Evaluation and Hydrological Application of a Data Fusing Method of Multi-Source Precipitation Products-A Case Study Over Tuojiang River Basin

Precipitation is an essential driving factor of hydrological models. Its temporal and spatial resolution and reliability directly affect the accuracy of hydrological modeling. Acquiring accurate areal precipitation needs substantial ground rainfall stations in space. In many basins, ground rainfall stations are sparse and uneven, so real-time satellite precipitation products (SPPs) have become an important supplement to ground-gauged precipitation (GGP). A multi-source precipitation fusion method suitable for the Soil and Water Assessment Tool (SWAT) model has been proposed in this paper. First, the multivariate inverse distance similarity method (MIDSM) was proposed to search for the optimal representative precipitation points of GGP and SPPs in sub-basins. Subsequently, the correlation-coefficient-based weighted average method (CCBWA) was presented and applied to calculate the fused multi-source precipitation product (FMSPP), which combined GGP and multiple satellite precipitation products. The effectiveness of the FMSPP was proven over the Tuojiang River Basin. In the case study, three SPPs were chosen as the satellite precipitation sources, namely the Climate Forecast System Reanalysis (CFSR), Tropical Rainfall Measuring Mission Project (TRMM), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network Climate Data Record (PERSIANN-CDR). The evaluation indicators illustrated that FMSPP could capture the occurrence of rainfall events very well, with a maximum Probability of Detection (POD) and Critical Success Index (CSI) of 0.92 and 0.83, respectively. Furthermore, its correlation with GGP, changing in the range of 0.84–0.96, was higher in most sub-basins on the monthly scale than the other three SPPs. These results demonstrated that the performance of FMSPP was the best compared with the original SPPs. Finally, FMSPP was applied in the SWAT model and was found to effectively drive the SWAT model in contrast with a single precipitation source. The FMSPP manifested the highest accuracy in hydrological modeling, with the Coefficient of Determination (R2) of 0.84, Nash Sutcliff (NS) of 0.83, and Percent Bias (PBIAS) of only −1.9%.

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Application of Satellite-Based and Observed Precipitation Datasets for Hydrological Simulation in the Upper Mahi River Basin of Rajasthan, India

Sustainability ◽

10.3390/su13147560 ◽

2021 ◽

Vol 13 (14) ◽

pp. 7560

Author(s):

Dinesh Singh Bhati ◽

Swatantra Kumar Dubey ◽

Devesh Sharma

Keyword(s):

River Basin ◽

Hydrological Modeling ◽

Environmental Changes ◽

Assessment Tool ◽

Swat Model ◽

Measurement Techniques ◽

Coefficient Of Determination ◽

Hydrological Simulation ◽

And Performance ◽

Trmm 3B42

Hydrological modeling is an important tool used for basin management and studying the impacts of extreme events in a river basin. In streamflow simulations, precipitation plays an essential role in hydrological models. Meteorological satellite precipitation measurement techniques provide highly accurate rainfall information with high spatial and temporal resolution. In this analysis, the tropical rainfall monitoring mission (TRMM) 3B42 V7 precipitation products were employed for simulating streamflow by using the soil water assessment tool (SWAT) model. With India Metrological Department and TRMM data, the SWAT model can be used to predict streamflow discharge and identify sensitive parameters for the Mahi basin. The SWAT model was calibrated for 2 years and then independently validated for 2 years by comparing observed and simulated streamflow. A strong correlation was observed between the calibration and validation results for the Paderdibadi station, with a Nash–Sutcliffe efficiency of >0.34 and coefficient of determination (R2) of >0.77. The SWAT model was used to adequately simulate the streamflow for the Upper Mahi basin with a satisfactory R2 value. The analysis indicated that TRMM 3B42 V7 is useful in SWAT applications for predicting streamflow and performance and for sensitivity analysis. In addition, satellite data may require correction before its utilization in hydrological modeling. This study is helpful for stakeholders in monitoring and managing agricultural, climatic, and environmental changes.

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Evaluation and Analysis of Grid Precipitation Fusion Products in Jinsha River Basin Based on China Meteorological Assimilation Datasets for the SWAT Model

Water ◽

10.3390/w11020253 ◽

2019 ◽

Vol 11 (2) ◽

pp. 253 ◽

Cited By ~ 9

Author(s):

Dandan Guo ◽

Hantao Wang ◽

Xiaoxiao Zhang ◽

Guodong Liu

Keyword(s):

Statistical Analysis ◽

River Basin ◽

Assessment Tool ◽

Swat Model ◽

Correlation Coefficients ◽

High Accuracy ◽

Jinsha River ◽

Hydrological Simulation ◽

Large Spatial Scale ◽

Satellite Precipitation

Highly accurate and high-quality precipitation products that can act as substitutes for ground precipitation observations have important significance for research development in the meteorology and hydrology of river basins. In this paper, statistical analysis methods were employed to quantitatively assess the usage accuracy of three precipitation products, China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS), next-generation Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) and Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), for the Jinsha River Basin, a region characterized by a large spatial scale and complex terrain. The results of statistical analysis show that the three kinds of data have relatively high accuracy on the average grid scale and the correlation coefficients are all greater than 0.8 (CMADS:0.86, IMERG:0.88 and TMPA:0.81). The performance in the average grid scale is superior than that in grid scale. (CMADS: 0.86(basin), 0.6 (grid); IMERG:0.88 (basin),0.71(grid); TMPA:0.81(basin),0.42(grid)). According to the results of hydrological applicability analysis based on SWAT model, the three kinds of data fail to obtain higher accuracy on hydrological simulation. CMADS performs best (NSE:0.55), followed by TMPA (NSE:0.50) and IMERG (NSE:0.45) in the last. On the whole, the three types of satellite precipitation data have high accuracy on statistical analysis and average accuracy on hydrological simulation in the Jinsha River Basin, which have certain hydrological application potential.

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Evaluation and Hydrological Application of CMADS against TRMM 3B42V7, PERSIANN-CDR, NCEP-CFSR, and Gauge-Based Datasets in Xiang River Basin of China

Water ◽

10.3390/w10091225 ◽

2018 ◽

Vol 10 (9) ◽

pp. 1225 ◽

Cited By ~ 19

Author(s):

Xichao Gao ◽

Qian Zhu ◽

Zhiyong Yang ◽

Hao Wang

Keyword(s):

River Basin ◽

Bayesian Model Averaging ◽

Assessment Tool ◽

Swat Model ◽

Model Averaging ◽

Tropical Rainfall Measuring Mission ◽

Probability Of Detection ◽

Climate Data ◽

Xiang River ◽

Better Than

Satellite-based and reanalysis precipitation products provide a practical way to overcome the shortage of gauge precipitation data because of their high spatial and temporal resolution. This study compared two reanalysis precipitation datasets (the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS), the National Centers for Environment Prediction Climate Forecast System Reanalysis (NCEP-CFSR)) and two satellite-based datasets (the Tropical Rainfall Measuring Mission 3B42 Version 7 (3B42V7) and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR)) with observed precipitation in the Xiang River basin in China at two spatial (grids and the whole basin) and two temporal (daily and monthly) scales. These datasets were then used as inputs to a SWAT model to evaluate their usefulness in hydrological prediction. Bayesian model averaging was used to discriminate dataset performance. The results show that: (1) for daily timesteps, correlations between reanalysis datasets and gauge observations are >0.55, better than satellite-based datasets; The bias values of satellite-based datasets are <10% at most evaluated grid locations and for the whole baseline. PERSIANN-CDR cannot detect the spatial distribution of rainfall events; the probability of detection (POD) of PERSIANN-CDR at most evaluated grids is <0.50; (2) CMADS and 3B42V7 are better than PERSIANN-CDR and NCEP-CFSR in most situations in terms of correlation with gauge observations; satellite-based datasets are better than reanalysis datasets in terms of bias; and (3) CMADS and 3B42V7 simulate streamflow well for both daily (The Nash-Sutcliffe coefficient (NS) > 0.70) and monthly (NS > 0.80) timesteps; NCEP-CFSR is worst because it substantially overestimates streamflow; PERSIANN-CDR is not good because of its low NS (0.40) during the validation period.

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A Comparative Evaluation of the Performance of CHIRPS and CFSR Data for Different Climate Zones Using the SWAT Model

Remote Sensing ◽

10.3390/rs12183088 ◽

2020 ◽

Vol 12 (18) ◽

pp. 3088

Author(s):

Yeganantham Dhanesh ◽

V. M. Bindhu ◽

Javier Senent-Aparicio ◽

Tássia Mattos Brighenti ◽

Essayas Ayana ◽

...

Keyword(s):

Open Access ◽

Assessment Tool ◽

Mean Squared Error ◽

Swat Model ◽

Hydrologic Model ◽

Probability Of Detection ◽

Satellite Precipitation ◽

Statistical Measures ◽

Monthly Scale ◽

Monthly Streamflow

The spatial and temporal scale of rainfall datasets is crucial in modeling hydrological processes. Recently, open-access satellite precipitation products with improved resolution have evolved as a potential alternative to sparsely distributed ground-based observations, which sometimes fail to capture the spatial variability of rainfall. However, the reliability and accuracy of the satellite precipitation products in simulating streamflow need to be verified. In this context, the objective of the current study is to assess the performance of three rainfall datasets in the prediction of daily and monthly streamflow using Soil and Water Assessment Tool (SWAT). We used rainfall data from three different sources: Climate Hazards Group InfraRed Rainfall with Station data (CHIRPS), Climate Forecast System Reanalysis (CFSR) and observed rain gauge data. Daily and monthly rainfall measurements from CHIRPS and CFSR were validated using widely accepted statistical measures, namely, correlation coefficient (CC), root mean squared error (RMSE), probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI). The results showed that CHIRPS was in better agreement with ground-based rainfall at daily and monthly scale, with high rainfall detection ability, in comparison with the CFSR product. Streamflow prediction across multiple watersheds was also evaluated using Kling-Gupta Efficiency (KGE), Nash-Sutcliffe Efficiency (NSE) and Percent BIAS (PBIAS). Irrespective of the climatic characteristics, the hydrologic simulations of CHIRPS showed better agreement with the observed at the monthly scale with the majority of the NSE values ranging between 0.40 and 0.78, and KGE values ranging between 0.62 and 0.82. Overall, CHIRPS outperformed the CFSR rainfall product in driving SWAT for streamflow simulations across the multiple watersheds selected for the study. The results from the current study demonstrate the potential of CHIRPS as an alternate open access rainfall input to the hydrologic model.

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Hydrological modeling of Upper Ribb watershed, Abbay Basin, Ethiopia.

Global NEST Journal ◽

10.30955/gnj.003152 ◽

2020 ◽

Keyword(s):

Surface Runoff ◽

Hydrological Modeling ◽

Assessment Tool ◽

Swat Model ◽

Simulated Data ◽

Coefficient Of Determination ◽

Climate Data ◽

Water Balance Components ◽

Discharge Data ◽

Forested Areas

<p>Hydrological modeling of a watershed is necessary for water resources planning and management. The hydrology of upper Ribb watershed has been analyzed using spatially semi-distributed Soil and water assessment tool (SWAT) model. This study aimed to determine the water balance components and its relation with the rainfall which reaches to the surface of the earth. Different spatio-temporal (land use, soil, digital elevation model, climate data, river discharge) data were used for hydrological modelling of Upper Ribb watershed. The applicability of SWAT model in Upper Ribb watershed has been evaluated using coefficient of determination (R2) and Nash Sutcliff efficiency (NSE) parameters. The calibration results revealed the observed data showed a very good agreement with the simulated data with the R2 and NSE values of 0.90 and 0.84 respectively. Similarly, the validation results of streamflow were acceptable with the R2 and NSE values of 0.80 and 0.82 respectively. The monthly average streamflow from Upper Ribb watershed were found 13.39 m3/s. The major portion of the rainfall contributes to the surface runoff due to the major percentage of the watershed is covered with agricultural lands. The groundwater flow was high in forested areas, while evapotranspiration was found very high in water bodies (Ribb reservoir). In this study area the rainfall showed a direct relationship with the streamflow. The ratio of streamflow and evapotranspiration with rainfall was 0.61 and 0.36 respectively. Due to the presence of high amount of surface runoff and evapotranspiration the deep recharge which contributes to the ground water is not that much significant.</p>

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Baseflow simulation using SWAT model in an inland river basin in Tianshan Mountains, Northwest China

Hydrology and Earth System Sciences ◽

10.5194/hess-16-1259-2012 ◽

2012 ◽

Vol 16 (4) ◽

pp. 1259-1267 ◽

Cited By ~ 69

Author(s):

Y. Luo ◽

J. Arnold ◽

P. Allen ◽

X. Chen

Keyword(s):

River Basin ◽

Hydrological Modeling ◽

Assessment Tool ◽

Swat Model ◽

Northwest China ◽

Tianshan Mountains ◽

Soil Freezing ◽

Low Flow ◽

Model Based ◽

The One

Abstract. Baseflow is an important component in hydrological modeling. The complex streamflow recession process complicates the baseflow simulation. In order to simulate the snow and/or glacier melt dominated streamflow receding quickly during the high-flow period but very slowly during the low-flow period in rivers in arid and cold northwest China, the current one-reservoir baseflow approach in SWAT (Soil Water Assessment Tool) model was extended by adding a slow- reacting reservoir and applying it to the Manas River basin in the Tianshan Mountains. Meanwhile, a digital filter program was employed to separate baseflow from streamflow records for comparisons. Results indicated that the two-reservoir method yielded much better results than the one-reservoir one in reproducing streamflow processes, and the low-flow estimation was improved markedly. Nash-Sutcliff efficiency values at the calibration and validation stages are 0.68 and 0.62 for the one-reservoir case, and 0.76 and 0.69 for the two-reservoir case. The filter-based method estimated the baseflow index as 0.60, while the model-based as 0.45. The filter-based baseflow responded almost immediately to surface runoff occurrence at onset of rising limb, while the model-based responded with a delay. In consideration of watershed surface storage retention and soil freezing/thawing effects on infiltration and recharge during initial snowmelt season, a delay response is considered to be more reasonable. However, a more detailed description of freezing/thawing processes should be included in soil modules so as to determine recharge to aquifer during these processes, and thus an accurate onset point of rising limb of the simulated baseflow.

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Comparison Study of Multiple Precipitation Forcing Data on Hydrological Modeling and Projection in the Qujiang River Basin

Water ◽

10.3390/w12092626 ◽

2020 ◽

Vol 12 (9) ◽

pp. 2626 ◽

Cited By ~ 2

Author(s):

Yongyu Song ◽

Jing Zhang ◽

Xianyong Meng ◽

Yuyan Zhou ◽

Yuequn Lai ◽

...

Keyword(s):

River Basin ◽

Hydrological Modeling ◽

Assessment Tool ◽

Water Cycle ◽

Swat Model ◽

Precipitation Data ◽

Simulation Performance ◽

Surface Water Resources ◽

Monthly Streamflow ◽

Key Factor

As a key factor in the water cycle and climate change, the quality of precipitation data directly affects the hydrological processes of the river basin. Although many precipitation products with high spatial and temporal resolutions are now widely used, it is meaningful and necessary to investigate and evaluate their merits and demerits in hydrological applications. In this study, two satellite-based precipitation products (Tropical Rainfall Measurement Mission, TRMM; Integrated Multi-satellite Retrievals for GPM, IMERG) and one reanalysis precipitation product (China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model, CMADS) are studied to compare their streamflow simulation performance in the Qujiang River Basin, China, using the SWAT model with gauged rainfall data as a reference. The main conclusions are as follows: (1) CMADS has stronger precipitation detection capabilities compared to gauged rainfall, while TRMM results in the most obvious overestimation in the four sub-basins. (2) In daily and monthly streamflow simulations, CMADS + SWAT mode offers the best performance. CMADS and IMERG can provide high quality precipitation data for data-scarce areas, and IMERG can effectively avoid the overestimation of streamflow caused by TRMM, especially on a daily scale. (3) The runoff projections of the three modes under RCP (Representative Concentration Pathway) 4.5 was higher than that of RCP 8.5 on the whole. IMERG + SWAT overestimates the surface water resources of the basin compared to CMADS + SWAT, while TRMM + SWAT provides the most stable uncertainty. These findings contribute to the comparison of the differences among the three precipitation products and provides a reference for the selection of precipitation data in similar regions.

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Simulation of Non-Point Source Pollution Based on SWAT Model - A Case Study of Ashi River Basin

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1073-1076.1751 ◽

2014 ◽

Vol 1073-1076 ◽

pp. 1751-1755

Author(s):

Fang Ma ◽

Xiao Feng Jiang ◽

Li Wang ◽

Dan Shan ◽

Xiong Wei Liang ◽

...

Keyword(s):

River Basin ◽

Stream Flow ◽

Assessment Tool ◽

Swat Model ◽

Validation Period ◽

Point Source Pollution ◽

Water Assessment ◽

Non Point Source Pollution ◽

Soil And Water

The Soil and Water Assessment Tool (SWAT) model was examined for its applicability in modeling stream-flow and nutrients (total nitrogen, TN and total phosphorus, TP) in Ashi River Basin, China covering an area of 3545 km2. This model was calibrated by using the observed data of monthly flow during 1996-2005 and nutrients (TN and TP) during 2006-2008, and validated by using the observed data of monthly flow during 2006-2010 and water quality during 2009-2010. For stream-flow, the monthly results of RE, R2 and ENS values reached 6.42%, 0.61 and 0.59 respectively for calibration period, whereas these were-12.83%, 0.69 and 0.67, respectively for validation period; for TN calibration, values of RE, R2 and ENS were-18.33%, 0.64 and 0.55 respectively, and for validation period they were-17.34%, 0.68 and 0.57 respectively; for TP calibration, values of RE, R2 and ENS were-4.32%, 0.61 and 0.56 respectively, and for validation period they were-18.02%, 0.67 and 0.58 respectively. Results show that SWAT has applicability in modeling stream-flow and nutrients (TN and TP) in cold and flat area.

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Assessment of the SWAT model in simulating watersheds in arid regions: Case study of the Yarmouk River Basin (Jordan)

Open Geosciences ◽

10.1515/geo-2020-0238 ◽

2021 ◽

Vol 13 (1) ◽

pp. 377-389

Author(s):

Majed Abu-Zreig ◽

Lubna Bani Hani

Keyword(s):

River Basin ◽

Assessment Tool ◽

Positive Impact ◽

Swat Model ◽

Development Project ◽

Coefficient Of Determination ◽

Statistical Measures ◽

Yarmouk River ◽

Monthly Runoff ◽

The Impact

Abstract The Soil and Water Assessment Tool (SWAT) was used to simulate monthly runoff in the Yarmouk River Basin (YRB). The objectives were to assess the performance of this model in simulating the hydrological responses in arid watersheds then utilized to study the impact of YRB agricultural development project on transport of sediments in the YRB. Nine and three years of input data, namely from 2005 to 2013, were used to calibrate the model, whereas data from 2014 to 2015 were used for model validation. Time series plots as well as statistical measures, including the coefficient of determination (R 2) and the Nash–Sutcliffe coefficient of efficiency (NSE) that range between 0 to 1 and −∞ to 1, respectively, between observed and simulated monthly runoff values were used to verify the SWAT simulation capability for the YRB. The SWAT model satisfactorily predicted mean monthly runoff values in the calibration and validation periods, as indicated by R 2 = 0.95 and NSE = 0.96 and R 2 = 0.91 and NSE = 0.63, respectively. The study confirmed the positive impact of soil conservation measures implemented in the YRB development project and confirmed that contouring can reduce soil loss from 15 to 44% during the study period. This study showed that the SWAT model was capable of simulating hydrologic components in the drylands of Jordan.

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Satellite-based Precipitation Datasets Evaluation Using Gauge Observation and Hydrological Modeling in a Typical Arid Land Watershed of Central Asia

Remote Sensing ◽

10.3390/rs13020221 ◽

2021 ◽

Vol 13 (2) ◽

pp. 221

Author(s):

Jiabin Peng ◽

Tie Liu ◽

Yue Huang ◽

Yunan Ling ◽

Zhengyang Li ◽

...

Keyword(s):

Central Asia ◽

Hydrological Modeling ◽

Assessment Tool ◽

Swat Model ◽

Tropical Rainfall Measuring Mission ◽

Northwest China ◽

Lake Basin ◽

Climate Data ◽

Bosten Lake ◽

Satellite Precipitation

Hydrological modeling has always been a challenge in the data-scarce watershed, especially in the areas with complex terrain conditions like the inland river basin in Central Asia. Taking Bosten Lake Basin in Northwest China as an example, the accuracy and the hydrological applicability of satellite-based precipitation datasets were evaluated. The gauge-adjusted version of six widely used datasets was adopted; namely, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (CDR), Climate Hazards Group Infrared Precipitation with Stations (CHIRPS), Global Precipitation Measurement Ground Validation National Oceanic and Atmospheric Administration Climate Prediction Center (NOAA CPC) Morphing Technique (CMORPH), Integrated Multi-Satellite Retrievals for GPM (GPM), Global Satellite Mapping of Precipitation (GSMaP), the Tropical Rainfall Measuring Mission (TRMM) and Multi-satellite Precipitation Analysis (TMPA). Seven evaluation indexes were used to compare the station data and satellite datasets, the soil and water assessment tool (SWAT) model, and four indexes were used to evaluate the hydrological performance. The main results were as follows: (1) The GPM and CDR were the best datasets for the daily scale and monthly scale rainfall accuracy evaluations, respectively. (2) The performance of CDR and GPM was more stable than others at different locations in a watershed, and all datasets tended to perform better in the humid regions. (3) All datasets tended to perform better in the summer of a year, while the CDR and CHIRPS performed well in winter compare to other datasets. (4) The raw data of CDR and CMORPH performed better than others in monthly runoff simulations, especially CDR. (5) Integrating the hydrological performance of the uncorrected and corrected data, all datasets have the potential to provide valuable input data in hydrological modeling. This study is expected to provide a reference for the hydrological and meteorological application of satellite precipitation datasets in Central Asia or even the whole temperate zone.

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