Comparison of performance of tile drainage routines in SWAT 2009 and 2012 in an extensively tile-drained watershed in the Midwest

Abstract. Subsurface tile drainage systems are widely used in agricultural watersheds in the Midwestern US and enable the Midwest area to become highly productive agricultural lands, but can also create environmental problems, for example nitrate-N contamination associated with drainage waters. The Soil and Water Assessment Tool (SWAT) has been used to model watersheds with tile drainage. SWAT2012 revisions 615 and 645 provide new tile drainage routines. However, few studies have used these revisions to study tile drainage impacts at both field and watershed scales. Moreover, SWAT2012 revision 645 improved the soil moisture based curve number calculation method, which has not been fully tested. This study used long-term (1991–2003) field site and river station data from the Little Vermilion River (LVR) watershed to evaluate performance of tile drainage routines in SWAT2009 revision 528 (the old routine) and SWAT2012 revisions 615 and 645 (the new routine). Both the old and new routines provided reasonable but unsatisfactory (NSE  <  0.5) uncalibrated flow and nitrate loss results for a mildly sloped watershed with low runoff. The calibrated monthly tile flow, surface flow, nitrate-N in tile and surface flow, sediment and annual corn and soybean yield results from SWAT with the old and new tile drainage routines were compared with observed values. Generally, the new routine provided acceptable simulated tile flow (NSE  =  0.48–0.65) and nitrate in tile flow (NSE  =  0.48–0.68) for field sites with random pattern tile and constant tile spacing, while the old routine simulated tile flow and nitrate in tile flow results for the field site with constant tile spacing were unacceptable (NSE  =  0.00–0.32 and −0.29–0.06, respectively). The new modified curve number calculation method in revision 645 (NSE  =  0.50–0.81) better simulated surface runoff than revision 615 (NSE  =  −0.11–0.49). The calibration provided reasonable parameter sets for the old and new routines in the LVR watershed, and the validation results showed that the new routine has the potential to accurately simulate hydrologic processes in mildly sloped watersheds.

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Comparison of performance of tile drainage routines in SWAT 2009 and 2012 in an extensively tile-drained watershed in the Midwest

10.5194/hess-2017-52 ◽

2017 ◽

Author(s):

Tian Guo ◽

Margaret Gitau ◽

Venkatesh Merwade ◽

Jeffrey Arnold ◽

Raghavan Srinivasan ◽

...

Keyword(s):

Calculation Method ◽

Assessment Tool ◽

Curve Number ◽

Surface Flow ◽

Tile Drainage ◽

Random Pattern ◽

Field Site ◽

Drainage Systems ◽

Nitrate N ◽

Tile Flow

Abstract. Subsurface tile drainage systems are widely used in agricultural watersheds in the Midwestern U.S. Tile drainage systems enable the Midwest area to become highly productive agricultural lands, but can also create environmental problems, for example nitrate-N contamination associated with drainage waters. The Soil and Water Assessment Tool (SWAT) has been used to model watersheds with tile drainage. SWAT2012 revisions 615 and 645 provide new tile drainage routines. However, few studies have used these revisions to study tile drainage impacts at both field and watershed scales. Moreover, SWAT2012 revision 645 improved the soil moisture based curve number calculation method, which has not been fully tested. This study used long-term (1991–2003) field site and river station data from the Little Vermilion River (LVR) watershed to evaluate performance of tile drainage routines in SWAT2009 revision 528 (the old routine) and SWAT2012 revisions 615 and 645 (the new routine). Both routines provided reasonable but unsatisfactory uncalibrated flow and nitrate loss results. Calibrated monthly tile flow, surface flow, nitrate-N in tile and surface flow, sediment and annual corn and soybean yield results from SWAT with the old and new tile drainage routines were compared with observed values. Generally, the new routine provided acceptable simulated tile flow (NSE = 0.50–0.68) and nitrate in tile flow (NSE = 0.50–0.77) for both field sites with random pattern tile and constant tile spacing, while the old routine simulated tile flow and nitrate in tile flow results for the field site with constant tile spacing were unacceptable (NSE = −0.77– −0.20 and −0.99–0.21 respectively). The new modified curve number calculation method in revision 645 (NSE = 0.56–0.82) better simulated surface runoff than revision 615 (NSE = −5.95 ~ 0.5). Calibration provided reasonable parameter sets for the old and new routines in LVR watershed, and the validation results showed that the new routine has the potential to accurately simulate hydrologic processes in mildly-sloped watersheds.

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Assessment of TMPA 3B42V7 and PERSIANN-CDR in Driving Hydrological Modeling in a Semi-Humid Watershed in Northeastern China

Remote Sensing ◽

10.3390/rs12193133 ◽

2020 ◽

Vol 12 (19) ◽

pp. 3133

Author(s):

Lu Zhang ◽

Zhuohang Xin ◽

Huicheng Zhou

Keyword(s):

Hydrological Modeling ◽

Assessment Tool ◽

Surface Flow ◽

Northeastern China ◽

Base Flow ◽

Hydrological Processes ◽

Superior Performance ◽

Climate Data ◽

Satellite Precipitation ◽

Precipitation Estimation

Recent developments of satellite precipitation products provide an unprecedented opportunity for better precipitation estimation, and thus broaden hydrological application. However, due to the errors and uncertainties of satellite products, a thorough validation is usually required before putting into the real hydrological application. As such, this study aims to provide a comprehensive evaluation on the performances of Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA) 3B42V7 and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), as well as their adequacies in simulating hydrological processes in a semi-humid region in the northeastern China. It was found that TMPA 3B42V7 showed a superior performance at the daily and monthly time scales, and had a favorable capture of the rainfall-intensity distribution. Intra-annual comparisons indicated a better representation of TMPA 3B42V7 from January to September, whereas PERSIANN-CDR was more reliable from October to December. The Soil and Water Assessment Tool (SWAT) driven by gauge precipitation data performed excellently with NSE > 0.9, while the performances of TMPA 3B42V7- and PERSIANN-CDR-based models are satisfactory with NSE > 0.5. The performances varied under different flow levels and hydrological years. Water balance analysis indicated a better performance of TMPA 3B42V7 in simulating the hydrological processes, including evapotranspiration, groundwater recharge and total runoff. The runoff compositions (i.e., base flow, subsurface flow, and surface flow) driven by TMPA 3B42V7 were more accordant with the actual hydrological features. This study will not only help recognize the potential satellite precipitation products for local water resources management, but also be a reference for the poor-gauged regions with similar hydrologic and climatic conditions around the world, especially the northeastern China and western Russia.

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Improved Curve Number Estimation in SWAT by Reflecting the Effect of Rainfall Intensity on Runoff Generation

Water ◽

10.3390/w11010163 ◽

2019 ◽

Vol 11 (1) ◽

pp. 163 ◽

Cited By ~ 7

Author(s):

Dejian Zhang ◽

Qiaoyin Lin ◽

Xingwei Chen ◽

Tian Chai

Keyword(s):

Rainfall Intensity ◽

Assessment Tool ◽

Flow Simulation ◽

Daily Rainfall ◽

Curve Number ◽

Base Flow ◽

Data Sets ◽

Rainfall Runoff ◽

Runoff Generation ◽

The Relationship

Determining the amount of rainfall that will eventually become runoff and its pathway is a crucial process in hydrological modelling. We proposed a method to better estimate curve number by adding an additional component (AC) to better account for the effects of daily rainfall intensity on rainfall-runoff generation. This AC is determined by a regression equation developed from the relationship between the AC series derived from fine-tuned calibration processes and observed rainfall series. When incorporated into the Soil and Water Assessment Tool and tested in the Anxi Watershed, it is found, overall, the modified SWAT (SWAT-ICN) outperformed the original SWAT (SWAT-CN) in terms of stream flow, base flow, and annual extreme flow simulation. These models were further evaluated with the data sets of two adjacent watersheds. Similar results were achieved, indicating the ability of the proposed method to better estimate curve number.

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Performance of HEC-HMS and SWAT to simulate streamflow in the sub-humid tropical Hemavathi catchment

Journal of Water and Climate Change ◽

10.2166/wcc.2021.072 ◽

2021 ◽

Author(s):

N. C. Sanjay Shekar ◽

D. C. Vinay

Keyword(s):

Model Calibration ◽

Assessment Tool ◽

Swat Model ◽

Model Performance ◽

Curve Number ◽

Coefficient Of Determination ◽

Hydrological Models ◽

Daily Streamflow ◽

Compensation Factor ◽

Elevation Model

Abstract The present study was conducted to examine the accuracy and applicability of the hydrological models Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center (HEC)- Hydrologic Modeling System (HMS) to simulate streamflows. Models combined with the ArcGIS interface have been used for hydrological study in the humid tropical Hemavathi catchment (5,427 square kilometer). The critical focus of the streamflow analysis was to determine the efficiency of the models when the models were calibrated and optimized using observed flows in the simulation of streamflows. Daily weather gauge stations data were used as inputs for the models from 2014–2020 period. Other data inputs required to run the models included land use/land cover (LU/LC) classes resulting from remote sensing satellite imagery, soil map and digital elevation model (DEM). For evaluating the model performance and calibration, daily stream discharge from the catchment outlet data were used. For the SWAT model calibration, available water holding capacity by soil (SOL_AWC), curve number (CN) and soil evaporation compensation factor (ESCO) are identified as the sensitive parameters. Initial abstraction (Ia) and lag time (Tlag) are the significant parameters identified for the HEC-HMS model calibration. The models were subsequently adjusted by autocalibration for 2014–2017 to minimize the variations in simulated and observed streamflow values at the catchment outlet (Akkihebbal). The hydrological models were validated for the 2018–2020 period by using the calibrated models. For evaluating the simulating daily streamflows during calibration and validation phases, performances of the models were conducted by using the Nash-Sutcliffe model efficiency (NSE) and coefficient of determination (R2). The SWAT model yielded high R2 and NSE values of 0.85 and 0.82 for daily streamflow comparisons for the catchment outlet at the validation time, suggesting that the SWAT model showed relatively good results than the HEC-HMS model. Also, under modified LU/LC and ungauged streamflow conditions, the calibrated models can be later used to simulate streamflows for future predictions. Overall, the SWAT model seems to have done well in streamflow analysis capably for hydrological studies.

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DETERMINATION OF CONTAMINATATED WELLS TO NO3-N: A NOVEL VULNERABILITY ASSESSMENT TOOL

Journal of Urban and Environmental Engineering ◽

10.4090/juee.2014.v8n2.243249 ◽

2015 ◽

pp. 243-249

Author(s):

Pijush Samui ◽

Barnali Dixon

Keyword(s):

Assessment Tool ◽

Promising Result ◽

Regional Scale ◽

Cost Effective ◽

Relevance Vector Machine ◽

Quality Data ◽

Support Vector ◽

Water Quality Data ◽

Nitrate N

Contamination of well with nitrate-N (NO3-N) posses various threats to human health. This problem becomes even more critical when these wells serve as source of drinking water as in the case of many rural parts of USA. This article employs Relevance Vector Machine (RVM) for determination of non-contaminated and contaminated well with nitrate-N (NO3-N) in Polk County, Florida (USA). This research will provide a regional scale integrated GIS-based modeling approach to predict NO3-N contamination of ground water in a cost effective way. This approach also allows for higher true positive results (TPR) with fewer variables when data are imprecise and full of uncertainty which is common with available regional scale data). RVM technique is a Bayesian extension of the Support Vector Machine (SVM). Here, the RVM has been used as a classification tool. Well water quality data (nitrate-N) from 6,917 wells provided by Florida Department of Environmental Protection (USA) has been used to develop the RVM model. An equation has been also presented from the developed RVM model. The developed RVM has been compared with the Artificial Neural Network (ANN) and SVM models. This study shows that the developed RVM produces promising result for prediction of non-contaminated and contaminated well with N. The model is important because its real world applications enable water managers to more effectively manage contaminant levels within specific watersheds.

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Hydrological modeling using the SWAT Model in urban and peri-urban environments: The case of Kifissos experimental sub-basin (Athens, Greece)

10.5194/hess-2021-482 ◽

2021 ◽

Author(s):

Evgenia Koltsida ◽

Nikos Mamassis ◽

Andreas Kallioras

Keyword(s):

Surface Runoff ◽

Hydrological Modeling ◽

Assessment Tool ◽

Swat Model ◽

Model Performance ◽

Curve Number ◽

Urban Environments ◽

Time Intervals ◽

Curve Number Method ◽

Hourly Rainfall

Abstract. SWAT (Soil and Water Assessment Tool) is a continuous time, semi-distributed river basin model that has been widely used to evaluate the effects of alternative management decisions on water resources. This study, demonstrates the application of SWAT model for streamflow simulation in an experimental basin with daily and hourly rainfall observations to investigate the influence of rainfall resolution on model performance. The model was calibrated for 2018 and validated for 2019 using the SUFI-2 algorithm in the SWAT-CUP program. Daily surface runoff was estimated using the Curve Number method and hourly surface runoff was estimated using the Green and Ampt Mein Larson method. A sensitivity analysis conducted in this study showed that the parameters related to groundwater flow were more sensitive for daily time intervals and channel routing parameters were more influential for hourly time intervals. Model performance statistics and graphical techniques indicated that the daily model performed better than the sub-daily model. The Curve Number method produced higher discharge peaks than the Green and Ampt Mein Larson method and estimated better the observed values. Overall, the general agreement between observations and simulations in both models suggests that the SWAT model appears to be a reliable tool to predict discharge over long periods of time.

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Estimation of Surface Runoff to Bahr AL-Najaf

Journal of Engineering ◽

10.31026/j.eng.2021.09.05 ◽

2021 ◽

Vol 27 (9) ◽

pp. 51-63

Author(s):

Ataa Ali Farhan ◽

Basim Sh. Abed

Keyword(s):

Surface Runoff ◽

Assessment Tool ◽

Curve Number ◽

Coefficient Of Determination ◽

Flow Conditions ◽

City Center ◽

P Factor ◽

Sensitive Parameters ◽

The City ◽

Water Assessment

The estimation of the amounts of Surface runoff resulting from rainfall in the water basins is of great importance in water resources management. The study area (Bahr Al-Najaf) is located on the western edge of the plateau and the southwestern part of the city center of Najaf, with an area of 2729.4 (km2). The soil and water assessment tool (SWAT) with ArcGIS software was used to simulate the runoff coming from the three main valleys (Kharr (A and B)), Shoaib Al-Rahimawi, and Maleh), that contribute the flow to the study area. The results of the model showed that the SWAT software was successfully simulating the flow conditions based on the coefficient of determination (R2), the Nash coefficient (NSE), P-factor, and R-factor for calibration (validation) ranged between 0.59-0.62 (0.51-0.59), 0.59-0.66 (0,.60-0.62), 0.57-0.76 (0.62-0.76), and 0.58-0.74 (0.55-0.70) respectively for these valleys. Moreover, the sensitivity results revealed that the most sensitive parameters in (SWAT-CUP) SWAT calibration and uncertainty programs are the curve number (CN2) for the runoff, soil available water capacity (SOL_AWC), and Saturated hydraulic conductivity (Soil_k), according to the calibration results for the main three valleys related the study area. Three hypothesis scenarios were implemented according to the assumed amount of precipitation that would submit a water level of 16,18, and 22 (m.a.m.s.l.) which would result in filling with the bounded lake, the whole study area, and exceeding the boundaries to flood part of the ancient Najaf City.

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Small Reservoir Impact on Simulated Watershed-Scale Nutrient Yield

Research Letters in Ecology ◽

10.1155/2007/12571 ◽

2007 ◽

Vol 2007 ◽

pp. 1-4 ◽

Cited By ~ 1

Author(s):

Shane J. Prochnow ◽

Joseph D. White ◽

Thad Scott ◽

Christopher Filstrup

Keyword(s):

Total Phosphorus ◽

Nutrient Loading ◽

Assessment Tool ◽

Agricultural Runoff ◽

Surface Flow ◽

Long Term Storage ◽

Nutrient Yield ◽

Potential Strategy ◽

The Impact

The soil and water assessment tool (SWAT) is used to assess the influence of small upland reservoirs (PL566) on watershed nutrient yield. SWAT simulates the impact of collectively increasing and decreasing PL566 magnitudes (size parameters) on the watershed. Totally removing PL566 reservoirs results in a 100%increase in total phosphorus and an 82%increase in total nitrogen, while a total maximum daily load (TMDL) calling for a 50%reduction in total phosphorus can be achieved with a 500%increase in the magnitude of PL566s in the watershed. PL566 reservoirs capture agriculture pollution in surface flow, providing long-term storage of these constituents when they settle to the reservoir beds. A potential strategy to reduce future downstream nutrient loading is to enhance or construct new PL566 reservoirs in the upper basin to better capture agricultural runoff.

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Parameter sensitivity analysis of SWAT model for streamflow simulation with multisource precipitation datasets

Hydrology Research ◽

10.2166/nh.2019.083 ◽

2019 ◽

Vol 50 (3) ◽

pp. 861-877 ◽

Cited By ~ 4

Author(s):

Jing Guo ◽

Xiaoling Su

Keyword(s):

Assessment Tool ◽

Swat Model ◽

Curve Number ◽

Model Parameters ◽

Base Temperature ◽

Streamflow Prediction ◽

Moisture Condition ◽

Simulation Performance ◽

Fitting Procedure ◽

Streamflow Simulation

Abstract Streamflow in the Shiyang River basin is numerically investigated based on the soil and water assessment tool (SWAT). The interpolation precipitation datasets of GSI, multisource satellite and reanalysis precipitation datasets including TRMM, CMDF, CFSR, CHIRPS and PGF are specially applied as the inputs for SWAT model, and the sensitivities of model parameters, as well as streamflow prediction uncertainties, are discussed via the sequential uncertainty fitting procedure (SUFI-2). Results indicate that streamflow simulation can be effectively improved by downscaling the precipitation datasets. The sensitivities of model parameters vary significantly with respect to different precipitation datasets and sub-basins. CN2 (initial SCS runoff curve number for moisture condition II) and SMTMP (base temperature of snow melt) are found to be the most sensitive parameters, which implies that the generations of surface runoff and snowmelt are extremely crucial for streamflow in this basin. Moreover, the uncertainty analysis of streamflow prediction indicates that the performance of simulation can be further improved by parameter optimization. It also demonstrates that the precipitation data from satellite and reanalysis datasets can be applied to streamflow simulation as effective inputs, and the dependences of parameter sensitivities on basin and precipitation dataset are responsible for the variation of simulation performance.

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Evaluation of swat-terrace performance for simulating the benefits of terraces on runoff and erosion

10.32469/10355/62522 ◽

2016 ◽

Author(s):

◽

Sitarrine Thongpussawal

Keyword(s):

Assessment Tool ◽

Swat Model ◽

Poor Performance ◽

Curve Number ◽

Hydrologic Model ◽

Watershed Scale ◽

Percent Reduction ◽

Slope Length ◽

Conservation Practice ◽

P Factor

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Terracing is a conservation practice to reduce erosion and intercept runoff from steep lands. Terraces control erosion and runoff by dividing long slopes into shorter slopes; thus, decreasing slope length, which reduces the magnitude and velocity of concentrated flow and allows for sediment to deposit in the cut segment of the terraces. The Soil and Water Assessment Tool (SWAT) is a continuous time, semi-distributed, watershed scale hydrologic model widely used to evaluate runoff and erosion. To account for terrace effects on runoff and erosion, SWAT has relied on reducing the slope length, adjusting the empirical Universal Soil Erosion Equation (USLE) support practice factor (P-factor), and adjusting the hydrologic runoff Curve Number (CN). This tool has limitations, and the runoff and erosion may not be well estimated because of changes in land shape after terrace installation. A modification of the SWAT (called SWAT-Terrace or SWAT-T) explicitly simulates runoff and erosion from terraces by separating terraces into three segments instead of evaluating the entire terrace. SWAT-T aims to improve the simulation of the hydrologic process of runoff and erosion from terraces. The objectives of this work are to 1) evaluate the performance of SWAT-T for simulating the terrace benefits on runoff and erosion from the Goodwater Creek Experimental Watershed (GCEW) at the Hydrologic Response Unit (HRU) and watershed scales, and 2) compare terrace benefits on runoff and erosion estimated with SWAT and with SWAT-T in GCEW. The SWAT model was parameterized for the slope length, USLE P-factor, and the CN. The SWAT-T model was parameterized for slope length, steepness, and USLE P-factor for three terrace segments. Data from 1993-2010 measured at the watershed outlet were used to evaluate the models. To estimate terrace benefits on runoff and erosion, models were compared with and without terraces. Results of SWAT-T showed good performance for the monthly runoff, but poor performance for the monthly erosion. This is probably because of large storms in spring 2002 that prevented planting, causing poorly simulated scheduling of actual field operations. SWAT-T showed [about]2 percent reduction in runoff and [about]13 percent reduction in erosion at the HRU scale and showed 0.1 percent reduction of runoff and [about]3 percent reduction in erosion at the watershed scale. For comparison of terrace benefits on runoff and erosion estimated with SWAT and with SWAT-T, SWAT-T showed more benefit in runoff and erosion at the HRU scale compared to SWAT. Results of SWAT-T showed a 13 percent reduction in runoff and a 95 percent reduction in erosion with terrace installation. Conversely, SWAT showed only a 0.03 percent reduction in runoff and an 89 percent reduction in erosion. Studies using the SWAT-T model indicated that the model may be used for quantifying the terrace benefits on runoff and erosion from terraced-cropped HRUs and watershed scales. Terrace algorithm incorporated in SWAT (SWAT-T) allowed model estimated runoff and erosion trapping in the cut terraced segment leading to better estimation of runoff and erosion.

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