Hydrologic Modelings/Gis as an Aid in Locating Monitoring Sites

Rosenthal, W. D.; Hoffman, D. W.

doi:10.13031/2013.13324

Cited by 21 publications

(14 citation statements)

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“…Similarly, based on monthly flows, it was found that ENS was equal to 0.88 and 0.90 for the calibration and validation periods, respectively. Comparable values of D v and ENS for daily and monthly flows simulated with SWAT are found in the literature (Hanratty and Stefan, 1998;King et al, 1999;Rosenthal and Hoffman 1999;Spruill et al, 2000;Eckhardt and Arnold, 2001;Weber et al, 2001;Fontaine et al, 2002;Neitsch et al, 2002c;Eckhardt et al, 2003;Tripathi et al, 2003). The value of ENS of 0.33 for the validation period with daily flows, though, is lower than what was found in the literature.…”

Section: Arcgis-swat Was Applied To the Upper Secosupporting

confidence: 53%

Arcgis-Swat: A Geodata Model and Gis Interface for Swat

Olivera

Valenzuela

Srinivasan

et al. 2006

J Am Water Resources Assoc

167

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This paper presents ArcGIS‐SWAT, a geodata model and geographic information system (GIS) interface for the Soil and Water Assessment Tool (SWAT). The ArcGIS‐SWAT data model is a system of geodatabases that store SWAT geographic, numeric, and text input data and results in an organized fashion. Thus, it is proposed that a single and comprehensive geodatabase be used as the repository of a SWAT simulation. The ArcGIS‐SWAT interface uses programming objects that conform to the Component Object Model (COM) design standard, which facilitate the use of functionality of other Windows‐based applications within ArcGIS‐SWAT. In particular, the use of MS Excel and MATLAB functionality for data analysis and visualization of results is demonstrated. Likewise, it is proposed to conduct hydrologic model integration through the sharing of information with a not‐model‐specific hub data model where information common to different models can be stored and from which it can be retrieved. As an example, it is demonstrated how the Hydrologic Modeling System (HMS) ‐ a computer application for flood analysis ‐ can use information originally developed by ArcGIS‐SWAT for SWAT. The application of ArcGIS‐SWAT to the Seco Creek watershed in Texas is presented.

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Section: Arcgis-swat Was Applied To the Upper Secosupporting

confidence: 53%

Arcgis-Swat: A Geodata Model and Gis Interface for Swat

Olivera

Valenzuela

Srinivasan

et al. 2006

J Am Water Resources Assoc

167

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show abstract

“…The SWAT model produced reasonable results in the simulation of runoff on a daily and annual basis from multiple subbasins, with the exception of a wooded subbasin. Rosenthal and Hoffman (1999) successfully used SWAT and a spatial database to simulate flows, sediment, and nutrient loadings on a 9,000 km 2 watershed in central Texas to locate potential water quality monitoring sites. SWAT was also successfully validated for streamflow and sediment loads for the Mill Creek Watershed in Texas for 1965-68 and 1968-75 (Srinivasan et al, 1998.…”

Section: Example Calibration/validation Studiesmentioning

confidence: 99%

The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions

Gassman

Reyes²,

Green³

et al. 2007

Transactions of the ASABE

2,389

1,574

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“…SWAT model with a spatial database has been successfully used to simulate flows, sediment, and nutrient loadings of a watershed (Rosenthal and Hoffman 1999). SWAT has been extensively used in many countries worldwide for discharge prediction as well as for soil and water conservation Spruill et al 2000;Zhang et al 2010).…”

Section: Introductionmentioning

confidence: 99%

SWAT Model Calibration and Uncertainty Analysis for Streamflow Prediction in the Kunwari River Basin, India, Using Sequential Uncertainty Fitting

et al. 2015

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The Kunwari River Basin (KRB) needs effective management of water resources for sustainable agriculture and flood hazard mitigation. The Soil and Water Assessment Tool (SWAT), a semi distributed physically based model, was chosen and set up in the KRB for hydrologic modeling. SWAT-CUP (SWAT-Calibration and Uncertainty Programs) was used for model calibration, sensitivity and uncertainty analysis, following the Sequential Uncertainty Fitting (SUFI-2) technique. The model calibration was performed for the period (1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999), with initial 3 years of warm up ; then, the model was validated for the subsequent 6 years of data (2000)(2001)(2002)(2003)(2004)(2005). To assess the competence of model calibration and uncertainty, two indices, the p-factor (observations bracketed by the prediction uncertainty) and the r-factor (achievement of small uncertainty band), were taken into account. The results Environ. Process. of SWAT simulations indicated that during the calibration the p-factor and the r-factor were reported as 0.82 and 0.76, respectively, while during the validation the p-factor and the r-factor were obtained as 0.71 and 0.72, respectively. After a rigorous calibration and validation, the goodness of fit was further assessed through the use of the coefficient of determination (R 2 ) and the Nash-Sutcliffe efficiency (NS) between the observed and the final simulated values. The results indicated that R 2 and NS were 0.77 and 0.74, respectively, during the calibration. The validation also indicated a satisfactory performance with R 2 of 0.71 and NS of 0.69. The results would be useful to the hydrological community, water resources managers involved in agricultural water management and soil conservation, as well as to those involved in mitigating natural hazards such as droughts and floods.

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Hydrologic Modelings/Gis as an Aid in Locating Monitoring Sites

Cited by 21 publications

References 0 publications

Arcgis-Swat: A Geodata Model and Gis Interface for Swat

Arcgis-Swat: A Geodata Model and Gis Interface for Swat

The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions

SWAT Model Calibration and Uncertainty Analysis for Streamflow Prediction in the Kunwari River Basin, India, Using Sequential Uncertainty Fitting

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