scholarly journals Assessing the sensitivity of SWAT physical parameters to potential evapotranspiration estimation methods over a coastal plain watershed in the southeastern United States

2016 ◽  
Vol 48 (2) ◽  
pp. 395-415 ◽  
Author(s):  
S. Zahra Samadi

One of the key inputs of a hydrologic budget is the potential evapotranspiration (PET), which represents the hypothetical upper limit to evapotranspirative water losses. However, different mathematical formulas proposed for defining PET often produce inconsistent results and challenge hydrological estimation. The objective of this study is to investigate the effects of the Priestley–Taylor (P–T), Hargreaves, and Penman–Monteith methods on daily streamflow simulation using the Soil and Water Assessment Tool (SWAT) for the southeastern United States. PET models are compared in terms of their sensitivity to the SWAT parameters and their ability to simulate daily streamflow over a five-year simulation period. The SWAT model forced by these three PET methods and by gauged climatic dataset showed more deficiency during low and peak flow estimates. Sensitive parameters vary in magnitudes with more skew and bias in saturated soil hydraulic conductivity and shallow aquifer properties. The results indicated that streamflow simulation using the P–T method performed well especially during extreme events’ simulation.

2019 ◽  
Vol 23 (2) ◽  
pp. 1113-1144 ◽  
Author(s):  
Abolanle E. Odusanya ◽  
Bano Mehdi ◽  
Christoph Schürz ◽  
Adebayo O. Oke ◽  
Olufiropo S. Awokola ◽  
...  

Abstract. The main objective of this study was to calibrate and validate the eco-hydrological model Soil and Water Assessment Tool (SWAT) with satellite-based actual evapotranspiration (AET) data from the Global Land Evaporation Amsterdam Model (GLEAM_v3.0a) and from the Moderate Resolution Imaging Spectroradiometer Global Evaporation (MOD16) for the Ogun River Basin (20 292 km2) located in southwestern Nigeria. Three potential evapotranspiration (PET) equations (Hargreaves, Priestley–Taylor and Penman–Monteith) were used for the SWAT simulation of AET. The reference simulations were the three AET variables simulated with SWAT before model calibration took place. The sequential uncertainty fitting technique (SUFI-2) was used for the SWAT model sensitivity analysis, calibration, validation and uncertainty analysis. The GLEAM_v3.0a and MOD16 products were subsequently used to calibrate the three SWAT-simulated AET variables, thereby obtaining six calibrations–validations at a monthly timescale. The model performance for the three SWAT model runs was evaluated for each of the 53 subbasins against the GLEAM_v3.0a and MOD16 products, which enabled the best model run with the highest-performing satellite-based AET product to be chosen. A verification of the simulated AET variable was carried out by (i) comparing the simulated AET of the calibrated model to GLEAM_v3.0b AET, which is a product that has different forcing data than the version of GLEAM used for the calibration, and (ii) assessing the long-term average annual and average monthly water balances at the outlet of the watershed. Overall, the SWAT model, composed of the Hargreaves PET equation and calibrated using the GLEAM_v3.0a data (GS1), performed well for the simulation of AET and provided a good level of confidence for using the SWAT model as a decision support tool. The 95 % uncertainty of the SWAT-simulated variable bracketed most of the satellite-based AET data in each subbasin. A validation of the simulated soil moisture dynamics for GS1 was carried out using satellite-retrieved soil moisture data, which revealed good agreement. The SWAT model (GS1) also captured the seasonal variability of the water balance components at the outlet of the watershed. This study demonstrated the potential to use remotely sensed evapotranspiration data for hydrological model calibration and validation in a sparsely gauged large river basin with reasonable accuracy. The novelty of the study is the use of these freely available satellite-derived AET datasets to effectively calibrate and validate an eco-hydrological model for a data-scarce catchment.


2012 ◽  
Vol 3 (3) ◽  
pp. 207-224 ◽  
Author(s):  
Dao Nguyen Khoi ◽  
Tadashi Suetsugi

The Be River Catchment was studied to quantify the potential impact of climate change on the streamflow using a multi-model ensemble approach. Climate change scenarios (A1B and B1) were developed from an ensemble of four GCMs (general circulation models) (CGCM3.1 (T63), CM2.0, CM2.1 and HadCM3) that showed good performance for the Be River Catchment through statistical evaluations between 15 GCM control simulations and the corresponding time series of observations at annual and monthly levels. The Soil and Water Assessment Tool (SWAT) was used to investigate the impact on streamflow under climate change scenarios. The model was calibrated and validated using daily streamflow records. The calibration and validation results indicated that the SWAT model was able to simulate the streamflow well, with Nash–Sutcliffe efficiency exceeding 0.78 for the Phuoc Long station and 0.65 for the Phuoc Hoa station, for both calibration and validation at daily and monthly steps. Their differences in simulating the streamflow under future climate scenarios were also investigated. The results indicate a 1.0–2.9 °C increase in annual temperature and a −4.0 to 0.7% change in annual precipitation corresponding to a change in streamflow of −6.0 to −0.4%. Large decreases in precipitation and runoff are observed in the dry season.


2020 ◽  
Author(s):  
Paul D. Wagner ◽  
Katrin Bieger ◽  
Jeffrey G. Arnold ◽  
Nicola Fohrer

<p>The hydrology of rural lowland catchments in Northern Germany is characterized by near-surface groundwater tables and extensive tile drainage. Previous research has shown that representing these characteristics with the hydrologic model SWAT (Soil and Water Assessment Tool) required an improvement of groundwater processes, which has been achieved by dividing the shallow aquifer into a fast and a slow shallow aquifer. The latest version of the Soil and Water Assessment Tool (SWAT+) features several improvements compared to previous versions of the model, e.g. the definition of landscape units that allow for a better representation of spatio-temporal dynamics. To evaluate the new model capabilities for lowland catchments, we assess the performance of SWAT+ in comparison to previous SWAT applications in the Kielstau Catchment in Northern Germany. The Kielstau Catchment is about 50 km² large, is dominated by agricultural land use, and has been thoroughly monitored since 2005. In particular, we explore the capabilities of SWAT+ in terms of watershed configuration and simulation of landscape processes by comparing two model setups. The first setup is comparable to previous SWAT models for the catchment, i.e. yields from hydrologic response units are summed up at subbasin level and added directly to the stream. In the second SWAT+ model, subbasins are divided into upland areas and floodplains and runoff is routed across the landscape before it reaches the streams. Model performance is assessed with regard to measured stream flow at the outlet of the catchment. Results from the new SWAT+ model confirm that two groundwater layers are necessary to represent stream flow in the catchment. The representation of routing processes from uplands to floodplains in the model further improved the simulation of stream flow. The outcomes of this study are expected to contribute to a better understanding and model representation of lowland hydrology.</p>


Author(s):  
N. C. Sanjay Shekar ◽  
D. C. Vinay

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.


2017 ◽  
Author(s):  
Sharad K. Jain ◽  
Sanjay K. Jain ◽  
Neha Jain ◽  
Chong-Yu Xu

Abstract. A large population depends on runoff from Himalayan rivers which have high hydropower potential; floods in these rivers are also frequent. Current understanding of hydrologic response mechanism of these rivers and impact of climate change is inadequate due to limited studies. This paper presents results of modeling to understand the hydrologic response and compute the water balance components of a Himalayan river basin in India viz. Ganga up to Devprayag. Soil and Water Assessment Tool (SWAT) model was applied for simulation of the snow/rainfed catchment. SWAT was calibrated with daily streamflow data for 1992–98 and validated with data for 1999–2005. Manual calibration was carried out to determine model parameters and quantify uncertainty. Results indicate good simulation of streamflow; main contribution to water yield is from lateral and ground water flow. Water yield and ET for the catchments varies between 43–46 % and 57–58 % of precipitation, respectively. The contribution of snowmelt to lateral runoff for Ganga River ranged between 13–20 %. More attention is needed to strengthen spatial and temporal hydrometeorological database for the study basins for improved modeling.


Author(s):  
Gengxi Zhang ◽  
Xiaoling Su ◽  
Olusola O. Ayantobo ◽  
Kai Feng ◽  
Jing Guo

Precipitation and temperature are significant inputs for hydrological models. Currently, many satellite and reanalysis precipitation and air temperature datasets exist at different spatio-temporal resolutions at a global and quasi-global scale. This study evaluated the performances of three open-access precipitation datasets (gauge-adjusted research-grade Global Satellite Mapping of Precipitation (GSMaP_Gauge), Climate Hazards Group Infrared Precipitation with Station data (CHIRPS), Climate Forecast System Reanalysis(CFSR)) and CFSR air temperature dataset in driving the Soil and Water Assessment Tool (SWAT) model required for the monthly simulation of streamflow in the upper Shiyang River Basin of northwest China. After a thorough comparison of six model scenarios with different combinations of precipitation and air temperature inputs, the following conclusions were drawn: (1) Although the precipitation products had similar spatial patterns, however, CFSR differs significantly by showing an overestimation; (2) CFSR air temperature yielded almost identical performance in the streamflow simulation than the measured air temperature from gauge stations; (3) among the three open-access precipitation datasets, CHIRPS produced the best performance. These results suggested that the CHIRPS precipitation and CFSR air temperature datasets which are available at high spatial resolution (0.05), could be a promising alternative open-access data source for streamflow simulation in the case of limited access to desirable gauge data in the data-scarce area.


2019 ◽  
Vol 50 (3) ◽  
pp. 861-877 ◽  
Author(s):  
Jing Guo ◽  
Xiaoling Su

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.


Water ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 1004 ◽  
Author(s):  
Guihua Liu ◽  
Zhiming He ◽  
Zhaoqing Luan ◽  
Shuhua Qi

Water supply availability has significant impacts on the biggest base for commodity grain production: The Sanjiang Plain in northeast China. The SWAT (soil and water assessment tool) model and IHACRES (identification of unit hydrographs and component flows from rainfall, evapotranspiration and streamflow data) model were used for modelling streamflow variability in the upper Naoli River watershed to determine the applicability of hydrological models to the marsh rivers. Both the SWAT and IHACRES models were suitable for streamflow simulation, having R2 (coefficient of determination) and NS (Nash–Sutcliffe) values greater than 0.7, and PBIAS (percent bias) smaller than 25%. The IHACRES model was easy to use, with less data-preparation, and was found to be a better choice for runoff simulation in a watershed less affected by human activity. The simulation result was better in primeval times, i.e., 1956–1966, than the period 1967–2005, when its performance was found to be unfavorable. In contrast, the complex, processes-based SWAT model was found to be more appropriate for simultaneously simulating streamflow variability. In addition, the effects of land use change and human activities in the watershed—where agricultural activities are intensive—were evaluated. The study found that the SWAT model was potentially suitable for water resource planning and management.


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