The document summarizes a study that delineated the Bark River Watershed using DEMs with different spatial resolutions (30m, 10m, 5ft) and compared the results to the actual watershed boundaries from the USGS. The 30m DEM was found to have the most accurate representation of the watershed area, being only 2.36% larger than the USGS measurement. While the 10m DEM was also similar, the 5ft DEM incorrectly cut off around half of the total watershed area due to lack of data and road crossings. The study aims to determine the best DEM resolution for accurate watershed delineation.
Prioritization Of Subwatersheds of Cauvery Region Based on Morphometric Analy...Mohammed Badiuddin Parvez
Prioritization of watershed has picked up significance in watershed management. Morphometic analysis is been commonly applied to prioritize the watershed. The present study makes an effort to organize subwatersheds dependent on morphometric characteristics using GIS techniques in Part of Cauvery region. There are twenty three Subwatersheds under this. Various morphometric parameters namely Bifurcation ratio(Rb), Drainage density(Dd), Stream frequency(Ns), Texture ratio(T), Form factor(Rf), Circularity ratio(Rc), Elongation Ratio(Re), length of overland flow, shape factor(Bs), drainage texture, compactness ratio (Cc) has been determined for each subwatershed and allotted position on premise of relationship as to arrive at a computed value for final ranking of subwatershed.
Birr - Identifying Critical Portions of the LandscapeJose A. Hernandez
Terrain attributes derived from digital elevation models can be used to identify critical source areas for water quality protection. A study calculated terrain attributes like slope, curvature, and stream power index for two pilot watersheds in Minnesota. Field surveys showed higher values of attributes like specific catchment area and stream power index corresponded to locations of gullies and other erosion features. The results indicate terrain analysis can efficiently identify priority areas for conservation practices to reduce sediment and nutrient runoff.
Evaluation of morphometric parameters derived from Cartosat-1 DEM using remot...Dr Ramesh Dikpal
The quantitative analysis of drainage system is
an important aspect of characterization of watersheds.
Using watershed as a basin unit in morphometric analysis
is the most logical choice because all hydrological and
geomorphic processes occur within the watershed. The
Budigere Amanikere watershed a tributary of Dakshina
Pinakini River has been selected for case illustration.
Geoinformatics module consisting of ArcGIS 10.3v and
Cartosat-1 Digital Elevation Model (DEM) version 1 of
resolution 1 arc Sec (*32 m) data obtained from Bhuvan
is effectively used. Sheet and gully erosion are identified in
parts of the study area. Slope in the watershed indicating
moderate to least runoff and negligible soil loss condition.
Third and fourth-order sub-watershed analysis is carried
out. Mean bifurcation ratio (Rb) 3.6 specify there is no
dominant influence of geology and structures, low drainage
density (Dd) 1.12 and low stream frequency (Fs) 1.17
implies highly infiltration subsoil material and low runoff,
infiltration number (If)1.3 implies higher infiltration
capacity, coarse drainage texture (T) 3.40 shows high
permeable subsoil, length of overland flow (Lg) 0.45
indicates under very less structural disturbances, less runoff
conditions, constant of channel maintenance (C) 0.9 indicates
higher permeability of subsoil, elongation ratio (Re)
0.58, circularity ratio (Rc) 0.75 and form factor (Rf) 0.26
signifies sub-circular to more elongated basin with high
infiltration with low runoff. It was observed from the
hypsometric curves and hypsometric integral values of the
watershed along with their sub basins that the drainage
system is attaining a mature stage of geomorphic development.
Additionally, Hypsometric curve and hypsometric
integral value proves that the infiltration capacity is high as
well as runoff is low in the watershed. Thus, these mormometric
analyses can be used as an estimator of erosion
status of watersheds leading to prioritization for taking up
soil and water conservation measures.
Groundwater districts need easy access to groundwater data for management decisions. A proposed solution is an interactive 3D hydrostratigraphic model of the county's formations, aquifers, water levels, and other data. Previous models created for other districts have been useful for understanding aquifer complexity, water level changes, and assisting with permits and questions. The proposed model would incorporate data from over 500 wells and could help the district with long-term planning and daily decisions.
Planning for water sensitive communities: the need for a bottom up systems ap...Michael Barry
This document discusses a study that investigates the impacts of making average demand assumptions versus using a bottom-up systems approach for water resource planning models. The study uses highly resolved, bottom-up models of the water networks in Greater Melbourne and Sydney as a baseline. It then modifies the models by replacing the spatially and temporally granular demand inputs with various average demand assumptions. The results show that average assumptions can lead to material differences in the models' predictive behavior and outcomes compared to the bottom-up approach. Specifically, average assumptions influence predictions of future water security and patterns of water flows through infrastructure in unpredictable and sometimes counterintuitive ways. The study concludes it is difficult to support the use of average demand assumptions for water resource
Jared Sartini completed a capstone project studying the effects of a remnant dam on Rum Creek in Kent County, Michigan. Field measurements were taken upstream and downstream of the dam, including bank erosion rates, substrate composition, and macroinvertebrate sampling. No significant differences were found between upstream and downstream areas. The dam is scheduled for removal to restore natural stream functions. Post-removal monitoring over 3 years is planned to evaluate the ecological response.
1) The document discusses improving hydrologic prediction for large urban areas like Dallas-Fort Worth through stochastic analysis of scale-dependent runoff response, advanced sensing, and high-resolution modeling.
2) It evaluates how variability in runoff and flood frequency in urban areas depends on catchment scale and precipitation factors, and how precipitation, soil, and land cover influence frequency.
3) It tests the limits of high-resolution hydrologic modeling for real-time forecasting by assessing sensitivity to rainfall and model parameter spatial resolution, finding that errors limit clear relationships once rainfall resolution reaches catchment scale.
Groundwater modeling has several purposes including understanding aquifer properties, characteristics, and response. It requires collecting hydrological, physical, and boundary condition data. Common groundwater modeling software includes MODFLOW and Sutra. The modeling process involves defining the problem, collecting data, choosing a code, running simulations, verifying results match field data through calibration, and using the model to inform management decisions.
Prioritization Of Subwatersheds of Cauvery Region Based on Morphometric Analy...Mohammed Badiuddin Parvez
Prioritization of watershed has picked up significance in watershed management. Morphometic analysis is been commonly applied to prioritize the watershed. The present study makes an effort to organize subwatersheds dependent on morphometric characteristics using GIS techniques in Part of Cauvery region. There are twenty three Subwatersheds under this. Various morphometric parameters namely Bifurcation ratio(Rb), Drainage density(Dd), Stream frequency(Ns), Texture ratio(T), Form factor(Rf), Circularity ratio(Rc), Elongation Ratio(Re), length of overland flow, shape factor(Bs), drainage texture, compactness ratio (Cc) has been determined for each subwatershed and allotted position on premise of relationship as to arrive at a computed value for final ranking of subwatershed.
Birr - Identifying Critical Portions of the LandscapeJose A. Hernandez
Terrain attributes derived from digital elevation models can be used to identify critical source areas for water quality protection. A study calculated terrain attributes like slope, curvature, and stream power index for two pilot watersheds in Minnesota. Field surveys showed higher values of attributes like specific catchment area and stream power index corresponded to locations of gullies and other erosion features. The results indicate terrain analysis can efficiently identify priority areas for conservation practices to reduce sediment and nutrient runoff.
Evaluation of morphometric parameters derived from Cartosat-1 DEM using remot...Dr Ramesh Dikpal
The quantitative analysis of drainage system is
an important aspect of characterization of watersheds.
Using watershed as a basin unit in morphometric analysis
is the most logical choice because all hydrological and
geomorphic processes occur within the watershed. The
Budigere Amanikere watershed a tributary of Dakshina
Pinakini River has been selected for case illustration.
Geoinformatics module consisting of ArcGIS 10.3v and
Cartosat-1 Digital Elevation Model (DEM) version 1 of
resolution 1 arc Sec (*32 m) data obtained from Bhuvan
is effectively used. Sheet and gully erosion are identified in
parts of the study area. Slope in the watershed indicating
moderate to least runoff and negligible soil loss condition.
Third and fourth-order sub-watershed analysis is carried
out. Mean bifurcation ratio (Rb) 3.6 specify there is no
dominant influence of geology and structures, low drainage
density (Dd) 1.12 and low stream frequency (Fs) 1.17
implies highly infiltration subsoil material and low runoff,
infiltration number (If)1.3 implies higher infiltration
capacity, coarse drainage texture (T) 3.40 shows high
permeable subsoil, length of overland flow (Lg) 0.45
indicates under very less structural disturbances, less runoff
conditions, constant of channel maintenance (C) 0.9 indicates
higher permeability of subsoil, elongation ratio (Re)
0.58, circularity ratio (Rc) 0.75 and form factor (Rf) 0.26
signifies sub-circular to more elongated basin with high
infiltration with low runoff. It was observed from the
hypsometric curves and hypsometric integral values of the
watershed along with their sub basins that the drainage
system is attaining a mature stage of geomorphic development.
Additionally, Hypsometric curve and hypsometric
integral value proves that the infiltration capacity is high as
well as runoff is low in the watershed. Thus, these mormometric
analyses can be used as an estimator of erosion
status of watersheds leading to prioritization for taking up
soil and water conservation measures.
Groundwater districts need easy access to groundwater data for management decisions. A proposed solution is an interactive 3D hydrostratigraphic model of the county's formations, aquifers, water levels, and other data. Previous models created for other districts have been useful for understanding aquifer complexity, water level changes, and assisting with permits and questions. The proposed model would incorporate data from over 500 wells and could help the district with long-term planning and daily decisions.
Planning for water sensitive communities: the need for a bottom up systems ap...Michael Barry
This document discusses a study that investigates the impacts of making average demand assumptions versus using a bottom-up systems approach for water resource planning models. The study uses highly resolved, bottom-up models of the water networks in Greater Melbourne and Sydney as a baseline. It then modifies the models by replacing the spatially and temporally granular demand inputs with various average demand assumptions. The results show that average assumptions can lead to material differences in the models' predictive behavior and outcomes compared to the bottom-up approach. Specifically, average assumptions influence predictions of future water security and patterns of water flows through infrastructure in unpredictable and sometimes counterintuitive ways. The study concludes it is difficult to support the use of average demand assumptions for water resource
Jared Sartini completed a capstone project studying the effects of a remnant dam on Rum Creek in Kent County, Michigan. Field measurements were taken upstream and downstream of the dam, including bank erosion rates, substrate composition, and macroinvertebrate sampling. No significant differences were found between upstream and downstream areas. The dam is scheduled for removal to restore natural stream functions. Post-removal monitoring over 3 years is planned to evaluate the ecological response.
1) The document discusses improving hydrologic prediction for large urban areas like Dallas-Fort Worth through stochastic analysis of scale-dependent runoff response, advanced sensing, and high-resolution modeling.
2) It evaluates how variability in runoff and flood frequency in urban areas depends on catchment scale and precipitation factors, and how precipitation, soil, and land cover influence frequency.
3) It tests the limits of high-resolution hydrologic modeling for real-time forecasting by assessing sensitivity to rainfall and model parameter spatial resolution, finding that errors limit clear relationships once rainfall resolution reaches catchment scale.
Groundwater modeling has several purposes including understanding aquifer properties, characteristics, and response. It requires collecting hydrological, physical, and boundary condition data. Common groundwater modeling software includes MODFLOW and Sutra. The modeling process involves defining the problem, collecting data, choosing a code, running simulations, verifying results match field data through calibration, and using the model to inform management decisions.
This document describes a study that used a 2D hydrodynamic model (HEC-RAS) to simulate unsteady flow and map flood inundation along a 20 km reach of the Brazos River near Richmond, Texas. The study aimed to model flow conditions over time during a flooding event in June 2016 and map flood extent. A DEM and land cover data were used to develop the 2D model mesh and assign Manning's n values. The model results showed good correlation with observed water surface elevations. Maximum velocities, depths, and flooded areas were identified. The analysis provides useful insights into flood behavior that could inform flood management.
This document summarizes a study that estimated design flood levels for 22 locations in the Brisbane River catchment using three different methods: flood frequency analysis, the design event approach, and Monte Carlo simulation. The methods were applied under both "no-dams" and "with-dams" conditions. Significant effort was spent reconciling the results of the three methods and validating them using observed data to achieve consistent design flood estimates across methods and locations. The paper describes the three estimation methods used and the reconciliation process adopted.
The document describes a proposed Monte Carlo framework for estimating design floods in the Brisbane River catchment in Australia. The framework would (1) generate synthetic flood events by sampling probabilities of factors like rainfall and reservoir levels, (2) use rainfall intensity data and spatial patterns to estimate rainfall for sub-catchments, (3) model runoff and routing through the catchment using a hydrological model, and (4) estimate flood levels, discharges and volumes at different locations and return periods through post-processing of model results. The framework aims to better represent the variability and interactions of all flood influencing factors compared to traditional methods.
Groundwater models are simplified representation of large and real hydrogeologic systems like river basins or watersheds. GWM is attempted to analyse the mechanisms which control the occurrence and movement of groundwater and to evaluate the policies, actions and designs which may affect the systems. These models are less complex prototypes of complex hydrogeologic systems developed using spatially varying aquifer parameters, hydrologic properties, geologic boundary conditions and positions of withdrawal wells or recharging structures. These are designed to compute how pumping or recharge might affect the local or regional groundwater levels.
The document summarizes work to model the highly modified flow network of the Guadalupe River Delta through field data collection and hydrodynamic modeling. Key points:
1) Field work was conducted to collect bathymetry data and map the complex channel network altered by diversions and restrictions using lidar and channel extraction tools.
2) A high-resolution hydrodynamic model called Frehd will be used to understand current conditions and inform management, representing features as boundary conditions on a 10m grid coarsened from lidar.
3) Sensors have been installed throughout the system to monitor inputs, outputs, and junctions to verify the Frehd model, which will focus on recovering this field-collected data.
Morphometric Studies of Fourth order Sub-Basins (FOSB’s) in North Bangalore M...Dr Ramesh Dikpal
The quantitative analysis of drainage system is an important aspect of characterization of watersheds. Using watershed as a basic unit in morphometric analysis is the most logical choice because all hydrologic and geomorphic processes occur within the watershed. The North Bangalore Metropolitan Region is constitutes a part of North Pennar, South Pennar and Cauvery Basins has been selected for the case illustration. Geo-informatics module consists of GIS mapping for location map, drainage map, surface water body map, sub-basin map etc are generated. Morphometric module consists of morphometric analysis for several drainage basin parameters include stream order, stream length, bifurcation ratio, drainage density, drainage frequency, form factor, elongation ratio, circularity ratio, texture ratio, length of overland flow and constant of channel maintenance are also calculated. An attempt has been made to utilize the interpretation capabilities of GIS to find out the relationship between the morphometric parameters at sub basin level.
This document summarizes the development of a web-based tool called the Fertilizer Forecaster that will provide daily recommendations on when and where to apply fertilizers and manures to minimize the risk of surface water contamination from runoff. The tool uses forecasts of soil moisture and runoff risk from three hydrological models. The researchers are evaluating methods to accurately represent variable source areas of runoff at the sub-field scale to provide localized runoff risk assessments. They will integrate soil moisture, runoff risk thresholds into the Fertilizer Forecaster and test it in real-time and with past weather data.
This project aims to develop a decision support system (DSS) to help water resource managers and agricultural producers manage water resources under increasing climate variability and growing food demand. The DSS will integrate hydrologic models, tools, and data to enable consideration of current and future water use and climate impacts. It will provide maps and analyses of water resources in southwest Michigan under different climate scenarios. Outreach will train stakeholders on using the DSS to inform local water management decisions.
1) The study evaluates the impacts of implementing low impact development (LID) techniques on peak discharge and runoff volume in an urban watershed in Washington D.C. using the Storm Water Management Model.
2) Three stormwater models (Rational Method, HEC-HMS, and SWMM) were used to simulate rainfall-runoff processes and estimate peak flows and volumes in the watershed.
3) The results found that LIDs can significantly reduce runoff volume by over 30% but have a negligible impact on peak discharge reduction. Integrating LIDs provides both environmental and economic benefits through reduced flooding and infrastructure costs.
Streamflow simulation using radar-based precipitation applied to the Illinois...Alireza Safari
This paper describes the application of a spatially distributed hydrological model WetSpa (Water and Energy Transfer between Soil, Plants and Atmosphere) using radar-based rainfall data provide by the United States Hydrology Laboratory of NOAA's National Weather Service for a distributed model intercomparison project. The model is applied to the
river basin above Tahlequah hydrometry station with 30-m spatial resolution and one hour time--step for a total simulation period of 6 years. Rainfall inputs are derived from radar. The distributed model parameters are based on an extensive database of watershed characteristics available for the region, including digital maps of DEM, soil type, and land use. The model is calibrated and validated on part of the river flow records. The simulated hydrograph shows a good correspondence with observation (Nash efficiency coeffiecient >80%, indicating that the model is able to simulate the relevant hydrologic processes in the basin accurately.
This document describes the development of a stage-discharge rating curve for Beaver Creek in Springfield, Ohio. Field discharge measurements were taken using acoustic Doppler velocimetry from June to November 2011. A synthetic rating curve was also created using the step-backwater method to estimate high flows beyond safe wading levels. The rating curve relates water surface elevation to discharge and will allow estimation of flows from continuous stage monitoring.
IDENTIFICATION OF GROUNDWATER POTENTIAL ZONES USING REMOTE SENSING AND GEOGRA...IAEME Publication
The document describes a study that used remote sensing and GIS techniques to identify groundwater potential zones in the Konakaluva sub-basin of India. Various thematic maps were generated from satellite imagery and other data sources. These maps were overlaid and assigned weights based on their influence on groundwater occurrence. Soil data was given the highest weight of 40%, while land use/cover and drainage density were also significant at 25% and 10%, respectively. An integrated groundwater potential zones map was produced that classified areas as very good, good, fair, moderate or poor potential zones based on the overlay analysis. The results can help with better planning and management of groundwater resources in the study area.
1) The document describes a study applying poststack acoustic impedance inversion to characterize subsalt reservoirs using 3D seismic data from the Walker Ridge protraction area in the Gulf of Mexico.
2) Inversion of a depth-migrated seismic volume was able to derive relative acoustic impedance, which was then used with a background model to estimate absolute acoustic impedance.
3) Comparison of inverted acoustic impedance to well logs showed good agreement, indicating the potential for quantitative seismic analysis of subsalt reservoirs despite challenges of low frequencies and complex salt geometry.
This document summarizes the use of an enhanced hydro-ecological model called RHESSys to explore the interactions between climate change, precipitation patterns, topography, and forests in a New York City water supply watershed. The model was implemented for Biscuit Brook watershed. Model outputs such as streamflow and vegetation cover under different tree species scenarios are presented. Future work includes additional model calibration, expanding the scale of modeling, and using the model to investigate climate change impacts on Catskill forests.
WE1.L10 - GRACE Applications to Regional Hydrology and Water Resourcesgrssieee
This document summarizes the applications of NASA's GRACE mission for monitoring regional hydrology and water resources. GRACE uses two satellites to measure small changes in Earth's gravity field caused by the redistribution of water on land and oceans. GRACE data has been used to monitor seasonal water storage changes, depleting groundwater aquifers, declining glaciers and ice sheets, and rising sea levels. Ensuring continuity of GRACE measurements is important for long-term climate monitoring, and NASA has proposed a GRACE Follow-On mission to launch in 2016 to fill the gap until next-generation gravity missions.
Data Requirements for Groundwater ModellingC. P. Kumar
Groundwater modeling requires data on the physical and hydrological framework of the aquifer. The physical framework data defines the aquifer geometry and properties, including topography, geology, aquifer thickness and boundaries. The hydrological framework data describes the flow in and out of the aquifer, such as water table elevations, recharge and discharge rates and areas. Collecting these types of data from existing sources and monitoring programs is the first step of any groundwater modeling study.
This document contains answers to remote sensing questions. It discusses how different factors like crop type, growth stage, soil conditions and weather impact spectral signatures. It also addresses how field checks are used to identify crop types and validate remote sensing data. Additional questions cover topics like spatial resolution advantages of different satellites, using imagery to monitor drought conditions and vegetation patterns across continents.
A study of the dissipation and tracer dispersion in a submesoscale eddy field...Sonaljit Mukherjee
This study uses high-resolution ocean model simulations to investigate subgrid dissipation and tracer dispersion in submesoscale eddy fields. It implements different subgrid mixing parameterizations to study their impact on resolved submesoscale flows and restratification. Results show enhanced dissipation occurs in localized regions at the periphery of eddies due to changes in ageostrophic shear production. Stronger eddy diffusivities reduce lateral buoyancy gradients and the rate of restratification. Salinity intrusions formed by mixed-layer eddies below the surface match observations, indicating the mechanism of tracer dispersion at submesoscales.
Soil degradation occurs through two main processes: erosion by water and wind, which removes solid material; and leaching, which removes soluble matter. Erosion involves mobilization, transport, and deposition of solids, while leaching involves solubilization, transport, and precipitation/fixation of dissolved components through physicochemical and biological processes like hydration and hydrolysis. Models like the Universal Soil Loss Equation are used to estimate soil degradation from erosion and leaching over large areas based on local measurements and factors such as climate, landscape, soil type, and land use. Soil losses at one site result in deposition elsewhere through aquatic, wind, or precipitation transport.
This mid-term presentation summarizes a master's thesis on modeling soil erosion in the Kankai Mai watershed in Nepal using the Universal Soil Loss Equation (USLE) model. Key points include:
1) The USLE model was implemented in ArcGIS to estimate soil loss rates across the watershed using factors like rainfall, soil type, slope, land use, and management practices.
2) Model parameters were calibrated and validated against observed sediment data, achieving R2 values over 0.7.
3) Results show the average annual sediment yield for the watershed is 21.94 tons/hectare and ranges from 18.04 to 25.07 tons/hectare in different
This document describes a study that used a 2D hydrodynamic model (HEC-RAS) to simulate unsteady flow and map flood inundation along a 20 km reach of the Brazos River near Richmond, Texas. The study aimed to model flow conditions over time during a flooding event in June 2016 and map flood extent. A DEM and land cover data were used to develop the 2D model mesh and assign Manning's n values. The model results showed good correlation with observed water surface elevations. Maximum velocities, depths, and flooded areas were identified. The analysis provides useful insights into flood behavior that could inform flood management.
This document summarizes a study that estimated design flood levels for 22 locations in the Brisbane River catchment using three different methods: flood frequency analysis, the design event approach, and Monte Carlo simulation. The methods were applied under both "no-dams" and "with-dams" conditions. Significant effort was spent reconciling the results of the three methods and validating them using observed data to achieve consistent design flood estimates across methods and locations. The paper describes the three estimation methods used and the reconciliation process adopted.
The document describes a proposed Monte Carlo framework for estimating design floods in the Brisbane River catchment in Australia. The framework would (1) generate synthetic flood events by sampling probabilities of factors like rainfall and reservoir levels, (2) use rainfall intensity data and spatial patterns to estimate rainfall for sub-catchments, (3) model runoff and routing through the catchment using a hydrological model, and (4) estimate flood levels, discharges and volumes at different locations and return periods through post-processing of model results. The framework aims to better represent the variability and interactions of all flood influencing factors compared to traditional methods.
Groundwater models are simplified representation of large and real hydrogeologic systems like river basins or watersheds. GWM is attempted to analyse the mechanisms which control the occurrence and movement of groundwater and to evaluate the policies, actions and designs which may affect the systems. These models are less complex prototypes of complex hydrogeologic systems developed using spatially varying aquifer parameters, hydrologic properties, geologic boundary conditions and positions of withdrawal wells or recharging structures. These are designed to compute how pumping or recharge might affect the local or regional groundwater levels.
The document summarizes work to model the highly modified flow network of the Guadalupe River Delta through field data collection and hydrodynamic modeling. Key points:
1) Field work was conducted to collect bathymetry data and map the complex channel network altered by diversions and restrictions using lidar and channel extraction tools.
2) A high-resolution hydrodynamic model called Frehd will be used to understand current conditions and inform management, representing features as boundary conditions on a 10m grid coarsened from lidar.
3) Sensors have been installed throughout the system to monitor inputs, outputs, and junctions to verify the Frehd model, which will focus on recovering this field-collected data.
Morphometric Studies of Fourth order Sub-Basins (FOSB’s) in North Bangalore M...Dr Ramesh Dikpal
The quantitative analysis of drainage system is an important aspect of characterization of watersheds. Using watershed as a basic unit in morphometric analysis is the most logical choice because all hydrologic and geomorphic processes occur within the watershed. The North Bangalore Metropolitan Region is constitutes a part of North Pennar, South Pennar and Cauvery Basins has been selected for the case illustration. Geo-informatics module consists of GIS mapping for location map, drainage map, surface water body map, sub-basin map etc are generated. Morphometric module consists of morphometric analysis for several drainage basin parameters include stream order, stream length, bifurcation ratio, drainage density, drainage frequency, form factor, elongation ratio, circularity ratio, texture ratio, length of overland flow and constant of channel maintenance are also calculated. An attempt has been made to utilize the interpretation capabilities of GIS to find out the relationship between the morphometric parameters at sub basin level.
This document summarizes the development of a web-based tool called the Fertilizer Forecaster that will provide daily recommendations on when and where to apply fertilizers and manures to minimize the risk of surface water contamination from runoff. The tool uses forecasts of soil moisture and runoff risk from three hydrological models. The researchers are evaluating methods to accurately represent variable source areas of runoff at the sub-field scale to provide localized runoff risk assessments. They will integrate soil moisture, runoff risk thresholds into the Fertilizer Forecaster and test it in real-time and with past weather data.
This project aims to develop a decision support system (DSS) to help water resource managers and agricultural producers manage water resources under increasing climate variability and growing food demand. The DSS will integrate hydrologic models, tools, and data to enable consideration of current and future water use and climate impacts. It will provide maps and analyses of water resources in southwest Michigan under different climate scenarios. Outreach will train stakeholders on using the DSS to inform local water management decisions.
1) The study evaluates the impacts of implementing low impact development (LID) techniques on peak discharge and runoff volume in an urban watershed in Washington D.C. using the Storm Water Management Model.
2) Three stormwater models (Rational Method, HEC-HMS, and SWMM) were used to simulate rainfall-runoff processes and estimate peak flows and volumes in the watershed.
3) The results found that LIDs can significantly reduce runoff volume by over 30% but have a negligible impact on peak discharge reduction. Integrating LIDs provides both environmental and economic benefits through reduced flooding and infrastructure costs.
Streamflow simulation using radar-based precipitation applied to the Illinois...Alireza Safari
This paper describes the application of a spatially distributed hydrological model WetSpa (Water and Energy Transfer between Soil, Plants and Atmosphere) using radar-based rainfall data provide by the United States Hydrology Laboratory of NOAA's National Weather Service for a distributed model intercomparison project. The model is applied to the
river basin above Tahlequah hydrometry station with 30-m spatial resolution and one hour time--step for a total simulation period of 6 years. Rainfall inputs are derived from radar. The distributed model parameters are based on an extensive database of watershed characteristics available for the region, including digital maps of DEM, soil type, and land use. The model is calibrated and validated on part of the river flow records. The simulated hydrograph shows a good correspondence with observation (Nash efficiency coeffiecient >80%, indicating that the model is able to simulate the relevant hydrologic processes in the basin accurately.
This document describes the development of a stage-discharge rating curve for Beaver Creek in Springfield, Ohio. Field discharge measurements were taken using acoustic Doppler velocimetry from June to November 2011. A synthetic rating curve was also created using the step-backwater method to estimate high flows beyond safe wading levels. The rating curve relates water surface elevation to discharge and will allow estimation of flows from continuous stage monitoring.
IDENTIFICATION OF GROUNDWATER POTENTIAL ZONES USING REMOTE SENSING AND GEOGRA...IAEME Publication
The document describes a study that used remote sensing and GIS techniques to identify groundwater potential zones in the Konakaluva sub-basin of India. Various thematic maps were generated from satellite imagery and other data sources. These maps were overlaid and assigned weights based on their influence on groundwater occurrence. Soil data was given the highest weight of 40%, while land use/cover and drainage density were also significant at 25% and 10%, respectively. An integrated groundwater potential zones map was produced that classified areas as very good, good, fair, moderate or poor potential zones based on the overlay analysis. The results can help with better planning and management of groundwater resources in the study area.
1) The document describes a study applying poststack acoustic impedance inversion to characterize subsalt reservoirs using 3D seismic data from the Walker Ridge protraction area in the Gulf of Mexico.
2) Inversion of a depth-migrated seismic volume was able to derive relative acoustic impedance, which was then used with a background model to estimate absolute acoustic impedance.
3) Comparison of inverted acoustic impedance to well logs showed good agreement, indicating the potential for quantitative seismic analysis of subsalt reservoirs despite challenges of low frequencies and complex salt geometry.
This document summarizes the use of an enhanced hydro-ecological model called RHESSys to explore the interactions between climate change, precipitation patterns, topography, and forests in a New York City water supply watershed. The model was implemented for Biscuit Brook watershed. Model outputs such as streamflow and vegetation cover under different tree species scenarios are presented. Future work includes additional model calibration, expanding the scale of modeling, and using the model to investigate climate change impacts on Catskill forests.
WE1.L10 - GRACE Applications to Regional Hydrology and Water Resourcesgrssieee
This document summarizes the applications of NASA's GRACE mission for monitoring regional hydrology and water resources. GRACE uses two satellites to measure small changes in Earth's gravity field caused by the redistribution of water on land and oceans. GRACE data has been used to monitor seasonal water storage changes, depleting groundwater aquifers, declining glaciers and ice sheets, and rising sea levels. Ensuring continuity of GRACE measurements is important for long-term climate monitoring, and NASA has proposed a GRACE Follow-On mission to launch in 2016 to fill the gap until next-generation gravity missions.
Data Requirements for Groundwater ModellingC. P. Kumar
Groundwater modeling requires data on the physical and hydrological framework of the aquifer. The physical framework data defines the aquifer geometry and properties, including topography, geology, aquifer thickness and boundaries. The hydrological framework data describes the flow in and out of the aquifer, such as water table elevations, recharge and discharge rates and areas. Collecting these types of data from existing sources and monitoring programs is the first step of any groundwater modeling study.
This document contains answers to remote sensing questions. It discusses how different factors like crop type, growth stage, soil conditions and weather impact spectral signatures. It also addresses how field checks are used to identify crop types and validate remote sensing data. Additional questions cover topics like spatial resolution advantages of different satellites, using imagery to monitor drought conditions and vegetation patterns across continents.
A study of the dissipation and tracer dispersion in a submesoscale eddy field...Sonaljit Mukherjee
This study uses high-resolution ocean model simulations to investigate subgrid dissipation and tracer dispersion in submesoscale eddy fields. It implements different subgrid mixing parameterizations to study their impact on resolved submesoscale flows and restratification. Results show enhanced dissipation occurs in localized regions at the periphery of eddies due to changes in ageostrophic shear production. Stronger eddy diffusivities reduce lateral buoyancy gradients and the rate of restratification. Salinity intrusions formed by mixed-layer eddies below the surface match observations, indicating the mechanism of tracer dispersion at submesoscales.
Soil degradation occurs through two main processes: erosion by water and wind, which removes solid material; and leaching, which removes soluble matter. Erosion involves mobilization, transport, and deposition of solids, while leaching involves solubilization, transport, and precipitation/fixation of dissolved components through physicochemical and biological processes like hydration and hydrolysis. Models like the Universal Soil Loss Equation are used to estimate soil degradation from erosion and leaching over large areas based on local measurements and factors such as climate, landscape, soil type, and land use. Soil losses at one site result in deposition elsewhere through aquatic, wind, or precipitation transport.
This mid-term presentation summarizes a master's thesis on modeling soil erosion in the Kankai Mai watershed in Nepal using the Universal Soil Loss Equation (USLE) model. Key points include:
1) The USLE model was implemented in ArcGIS to estimate soil loss rates across the watershed using factors like rainfall, soil type, slope, land use, and management practices.
2) Model parameters were calibrated and validated against observed sediment data, achieving R2 values over 0.7.
3) Results show the average annual sediment yield for the watershed is 21.94 tons/hectare and ranges from 18.04 to 25.07 tons/hectare in different
For a new better version of this tutorial see my Google Slides with embedded videos.
https://docs.google.com/presentation/d/1MftEOT3uvYpCVwUaLMhsesm5Que-Kr7GQRV4pKZ2SNQ/edit?usp=sharing
This is a 2016 tutorial on how to do watershed delineation using ArcMap 10. It is an open education resource. Please let me know if you find it useful or see something that could be improved. Feel free to use it for teaching Geographic Information Science.
Soil Erosion for Vishwamitri River watershed using RS and GISvishvam Pancholi
1) This document summarizes a study of soil erosion in the Vishwamitri River watershed using the Universal Soil Loss Equation (USLE).
2) The USLE factors of rainfall (R), soil erodibility (K), slope length and steepness (LS), crop management (C), and supporting practices (P) were calculated for four sub-watersheds using GIS and remote sensing data.
3) The results showed that two of the sub-watersheds (SW1 and SW2) have very severe soil erosion rates of over 97 and 129 tons/ha/year respectively, and should be prioritized for soil conservation measures.
This document discusses GIS tools and techniques for watershed analysis including DEM, fill sinks, flow direction, flow accumulation, conditional elevation, stream ordering, snapping pour points, watershed delineation, basin delineation, and calculating flow length. Key steps are opening a DEM, preprocessing the DEM with fill and flow tools, defining streams and pour points, delineating watersheds, and calculating attributes like flow length. The overall goal is to use GIS to analyze watersheds, drainage patterns, and water flow across landscapes.
This document provides an analysis of the Platte River watershed located in Grant County, Wisconsin. It describes the watershed characteristics including land use, soils, precipitation trends, and stream geomorphology. Two sediment models are developed using factors like slope, soils, land use, and distance to streams to identify areas of high, medium, and low sediment runoff potential. The models are then compared to phosphorus export coefficients from another model called PRESTO to evaluate similarities between areas identified as high or low risk. The analysis finds the second sediment model more accurately identifies a small portion of the watershed as high risk, while the models show similarities for areas identified as low risk.
This document summarizes a study that assessed the clarity of New Jersey lakes using predicted Secchi disk transparency (SDT) derived from Landsat 8 satellite imagery. Two models were tested to predict SDT based on Landsat band reflectance. The predicted SDT showed poor correlation with observed field data for most lakes, but correlation improved significantly when only deeper lakes (>8 meters) were considered, possibly due to reduced interference from lake bottoms in reflectance readings. The study aims to evaluate if satellite imagery can efficiently monitor lake clarity compared to conventional in situ measurements.
A GIS-Based Framework to Identify Opportunities to Use Surface Water to Offse...ASADULISLAMSORIF
The state of Louisiana (Fig. 1) is
characterized by a humid subtropical
climate and receives about 150 cm of
rain per year.
Louisiana hosts about 40% of the
freshwater wetlands in the U.S. is a hub
for the petroleum industry and the third
leading producer of rice in the U.S. Louisiana is also a leading exporter of
aquaculture products
This study analyzed changes in thermokarst lakes near Chersky, Russia between 1965 and 2011 using historical photographs and satellite imagery. The total lake area increased by 2,801,400 square meters over this period. Specifically, the number of small lakes increased while the number of large lakes decreased. Additionally, small lakes made up a greater percentage of the total lake area in 2011 compared to 1965. This suggests climate change is contributing to the drainage of larger lakes and expansion of smaller, more numerous water bodies in the region.
This document summarizes a vulnerability analysis of sub-basins in Massachusetts to determine which are most likely to experience water stress under new regulations. The analysis scored sub-basins based on 7 factors like population change, groundwater permits, and surface water resources. It found the eastern and southwest parts of the state most vulnerable due to high population growth. Over 76% of the state's area had medium vulnerability. The analysis can help identify which sub-basins may need to implement strategies to minimize water use under the new Water Management Act.
The images show Lake Mead in 1994 and 2015, with a decrease in water coverage of 34.42% and an increase in exposed land of 172.56% over those 21 years. By comparing water levels to the changes in lake size, approximately 4.5 trillion gallons of water have been lost from Lake Mead between September 1994 and 2015.
StreamFlow Variability of 21 Watersheds, OregonDonnych Diaz
This study analyzed the relationship between streamflow runoff and physical attributes in 21 Oregon watersheds. Monthly streamflow data from 1958-2008 was collected and watershed characteristics like elevation, slope, aspect and land cover were determined. A multiple regression model found land cover, elevation and aspect significantly correlated with winter streamflow, but not summer flow. This suggests precipitation is important and the model needs additional variables like soil and snowpack to better predict streamflow runoff.
This document is a final project analysis by Paige A Whitfield for a GEOG 3315 course. The project analyzes soil thickness and water quality sites in Georgia watersheds. Whitfield gathered soil, water quality, and watershed boundary data for areas of Georgia. Through analysis in GIS, Whitfield found relationships between thin soil areas, water quality site locations, and watershed boundaries. Maps were created to show watersheds with high ratios of thin soil coverage correlated with more water quality sites. The analysis suggests areas with thinner soils may be more vulnerable to pollution entering water systems.
This is the talk I gave at MUSE (the museum of Science) in Trento 21st of March 2016. I talked about interaction between hydrology and forests at various scales. Presentation includes a nice set of review papers (with links to pdfs).
The document discusses the need for high resolution digital elevation data to identify critical areas for targeting conservation practices in Minnesota. Precision conservation, which focuses practices on disproportionately polluting areas, can better protect water quality and habitat than spreading practices evenly. Lidar data can help identify critical sources of runoff and pollution like upland depressions, eroding stream banks, and ravines. Targeting best management practices to these critical areas identified through terrain analysis of high resolution elevation data can maximize the impact of conservation efforts.
This study examined the spatial heterogeneity of buried soils and post-settlement sediments in streams in the Christina River Basin. The thickness and composition of buried organic soils and overlying post-settlement layers varied substantially between study sites, indicating a heterogeneous pre-settlement floodplain landscape. Additionally, post-settlement sediment deposition was thicker above old mill dam locations than predicted by previous studies. Moving forward, the study will analyze carbon and nutrient contents to better understand the potential for carbon sequestration and pollution transport in these systems.
identification of ground water potential zones using gis and remote sensingtp jayamohan
This document summarizes a study that mapped groundwater potential zones in the Muvattupuzha block of Kerala, India using GIS and remote sensing. Key factors like geology, geomorphology, lineaments, drainage density, rainfall, land use, slope and soils were analyzed as layers in GIS. Weighted overlay analysis was used to delineate excellent, moderate and poor groundwater potential zones. Validation with field data found good correlation. The study aims to aid groundwater development and management to address water scarcity in the region.
This document summarizes a study that assessed tidal flood inundation on coastal agricultural lands in Central Java Province, Indonesia. The study (1) mapped tidal inundation in the coastal area using DEM data and a 150cm water depth scenario, (2) considered uncertainty from DEM vertical accuracy, and (3) assessed changes in paddy field area between 2000 and 2010 land use maps. The results showed some paddy fields changed to settlements and fish ponds, following the pattern of the tidal inundation map, suggesting the coastal area has been threatened by increasing tidal flooding over the past ten years.
The document presents research on ravines in the Minnesota River Basin. It defines ravines and describes their impacts on sedimentation. The objectives were to identify and characterize ravines using LiDAR and DEM data. Ravines delineated with LiDAR were more accurate than with 30m DEMs. An automated GIS method was developed to identify ravines using slope, aspect, and catchment area thresholds. Ravines contribute significantly to sediment in the Minnesota River Basin.
The document summarizes the analysis of soil erosion potential in the San Marcos Watershed using the RUSLE model in GIS. The RUSLE model calculates average annual soil loss based on 5 factors - rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), land cover (C), and conservation practices (P). Spatial data for each factor was obtained and analyzed in GIS. The results showed higher soil erosion potential in the northwest area due to steeper slopes as indicated by the higher LS values.
The document outlines a methodology for investigating how channel size, efficiency, and gradient change with distance downstream. It presents 3 hypotheses and describes primary data that will be collected, including cross-sectional area, velocity, discharge, wetted perimeter, hydraulic radius, gradient, and roughness. Secondary data on climate, human management, and geology is also deemed relevant. A risk assessment is required and must be linked to the methodologies. Specific methods are described for measuring cross-sectional area, including using ranging poles and a tape measure to find width and depth at points across the channel. Calculations and a justification are provided. GIS use is recommended for maps, risk assessment, and collecting secondary data.
Tomer - Challenges of Developing Conservation Planning ToolsJose A. Hernandez
1. The document discusses using LIDAR topographic data to develop tools for conservation planning. It explores how LIDAR data can be used to target practices to improve water quality by identifying pollutant pathways and opportunities for treatment.
2. The document examines challenges in using LIDAR data such as accounting for accuracy errors, determining the appropriate scale of analysis, and modeling hydrologic flow across different landscapes and existing conservation practices.
3. It emphasizes that while LIDAR data shows great detail and potential for conservation planning, its accuracy on non-hard surfaces and representation of actual flow routing needs to be validated, and it cannot replace on-site knowledge.
- The document analyzes average annual soil loss in the Sevenmile Creek watershed located in southern Iowa using the modified soil loss equation (RUSLE).
- Key factors that influence soil loss according to the RUSLE include rainfall/runoff (R factor), soil erodibility (K factor), slope length and steepness (LS factor), land cover/management practices (C factor), and conservation practices (P factor).
- GIS data on rainfall, soil properties, elevation, land cover, and watershed boundaries were compiled and analyzed spatially using RUSLE to estimate average annual soil loss per acre for the Sevenmile Creek watershed.
Similar to Masek_Watershed Deliniation Portfolio (20)
1. 1 | P a g e
Bark River Watershed Delineation & DEM Accuracy Assessment
Partnership between Save our Lake Foundation and Kennedy Consulting
Created By: Ryan Masek
Introduction:
Within the confines of a naturally occurring landscape, hills and valleys act as natural barriers
that separate rivers, creeks, and lakes. This separation of water eventually converges at one point and
can be classified as the end of a watershed, also known as the outlet. To accurately delineate watershed
boundaries a Digital Elevation Model (DEM) must be used. DEMs can have a variety of resolutions
which will affect the accuracy of the watershed that is being delineated. The spatial resolution of the
DEMs refers to the pixel size. Accurate representation of a watershed’s boundaries is crucial to reduce
criticism and also have the most accurate representation, given the available resources. Watersheds are
useful for many reasons, such as the ability to show the specific percentages of land use classifications
in the area. The watershed that is of particular importance for this report was the Bark River Watershed
of Waukesha County.
The Bark River Watershed is located in the northwestern portion of Waukesha County and the
southern portion of Washington County. The primary water body within the watershed is Nagawicka
Lake. Nagawicka Lake is surrounded by a variety of land uses such as agricultural, urban, and forested
lands. Urban and agricultural areas can produce runoff which can contain many nutrients such as
nitrogen and phosphorus which can be detrimental to lake health, chemically and physically. Excess
nutrients entering a water body can cause a lake to turn green. Not only is this green color unappealing
to the residents and visitors of Nagawicka Lake it can also be an indicator of poor of lake health. Under
the right conditions, excess nutrients can cause algal blooms such as blue green algae which is toxic to
aquatic life and if ingested, toxic to humans and animals as well. Delineating the watershed
surrounding Nagawicka Lake allows for the land uses to be determined and know the major source of
pollution.
In this study, the Save our Lakes Foundation hired Kennedy Consulting® to delineate the Bark
River Watershed and compare the accuracy of the delineations with three resolutions of DEMs (5-
Foot, 10 Meter, and 30 Meter). The accuracy of the delineations will be cross referenced with a
credible source (United States Geological Survey) based upon the area, perimeter, surface volume of
the watershed. Through this delineation process, I hope to answer three research questions to assess
the accuracy and consistency of DEMs with different spatial resolutions.
1. What is the area of each watershed delineation?
2. What is the perimeter of each watershed delineation?
3. What is the surface volume of each watershed delineation?
Methods
The geodatabase was organized approximately as follows in table 1. The primary data layers
were the three DEMs, (30 Meter, 10 Meter, and 5-foot). A land use and land cover raster data layer
was used to show the percentages of land use types in the watershed. The vector layers were organized
into a feature dataset. The only features in the dataset were a study area layer showing Washington and
Waukesha counties and a hydrology layer, which can either be a polygon or a polyline feature class.
The hydrology allowed for the lake to be located more easily and allowed for the outlet of the
watershed to be located more easily.
2. 2 | P a g e
Table 1: Physical model for watershed delineation of the Bark River Watershed which surrounds Nagawicka Lake.
Results:
When comparing the data to the United States Geological Survey the 30 Meter DEM had the
least amount of difference. The 30 Meter delineation had an increase in 681 acres over the actual size
which is about 2.36% difference, (Table 2). The 10 Meter DEM was similar to the 30 Meter in almost
all values, but they had a higher percentage of difference than the 30 Meter. The 10 Meter DEM
delineation was 991 acres larger than the USGS delineation, which is 3.42% difference, (Table 2). By
comparing the 30 Meter DEM delineation to the 10 Meter delineation, a difference of 309 acres is
determined. This is a 1.06% difference in area.
The 5-foot DEM was not used in comparing any of the parameters since the source data did not
encompass the entire watershed. Because of this, there was a noticeable difference of 13,029 acres
between the 5-foot and the USGS data. This is a 61.43% difference, (Table 2). There is also a large
difference between the 5-foot and the 30 Meter and/or the 10 Meter. This data is not useful because it
shows only about half of the watershed. If the results of this comparison were actually considered,
without taking into account the lack of data for the 5-foot, there would appear to be a very large
difference in the quality of data from the 5-foot and the 30 Meter and 10 Meter. Because of this, the 5-
foot values are essentially excluded from this report. The values are listed in Table 2 for reference, but
they are not influential or at least should not be considered to be until data for Washington County is
located.
An authoritative data source was not located for both the perimeter and surface volume.
Because of this, the results could not be accurately assessed to a known value. All data and values are
listed in Table 2, but much of the collected data is not fully usable apart from comparing between the
30 Meter and the 10 Meter delineations created during this project. The 5-foot DEM is much different
than the 30 Meter and the 10 Meter DEM because of its lack of data from Washington County. The
surface volume is actually noticeable because it is actually larger than the 30 Meter and the 10 Meter
while encompassing a smaller spatial extent. This may be due to the fineness of detail of the spatial
resolution. Since more specific entities are noticed by the 5-foot DEM, more surfaces may be able to
be detected thus increasing the surface volume.
Comparing the spatial extent of the three DEMs’ watersheds is slightly difficult because the
differences between them are often quite minute. The 30 Meter and the 10 Meter look very similar and
their areas are actually quite similar to support this statement. There are some slight variations at
certain points, but in general the 30 Meter seems to be slightly rounded-off likely due to the lower
resolution imagery. The 30 Meter lumps more into each cell, likely creating a more generalized and
less specific image. This pattern is true for the 5ft image as well. There are more very slight and minor
alterations along the periphery of the watershed. There are some areas that are not included in the 5-
foot DEM. For example, the very southwestern most portion of the 30 Meter and 10 Meter DEMs are
not present in the 5-foot. The three DEM’s are similar, but the 5-foot is the most different of the three.
Geodatabase Feature Dataset Feature Class / Raster
Class
Type FieldName FieldType
Sample
Value
Domain
Values Topology
FID Short Integer 2131
Shape length Double 6,000 Feet
Shape Area Double 4,000 Acres
30 Meter DEM Raster
10 Meter DEM Raster
5 Foot DEM Raster
Land Cover Raster
Watershed_Delini
ation_Features
Watershed_D
eliniation.gdb
Raster_Features
Length DoubleHydrology 12.02 ft Hydro_Clip
Lakes, rivers
and streams
must be within
the study area
Polyline
Study Area (Waukesha
County and Washington
County)
Polygon
3. 3 | P a g e
One of the main
limitations of this project
was the limitation of data
for the 5-foot DEM .
There was no readily
available 5-foot DEM for
Washington County. This
was problematic because
the watershed stretched
from Waukesha County
into , the 5-foot Another
limitation is that the 5-
foot DEM is almost too
accurate and cut off the
watershed due to a few
road crossing on the north
east and south western corners of the watershed (Map 1). This misrepresents the watershed due to the
fact that approximately 47% of the watershed is missing from part of Washington and Waukesha
County.
Conclusions:
According to the United State Geological Survey, the Bark
River watershed is 28,493 acres (Table 2). In this watershed
delineation, 30 Meter DEM came back with a watershed size of
29,174 acres (Table 2). This difference in watershed size is 2.36%
which means the 30 Meter DEM is the most accurate representation
of the Bark River Watershed (Table 2). Although, the 10 Meter DEM
was not far off; it had an area of 29,483 acres (Table 2). This was a
percent difference of 3.42% (Table 2). The area of the 5-foot DEM
came out to 15,464 acres (Table 2). The 5-foot DEM is almost too
accurate and cut off the watershed due to a few road crossing on the
north east and south western corners of the watershed (Map 1). Due
to a few road crossings and the lack of data for Washington County,
almost half of the watershed is not being represented. If an individual
was to delineate the sub-watersheds within the bark river watershed,
a 5-foot DEM would not be a bad idea. This smaller pixel size could
find some of the smaller watersheds that are cut off by roads. But if
an individual was going to just delineate a watershed, a 30 Meter or a
10 Meter would produce the best results.
Table 3 shows the land use percentages for the Bark River Watershed. Agriculture is the
dominant land use of the watershed (38.71%) which could be a cause for concern for the Save the
Lakes Foundation due to possible runoff which could lead to lake pollution. Washington County and
Waukesha County may want to develop some best management practices for the future health and
stability of Nagawicka Lake. This high percentage of agriculture could cause an increase in pollution
due to fertilizer runoff which could possibly decrease the health of Nagawicka Lake.
Area
(Acres)
Perimeter
(Meters)
Surface Volume
(Meters Cubed)
30 Meter 29,174.18 103,799.54 3,590,356,950
10 Meter 29,483.63 106,329.82 3,747,404,009
5 Foot 15,464.00 90,357.71 4,277,621,216.95
Actual Size (USGS) 28,493.00 Data not available Data not available
Difference (10m - 30m) -309.45 -2,530.28 -157,047,059
Percent Different (10m - 30m) 1.06 2.41 4.28
Difference (5ft-10m) -14,019.63 -15,972.12 530,217,207.95
Percent Different (5ft-10m) -62.38 -16.24 13.21
Difference (5ft-30m) -13,710.18 -13,441.84 687,264,266.95
Percent Different (5ft-30m) -61.43 -13.85 17.47
Difference (30m-actual) 681.18
Percent difference actual 30m 2.36
Difference (10m-actual) 990.63
Percent difference actual 10m 3.42
Difference (5ft-actual) -13,029.00
Percent difference actual 5ft -59.28
Land Use
Count (#
of
pixels)
Percent
Land Use
Agriculture 34,954 38.71
Barren 3,796 4.20
Forests 12,805 14.18
Forested
Wetland 2,848 3.15
Grassland 17,298 19.16
Open Water 4,895 5.42
Shrubland 603 0.67
Urban 7,254 8.03
Wetland 5,845 6.47
Total 90,298 100
Table 3: This table summarizes the
percentages of land use displayed on
Map 1 for the Bark River Watershed
Table 2: This table summarizes the
Area, Perimeter, surface volume as
well as the percent difference of the
30 Meter, 10 Meter, and 5 Foot the
Bark River Watershed
4. 4 | P a g e
Map 1: This map includes the 30 Meter, 10 Meter, and 5 Foot watershed delineations as well as the
landuse surrounding Nagawicka Lake. This watershed is known as the Bark River Watershed. See table 2
for landuse percentage values
5. 5 | P a g e
Workflow Scripts:
The following methodology will primarily cover the steps taken to delineate the Nagawicka
Watershed and the steps needed to compile all data required to answer the research questions.
To delineate the Nagawicka Watershed, the DEMs were initially sized in the computer display
to the area surrounding the watershed but with some extra space on the northern size of the lake to
allow for the watershed to be delineated up into Washington County. Once the study area was sized
into the display, a fill function was used to fill all extra holes or low spots in the landscape that are
represented in the DEM, (figure 1). The fill was limited to the extent of the screen.
Figure 1: Fill Function
After the fill was completed, a flow direction process found under the hydrology tools in
ArcGIS had to be performed, (figure 2). The flow direction was limited to the extent of the screen and
created a new layer based on the slope of the landscape. It created a raster based on the flow direction
from one cell to its steepest downslope neighboring cell. This was useful because it accounted for
natural water drainage based on the elevation changes and allowed for the boundaries of the watershed
to be created later on.
Figure 2: Flow Direction Process
After the flow direction, a flow accumulation, (Hydrology Tools – ArcGIS), had to be
developed, (figure 3). The flow accumulation was limited to the extent of the screen and created a new
layer showing the areas of the study area where the most water would collect. It highlighted cells that
have the most other cells that would likely flow into it. It created a black and white image showing the
areas where water collected as white and the areas where water flowed from as black.
Figure 3: Flow Accumulation Process
6. 6 | P a g e
Once the flow accumulation was created, the pour point had to be placed. The pour point of the
watershed indicated where the outlet of the watershed is located. This pour point helped to limit the
extent of the watershed to stop at a certain point. A new feature class had to be made to allow for a
point to be placed, (figure 4). The point was placed along a high accumulation pixel at the south-
western border of the Nagawicka Lake near a dam.
Figure 4: Pour Point Process
Next came the actual watershed creation (Hydrology Tools – ArcGIS). The watershed was
created using the pour point and the flow accumulation (Figure 5), which was based off the flow
direction. A watershed process was performed thus delineating the watershed around Nagawicka. This
process was performed for each resolution of DEM. At this point, the watershed had been created. The
next step was to perform some alterations to and with the watershed to answer the mentioned research
questions.
Figure 5: Watershed Process
To determine the area and perimeter of the watershed, the watershed had to be converted to a
polygon instead of a raster layer. This was accomplished using a “Raster to Polygon” function (figure
6). Once the new polygon was created, two new fields were added to the attribute table, “Area” and
“Perimeter”. These two fields were set as a double and their geometry was calculated to determine
their quantitative values.
Figure 6: Raster to Polygon Process
To determine the surface volume, an “Extract by Mask” had to be performed on the DEM-Fill
layer, (figure 7). The raster mask was limited to the extent of the watershed polygon. The raster mask
acted as a “Clip” and made a new layer of DEM that showed only the area that was included in the
watershed. Once this new, limited DEM was created, a “Surface Volume” process was performed on
the masked DEM, (figure 8). No boundary height was established because the volume for the entire
7. 7 | P a g e
layer was desired. The surface volume was determined in a table in ArcMap. The values for area,
perimeter, and surface volume were recorded in Microsoft Excel.
Figure 7: Raster Mask Process
Figure 8: Surface Volume Process
References
Garn, H., Robertson, D., Rose, W., Goddard, G., & Horwatich, J. (2013.). Water Quality, Hydrology,
and Response to Changes in Phosphorus Loading of Nagawicka Lake, a Calcareous Lake in
Waukesha County, Wisconsin.
United States Geological Survey. 2015.