This document discusses the design of hydro-meteorological networks. It begins by defining hydrology and explaining the need for engineering hydrology data. It then describes the types of data collected, including meteorological, hydrological, and spatial data. Principles of data analysis are outlined, including correcting measurements, estimating missing data, and checking consistency. The document discusses objectives and types of hydro-meteorological networks. It provides guidelines for the design process, including evaluating existing networks and prioritizing stations. World Meteorological Organization criteria for minimum network density are also presented.
Presentation by Andrew Warren (Deltares, Netherlands) at the Climate Adaptation Symposium 2023, during the Delft Software Days - Edition 2023 (DSD-INT 2023). Wednesday, 29 November 2023, Delft.
Presentation by Umit Taner (Deltares, Netherlands) at the Climate Adaptation Symposium 2023, during the Delft Software Days - Edition 2023 (DSD-INT 2023). Wednesday, 29 November 2023, Delft.
Big Data Framework for Predictive Risk Assessment of Weather Impacts on Elect...Power System Operation
Loss of electric power leads to major economic, social, and environmental impacts. It is estimated that the Annual economic impacts from weather-related electric grid outages in the U.S. result in as high as $150 billion. Due to the high level of environmental exposure of the electric utility overhead infrastructure, the most dominant cause of electricity outages is weather impact. More than 70% of electric power outages are caused by weather, either directly (e.g., lightning strikes to the equipment, trees coming in contact with lines under high wind speeds), or indirectly due to weather-caused increases in equipment deterioration rates or overloading (e.g. insulation deterioration, line overloading due to high temperature causing high demand). This paper illustrates how the impact of severe weather can be significantly reduced, and in some cases even eliminated, by accurate prediction of where faults may occur and what equipment may be vulnerable. With this predicted assessment of network vulnerabilities and expected exposure, adequate mitigation approaches can be deployed.
To solve the problem, variety of approaches have been deployed but none seem to be addressing the problem comprehensively. We are introducing a predictive approach that uses Big Data analytics based on machine learning using variety of utility measurements and data not coming from utility infrastructure, such as weather, lightning, vegetation, and geographical data, which also comes in great volumes, is necessary. The goal of this paper is to provide a comprehensive description of the use of Big Data to assess weather impacts on utility assets. In the study reported in this paper a unified data framework that enables collection and spatiotemporal correlation of variety of data sets is developed. Different prediction algorithms based on linear and logistic regression are used. The spatial and temporal dependencies between components and events in the smart grid are leveraged for the high accuracy of the prediction algorithms, and its capability to deal with missing and bad data. The study approach is tested on following applications related to weather impacts on electric networks: 1) Outage prediction in Transmission, 2) Transmission Line Insulation Coordination, 3) Distribution Vegetation Management, 4) Distribution Transformer Outage Prediction, and 5) Solar Generation Forecast. The algorithms shows high accuracy of prediction for all applications of interest.
Flood is the most devastating environmental hazard throughout the world causing loss of precious human lives
and damage to infrastructure. They occur by unusual overflow of water over the banks of rivers or channels
thus inundating the surrounding area. The magnitude and intensity of floods depends on hydrological and
physical characteristics of the catchment and river channel. Adverse effects of these floods can be alleviated
through mapping of floodplain which is essentially the area around the channel which is likely to be flooded.
One of the methods of floodplain delineation is modeling the river flow using computer models such as the
Hydrologic Engineering Center River Analysis System (HEC-RAS). In this study the application of 2D HEC-RAS
river model is used to develop a floodplain map of river Kabul.
Sachpazis: ewra2005, A Hydrogeotechnical Integrated SystemDr.Costas Sachpazis
«A Hydrogeotechnical Integrated System for Water Resources Management of Attica – Greece». Presented in the 6th International Conference of the European Water Resources Association (EWRA2005), held in Menton (France) on 7-10 September 2005. Cooperation with Manoliadis Odysseus, Baronos Athina, and Tsapraili Chrysanthy. 2005
Low-Cost Approximate and Adaptive Techniques for the Internet of ThingsDemetris Trihinas
Seminar talk given at the Univerisity of Pittsburgh providing an overview of self-adaptive monitoring techniques tackling data management and energy-efficiency for the internet of things
Presentation by Andrew Warren (Deltares, Netherlands) at the Climate Adaptation Symposium 2023, during the Delft Software Days - Edition 2023 (DSD-INT 2023). Wednesday, 29 November 2023, Delft.
Presentation by Umit Taner (Deltares, Netherlands) at the Climate Adaptation Symposium 2023, during the Delft Software Days - Edition 2023 (DSD-INT 2023). Wednesday, 29 November 2023, Delft.
Big Data Framework for Predictive Risk Assessment of Weather Impacts on Elect...Power System Operation
Loss of electric power leads to major economic, social, and environmental impacts. It is estimated that the Annual economic impacts from weather-related electric grid outages in the U.S. result in as high as $150 billion. Due to the high level of environmental exposure of the electric utility overhead infrastructure, the most dominant cause of electricity outages is weather impact. More than 70% of electric power outages are caused by weather, either directly (e.g., lightning strikes to the equipment, trees coming in contact with lines under high wind speeds), or indirectly due to weather-caused increases in equipment deterioration rates or overloading (e.g. insulation deterioration, line overloading due to high temperature causing high demand). This paper illustrates how the impact of severe weather can be significantly reduced, and in some cases even eliminated, by accurate prediction of where faults may occur and what equipment may be vulnerable. With this predicted assessment of network vulnerabilities and expected exposure, adequate mitigation approaches can be deployed.
To solve the problem, variety of approaches have been deployed but none seem to be addressing the problem comprehensively. We are introducing a predictive approach that uses Big Data analytics based on machine learning using variety of utility measurements and data not coming from utility infrastructure, such as weather, lightning, vegetation, and geographical data, which also comes in great volumes, is necessary. The goal of this paper is to provide a comprehensive description of the use of Big Data to assess weather impacts on utility assets. In the study reported in this paper a unified data framework that enables collection and spatiotemporal correlation of variety of data sets is developed. Different prediction algorithms based on linear and logistic regression are used. The spatial and temporal dependencies between components and events in the smart grid are leveraged for the high accuracy of the prediction algorithms, and its capability to deal with missing and bad data. The study approach is tested on following applications related to weather impacts on electric networks: 1) Outage prediction in Transmission, 2) Transmission Line Insulation Coordination, 3) Distribution Vegetation Management, 4) Distribution Transformer Outage Prediction, and 5) Solar Generation Forecast. The algorithms shows high accuracy of prediction for all applications of interest.
Flood is the most devastating environmental hazard throughout the world causing loss of precious human lives
and damage to infrastructure. They occur by unusual overflow of water over the banks of rivers or channels
thus inundating the surrounding area. The magnitude and intensity of floods depends on hydrological and
physical characteristics of the catchment and river channel. Adverse effects of these floods can be alleviated
through mapping of floodplain which is essentially the area around the channel which is likely to be flooded.
One of the methods of floodplain delineation is modeling the river flow using computer models such as the
Hydrologic Engineering Center River Analysis System (HEC-RAS). In this study the application of 2D HEC-RAS
river model is used to develop a floodplain map of river Kabul.
Sachpazis: ewra2005, A Hydrogeotechnical Integrated SystemDr.Costas Sachpazis
«A Hydrogeotechnical Integrated System for Water Resources Management of Attica – Greece». Presented in the 6th International Conference of the European Water Resources Association (EWRA2005), held in Menton (France) on 7-10 September 2005. Cooperation with Manoliadis Odysseus, Baronos Athina, and Tsapraili Chrysanthy. 2005
Low-Cost Approximate and Adaptive Techniques for the Internet of ThingsDemetris Trihinas
Seminar talk given at the Univerisity of Pittsburgh providing an overview of self-adaptive monitoring techniques tackling data management and energy-efficiency for the internet of things
In literature, there are two categories for the analysis of Water Distribution Networks (WDN). The first is Demand Driven Analysis (DDA) at which engineers satisfies the demand at each node and then calculate the pressure in the design of new networks. Softwares like EPANET and other commercial ones comprises the DDA methodologies. Normally, engineers do not take into consideration the sudden events (i.e excessive firefighting demand, excessive demand in some junctions, pipe failure, or pump failure). These events may produce negative pressure problems to the network leading to deficient nodes. In the second category named Pressure Driven Analysis (PDA), researchers attempted to solve the negative pressure problem. Indeed, the PDA methods are treated into three different ways. (i) Modifying the hydraulic solver source code by introducing a new PDA method, or (ii) adding artificial elements like check valve, internal dummy node, flow control valve, reservoir or emitter to network demand nodes, or (iii) adding some of the previous explained artificial elements to demand nodes which are suffering from pressure deficiency. Many researchers try to take into consideration the extended period simulation (EPS) in the water network. Until now, there are many challenges facing researchers to come over the problem of deficient nodes. In this paper, a comparison between results (Demand & Pressure) of a case study when using different PDA methods.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
DEVELOPMENT OF CLEAN WATER DISTRIBUTION NETWORK CAPACITY BY USING WATERCADIAEME Publication
In this study a network model was constructed for the hydraulic analysis and
design of a small community (Kedungkandang District) water distribution network in
East Java Province of Indonesia by using Water cad simulator. The analysis included
a review of pressures, velocities and head loss gradients under steady state average
day need. The clean water availability in the location study is 560 l/s, however the
local society that is 23,213 consumers can only use in amount of 116 l/s. The
assessment of existing condition due to the pipe hydraulic condition and the
development of capacity network increasing are carried out by using the program of
Water cad vs. XM Edition. The development condition consists of 27,284 populations.
Result indicates that the average discharge need is 41.763 l/s, however in the peak
hour need there is needed 65.150 l/s on 2031. The water pressure in the development
area is 2.3 atm on 06.00 am
Viene descritta la piattaforma EiAGRID/SmartGeo, un portale di calcolo e analisi dati per sismica a riflessione e acquisizioni GPR multioffset, che mette a disposizione dell'utente una serie di servizi di calcolo e di processing accessibili attraverso un'interfaccia Web basata su un'infrastruttura Grid. La piattaforma consente all'utente in campo, tramite un dispositivo client (laptop, PC, tablet, etc.), di usufruire di una serie di servizi computazionali che risiedono e girano su server remoti, secondo il paradigma SaaS (Software as a Service). Verranno illustrate le soluzioni modellistiche e tecnologiche adottate e alcuni risultati ottenuti su dati reali.
2018 National Tanks Conference & Exposition: HRSC Data VisualizationAntea Group
Two of our High-Resolution Site Characterization (HRSC) Data Visualization posters featured at the 2018 NTC Conference in Louisville, KY.
1. Using Data Management and 3-Dimensional Data Visualization to Generate More Complete Conceptual Site Models and Streamline Site Closure
2. High-Resolution Site Characterization (HRSC) and 3-Dimensional Data Visualization for a Fractured Rock Site: A Path to Streamlined Closure
Information and Communication Technology in Water Management: A Case StudyBRNSS Publication Hub
Smartphones, smart watches, smart cars, and smart grids - everything is smart nowadays, even water. Living in the smart city, Bhubaneswar, I have never encountered a lack of fresh water. However, the global picture looks quite different. Water scarcity affects every continent. According to a UN investigation, around 1.2 billion people live in areas of physical water scarcity. A further 1.6 billion people face economic water shortages (where countries lack the necessary infrastructure to take water from rivers and aquifers). There is enough fresh water on the planet for 7 billion people but it is distributed unevenly and too much of it is wasted or polluted. This study will find a solution of this problem.
Assessment and Analysis of Maximum Precipitation at Bharkawada Village, Palan...RSIS International
Efficient Storm water network is the main tool to prevent the water gatheration and scattering of a city. Selecting the Bharkawada as study area and its problem was identified to be of very less effective drainage system. In this study methods have been adopted to identify the possibilities of completing the research for designing the storm water drainage design. Our main aim is to design a very efficient and rpid drainage system which should drain the water very fastly with less concentration time and less spreading of water with less provision of slope. The present design is based on rainfall data. Past 30 years rainfall data has been taken for study. The system has been designed considering in total of 65% of the impervious area. Estimated rainfall intensity has been calculated as 33.02527 mm/hour with a recurrence interval of 2 years from the detailed analysis of rainfall data of 34 years. Rainfall Intensity is estimated after frequency analysis of the rainfall data. The calculated runoff is 25.056 m3/s, which can be used as a design discharge for network designing. Different methods can be used for runoff estimation. Here, Rational method seems to be best for use in estimation of storm water runoff. The outfalls of system are directed to proposed lakes. Ere at this stage rainfall calculations have been done and in future work complete rainfall and runoff analysis will be carried out for storm water network.
Climate data can provide a great deal of information about the atmospheric environment that impacts almost all aspects of human endeavour. This module explains the importance of climate data, its storage, security, applications and other aspects, in a nutshell.
In literature, there are two categories for the analysis of Water Distribution Networks (WDN). The first is Demand Driven Analysis (DDA) at which engineers satisfies the demand at each node and then calculate the pressure in the design of new networks. Softwares like EPANET and other commercial ones comprises the DDA methodologies. Normally, engineers do not take into consideration the sudden events (i.e excessive firefighting demand, excessive demand in some junctions, pipe failure, or pump failure). These events may produce negative pressure problems to the network leading to deficient nodes. In the second category named Pressure Driven Analysis (PDA), researchers attempted to solve the negative pressure problem. Indeed, the PDA methods are treated into three different ways. (i) Modifying the hydraulic solver source code by introducing a new PDA method, or (ii) adding artificial elements like check valve, internal dummy node, flow control valve, reservoir or emitter to network demand nodes, or (iii) adding some of the previous explained artificial elements to demand nodes which are suffering from pressure deficiency. Many researchers try to take into consideration the extended period simulation (EPS) in the water network. Until now, there are many challenges facing researchers to come over the problem of deficient nodes. In this paper, a comparison between results (Demand & Pressure) of a case study when using different PDA methods.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
DEVELOPMENT OF CLEAN WATER DISTRIBUTION NETWORK CAPACITY BY USING WATERCADIAEME Publication
In this study a network model was constructed for the hydraulic analysis and
design of a small community (Kedungkandang District) water distribution network in
East Java Province of Indonesia by using Water cad simulator. The analysis included
a review of pressures, velocities and head loss gradients under steady state average
day need. The clean water availability in the location study is 560 l/s, however the
local society that is 23,213 consumers can only use in amount of 116 l/s. The
assessment of existing condition due to the pipe hydraulic condition and the
development of capacity network increasing are carried out by using the program of
Water cad vs. XM Edition. The development condition consists of 27,284 populations.
Result indicates that the average discharge need is 41.763 l/s, however in the peak
hour need there is needed 65.150 l/s on 2031. The water pressure in the development
area is 2.3 atm on 06.00 am
Viene descritta la piattaforma EiAGRID/SmartGeo, un portale di calcolo e analisi dati per sismica a riflessione e acquisizioni GPR multioffset, che mette a disposizione dell'utente una serie di servizi di calcolo e di processing accessibili attraverso un'interfaccia Web basata su un'infrastruttura Grid. La piattaforma consente all'utente in campo, tramite un dispositivo client (laptop, PC, tablet, etc.), di usufruire di una serie di servizi computazionali che risiedono e girano su server remoti, secondo il paradigma SaaS (Software as a Service). Verranno illustrate le soluzioni modellistiche e tecnologiche adottate e alcuni risultati ottenuti su dati reali.
2018 National Tanks Conference & Exposition: HRSC Data VisualizationAntea Group
Two of our High-Resolution Site Characterization (HRSC) Data Visualization posters featured at the 2018 NTC Conference in Louisville, KY.
1. Using Data Management and 3-Dimensional Data Visualization to Generate More Complete Conceptual Site Models and Streamline Site Closure
2. High-Resolution Site Characterization (HRSC) and 3-Dimensional Data Visualization for a Fractured Rock Site: A Path to Streamlined Closure
Information and Communication Technology in Water Management: A Case StudyBRNSS Publication Hub
Smartphones, smart watches, smart cars, and smart grids - everything is smart nowadays, even water. Living in the smart city, Bhubaneswar, I have never encountered a lack of fresh water. However, the global picture looks quite different. Water scarcity affects every continent. According to a UN investigation, around 1.2 billion people live in areas of physical water scarcity. A further 1.6 billion people face economic water shortages (where countries lack the necessary infrastructure to take water from rivers and aquifers). There is enough fresh water on the planet for 7 billion people but it is distributed unevenly and too much of it is wasted or polluted. This study will find a solution of this problem.
Assessment and Analysis of Maximum Precipitation at Bharkawada Village, Palan...RSIS International
Efficient Storm water network is the main tool to prevent the water gatheration and scattering of a city. Selecting the Bharkawada as study area and its problem was identified to be of very less effective drainage system. In this study methods have been adopted to identify the possibilities of completing the research for designing the storm water drainage design. Our main aim is to design a very efficient and rpid drainage system which should drain the water very fastly with less concentration time and less spreading of water with less provision of slope. The present design is based on rainfall data. Past 30 years rainfall data has been taken for study. The system has been designed considering in total of 65% of the impervious area. Estimated rainfall intensity has been calculated as 33.02527 mm/hour with a recurrence interval of 2 years from the detailed analysis of rainfall data of 34 years. Rainfall Intensity is estimated after frequency analysis of the rainfall data. The calculated runoff is 25.056 m3/s, which can be used as a design discharge for network designing. Different methods can be used for runoff estimation. Here, Rational method seems to be best for use in estimation of storm water runoff. The outfalls of system are directed to proposed lakes. Ere at this stage rainfall calculations have been done and in future work complete rainfall and runoff analysis will be carried out for storm water network.
Climate data can provide a great deal of information about the atmospheric environment that impacts almost all aspects of human endeavour. This module explains the importance of climate data, its storage, security, applications and other aspects, in a nutshell.
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Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
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Design and Analysis of Algorithms-DP,Backtracking,Graphs,B&B
Chapter 1.pdf
1. Hydro-Metrological Network Design
HWRE-3122
Mengistu .Z (MSc in Hydraulic Engineering )
Lecturer @ Hydraulic and Water Resources Engineering department
Mizan Tepi university
Email: mengistu.zantet@gmail.com
mengistuzantet@mtu.edu.et
P.O.Box: 260
Tepi, Ethiopia
03-Dec-22 1
2. 1.1 General aspects of Hydro-Metrological Network Design
1) General
2) Hydrologist data type
3) Sources of hydrological data:
4) Principles of Data Analysis
5)Design of meteorological data network
6)site selection survey, general site selection guideline, criteria for
water level gauging sites,
7)sediment discharge and sedimentation, and water quality stations
03-Dec-22
mengistuzantet@mtu.edu.et
lecturer@ Hydraulic and water
resources Engineering Department 2
3. General
Hydrology means the science of water and it deals
with the Occurrence, Circulation &Distribution of
water of the earth and earth’s atmosphere.
In general hydrology is a very broad subject of an
inter-disciplinary nature drawing support from allied
sciences such as: Meteorology, Geology, Statistics
Chemistry, Physics & Fluid mechanics
03-Dec-22
mengistuzantet@mtu.edu.et
lecturer@ Hydraulic and water
resources Engineering Department 3
4. We need of Engineering Hydrology
03-Dec-22
mengistuzantet@mtu.edu.et
lecturer@ Hydraulic and water
resources Engineering Department 4
For Estimation of water resources
For Study of processes such as: Precipitation,
Runoff, Evapotranspiration & their interaction
Study of problems such as: Floods & drought
Strategies to combat them
Design & operation of water resources engineering projects
such as: Irrigation, Water supply, Flood control, Water power
5. Hydrologist data type
03-Dec-22
mengistuzantet@mtu.edu.et
lecturer@ Hydraulic and water
resources Engineering Department 5
1) Meteorological Data
Weather records (temperature, humidity & wind speed)
Precipitation data
Evaporation & transpiration data
Infiltration characteristics of an area / catchment
6. Cont.….
2) Hydrological Data
Stream-flow records
Sediment Data
Groundwater characteristics
Water quality data
3) spatial data
Soil of the area
Land use and Land cover and
Physical & geological
characteristics of the area
03-Dec-22
mengistuzantet@mtu.edu.et
lecturer@ Hydraulic and water
resources Engineering Department 6
7. Sources of hydrological data:
03-Dec-22
mengistuzantet@mtu.edu.et
lecturer@ Hydraulic and water
resources Engineering Department 7
In Ethiopia,
Meteorological data are collected from Ethiopian Meteorological
service agency.
Stream flow data of various rivers and streams can be found from Ministry of
water resources or any other concerned bureaus or departments.
Data on Evaporation, transpiration, infiltration will be available in ministry of
agriculture, or water resources or any other concerned departments.
The physical data of the area can be obtained from topographic map of the area
available with mapping agencies or specific studies conducted at the respective
areas.
8. Principles of Meteorological data analysis
03-Dec-22
mengistuzantet@mtu.edu.et
lecturer@ Hydraulic and water
resources Engineering Department 8
a) Corrections to Point Measurements
b) Estimation of Missing Data
c) Estimating Mean Precipitation Over an Area
d) Checking the Consistency of Point Measurements
9. A) Corrections to Point Measurements
evaporation losses
Systematic errors
Instrument errors
wind eddies affecting the catch of the
smaller raindrops and snowflakes.
03-Dec-22
mengistuzantet@mtu.edu.et
lecturer@ Hydraulic and water
resources Engineering Department 9
10. B) Estimation of Missing Data
03-Dec-22
mengistuzantet@mtu.edu.et
lecturer@ Hydraulic and water
resources Engineering Department 10
1)Simple arithmetic average Method
2) Normal ratio Method
3) Regression Method
4) Inverse Distance (Grid) Method
11. c) Estimating Mean Precipitation Over an Area
03-Dec-22
mengistuzantet@mtu.edu.et
lecturer@ Hydraulic and water
resources Engineering Department 11
1) Arithmetical-Mean Method
2) Thiessen- polygon Mean Method
3) Isohyet Mean Method
4) Quadrant Mean Method/ Grid point Mean
Method
12. d) Checking the Consistency of Point Measurements
03-Dec-22
mengistuzantet@mtu.edu.et
lecturer@ Hydraulic and water
resources Engineering Department 12
the most common method of checking for inconsistency
of a record is the Double-Mass Curve analysis (DMC).
13. Hydro-Metrological Network Design
03-Dec-22
mengistuzantet@mtu.edu.et
lecturer@ Hydraulic and water
resources Engineering Department 13
is an organized system for collection of information of
specific kinds such as precipitation, runoff, water
quality, sedimentation and other climate parameters.
Data on temporal and spatial characteristics of water
resources of a region are obtained by a network of
observational stations
14. Objectives of Hydro-Metrological network design
03-Dec-22
mengistuzantet@mtu.edu.et
lecturer@ Hydraulic and water
resources Engineering Department 14
Water resources assessment at basin or sub-basin scale
Water resources assessment for administrative geographical
unit
Water resources project planning like, irrigation, water
supply ,hydropower etc
Flood management
Assessing impacts of Climate Change on Water Resources
15. Why hydrometeorologic networks?
An appropriate hydrometeorologic network provide the
desired information
Principle: you can not manage thing that you are not
measure
03-Dec-22
mengistuzantet@mtu.edu.et
lecturer@ Hydraulic and water
resources Engineering Department 15
16. Monitoring hydrometeorologic Networks
is composed of a group of observational stations, set-
up and operated to observe underlying variables and
address a single or a set of interrelated objectives.
Average area served by a hydrological station is known
as density of a hydrological network.
03-Dec-22
mengistuzantet@mtu.edu.et
lecturer@ Hydraulic and water
resources Engineering Department 16
17. Minimum hydrometeorologic Network
Minimum number of stations necessary to initiate planning
for the economic development of the water resources
Minimum network will avoid serious deficiencies in
developing and managing water resources on a scale
commensurate with the overall level of economic
development of the country
03-Dec-22 17
18. Cont.…
03-Dec-22
mengistuzantet@mtu.edu.et
lecturer@ Hydraulic and water
resources Engineering Department 18
If the existing may not be adequate for the
formulation of detailed development plans,
Developed as rapidly as possible by
incorporating existing stations as appropriate.
19. Design of hydrometeorologic Monitoring Networks
Determine cost of establishing and running network:
costs for land acquisition,
station construction,
equipment, operation, maintenance, staff costs, etc.
An optimum network is obtained when amount and quality of
data collected is economically justifiable and meets users’ needs.
03-Dec-22 19
20. Types of Hydrometeorologic Networks
BASIC OR
PRIMARY
NETWORK:
Provide
basic/minimu
m data for
studies and
should run
continuously
and
indefinitely.
Low density
of stations.
SECONDARY
NETWORK
: are operational for a
short time to
establish a good
correlation with
principal stations.
Density
supplementary to
basic network, to
meet accuracy
demands.
DEDICATED
NETWORK
put in place for a
certain project:
project objectives
determine network
density and period of
operation.
NETWORKS
FOR
REPRESENTAT
IVE BASINS:
to study certain
phenomena in
detail, e.g., for
research
purpose.
21. Hydrometeorologic Network Design Process
03-Dec-22
mengistuzantet@mtu.edu.et
lecturer@ Hydraulic and water
resources Engineering Department 21
1) Network design activity begins with collection of basin maps
and background information about the area/region.
2) Identify the objectives of the network by define the data users
and the purpose for which the data is needed. What is the
required data frequency?
3) Critically evaluate the existing network and find out how
well it meets the required objectives?
4) Review existing database to identify gaps, ascertain variability
in catchment behavior.
22. Cont..
03-Dec-22
mengistuzantet@mtu.edu.et
lecturer@ Hydraulic and water
resources Engineering Department 22
5) Identify the weather the existing network is over-design (if
any) or under designed. New stations may be proposed and
existing stations may be deleted/shifted (if required so).
6) Prioritize stations by following appropriate classification
system.
7) Decide on approximate location of sites and carryout site
23. Cont..
03-Dec-22
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8) Review revised network in relation to overall
objectives and available budget; adjust it as necessary.
9) Estimate average capital and recurrent costs of
installing and maintaining different categories of stations
and overall cost of operating and maintaining the network.
10) Prepare a realistic and achievable implementation
plan.
24. WMO Criteria for Minimum Network Density
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The World Meteorological Organization (1976) has
recommended the minimum network densities for general
hydro-meteorological practices.
I. For plain regions of temperate Mediterranean and tropical
zones one station for 600- 900 sq. km.
II. For mountainous region of temperate Mediterranean and
tropical zones one station for 100-250 sq. km.
III. For arid and polar region one station for 1,500-10,000 sq.
25. Prioritisation system
– In the first instance, “ideal” network size is determined.
– All potential users of data should be consulted.
– Each station in “ideal” network should be prioritised.
Hydrometeorologic Network Density
Category Priority Relative Importance
A High Major, multi-purpose WRD project, State
boundary river, operation of major scheme,
major ungauged basin, heavily polluted
majorWS source
B Medium Medium scale WRD project, secondary basin,
industrial development area (i.e. potential
water quality problems)
C Low Minor irrigation project site, secondary
gauging station on tertiary tributary, major
water course but already extensively gauged
26. Financial Aspects of hydrometeorologic network design
Monetary requirements should match with the
budget so that the proposed network is sustainable.
In case of deficit in the budget, the network should
be realigned or additional budget should be
arranged.
Stations in the network may be prioritized to best
attain the objectives, given the constraints.
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27. Rain gauge Network Design
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To get a representative picture of a storm over a
catchment the number of rain gauges should be as large as
possible.
On the other hand economic considerations to a large
extent and other considerations such as topography,
accessibility to some extent restrict the number of gauges
to be maintained
28. Objective of measuring rainfall network
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1) Water resources assessment, projects planning and management
1) Drinking/ Industrial/ Municipal water supply, Navigation,
Recreation Activities
2) Hydrologic design of structures,
3) Agriculture Water Management
1) Irrigation, Rain-fed agriculture
4) Disaster warning systems, and protection:
1) Flooding, Drainage, hydrological forecasting
5) Ecologically sound water systems:
1) Ecology and Forestry, Erosion, Discharge of effluents
Hydropower generation
Research
29. Methods of Rainfall Network Design
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1. Cv, Method
2. Key Station Network Method
3. Spatial correlation Method
4. Entropy Method
5. WMO Guidelines
30. Cv, Method
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If there are already some rain gauges in the
catchment, the optimal number of stations that should
exist to have an assigned percentage of error in the
estimation of mean rainfall is obtained by statistical
analysis follow the following steps
31. Steps of Cv Method
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32. Example#1
There are four rain gauges stations existing in the
catchments of a river .The average annual rainfall values
of theses station are 800,620,400 and 540 mm
respectively, if the it is desired to limit the error in the
mean values of rainfall in the catchment to be 10%
A) Determine the optimal number of rain gauges
B) How many more gauges will then be required to be
installed
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34. Example#2
A catchment has eight rain gauge stations. The annual
rainfall recorded by these gauges in a given year are as
listed in column 2 of the following Table
A) What should be the minimum number of the rain gauges in
the catchment for estimating the mean rainfall with an error
of less than 7% ?
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36. Example#3
A catchment has six rain gauge stations. In a year, the
annual rainfall recorded by the gauges are shown below.
For a 10% error in the estimation of the mean rainfall
A) calculate the optimum number of stations in the
catchment
B) Additional rain gauges required
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38. Elaborate and
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1) Determine the optimum number of rain-gauge stations to be
established in the basin if it is desired to limit the error in the
mean value of rainfall to 10%.
2) Indicate how you are going to distribute the additional rain-
gauge stations required, if any.
3) What is the percentage accuracy of the existing network in the
estimation of the average depth of rainfall
over the basin ?
39. Site selected for Stream gauging
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Places where major rivers cross State borders;
Locations of proposed dams/diversion/run-of-river
schemes including diversions or offtakes/joining
points for (proposed) inter-basin water transfers link
canals;
40. Cont..
Locations whose data may be needed for flood
forecasting;
Conservation areas and areas of ecological interest;
Areas of water supply shortages;
Areas expected to have significant land use change,
e.g., de-forestation or reforestation;
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41. Evaluation and Adequacy of Networks
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To evaluate the networks, the existing network and
proposed new stations should be marked on a 1:250,000
map.
The catchment area for each river gauging station could
be estimated from the basin maps (hard copy or in GIS).
Scanning the network systematically, the following
questions need to be considered for each station:
42. Questions of Evaluation of network
1) What purpose will the station fulfill?
2) Does a better location exist nearby?
3) Have any developments (e.g. dam construction) taken place or are
likely which could affect this station?
4) How close are the nearest upstream and downstream gauging stations?
5) Two stations should not be very close unless there are specific reasons.
6) Does any other organization operate a gauging station in the vicinity? If
yes, could the data from that station serve the purpose expected from
this station?
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43. Site Selection Surveys
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To select the most appropriate site for a station, site
selection surveys are carried out.
These surveys can be divided into four distinct phases:
a) Desk study,
b) Reconnaissance surveys,
c) Topographic surveys, and
d) other surveys
44. General site selection guidelines
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1) The approach channel should be of uniform cross-section
and free from irregularities
2) Sites where high sediment deposition or scouring occurs or
those which are subject to weed growth should be avoided.
3) Locations which are subject to high turbulence or wind
effects should be avoided.
4) The channel bed should be solid, relatively smooth and free
from obstructions
45. Cont..
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5) The station should be located where the flood plain is at its
narrowest and the out of bank flood flow is the minimum.
6) The banks of the river should be high and steep and free from
larger vegetation
7) River banks at the site should be well-defined, stable, and free
from vegetation and other obstructions.
8) Downstream conditions should preferably be stable
46. Cont.…
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9) Factors such as unhindered access to the site in all seasons,
availability of office accommodation in to account
10) Enough land should be available near the site to install various
instruments
11) Sites with a tendency for formation of vortices, reverse flow
or dead water shall be avoided
12) The measuring section should be away from obstructions
(artificial and natural) and control structures
47. Water Level / River stage
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Water level or river stage is the primary variable
that is measured at stream gauging sites and most
frequent measurements pertain to river stage.
Stage (height of water surface) is observed at all
stream-gauging stations to determine discharge.
48. Criteria for Water Level Gauging Sites
1) Steep banks or sides are preferred
2) The stage measurement device should be installed as close to the
edge of the stream as possible
3) To minimize the effects of turbulence and high velocities, water
level measuring devices can be installed in a suitable stilling bay at
the bank
4) It is desirable to have access to the site and gauge posts at all
times.
5) The site should not a tendency to collect floating debris
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49. Lake and reservoir stages
Stage, temperature, surge, salinity, ice formation,
etc., should be observed at lake and reservoir stations.
Stations should be established on lakes and reservoirs
with surface areas greater than 100 km2
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50. Lake and reservoir station
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51. Criteria for Streamflow Measurement Sites
1) The measurement section should be clearly visible across
its width and unobstructed by trees
2) There should be sufficient depth of flow across the whole
cross-section:
3) Sites with mobile beds and bank shall be avoided.
4) In some rivers, this is not possible and the site may be
chosen so that the bed and bank changes are minimized.
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52. Cont.…
4) Ideally, flow should be confined to a single channel. When this is
not possible, each channel should be gauged separately to obtain the
total flow.
5) The site shall be sufficiently far away from the disturbance caused
by rapids and falls.
6) If the site is upstream of confluence of two rivers, it should be
located sufficiently far upstream so that it is beyond backwater and
any disturbance due to joining of two rivers.
7) Velocities should be well in excess of the minimum required speed
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53. Sediment discharge and sedimentation
Sediment stations may be designed either to measure
total sediment discharge to the ocean or to measure the
erosion, transport and deposition of sediment within a
country, basin, etc.
An optimum network would contain a sediment station
at the mouth of each important river discharging into
the sea
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54. Sediment discharge and sedimentation
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55. Water quality stations
The usefulness of a water supply depends, to a large degree, on
its chemical quality.
The greater the water quality fluctuation, the greater the
frequency of measurement required.
In humid regions, where concentrations of dissolved matter are
low, fewer observations are needed than in dry climates, where
concentrations, particularly of critical ions such as sodium, may
be high.
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