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

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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Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part II: Climate Change Impact Assessment)

Water ◽

10.3390/w13111548 ◽

2021 ◽

Vol 13 (11) ◽

pp. 1548

Author(s):

Suresh Marahatta ◽

Deepak Aryal ◽

Laxmi Prasad Devkota ◽

Utsav Bhattarai ◽

Dibesh Shrestha

Keyword(s):

Climate Change ◽

River Basin ◽

Climate Models ◽

Assessment Tool ◽

Swat Model ◽

Global Climate Models ◽

Climate Data ◽

The Future ◽

The Impact ◽

Mountainous River

This study aims at analysing the impact of climate change (CC) on the river hydrology of a complex mountainous river basin—the Budhigandaki River Basin (BRB)—using the Soil and Water Assessment Tool (SWAT) hydrological model that was calibrated and validated in Part I of this research. A relatively new approach of selecting global climate models (GCMs) for each of the two selected RCPs, 4.5 (stabilization scenario) and 8.5 (high emission scenario), representing four extreme cases (warm-wet, cold-wet, warm-dry, and cold-dry conditions), was applied. Future climate data was bias corrected using a quantile mapping method. The bias-corrected GCM data were forced into the SWAT model one at a time to simulate the future flows of BRB for three 30-year time windows: Immediate Future (2021–2050), Mid Future (2046–2075), and Far Future (2070–2099). The projected flows were compared with the corresponding monthly, seasonal, annual, and fractional differences of extreme flows of the simulated baseline period (1983–2012). The results showed that future long-term average annual flows are expected to increase in all climatic conditions for both RCPs compared to the baseline. The range of predicted changes in future monthly, seasonal, and annual flows shows high uncertainty. The comparative frequency analysis of the annual one-day-maximum and -minimum flows shows increased high flows and decreased low flows in the future. These results imply the necessity for design modifications in hydraulic structures as well as the preference of storage over run-of-river water resources development projects in the study basin from the perspective of climate resilience.

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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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The China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS) Application in China: A Case Study in Heihe River Basin

10.20944/preprints201612.0091.v2 ◽

2017 ◽

Cited By ~ 10

Author(s):

Xian-yong Meng ◽

Hao Wang ◽

Si-yu Cai ◽

Xue-song Zhang ◽

Guo-yong Leng ◽

...

Keyword(s):

River Basin ◽

Large Scale ◽

Hydrologic Modeling ◽

Hydrological Modeling ◽

Assessment Tool ◽

Swat Model ◽

Heihe River Basin ◽

Heihe River ◽

Climate Data ◽

Weather Stations

Large-scale hydrological modeling in China is challenging given the sparse meteorological stations and large uncertainties associated with atmospheric forcing data.Here we introduce the development and use of the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) in the Heihe River Basin(HRB) for improving hydrologic modeling, by leveraging the datasets from the China Meteorological Administration Land Data Assimilation System (CLDAS)(including climate data from nearly 40000 area encryption stations, 2700 national automatic weather stations, FengYun (FY) 2 satellite and radar stations). CMADS uses the Space Time Multiscale Analysis System (STMAS) to fuse data based on ECWMF ambient field and ensure data accuracy. In addition, compared with CLDAS, CMADS includes relative humidity and climate data of varied resolutions to drive hydrological models such as the Soil and Water Assessment Tool (SWAT) model. Here, we compared climate data from CMADS, Climate Forecast System Reanalysis (CFSR) and traditional weather station (TWS) climate forcing data and evaluatedtheir applicability for driving large scale hydrologic modeling with SWAT. In general, CMADS has higher accuracy than CFRS when evaluated against observations at TWS; CMADS also provides spatially continuous climate field to drive distributed hydrologic models, which is an important advantage over TWS climate data, particular in regions with sparse weather stations. Therefore, SWAT model simulations driven with CMADS and TWS achieved similar performances in terms of monthly and daily stream flow simulations, and both of them outperformed CFRS. For example, for the three hydrological stations (Ying Luoxia, Qilian Mountain, and ZhaMasheke) in the HRB at the monthly and daily Nash-Sutcliffe efficiency ranges of 0.75-0.95 and 0.58-0.78, respectively, which are much higher than corresponding efficiency statistics achieved with CFSR (monthly: 0.32-0.49 and daily: 0.26 – 0.45). The CMADS dataset is available free of charge and is expected to a valuable addition to the existing climate reanalysis datasets for deriving distributed hydrologic modeling in China and other countries in East Asia.

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Assessment of Climate Change Impacts on River Flow Regimes in the Upstream of Awash Basin, Ethiopia: Based on IPCC Fifth Assessment Report (AR5) Climate Change Scenarios

Hydrology ◽

10.3390/hydrology7040098 ◽

2020 ◽

Vol 7 (4) ◽

pp. 98

Author(s):

Mekonnen H. Daba ◽

Songcai You

Keyword(s):

Climate Change ◽

River Basin ◽

River Flow ◽

Assessment Tool ◽

Swat Model ◽

Resource Planning ◽

Global Climate Models ◽

Climate Change Scenarios ◽

Climate Data ◽

Awash River Basin

The Awash River Basin is the most irrigated area in Ethiopia, which is facing critical water resources problems. The main objective of this study was to assess the impacts of climate change on river flows in the upper Awash Subbasin, Ethiopia, using the soil and water assessment tool (SWAT) hydrological model. The ensemble of two global climate models (CSIRO-Mk3-6-0 and MIROC-ESM-CHEM with RCP4.5 and RCP8.5) for climate data projections (the 2020s, 2050s, and 2080s) and historical climate data from 1981–2010 was considered. Bias-corrections were made for both the GCM data. SWAT model was calibrated and validated to simulate future hydrologic variables in response to changes in rainfall and temperature. The results showed that the projected climate change scenarios were an increase in rainfall for the period of the 2020s but reduced for the periods of 2050s and 2080s. The annual mean temperature increases, ranging from 0.5 to 0.9 °C under RCP4.5 and 0.6 to 1.2 °C under RCP8.5 for all time slices. In the 2020s, annual mean rainfall increases by 5.77% under RCP4.5 and 7.80% under RCP8.5, while in 2050s and 2080s time slices, rainfall decrements range from 3.31 to 9.87% under RCP4.5 and 6.80 to 16.22% under RCP8.5. The change in rainfall and temperature probably leads to increases in the annual streamflow by 5.79% for RCP4.5 and 7.20% for RCP8.5 in the 2020s, whereas decreases by 10.39% and 11.45% under RCP4.5; and 10.79% and −12.38% for RCP8.5 in 2050s and 2080s, respectively. Similarly, in the 2020s, an increment of annual runoff was 10.73% for RCP4.5 and 12.08% for RCP8.5. Runoff reduces by 12.03% and 4.12% under RCP4.5; and 12.65% and 5.31% under RCP8.5 in the 2050s and the 2080s, respectively. Overall, the results revealed that changes in rainfall and temperature would have significant impacts on the streamflow and surface runoff, causing a possible reduction in the total water availability in the subbasin. This study provides useful information for future water resource planning and management in the face of climate change in the upper Awash River basin.

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Proportional coefficient method applied to TRMM rainfall data: case study of hydrological simulations of the Hotan River Basin (China)

Journal of Water and Climate Change ◽

10.2166/wcc.2017.080 ◽

2017 ◽

Vol 8 (4) ◽

pp. 627-640 ◽

Cited By ~ 3

Author(s):

Min Luo ◽

Tie Liu ◽

Fanhao Meng ◽

Yongchao Duan ◽

Yue Huang ◽

...

Keyword(s):

Snow Cover ◽

River Basin ◽

Assessment Tool ◽

Swat Model ◽

Tropical Rainfall Measuring Mission ◽

Temporal Variations ◽

Rain Gauge ◽

Hydrological Modelling ◽

Hydrological Simulation

Abstract A low-density rain gauge network is always a major obstacle for hydrological modelling, particularly for alpine and remote regions. The availability of the Tropical Rainfall Measuring Mission (TRMM) rainfall products provides an opportunity for hydrological modelling, although the results must be validated and corrected before they can be used in further applications. In this paper, the combination of proportional coefficients with cross-checking by hydrological modelling was proposed as a method to improve the quality of TRMM data in a rural mountainous region, the Hotan River Basin. The performance of the Soil and Water Assessment Tool (SWAT) model was examined using streamflow and snow cover measurements. The corrected results suggest that the proportional coefficient approach could effectively improve the TRMM data quality. A verification of the hydrological model outputs indicated that the simulated streamflow was consistent with the observed runoff. Moreover, the modelled snow cover patterns presented similar spatial and temporal variations to the remotely sensed snow cover, and the correlation coefficient ranged from 0.63 to 0.98. The results from the TRMM correction and hydrological simulation approach indicated that this method can significantly improve the precision of TRMM data and can meet the requirements of hydrological modelling.

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Predicting Tropical Monsoon Hydrology Using CFSR and CMADS Data over the Cau River Basin in Vietnam

Water ◽

10.3390/w13091314 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1314

Author(s):

Duy Minh Dao ◽

Jianzhong Lu ◽

Xiaoling Chen ◽

Sameh A. Kantoush ◽

Doan Van Binh ◽

...

Keyword(s):

River Basin ◽

Assessment Tool ◽

Swat Model ◽

Correlation Coefficients ◽

Strong Correlations ◽

Climate Forecast System Reanalysis ◽

Rain Gauges ◽

First Time ◽

Resource Research ◽

Better Than

To improve knowledge of this matter, the potential application of two gridded meteorological products (GMPs), the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) and Climate Forecast System Reanalysis (CFSR), are compared for the first time with data from ground-based meteorological stations over 6 years, from 2008 to 2013, over the Cau River basin (CRB), northern Vietnam. Statistical indicators and the Soil and Water Assessment Tool (SWAT) model are employed to investigate the hydrological performances of the GMPs against the data of 17 rain gauges distributed across the CRB. The results show that there are strong correlations between the temperature reanalysis products in both CMADS and CFSR and those obtained from the ground-based observations (the correlation coefficients range from 0.92 to 0.97). The CFSR data overestimate precipitation (percentage bias approximately 99%) at both daily and monthly scales, whereas the CMADS product performs better, with obvious differences (compared to the ground-based observations) in high-terrain areas. Regarding the simulated river flows, CFSR-SWAT produced “unsatisfactory”, while CMADS-SWAT (R2 > 0.76 and NSE > 0.78) performs better than CFSR-SWAT on the monthly scale. This assessment of the applicative potential of GMPs, especially CMADS, may further provide an additional rapid alternative for water resource research and management in basins with similar hydro-meteorological conditions.

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

Remote Sensing ◽

10.3390/rs13132630 ◽

2021 ◽

Vol 13 (13) ◽

pp. 2630

Author(s):

Yao Li ◽

Wensheng Wang ◽

Guoqing Wang ◽

Siyi Yu

Keyword(s):

River Basin ◽

Hydrological Modeling ◽

Assessment Tool ◽

Swat Model ◽

Weighted Average ◽

Probability Of Detection ◽

Coefficient Of Determination ◽

Maximum Probability ◽

Satellite Precipitation

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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Modeling the response of non-perennial streams to climate change impact: The Bouregreg watershed in Morocco

10.5194/egusphere-egu21-9414 ◽

2021 ◽

Author(s):

Anna Maria De Girolamo ◽

Youssef Brouziyne ◽

Lahcen Benaabidate ◽

Aziz Aboubdillah ◽

Ali El Bilali ◽

...

Keyword(s):

Climate Change ◽

Assessment Tool ◽

Swat Model ◽

Circulation Model ◽

Hybrid Modeling ◽

Climate Data ◽

Global Circulation Model ◽

Stream Network ◽

Modeling Framework ◽

Modeling Approach

<p>The non-perennial streams and rivers are predominant in the Mediterranean region and play an important ecological role in the ecosystem diversity in this region. This class of streams is particularly vulnerable to climate change effects that are expected to amplify further under most climatic projections. Understanding the potential response of the hydrologic regime attributes to climatic stress helps in planning better conservation and management strategies. Bouregreg watershed (BW) in Morocco, is a strategic watershed for the region with a developed non-perennial stream network, and with typical assets and challenges of most Mediterranean watersheds. In this study, a hybrid modeling approach, based on the Soil and Water Assessment Tool (SWAT) model and Indicator of Hydrologic Alteration (IHA) program, was used to simulate the response of BW's stream network to climate change during the period: 2035-2050. Downscaled daily climate data from the global circulation model CNRM-CM5 were used to force the hybrid modeling framework over the study area. Results showed that, under the changing climate, the magnitude of the alteration will be different across the stream network; however, almost the entire flow regime attributes will be affected. Under the RCP8.5 scenario, the average number of zero-flow days will rise up from 3 to 17.5 days per year in some streams, the timing of the maximum flow was calculated to occur earlier by 17 days than in baseline, and the timing of the minimal flow should occur later by 170 days in some streams. The used modeling approach in this study contributed in identifying the most vulnerable streams in the BW to climate change for potential prioritization in conservation plans.</p>

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Applicability and Hydrologic Substitutability of TMPA Satellite Precipitation Product in the Feilaixia Catchment, China

Water ◽

10.3390/w12061803 ◽

2020 ◽

Vol 12 (6) ◽

pp. 1803

Author(s):

Xiaoli Chen ◽

Guoru Huang

Keyword(s):

Assessment Tool ◽

Swat Model ◽

Tropical Rainfall Measuring Mission ◽

Climatic Conditions ◽

High Latitudes ◽

Climate Trends ◽

Runoff Simulation ◽

Satellite Precipitation ◽

Precipitation Analysis ◽

Water Assessment

The assessment of various precipitation products’ performances in extreme climatic conditions has become a topic of interest. However, little attention has been paid to the hydrological substitutability of these products. The objective of this study is to explore the performance of the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) product in the Feilaixia catchment, China. To assess its applicability in extreme consecutive climates, several statistical indices are adopted to evaluate the TMPA performance both qualitatively and quantitatively. The Cox–Stuart test is used to investigate extreme climate trends. The Soil and Water Assessment Tool (SWAT) model is used to test the TMPA hydrological substitutability via three scenarios of runoff simulation. The results demonstrate that the overall TMPA performance is acceptable, except at high-latitudes and locations where the terrain changes greatly. Moreover, the accuracy of the SWAT model is high both in the semi-substitution and full-substitution scenarios. Based on the results, the TMPA product is a useful substitute for the gauged precipitation in obtaining acceptable hydrologic process information in areas where gauged sites are sparse or non-existent. The TMPA product is satisfactory in predicting the runoff process. Overall, it must be used with caution, especially at high latitudes and altitudes.

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Multi-site calibration and validation of SWAT with satellite-based evapotranspiration in a data-sparse catchment in southwestern Nigeria

Hydrology and Earth System Sciences ◽

10.5194/hess-23-1113-2019 ◽

2019 ◽

Vol 23 (2) ◽

pp. 1113-1144 ◽

Cited By ~ 12

Author(s):

Abolanle E. Odusanya ◽

Bano Mehdi ◽

Christoph Schürz ◽

Adebayo O. Oke ◽

Olufiropo S. Awokola ◽

...

Keyword(s):

Soil Moisture ◽

River Basin ◽

Model Calibration ◽

Hydrological Model ◽

Assessment Tool ◽

Potential Evapotranspiration ◽

Swat Model ◽

Water Balance Components ◽

Southwestern Nigeria ◽

Calibration And Validation

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.

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