: “ 1 Conventional and DWLR assisted water level monitoring.doc” Version 10/10/02 Page 7
6. Handout
11. HP Trng Module File: “ 1 Conventional and DWLR assisted water level monitoring.doc” Version 10/10/02 Page 8
7. Additional handout
These handouts are distributed during delivery and contain test questions, answers to
questions, special worksheets, optional information, and other matters you would not like to
be seen in the regular handouts.
It is a good practice to pre-punch these additional handouts, so the participants can easily
insert them in the main handout folder.
12. World Bank & Government of The Netherlands funded
Training module # 2
Role of DWLR data in
Groundwater Resource
Estimation
New Delhi, March 2000
CSMRS Building, 4th Floor, Olof Palme Marg, Hauz Khas,
New Delhi – 11 00 16 India
Tel: 68 61 681 / 84 Fax: (+ 91 11) 68 61 685
E-Mail: dhvdelft@del2.vsnl.net.in
DHV Consultants BV & DELFT HYDRAULICS
with
HALCROW, TAHAL, CES, ORG & JPS
13. HP Trng Module File: “ 2 Role of DWLR data in GW Resource Estimation.doc” Version 10/10/02 Page 1
Table of contents
Page
1. Module context 2
2. Module profile 3
3. Session plan 4
4. Main text 5
5. Overhead/flipchart master 6
6. Handout 7
7. Additional handout 8
14. HP Trng Module File: “ 2 Role of DWLR data in GW Resource Estimation.doc” Version 10/10/02 Page 2
1. Module context
While designing a training course, the relationship between this module and the others,
would be maintained by keeping them close together in the syllabus and place them in a
logical sequence. The actual selection of the topics and the depth of training would, of
course, depend on the training needs of the participants, i.e. their knowledge level and skills
performance upon the start of the course.
15. HP Trng Module File: “ 2 Role of DWLR data in GW Resource Estimation.doc” Version 10/10/02 Page 3
2. Module profile
Title : Role of DWLR data in Groundwater Resource Estimation
Target group : Hydrogeologists, Asst-Hydrogeologists, Senior Technical Assistant
Duration : One Session of 60 minutes
Objectives : After the training the participants will be able to:
• Appreciate the utility of high frequency DWLR water level
monitoring.
• Correlate the rainfall hyetograph to the corresponding water
level hydrograph.
• Appreciate the utility of high frequency ground water levels for
systematic assessment of ground water resources.
Key concepts : • Understanding the recharge process
• Lumped water balance
• Role of DWLR data
Training methods : Lecture
Training tools
required
: OHS
Handouts : As provided in this module
Further reading
and references
:
16. HP Trng Module File: “ 2 Role of DWLR data in GW Resource Estimation.doc” Version 10/10/02 Page 4
3. Session plan
No Activities Time Tools
1 • Discuss the prevailing Water balance computations for
unconfined aquifers
• Scope for improvement of water balance computations by
using DWLR data
• Methodology for selection of water balance periods
• Identification of effective rainfall events
• Estimation of evapotranspiration loss
30 min OHS
2 • Illustration 10 min OHS
3 Feedback 15 min
4 Wrap up 5 min
17. HP Trng Module File: “ 2 Role of DWLR data in GW Resource Estimation.doc” Version 10/10/02 Page 5
4. Main text
Contents
1. Understanding the Recharge Process 1
2. Lumped Water Balance 2
3. Role of DWLR data 3
18. HP Trng Module File: “ 2 Role of DWLR data in GW Resource Estimation.doc” Version 10/10/02 Page 1
Role of DWLR data in Groundwater Resource Estimation
An important activity of many of groundwater practitioners in India is to estimate the
groundwater resource (mainly monsoon recharge) by a lumped water balance of the
unconfined aquifer, in accordance with GEC-84/97 norms. The high frequency water table
data from the DWLRs can assist a practitioner in conducting such estimations more
rationally and credibly. A few possible applications of such data are described in the
following paragraphs.
1. Understanding the Recharge Process
The high frequency DWLR water table data can assist a groundwater practitioner in
understanding the recharge process. Such an understanding can lead to quantification of
recharge parameters, which may be useful in conducting the resource estimation.
The water infiltrated into the ground surface has to follow a circuitous path through the
unsaturated zone extending from ground to the water table. As the water flows through the
unsaturated zone, a part of it may be held back in soil storage and another part transpired by
the vegetation. The conductivity of dry soil is very low. Thus, at the beginning of a rainy
season (when the soil may be dry), most part of (or all of) the infiltrated water may be held
back in the soil and there may practically be no recharge. However, as the initial rainfall
events build up the soil moisture, the recharge process may be initiated. Thus, the rainfall
has to accumulate to a certain level (RC), before a rainfall event starts producing recharge.
Further, since the water has to flow through the unsaturated zone before it appears as
recharge at the water table, there would be an inevitable lag (Tg) between a rainfall event
and the consequent recharge. As discussed in the following section, recharge parameters
RC and Tg need to be estimated for a proper resource assessment
There are two ways of determining these recharge parameters. First is to simulate the flow
of water through the unsaturated zone extending from the ground surface to the water table.
Unsaturated flow is a complex phenomenon and its simulation requires intensive data of soil,
which may not be available on a regional scale. The other way is to study the impact of the
recharge derived from a rainfall event, on the water table. With the advent of the high
frequency water level data emanating from the DWLRs, it is literally possible to see the
signatures of a rainfall event upon the water table hydrograph and identify the above
mentioned recharge parameters. This is accomplished in the following steps:
• Superpose the hyetographs of all the rainfall events of a rainy season over the
corresponding water table hydrograph.
• Study the water level response following each rainfall event, starting from the beginning
of the rainy season.
• Identify the first rainfall event (say X) which is followed by a conspicuous water table
rise.
• Compute the cumulative rainfall preceding the X rainfall event. This provides the RC
• Study the time lags between the rainfall events (starting from X) and the following water
table rises. Determine an average time lag. This provides Tg.
19. HP Trng Module File: “ 2 Role of DWLR data in GW Resource Estimation.doc” Version 10/10/02 Page 2
For an illustration, refer to the figure 1 showing the rainfall events superposed over the high
frequency water table data observed at Yeldurthy from May 27 to Oct 12, 1999. It is clear
that the infiltration from all the rainfall events prior to Aug 1 does not lead to any recharge. It
apparently is used up in building the soil moisture and providing the evapotranspiration.
Thus RC may be estimated by adding up all the rainfall events preceding Aug 1. Similarly,
the time lag between a productive rainfall event and the consequent recharge is clearly
visible in the figure.
Fig 1 Hydrograph of high frequency water table data observed at Yeldurthy, Medak
district Andhra Pradesh with rainfall events superposed
2. Lumped Water Balance
The current practice of recharge assessment typically is based upon water balance study of
the unconfined aquifer. A water balance study involves an application of the continuity
equation to the unconfined aquifer. The continuity equation in this context is a statement to
the effect that the difference between the net recharge volume (I) and net discharge volume
(O) equals the change of groundwater storage ( S). I, O and S must be in respect of the
same aquifer area and the time period.
I - O = S
∆S = Sy.∆h
Where Sy is the Specific yield of the aquifer, and ∆h is the change in the spatially averaged
water table elevation in the chosen period. This equation can be used to estimate anyone of
the recharge or discharge components, or storage parameter.
Typically, this approach is adopted for estimating the Specific yield and the recharge from
monsoon rainfall. This involves first dividing a hydrologic year into the monsoon and non-
monsoon periods. The Specific yield is estimated by carrying out the water balance of the
non-monsoon period. Subsequently, the rainfall recharge is estimated by carrying out the
water balance study of the monsoon season, employing the pre-computed value of the
Specific yield.
20. HP Trng Module File: “ 2 Role of DWLR data in GW Resource Estimation.doc” Version 10/10/02 Page 3
3. Role of DWLR data
The above stated strategy of water balance studies can be improved upon by employing the
high frequency water table data emanating from DWLRs. These data shall permit a more
realistic water balance study and hence a more accurate assessment of recharge.
3.1 Periods of water balance
For estimation of a specific component of the water balance, it is necessary to select a
period during which the component is just fully generated. Any period less than that shall
lead to an underestimation of the component. A longer period shall attenuate the
predominance of the component and hence shall lead to a less reliable estimate of the
component. Thus for estimating the rainfall recharge by carrying out water balance study of
a rainy season, it shall be desirable to define a period during which the entire rainfall
recharge just occurs. This period could be different from the period of the monsoon rainfall
because of the inevitable time lag between the occurrence of the rainfall and the consequent
recharge. The period must span between the discrete times of the lowest and the highest
water table and not the start and end of the rainy season. Similarly while estimating the
specific yield by carrying out the water balance of the dry period, the duration of the water
balance should incorporate the maximum possible decline from the viewpoint of activation of
the specific yield. This implies that the duration should span between the discrete times of
the highest and the lowest water table.
Thus, for optimal identification of the specific yield it is necessary to carry out the water
balance study from the highest (peak) to the lowest (trough) water table. Similarly for optimal
estimation of rainfall recharge, it is necessary to carry out the water balance study from the
lowest (trough) to the highest (peak) water table. This calls for an identification of the peaks
and troughs and their times of occurrence.
The frequency of manual monitoring of water table is generally not adequate to estimate the
peaks and troughs accurately. The high frequency data from the DWLRs shall permit
identification of true hydrograph of water level. A true hydrograph can lead to estimation of
the pre-monsoon (troughs) and the post-monsoon water table elevations (peaks), and their
times of occurrences; with a far higher resolution. Thus, the identified peak may be higher
and the trough lower, than the corresponding estimates derived from the manually monitored
hydrographs. This is illustrated in figure 2. The figure shows two years’ six hourly DWLR
data, and manually monitored four-yearly data, from Nuthangal village in Nalgonda district of
Andhra Pradesh. The hydrograph of the manually monitored data underestimates the peak
by about a meter.
21. HP Trng Module File: “ 2 Role of DWLR data in GW Resource Estimation.doc” Version 10/10/02 Page 4
Fig 2. Hydrograph showing two years’ six hourly DWLR data, and manually
monitored four-yearly data, from Nuthangal village in Nalgonda district of Andhra
Pradesh
3.2 Selection of water balance years
As already discussed, the rainfall recharge during a rainy season starts occurring only after a
cumulative rainfall RC has occurred from the beginning of the season. Thus, if the total
rainfall in a rainy season is equal to or less than RC, there may not be any rainfall recharge.
As such, the years selected for estimation of recharge should have rainfall well above RC. As
already discussed, this parameter can be estimated from the DWLR-derived water table
hydrographs and the corresponding rainfall hyetographs.
3.3 Identification of effective rainfall events
Identification of unambiguous times of the peak and the trough leads to an explicit
determination of the time period of a water balance study. Thus, all other components of
recharge and discharge in the water balance equation must correspond to this period. In this
context, a special reference is called for in respect of the rainfall. Rainfall does not appear
explicitly in the water balance equation. However, it does appear implicitly as rainfall-
recharge. Thus, only such rainfall should be included in the water balance study, whose
recharge occurs within the identified period. This could mean inclusion of a rainfall event,
which occurred before the period, or exclusion of an event occurring towards the end of the
period. This can be accomplished knowing the lag parameter of recharge Tg. As already
discussed, this parameter can be estimated from the DWLR derived water table hydrographs
and the corresponding rainfall hyetographs Fig 3.
22. HP Trng Module File: “ 2 Role of DWLR data in GW Resource Estimation.doc” Version 10/10/02 Page 5
Fig3. Water table hydrograph and the corresponding rainfall hyetograph from
Garedapally village, Nalgonda district, Andhra Pradesh
3.4 Estimation of evapotranspiration loss
Evapotranspiration from the unconfined aquifer forms a component of the net discharge from
the aquifer. This loss could be quite significant during rainy seasons. Its estimation
essentially requires identification of such periods during which the depth to water table falls
below a shallow critical depth – dependent upon the capillary rise/root zone depth.
Identifying such periods on the basis of just pre and post monsoon depths could be quite
subjective and could lead to distorted estimates. Some periods may be missed altogether;
others may be overestimated or underestimated. On the other hand, water table depth
hydrographs derived from the DWLR data shall have much higher resolution and thus, shall
permit a far more accurate identification of such periods.
23. HP Trng Module File: “ 2 Role of DWLR data in GW Resource Estimation.doc” Version 10/10/02 Page 6
5. Overhead/flipchart master
24. HP Trng Module File: “ 2 Role of DWLR data in GW Resource Estimation.doc” Version 10/10/02 Page 7
6. Handout
25. HP Trng Module File: “ 2 Role of DWLR data in GW Resource Estimation.doc” Version 10/10/02 Page 8
7. Additional handout
These handouts are distributed during delivery and contain test questions, answers to
questions, special worksheets, optional information, and other matters you would not like to
be seen in the regular handouts.
It is a good practice to pre-punch these additional handouts, so the participants can easily
insert them in the main handout folder.
26. HP Trng Module File: “ 2 Role of DWLR data in GW Resource Estimation.doc” Version 10/10/02 Page 1
27. World Bank & Government of The Netherlands funded
Training module # 3
Other applications of DWLR
data
New Delhi, March 2000
CSMRS Building, 4th Floor, Olof Palme Marg, Hauz Khas,
New Delhi – 11 00 16 India
Tel: 68 61 681 / 84 Fax: (+ 91 11) 68 61 685
E-Mail: dhvdelft@del2.vsnl.net.in
DHV Consultants BV & DELFT HYDRAULICS
with
HALCROW, TAHAL, CES, ORG & JPS
28. HP Trng. Module File: “ 3 Other applications of DWLR data.doc” Version 10/10/02 Page 1
Table of contents
Page
1. Module context 2
2. Module profile 3
3. Session plan 4
4. Main text 5
5. Overhead/flipchart master 6
6. Handout 7
7. Additional handout 8
29. HP Trng. Module File: “ 3 Other applications of DWLR data.doc” Version 10/10/02 Page 2
1. Module context
While designing a training course, the relationship between this module and the others,
would be maintained by keeping them close together in the syllabus and place them in a
logical sequence. The actual selection of the topics and the depth of training would, of
course, depend on the training needs of the participants, i.e. their knowledge level and skills
performance upon the start of the course. This module is related to module 2 and should be
referred during the discussions.
30. HP Trng. Module File: “ 3 Other applications of DWLR data.doc” Version 10/10/02 Page 3
2. Module profile
Title : Other applications of DWLR data
Target group : Hydrogeologists, Asst-Hydrogeologists, Senior Technical Assistant
Duration : One Session of 60 minutes
Objectives : After the training the participants will be able to:
• Appreciate the utility of high frequency DWLR water level
monitoring
• Enhance the professional practice beyond the primary task of
Ground water Resource Assessment
Key concepts : Conjunctive use planning
• Identification of over-exploited areas
• Scheduling of Pumpages
• Calibration of aquifer response models
• Identification of Cycles
Training methods : Lecture
Training tools
required
: OHS
Handouts : As provided in this module
Further reading
and references
:
31. HP Trng. Module File: “ 3 Other applications of DWLR data.doc” Version 10/10/02 Page 4
3. Session plan
No Activities Time Tools
1 • Discuss the utility of high resolution water level data in
water logged areas, over-exploited areas, coastal areas.
• Discuss the utility of high resolution data for reliable and
credible model calibration.
30 min OHS
2 • Illustrations 10 min OHS
3 Feedback 15 min
4 Wrap up 5 min
32. HP Trng. Module File: “ 3 Other applications of DWLR data.doc” Version 10/10/02 Page 5
4. Main text
Contents
1. Conjunctive use Planning 1
2. Identification of Over-Exploited areas 2
3. Scheduling of Pumpage 2
4. Calibration of Aquifiers Response Models 3
5. Identifications of Cycles 3
33. HP Trng. Module File: “ 3 Other applications of DWLR data.doc” Version 10/10/02 Page 1
Other applications of DWLR data
The high frequency water level data from DWLRs, apart from permitting a more rational and
credible lumped water balance studies, can be useful in many other ways such as follows:
1. Conjunctive use Planning
Conjunctive use of the canal water and the groundwater in a canal command area is
essentially aimed at avoiding water logging of the land. A land is considered to be water
logged if the water table depth (below ground) is lower than a stipulated critical depth. Thus,
a check for water logged conditions essentially involves a study of the water table depth
hydrograph at a few key points with in the study area. The study leads to identification of
such periods (if any) during which the depth is found to be less than the critical value. The
manually monitored water table hydrographs are generally not of high enough resolution to
identify such periods of water logging. Some water logging periods may be missed
altogether; others may be overestimated or underestimated. On the other hand, water table
depth hydrographs derived from the DWLR data shall have much higher resolution and thus,
shall permit a far more accurate identification of water logging periods. This is illustrated in
figure 1. The figure shows a DWLR-derived water table hydrograph from a canal command
area. The water table rise coinciding with canal opening, and decline after its closure, and
the consequent waterlogged periods are quite visible in the hydrograph. Such an
identification of the waterlogged conditions can lead to much better planning of the
groundwater development in the command area.
Fig 1 shows the Water level hydrograph from canal command area
34. HP Trng. Module File: “ 3 Other applications of DWLR data.doc” Version 10/10/02 Page 2
2. Identification of Over-Exploited areas
Over exploited areas are characterised by falling annual peaks and troughs (refer figure 2).
Thus, to identify such areas, it would be necessary to identify annual peaks and troughs of
successive years. As already mentioned, the hydrograph derived from manually monitored
water levels may miss either peak or trough or both. The high frequency data from the
DWLRs shall permit identification of true hydrograph of water level and hence the peaks and
troughs.
Fig 2 shows the Water level hydrograph from an over exploited area
3. Scheduling of Pumpage
The high frequency data from DWLRs may provide useful prompts regarding opportunity
times for pumpage. A few examples are as follows:
3.1 Coastal Aquifers
In coastal aquifers the times of daily peaks and troughs may to a large extent be governed
35. HP Trng. Module File: “ 3 Other applications of DWLR data.doc” Version 10/10/02 Page 3
by the tidal cycle (refer figure 3). The DWLR data can permit its identification, which may
assist in designing daily pumping schedules.
3.2 Canal Commands
Seepage from canal may recharge the water table and may lead to its rise in the vicinity of
the canal. However, there would be a time lag between the beginning of the discharge in the
canal and the rise (refer figure 4). The rise may sustain for a while even after the closure of
the canal discharge. The DWLR data can assist in identifying such time lags and hence the
opportunity times for the pumpage.
Fig 4 shows recharge to the water table hydrograph showing recharge
contributions after canal openings
4. Calibration of Aquifiers Response Models
Aquifer response modelling is a powerful tool to check the feasibility of a given spatial and
temporal pattern of discharge and/or recharge. Thus, such models are being increasingly put
to use to plan various activities like groundwater development, artificial recharge, conjunctive
use etc. These models are very data intensive and require among others, spatially
distributed aquifer parameters. Such data are almost never available, and thus, have to be
derived by calibration. Calibration implies running the model in the historical period and
arriving at such distributions of the parameters which lead to the closest possible match
between the observed and the computed water level hydrographs/contours. It is evident that
the high frequency data from the DWLRs shall permit far more reliable and credible model
calibrations.
5. Identifications of Cycles
A water level hydrograph represents the resultant effect of a number of phenomenon
many of which may be periodic (that is, self repeating). Each periodic phenomenon
imparts a periodicity to the hydrograph. However, due to their superposition, all these
36. HP Trng. Module File: “ 3 Other applications of DWLR data.doc” Version 10/10/02 Page 4
periodicities may not be visible. Usually the hydrograph derived from manually
monitored data, may comprise only an annual cycle displaying a relatively fast rise
from trough to peak, followed by a short fast recession and finally a prolonged slow
recession till the trough. (However, some exceptional phenomena like extreme
exploitation, artificial recharge, discontinuation of pumpage may modify this trend.)
On the other hand, a hydrograph derived from DWLR data shall comprise apart from
an annual cycle, many cycles of shorter durations like seasonal, barometric, daily,
tidal etc.
5.1 Harmonic Analysis
Harmonic analysis is essentially a numerical algorithm capable of breaking a time
series of a periodic attribute into these hidden periodicities (or say cycles). (The
analysis however, is applicable only to stationary time series i.e., to time series
devoid of any long-term trend.) The analysis reveals periodicities hidden in the time
series. This may ultimately facilitate identification of significant or dominant cycles. A
hydrograph is essentially a time series of water levels and cycles hidden in it may be
identified by Harmonic analysis. The details of Harmonic analysis shall be discussed
subsequently.
37. HP Trng. Module File: “ 3 Other applications of DWLR data.doc” Version 10/10/02 Page 6
5. Overhead/flipchart master
38. Hydrology Project Training Module File: “ 3 Other applications of DWLR data.doc” Version 10/10/02 Page 8
6. Handout
39. Hydrology Project Training Module File: “ 3 Other applications of DWLR data.doc” Version 10/10/02 Page 8
7. Additional handout
These handouts are distributed during delivery and contain test questions, answers to
questions, special worksheets, optional information, and other matters you would not like to
be seen in the regular handouts.
It is a good practice to pre-punch these additional handouts, so the participants can easily
insert them in the main handout folder.
40. World Bank & Government of The Netherlands funded
Training module # 4
How to identify the cycles using
Harmonic Analysis
New Delhi, March 2000
CSMRS Building, 4th Floor, Olof Palme Marg, Hauz Khas,
New Delhi – 11 00 16 India
Tel: 68 61 681 / 84 Fax: (+ 91 11) 68 61 685
E-Mail: dhvdelft@del2.vsnl.net.in
DHV Consultants BV & DELFT HYDRAULICS
with
HALCROW, TAHAL, CES, ORG & JPS
41. HP Trng. Module File: “ 4 How to identify the cycles using Harmonic Analysis.doc” Version 10/10/02 Page 1
Table of contents
Page
1. Module context 2
2. Module profile 3
3. Session plan 4
4. Main text 5
5. Overhead/flipchart master 1
6. Handout 2
7. Additional handout 3
42. HP Trng. Module File: “ 4 How to identify the cycles using Harmonic Analysis.doc” Version 10/10/02 Page 2
1. Module context
While designing a training course, the relationship between this module and the others,
would be maintained by keeping them close together in the syllabus and place them in a
logical sequence. The actual selection of the topics and the depth of training would, of
course, depend on the training needs of the participants, i.e. their knowledge level and skills
performance upon the start of the course. This module is related to module 2 & 3 and should
be referred during the discussions.
43. HP Trng. Module File: “ 4 How to identify the cycles using Harmonic Analysis.doc” Version 10/10/02 Page 3
2. Module profile
Title : How to identify the cycles using Harmonic Analysis
Target group : Hydrogeologists, Asst-Hydrogeologists, Senior Technical Assistant
Duration : One Session of 45 minutes
Objectives : After the training the participants will be able to:
• Understand the concept of Harmonic analysis,
Key concepts : Components of a hydrologic time series
• The Harmonics
• Variance or power of a harmonic
• Perodogram
• Identifiable Cycles
• What to do with Cycles
• Analysis of hydrograph recession
• Estimation of tidal efficiency
• Estimation of barometric efficiency
Training methods : Lecture
Training tools
required
: OHS
Handouts : As provided in this module
Further reading
and references
:
44. HP Trng. Module File: “ 4 How to identify the cycles using Harmonic Analysis.doc” Version 10/10/02 Page 4
3. Session plan
No Activities Time Tools
1 • Discuss the periodicities in time series.
• Describe the harmonics and periodogram
• Discuss the methodology of harmonic analysis, isolation of
dominant cycles.
• Describe the estimation of T&S by analysing the
hydrograph recession
• Describe the estimation of Tidal Efficiency and barometric
efficiency using the hydrograph
30 min OHS
2 • Illustration 5 min OHS
3 Feedback 10 min
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4. Main text
Contents
1. Components of a Hydrologic Time Series 1
2. The Harmonics 1
2.1 Identifiable Harmonics 2
3. Periodogram 2
4. An Illustration 2
5 What to do with cycles 5
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How to identify the cycles using Harmonic Analysis
1. Components of a Hydrologic Time Series
A hydrologic time series (say of groundwater level) represents the resultant effect of a
number of phenomenon many of which may be periodic (that is, self repeating). Each
periodic phenomenon imparts a periodicity to the time series. However, due to their
superposition, all these periodicities may not be visible in the time series. Harmonic analysis
is essentially aimed at breaking up the time series into these hidden periodicities (or say
cycles). This reveals the hidden periodicities. This may ultimately facilitate identification of
significant or dominant cycles.
Each periodicity is represented by an independent time series of the form of a sinusoid wave
(also known as a harmonic) and having its own parameters. The parameters include
wavelength (time period), amplitude and starting point. Thus, first step of the analysis
involves computation of the parameters. The parameters are so computed that superposition
(summation) of the sinusoids leads to the original time series. Further sum of variances of
individual sinusoids equals the variance of the original time series. The computed
parameters permit an identification of the predominant cycles.
2. The Harmonics
Consider a time series comprising n attribute data (Yi, i varying from 0 to n-1) at a uniform
time interval (say ∆t). Thus, the total span of the time series is ∆t.(n-1). Spectral analysis
describes the departure of the attribute (Y) from its arithmetic mean [say, (a0/2)], as a sum of
(n-1)/2 harmonics [Hj, j varying from 1 to (n-1)/2]. Thus. Y at any time t since the beginning
of the series is given by the following equation:
∑
−
=
+=
2/)1(
12
1
)(
n
j
jo HatY
where:
∑
−
=
=
1
0
2 n
i
io Y
n
a
)()( θθ jSinbjCosaH jjj +=
where:
tn
t
∆
=
π
θ
2
∑
−
=
=
1
0
22 n
i
ij
n
ij
CosY
n
a
π
∑
−
=
π
=
1n
0i
ij
n
ij2
SinY
n
2
b
47. HP Trng. Module File: “ 4 How to identify the cycles using Harmonic Analysis.doc” Version 10/10/02 Page 2
The jth
harmonic represents a phenomenon of a time period equal to (n-1). ∆t/j. Since j varies
from 1 to (n – 1)/2, the time period of the identifiable harmonics varies from (n-1) ∆t to 2∆t.
2.1 Identifiable Harmonics
Thus, the smallest identifiable cycle is of time period 2∆t, and time period of the longest
identifiable cycle is the time domain (that is, length) of the time series. However, in practice
only the cycles of time period lying in the range 4∆t to one fourth (or even one sixth) of the
time domain may be identified reliably.
For example, for correctly identifying an annual cycle the length of the time series must be at
least four years. Further, if a daily cycle is to be identified, the interval must be 6 hours or
less.
2.2 Variance or power of a harmonic
The variance (or power) of the jth
harmonic is given by the following expression:
22
jjj baA +=
As pointed out earlier, the variance of the time series equals sum of the variances of the
individual harmonics. Variance is a measure of the scatter of a time series around the mean.
Thus, it can be inferred that variance of a harmonic is a proportional to its relative dominance
in the original time series and therefore, may be viewed as a measure of the relative
significance of the associated phenomenon.
3. Periodogram
A plot of the variance versus the harmonic number (j) is known as periodogram of the time
series. Since this plot comprises discrete number of variance values, it is also known as
discrete power spectrum.
By a visual inspection of the periodogram, one can identify the dominant harmonic numbers,
i.e., serial numbers of the harmonics displaying conspicuously high variance. Knowing the
harmonic numbers, the corresponding time periods can be computed.
4. An Illustration
As an illustration, harmonic analysis is performed on six days’ 144 hourly data of water level
monitored at OUAT campus, Bhubaneswar, from Oct 22 to 28, 1999 (refer figure 1).
Subsequent data were not included in the analysis, since they are rendered non-stationary
by the infamous cyclone. (That is, perform the analysis only such part of the time series
which does not display a long term trend.) The outcome of the analyses revealed that the
time series comprises three dominant cycles of time periods 8, 12 and 24 hours (refer figure
2). The identified cycles are shown in figures 3. The possible composite daily cycle obtained
by superposing these three cycles is shown in figure 4.
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Fig 1. DWLR Data monitored at OUAT campus, Bhubaneswar, Orissa
Fig;2 Periodogram showing the result of the harmonic analysis
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Fig.3. Amplitude of fluctuations in different cycles
Fig.4 Cumulative fluctuation for 6hr, 8hr, 12hr and 24 hr cycle
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5. What to do with cycles?
Harmonic analysis is essentially a mathematical tool facilitating isolation of dominant cycles
from a stationary time series. Such isolated cycles shall be free from the noise and thus,
could be viewed as intrinsic cycles. Being a mathematical tool, harmonic analysis does not
lead to the physics of the identified cycles. The physics has in fact to be identified by the
practitioner of the analysis. This essentially implies identification of phenomenon (such as,
daily pumping/recovery, tidal effects, seasonal rainfall/pumpage/irrigation recharge)
responsible for the identified cycles. The groundwater practitioners can infer the relative
influence of the cycles on the groundwater system and can prioritise the field-work for their
identification accordingly. This can be professionally very gratifying and could result in
improvement of existing practices or evolution of new practices. A few suggestions are as
follows:
5.1 Analysis of hydrograph recession
The recession of a hydrograph comprises its declining phase, that is, from peak to the
trough. The recession may result from processes like natural drainage to the hydraulically
connected streams, pumpage and evapotranspiration.
A recession predominantly resulting from the natural drainage is related to the aquifer
geometry and the diffusivity (T/S). Thus, an analysis of such a recession can provide a
preliminary estimate of the diffusivity, which in turn may lead to estimation of transmissivity
or the storage coefficient, knowing the other. The steps of the computation are as follows:
• Isolate the intrinsic annual cycle from the time series. Derive the corresponding annual
cycle of the driving head by shifting the datum to stage of the draining stream during the
period of the recession.
• Plot the recession curve (log of the driving head versus the time). The curve may reveal
two or more straight lines segments. The first one, usually steep and short, may
represent a fast recession. This is usually followed by a relatively flat and long segment,
representing a moderate/slow recession.
• Assuming a linear relation between log of the driving head and the time, carry out a
regression analysis of the dominant segment of the recession. Hence compute the
depletion time. The time for one log cycle (to the base ten) change in the driving head,
divided by 2.3, is termed as the depletion time.
• The depletion time in general can be expressed as (k.L2
.T/S); where L is the distance of
the sampled well from the draining stream along the flowline and k is a constant
depending upon the boundary conditions. It could vary from 0.405 (drainage on both
sides of the well) to 1.0 (drainage only on one side).
The analysis described above holds for the recession of the outflow hydrograph also. The
outflow may manifest as stream flow during dry season (when the entire stream flow may be
derived from groundwater drainage) or as spring flow. The flow time series if available, may
also be analysed in a similar way. This may provide a means of corroborating the estimate of
diffusivity arrived at by analysing the driving head time series.
5.2 Estimation of tidal efficiency
Tidal efficiency (TE) is defined as the ratio of the piezometric head fluctuation resulting
exclusively from tides, to the causative fluctuation of the tide level. It’s estimate can provide
a tentative value of specific storage (Ss) in accordance with the following equation:
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)1/( TESs −= γθβ
Where γ is the specific weight of water, θ is the porosity of aquifer and β is the inverse of the
bulk modulus elasticity of water.
Tidal efficiency may be estimated by separating tidal cycles from the water level hydrograph
of a piezometer tapping a confined aquifer in coastal region. Knowing the tidal variations in
the sea in the vicinity, the tidal efficiency can be computed.
5.3 Estimation of barometric efficiency
Barometric efficiency (BE) is defined as the ratio of the piezometric head fluctuation resulting
exclusively from the atmospheric pressure fluctuations, to the causative fluctuation of the
atmospheric pressure expressed as head of water. It’s estimate can also provide a tentative
value of specific storage (Ss) in accordance with the following equation:
BESs /γθβ=
Barometric efficiency may be estimated by first identifying the time period of a barometric
cycle from the atmospheric pressure data and subsequently separating a cycle of the
identified period from the water level hydrograph of a piezometer tapping a confined aquifer
in that area.
5.4 Software
The technical consultants to the Hydrology Project have conceptualised an approach for
Harmonic analysis. The approach has been assimilated in a software, christened as DWLR-
ANALYST.
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5. Overhead/flipchart master
53. HP Trng. Module File: “ 4 How to identify the cycles using Harmonic Analysis.doc” Version 10/10/02 Page 2
6. Handout
54. HP Trng. Module File: “ 4 How to identify the cycles using Harmonic Analysis.doc” Version 10/10/02 Page 3
7. Additional handout
These handouts are distributed during delivery and contain test questions, answers to
questions, special worksheets, optional information, and other matters you would not like to
be seen in the regular handouts.
It is a good practice to pre-punch these additional handouts, so the participants can easily
insert them in the main handout folder.
55. World Bank & Government of The Netherlands funded
Training module # 5
Understanding the Concept of Optimal
Monitoring frequency of DWLR
New Delhi, March 2000
CSMRS Building, 4th Floor, Olof Palme Marg, Hauz Khas,
New Delhi – 11 00 16 India
Tel: 68 61 681 / 84 Fax: (+ 91 11) 68 61 685
E-Mail: dhvdelft@del2.vsnl.net.in
DHV Consultants BV & DELFT HYDRAULICS
with
HALCROW, TAHAL, CES, ORG & JPS
56. HP Trng. Module File: “ 5 Concept of Optimal Monitoring frequency of DWLR.doc” Version 10/10/02 Page 1
Table of contents
Page
1. Module context 2
2. Module profile 3
3. Session plan 4
4. Main text 5
5. Overhead/flipchart master 6
6. Handout 7
7. Additional handout 8
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1. Module context
While designing a training course, the relationship between this module and the others,
would be maintained by keeping them close together in the syllabus and place them in a
logical sequence. The actual selection of the topics and the depth of training would, of
course, depend on the training needs of the participants, i.e. their knowledge level and skills
performance upon the start of the course. This module is related to module 2, 3 & 4 and
should be referred during the discussions.
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2. Module profile
Title : Understanding the Concept of Optimal Monitoring frequency
of DWLR
Target group : Hydrogeologists, Asst-Hydrogeologists, Senior Technical Assistant
Duration : One Session of 45 minutes
Objectives : After the training the participants will be able to:
• Arrive at optimal monitoring frequency for any given intended
use of the DWLR data.
Key concepts : • Credibility of derived attribute(s)
• Preserving the hydrograph shape
• Identification of Cycles
• Correlation
Training methods : Lecture
Training tools
required
: OHS
Handouts : As provided in this module
Further reading
and references
:
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3. Session plan
No Activities Time Tools
1 • Describe the strategies to be adopted for arriving at optimal
monitoring frequency, ensuring the credibility of the
attributes, preserving the shape of hydrograph.
30 min
2 • Illustration 5 min OHS
3 Feedback 10 min
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4. Main text
Contents
1. Objective based Optimal Frequency 1
2. Optimizing Criteria 1
3. Optimizing Strategy 2
4. Correlation 3
5 Software 4
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Understanding the Concept of Optimal Monitoring frequency of DWLR
1. Objective based Optimal Frequency
The high frequency data emanating from the DWLRs shall assist the hydrogeologists in
performing their professional activities more objectively and hence more credibly. The
requirement of the frequency can apparently not be uniquely defined and shall depend upon
the intended use of the high frequency data as well as upon the local hydrogeological and
hydrological characteristics. For example, an aquifer having low specific yield may display
faster water level variations and hence may need a higher frequency of monitoring. Similarly,
if the objective is to estimate only the peaks and troughs, a higher frequency may be
adopted around the beginning and the end of the rainy seasons and a lower frequency may
be adopted at other times. On the other hand if the objective is to arrive at a true
hydrograph, a uniformly high frequency may have to be adopted. A few strategies for arriving
at the optimal monitoring frequency are described in the following paragraphs:
2. Optimizing Criteria
It follows from the preceding paragraph that there does not exist any unique optimal
monitoring frequency. The optimal monitoring frequency would depend upon the expectation
from (or intended use/uses of) the hydrograph to be monitored. Some criteria could be as
follows:
2.1 Credibility of Derived Attribute(s)
There may normally be a few well-defined objectives of monitoring the water
table/piezometric head. The objectives may relate to deriving one or more of the
following attributes from the observed hydrograph.
• Peak of the hydrograph
• Trough of the hydrograph
• Range of water level fluctuation
• Time of shallow water level, i.e., time during which the water level rises above a
stipulated shallow critical level
• Time of deep water level, i.e., time during which the water level falls below a stipulated
deep critical level
Thus, the criteria would be to arrive at such monitoring frequency that the desired attribute(s)
as derived from the observed hydrograph is (are) close enough to the true values (i.e., the
values derived from the true hydrograph).
2.2 Preserving the Hydrograph Shape
This implies that the selected monitoring interval should be such that the monitored
hydrograph resembles closely with the true hydrograph. This is indeed the most stringent
and all-encompassing expectation requiring uniformly small monitoring intervals. The
intervals would depend upon the degree of the desired resemblance. As discussed
subsequently, correlation is an index of similarity between the shapes of two time series. It
shall be an index of resemblance if the two time series display the variation of the same
variable. Thus, the criteria could be to arrive at such an interval which ensures a high
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enough correlation between the true and the monitored hydrographs.
2.3 Identification of Cycles
As already stated, the cycle of smallest time period that can be identified (or separated) by
the Spectral analysis is 4∆t, where ∆t is the interval between two successive water level
data. Thus, the monitoring interval has to be at lone fourth of the time period of the smallest
cycle intended to be identified.
3. Optimizing Strategy
It follows from the above discussion that for optimising the monitoring frequency, we shall
require the true hydrograph. The hydrograph of smallest feasible interval (say hourly) could
be deemed as the true hydrograph. Therefore, it is necessary to first procure a time series of
water level with small enough monitoring interval. Subsequently under-sampled hydrographs
of increasing monitoring intervals, are simulated as follows:
• Knock off the intermittent data from the true hydrograph to simulate the under-sampled
series of the chosen larger interval.
• Simulate the under-sampled hydrograph by estimating the knocked off data by linear
interpolation.
The simulated under-sampled hydrographs may be analysed to arrive at the optimal
monitoring frequency as follows:
3.1 Credible Attribute Estimation
Compute the desired attribute from the true hydrograph and from each of the simulated
under-sampled hydrographs. Terming the attribute value as computed from the true
hydrograph as X and the values computed from ith
simulated under-sampled hydrograph as
Ai, compute the loss array [Li = ABS(X - Ai)/S]. Here, S is a relevant quantity for normalizing
the error. Thus the array represents the loss of information (expressed as a fraction of the
chosen S) on account of increasing the time interval from the minimum feasible to the one
incorporated in ith
simulated under-sampled hydrograph. This array could be interpreted for
specific attributes as follows:
Peak, Trough and Range: (Over-estimation of depth to peak, under-estimation of depth to
trough, and consequent under-estimation of the range) Selecting S as the true range (that
is, vertical distance from trough to peak in the true hydrograph), the array shall represent the
loss of information expressed as a fraction of the true range.
Time of shallow/deep water level: Selecting S as true period, the array shall represent the
loss expressed as a fraction of the true time.
Plot the computed array [Li ] versus the corresponding intervals of the simulated under-
sampled hydrographs. Assigning an acceptable level of the loss, pick up the optimal interval
of monitoring.
3.2 Preservation of Hydrograph Shape
The simulated under-sampled hydrographs of increasing time interval may be successively
compared visually with the true hydrograph. This may lead to a threshold interval beyond
which the two series may cease to resemble each other. Alternatively, this could be done
more objectively in the following steps:
• Compute the correlation (described in the following section) between the true
hydrograph and each of the simulated under-sampled hydrographs.
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• Plot the computed correlations against the time interval.
• Pick up the optimal interval corresponding to the minimum desired similarity between the
two hydrographs.
•
3.3 Identification of Cycles
The longest permissible interval for identifying a cycle of any time period, by Harmonic
analysis is half the time period. For a more reliable identification of the cycle, it may be
desirable to further restrict the longest permissible interval say to one fourth of the time
period. Thus, for identifying a daily cycle, it may be desirable to have an interval no bigger
than 6 hours.
4. Correlation
This statistic determines the degree of linear interrelation (that is, scaled similarity) between
two time series.
A direct linear relation (that is, as one series rises, the other also rises and vice versa) is
termed as positive correlation. An inverse linear relation (that is, as one series rises, the
other declines and vice versa) is termed as negative correlation. If the rise of one series has
apparently no effect on the other, the two series are known to be uncorrelated.
The two series must have the same data frequency and an adequately long overlap. A
correlation between two series falling in different time spans can be computed by analysing
the overlapping period only, that is, by curtailing one or both the series. If there is no
overlapping period, the correlation can not be estimated. If the two series comprise data at
different frequencies, it is necessary to manipulate one of the two series to ensure
frequency-compatibility. Thus, either the series of higher frequency (say series of DWLR
data) may be pruned, or the missing data in the series of low frequency (say series of
manual data) may be interpolated.
This correlation is essentially a normalised covariance between the pivotal and the derived
series. Thus, the correlation ® between two series (xi, i = 1, 2, ……., n) and (yi, i = 1, 2,
………, n) shall be given by the following equation:
COR =
yx
ii
n
i
SS
yyxx
.
)).((
1
−−∑=
;1
n
x
x
i
n
i
∑=
=
n
y
y
i
n
i
∑=
= 1
Sx = 2
1
)( xxi
n
i
−∑=
; Sx = 2
1
)( yyi
n
i
−∑=
;
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Two positively correlated time series shall have a correlation greater than zero and it may go
up to +1. A correlation of +1 indicates a perfect positive correlation, that is, a direct
proportionality of the fluctuations in the two series and hence a perfect linearity with positive
gradient between the two variables. Similarly, two negatively correlated time series shall
have a correlation less than zero and it may go up to –1. A correlation of –1 indicates a
perfect negative correlation, that is, an inverse proportionality and hence a perfect linearity
with negative slope. Two uncorrelated series shall have a zero correlation.
5 Software
The above stated approach for optimising the monitoring frequency was conceptualised by
technical consultants to the Hydrology Project. The approach has been assimilated in a
software, christened as DWLR-ANALYST.
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5. Overhead/flipchart master
66. HP Trng. Module File: “ 5 Concept of Optimal Monitoring frequency of DWLR.doc” Version 10/10/02 Page 7
6. Handout
67. HP Trng. Module File: “ 5 Concept of Optimal Monitoring frequency of DWLR.doc” Version 10/10/02 Page 8
7. Additional handout
These handouts are distributed during delivery and contain test questions, answers to
questions, special worksheets, optional information, and other matters you would not like to
be seen in the regular handouts.
It is a good practice to pre-punch these additional handouts, so the participants can easily
insert them in the main handout folder.
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