Application of meteorological element combination-driven SWAT model based on meteorological datasets in alpine basin

Abstract Thus far, reanalysis-based meteorological products have drawn little attention to the influence of meteorological elements of products on hydrological modeling. This study aims to evaluate the hydrological application potential of the precipitation, temperature, and solar radiation of the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) and Climate Forecast System Reanalysis (CFSR) in an alpine basin. The precipitation, temperature, and solar radiation of the gauge-observed meteorological dataset (GD), CFSR, and CMADS were cross-combined, and 20 scenarios were constructed to drive the SWAT model. From the comprehensive comparisons of all scenarios, we drew the following conclusions: (1) among the three meteorological elements, precipitation has the greatest impact on the simulation results, and using GD precipitation from sparse stations yielded better performance than CMADS and CFSR; (2) although the SWAT modeling driven by CMADS and CFSR performed poorly, with CMADS underestimation and CFSR overestimation, the temperature and solar radiation of CMADS and CFSR can be an alternative data source for streamflow simulation; (3) models using GD precipitation, CFSR temperature, and CFSR solar radiation as input yielded the best performance in streamflow simulation, suggesting that these data sources can be applied to this data-scarce alpine region.

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A Review of SWAT Model Application in Africa

Water ◽

10.3390/w13091313 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1313

Author(s):

George Akoko ◽

Tu Hoang Le ◽

Takashi Gomi ◽

Tasuku Kato

Keyword(s):

Climate Change ◽

Land Use ◽

Water Resources ◽

Hydrological Modeling ◽

Assessment Tool ◽

Swat Model ◽

Data Availability ◽

Mitigation Measures ◽

Model Parameterization ◽

Basin Scale

The soil and water assessment tool (SWAT) is a well-known hydrological modeling tool that has been applied in various hydrologic and environmental simulations. A total of 206 studies over a 15-year period (2005–2019) were identified from various peer-reviewed scientific journals listed on the SWAT website database, which is supported by the Centre for Agricultural and Rural Development (CARD). These studies were categorized into five areas, namely applications considering: water resources and streamflow, erosion and sedimentation, land-use management and agricultural-related contexts, climate-change contexts, and model parameterization and dataset inputs. Water resources studies were applied to understand hydrological processes and responses in various river basins. Land-use and agriculture-related context studies mainly analyzed impacts and mitigation measures on the environment and provided insights into better environmental management. Erosion and sedimentation studies using the SWAT model were done to quantify sediment yield and evaluate soil conservation measures. Climate-change context studies mainly demonstrated streamflow sensitivity to weather changes. The model parameterization studies highlighted parameter selection in streamflow analysis, model improvements, and basin scale calibrations. Dataset inputs mainly compared simulations with rain-gauge and global rainfall data sources. The challenges and advantages of the SWAT model’s applications, which range from data availability and prediction uncertainties to the model’s capability in various applications, are highlighted. Discussions on considerations for future simulations such as data sharing, and potential for better future analysis are also highlighted. Increased efforts in local data availability and a multidimensional approach in future simulations are recommended.

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Evaluation of Open Access Precipitation and Temperature Products Using SWAT in Shiyang River Basin, Northwest China

10.20944/preprints202003.0294.v1 ◽

2020 ◽

Author(s):

Gengxi Zhang ◽

Xiaoling Su ◽

Olusola O. Ayantobo ◽

Kai Feng ◽

Jing Guo

Keyword(s):

Open Access ◽

River Basin ◽

Air Temperature ◽

Assessment Tool ◽

Swat Model ◽

Northwest China ◽

Promising Alternative ◽

Shiyang River Basin ◽

Streamflow Simulation ◽

Precipitation And Temperature

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.

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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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Evaluation of hydrological modeling using climatic station and gridded precipitation dataset

MAUSAM ◽

10.54302/mausam.v71i4.63 ◽

2021 ◽

Vol 71 (4) ◽

pp. 717-728

Author(s):

KHAN WISAL ◽

KHAN ASIF ◽

KHAN AFED ULLAH ◽

KHAN MUJAHID

Keyword(s):

Hydrological Modeling ◽

Assessment Tool ◽

Swat Model ◽

Indus Basin ◽

Gridded Data ◽

Flow Data ◽

Rainfall Events ◽

Station Data ◽

Measured Flow ◽

Water Assessment

The conventional rainfall data estimates are relatively accurate at some points of the region. The interpolation of such type of data approximates the actual rainfield however in data scarce regions; the resulted rainfield is the rough estimate of the actual rainfall events. In data scarce regions like Indus basin Pakistan, the data obtained through remote sensing can be very useful. This research evaluates two types of gridded data i.e., European Reanalysis (ERA) interim and Japanese Reanalysis 55 years (JRA-55) along with the climatic station data for three small dams in Pakistan. Since no measured flow data is available at these dams, the nearest possible catchments where flow data is available are calibrated and the calibrated parameters of these catchments are then used in actual dams for simulating the flow from all the three types of data using Soil and Water Assessment Tool (SWAT). The results of the comparison of gridded and rainguage precipitation shows that gridded data highly overestimates the climatic station data. Similar results were observed in the comparison of flow simulated by SWAT model. The Peak flood calculated from JRA-55 overestimates while the Era-Interim peak floods are comparable to that of climatic stations in two of the three catchments.

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Hydrological modeling using the SWAT model based on two types of data from the watershed of Beni Haroun dam, Algeria

Journal of Water and Land Development ◽

10.2478/jwld-2019-0065 ◽

2019 ◽

Vol 43 (1) ◽

pp. 76-89 ◽

Cited By ~ 1

Author(s):

Zakaria Kateb ◽

Hamid Bouchelkia ◽

Abdelhalim Benmansour ◽

Fadila Belarbi

Keyword(s):

Remote Sensing ◽

Hydrological Modeling ◽

Assessment Tool ◽

Hydrological Cycle ◽

Swat Model ◽

Soil Mapping ◽

Digital Soil Mapping ◽

Validation Period ◽

Calibration Period ◽

Water Assessment

AbstractThe dam of Beni Haroun is the largest in Algeria, and its transfer structures feed seven provinces (wilayas) in the eastern part of Algeria. Due to its importance in the region, it has now become urgent to study its watershed as well as all the parameters that can influence the water and solid intakes that come into the dam. The Soil and Water Assessment Tool (SWAT) model is used to quantify the water yields and identify the vulnerable spots using two scenarios. The first one uses worldwide data (GlobCover and HWSD), and the second one employs remote sensing and digital soil mapping in order to determine the most suitable data to obtain the best results. The SWAT model can be used to reproduce the hydrological cycle within the watershed. Concerning the first scenario, during the calibration period, R2 was found between 0.45 and 0.69, and the Nash–Sutcliffe efficiency (NSE) coefficient was within the interval from 0.63 to 0.80; in the validation period, R2 lied between 0.47 and 0.59, and the NSE coefficient ranged from 0.58 to 0.64. As for the second scenario, during the calibration period, R2 was between 0.60 and 0.66, and the NSE coefficient was between 0.55 and 0.75; however, during the validation period, R2 was in the interval from 0.56 to 0.70, and the NSE coefficient within the range 0.64–0.70. These findings indicate that the data obtained using remote sensing and digital soil mapping provide a better representation of the watershed and give a better hydrological modelling.

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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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Intercomparison of a Lumped Model and a Distributed Model for Streamflow Simulation in the Naoli River Watershed, Northeast China

Water ◽

10.3390/w10081004 ◽

2018 ◽

Vol 10 (8) ◽

pp. 1004 ◽

Cited By ~ 2

Author(s):

Guihua Liu ◽

Zhiming He ◽

Zhaoqing Luan ◽

Shuhua Qi

Keyword(s):

Northeast China ◽

Assessment Tool ◽

Swat Model ◽

Resource Planning ◽

Coefficient Of Determination ◽

Distributed Model ◽

The Sanjiang Plain ◽

River Watershed ◽

Streamflow Variability ◽

Streamflow Simulation

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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Inter-Comparison of Gauge-Based Gridded Data, Reanalysis and Satellite Precipitation Product with an Emphasis on Hydrological Modeling

Atmosphere ◽

10.3390/atmos11111252 ◽

2020 ◽

Vol 11 (11) ◽

pp. 1252

Author(s):

Sridhara Setti ◽

Rathinasamy Maheswaran ◽

Venkataramana Sridhar ◽

Kamal Kumar Barik ◽

Bruno Merz ◽

...

Keyword(s):

Hydrological Modeling ◽

Assessment Tool ◽

Swat Model ◽

Good Alternative ◽

Model Parameters ◽

Reanalysis Dataset ◽

Precipitation Product ◽

Statistical Measures ◽

Soil Water Assessment Tool ◽

Satellite Product

Precipitation is essential for modeling the hydrologic behavior of watersheds. There exist multiple precipitation products of different sources and precision. We evaluate the influence of different precipitation product on model parameters and streamflow predictive uncertainty using a soil water assessment tool (SWAT) model for a forest dominated catchment in India. We used IMD (gridded rainfall dataset), TRMM (satellite product), bias-corrected TRMM (corrected satellite product) and NCEP-CFSR (reanalysis dataset) over a period from 1998–2012 for simulating streamflow. The precipitation analysis using statistical measures revealed that the TRMM and CFSR data slightly overestimate rainfall compared to the ground-based IMD data. However, the TRMM estimates improved, applying a bias correction. The Nash–Sutcliffe (and R2) values for TRMM, TRMMbias and CFSR, are 0.58 (0.62), 0.62 (0.63) and 0.52 (0.54), respectively at model calibrated with IMD data (Scenario A). The models of each precipitation product (Scenario B) yielded Nash–Sutcliffe (and R2) values 0.71 (0.76), 0.74 (0.78) and 0.76 (0.77) for TRMM, TRMMbias and CFSR datasets, respectively. Thus, the hydrological model-based evaluation revealed that the model calibration with individual rainfall data as input showed increased accuracy in the streamflow simulation. IMD and TRMM forced models to perform better in capturing the streamflow simulations than the CFSR reanalysis-driven model. Overall, our results showed that TRMM data after proper correction could be a good alternative for ground observations for driving hydrological models.

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STREAMFLOW SIMULATION: COMPARISON BETWEEN SOIL WATER ASSESSMENT TOOL AND ARTIFICIAL NEURAL NETWORK MODELS

FUDMA Journal of Sciences ◽

10.33003/fjs-2021-0502-638 ◽

2021 ◽

Vol 5 (2) ◽

pp. 173-182

Author(s):

Shehu Usman Haruna ◽

Aliyu Kasim Abba ◽

Rabi'u Aminu

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Soil Water ◽

Assessment Tool ◽

Swat Model ◽

Coefficient Of Determination ◽

Artificial Neural ◽

Soil Water Assessment Tool ◽

Water Assessment ◽

Streamflow Simulation

The present study compared the performance of two different models for streamflow simulation namely: Soil Water Assessment Tool (SWAT) and the Artificial Neural Network (ANN). During the calibration periods, the Nash-Sutcliff (NS) and Coefficient of Determination (R2) for SWAT was 0.74 and 0.81 respectively, whereas for ANN, it was 0.99 and 0.85 respectively. The ANN performs better during the validation period as the result revealed with NS and R2 having 0.98 and 0.89 respectively, while for the SWAT model it was 0.71 and 0.74 respectively. Based on the recommended comparison of graphical and statistical evaluation performances of both models, the ANN model performed better in estimating peak flow events than the SWAT model in the Upper Betwa Basin. Furthermore, the rigorous time required and expertise for calibration of the SWAT is much less as compared with the ANN. Moreover, the results obtained from both models demonstrate the performances of the

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

Hydrology Research ◽

10.2166/nh.2016.034 ◽

2016 ◽

Vol 48 (2) ◽

pp. 395-415 ◽

Cited By ~ 12

Author(s):

S. Zahra Samadi

Keyword(s):

United States ◽

Assessment Tool ◽

Potential Evapotranspiration ◽

Swat Model ◽

Southeastern United States ◽

Shallow Aquifer ◽

Estimation Methods ◽

Physical Parameters ◽

Daily Streamflow ◽

Streamflow Simulation

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.

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