A SWAT model validation of nested-scale contemporaneous stream flow, suspended sediment and nutrients from a multiple-land-use watershed of the central USA

Zeiger, Sean J.; Hubbart, Jason A.

doi:10.1016/j.scitotenv.2016.07.178

Cited by 66 publications

(42 citation statements)

References 51 publications

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“…Sanborn Field, South Farm, and Jefferson Farm monitoring sites were used for validation. Three model performance criteria were used to evaluate the model performance including percent bias (PBIAS), root mean square error (RMSE), and mean absolute error (MAE) [35,46,47].…”

Section: Surface-fitting Map Methodsmentioning

confidence: 99%

“…Three model performance criteria were used to evaluate the model performance including PBIAS, RMSE, and MAE [35,46,47]. Sanborn Field, South Farm, and Jefferson Farm monitoring sites were used for validation.…”

Section: Remotely-sensed Map Methodsmentioning

confidence: 99%

“…The stage was measured at each Hinkson Creek gauging site using Sutron Accubar ® constant flow bubblers with an accuracy of 0.02% at 0-7.6 m to 0.05% at 7.6-15.4 m [35][36][37][38]. Precipitation and stage data were stored on Campbell Scientific CR-1000 data loggers.…”

Section: Site Descriptionmentioning

confidence: 99%

“…The study catchment was divided by two Level II Ecoregions [35]. The agricultural headwaters were within the Great Plains ecoregion while the urbanizing lower elevations were in the Ozark Highlands ecoregion.…”

Section: Calibrated Model Performancementioning

confidence: 99%

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An Assessment of Mean Areal Precipitation Methods on Simulated Stream Flow: A SWAT Model Performance Assessment

Zeiger

Hubbart

2017

Water

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Accurate mean areal precipitation (MAP) estimates are essential input forcings for hydrologic models. However, the selection of the most accurate method to estimate MAP can be daunting because there are numerous methods to choose from (e.g., proximate gauge, direct weighted average, surface-fitting, and remotely sensed methods). Multiple methods (n = 19) were used to estimate MAP with precipitation data from 11 distributed monitoring sites, and 4 remotely sensed data sets. Each method was validated against the hydrologic model simulated stream flow using the Soil and Water Assessment Tool (SWAT). SWAT was validated using a split-site method and the observed stream flow data from five nested-scale gauging sites in a mixed-land-use watershed of the central USA. Cross-validation results showed the error associated with surface-fitting and remotely sensed methods ranging from −4.5% to −5.1%, and −9.8% to −14.7%, respectively. Split-site validation results showed the percent bias (PBIAS) values that ranged from −4.5% to −160%. Second order polynomial functions especially overestimated precipitation and subsequent stream flow simulations (PBIAS = −160) in the headwaters. The results indicated that using an inverse-distance weighted, linear polynomial interpolation or multiquadric function method to estimate MAP may improve SWAT model simulations. Collectively, the results highlight the importance of spatially distributed observed hydroclimate data for precipitation and subsequent steam flow estimations. The MAP methods demonstrated in the current work can be used to reduce hydrologic model uncertainty caused by watershed physiographic differences.

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Section: Surface-fitting Map Methodsmentioning

confidence: 99%

Section: Remotely-sensed Map Methodsmentioning

confidence: 99%

Section: Site Descriptionmentioning

confidence: 99%

Section: Calibrated Model Performancementioning

confidence: 99%

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An Assessment of Mean Areal Precipitation Methods on Simulated Stream Flow: A SWAT Model Performance Assessment

Zeiger

Hubbart

2017

Water

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“…In watersheds with a combination of agriculture, urbanization, industry, and mining (i.e., mixed-land-use watersheds) it can be challenging to link specific land use activities to degraded biological condition or biological impairment [3,[17][18][19]. Biological impairment can be the result of land use practices, hydrology, water quality alteration, or other aquatic habitat limitations, and is most often a combination of factors [1].…”

Section: Assessing Aquatic Physical Habitatmentioning

confidence: 99%

Challenges in Aquatic Physical Habitat Assessment: Improving Conservation and Restoration Decisions for Contemporary Watersheds

et al. 2017

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Attribution of in-stream biological impairment to anthropogenic activities and prioritization for restoration and/or conservation can be challenging in contemporary mixed-land-use watersheds. Critical information necessary to improve decision making can be costly and labor intensive, and thus unobtainable for many municipalities. A reduced cost, rapid stream physical habitat assessment (rPHA) can yield information that, when paired with land use data may reveal causal patterns in aquatic physical habitat degradation, and thus assist targeting sites for restoration. However, a great deal of work is needed to reduce associated costs, and validate the potential of rPHA for documenting fine-scale incremental change in physical habitat conditions in complex contemporary watersheds. The following commentary serves to draw attention to rPHA challenges and research needs including (but not limited to) field-based validation and optimization of new remote sensing technologies, evaluation of the accuracy and representativeness of rapid vegetation survey methods, refinement of analytical methods, and consideration of legacy land use impacts and hydrologic system evolution in rPHA results interpretation. Considering the value of rPHA-generated data for improvement of watershed resource management, such challenges constitute timely, high-impact research opportunities for investigators wishing to advance complex, contemporary aquatic ecosystem management.

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Effect of land use change on hydrology of forested watersheds

Dogan

Karpuzcu

2021

Ecohydrology

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Land use/cover changes (LUCCs) in megacities can be rapid and extensive and lead to unintended consequences in sustainable watershed management. The aim of this study was to investigate effects of LUCC on hydrological components using Soil & Water Assessment Tool (SWAT) model in Terkos Basin, Turkey. Four LUCC scenarios (deforestation, urbanization, decrease in agricultural land and expansion in agricultural land) were set up regarding possible future land use changes in the watershed. Surface runoff was the main hydrological component that was impacted by LUCCs. Urbanization and conversion into agricultural lands scenarios resulted in considerable increases in surface runoff. Annual change of surface runoff for urbanization and conversion into agricultural lands scenarios was over 45% when compared to the baseline scenario. More remarkable changes were seen in dry months among the scenarios. Controlling the overall response of the hydrological systems to LUCC depends on better understanding of surface runoff processes. LUCC scenarios were also assessed based on freshwater availability components blue water and green water. The average annual total blue water potential, annual total green water flow and average green water storage of studied sub‐basin were 537, 584 and 108 mm/year for the baseline scenario, respectively. The trends of the blue water flow and green water storage were similar for each scenario, in that they were closely related to precipitation. This study provides valuable insight into hydrological impacts of possible land use changes on forested watersheds.

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A SWAT model validation of nested-scale contemporaneous stream flow, suspended sediment and nutrients from a multiple-land-use watershed of the central USA

Cited by 66 publications

References 51 publications

An Assessment of Mean Areal Precipitation Methods on Simulated Stream Flow: A SWAT Model Performance Assessment

An Assessment of Mean Areal Precipitation Methods on Simulated Stream Flow: A SWAT Model Performance Assessment

Challenges in Aquatic Physical Habitat Assessment: Improving Conservation and Restoration Decisions for Contemporary Watersheds

Effect of land use change on hydrology of forested watersheds

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