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

Water ◽  
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.

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

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 253 ◽  
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.

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

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1225 ◽  
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.

scholarly journals Investigate the Applicability of CMADS and CFSR Reanalysis in Northeast China

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 996 ◽  
Author(s):  
Limin Zhang ◽  
Xianyong Meng ◽  
Hao Wang ◽  
Mingxiang Yang ◽  
Siyu Cai
Keyword(s):  
Northeast China ◽  
Assessment Tool ◽  
Meteorological Data ◽  
Swat Model ◽  
Poor Performance ◽  
Runoff Simulation ◽  
Reanalysis Dataset ◽  
Climate Forecast System Reanalysis ◽  
Maximum Minimum ◽  
Better Than

Reanalysis datasets can provide alternative and complementary meteorological data sources for hydrological studies or other scientific studies in regions with few gauge stations. This study evaluated the accuracy of two reanalysis datasets, the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) and Climate Forecast System Reanalysis (CFSR), against gauge observations (OBS) by using interpolation software and statistical indicators in Northeast China (NEC), as well as their annual average spatial and monthly average distributions. The reliability and applicability of the two reanalysis datasets were assessed as inputs in a hydrological model (SWAT) for runoff simulation in the Hunhe River Basin. Statistical results reveal that CMADS performed better than CFSR for precipitation and temperature in NEC with the indicators closer to optimal values (the ratio of standard deviations of precipitation and maximum/minimum temperature from CMADS were 0.92, 1.01, and 0.995, respectively, while that from CFSR were 0.79, 1.07, and 0.897, respectively). Hydrological modelling results showed that CMADS + SWAT and OBS + SWAT performed far better than CFSR + SWAT on runoff simulations. The Nash‒Sutcliffe efficiency (NSE) of CMADS + SWAT and OBS + SWAT ranged from 0.54 to 0.95, while that of CFSR + SWAT ranged from −0.07 to 0.85, exhibiting poor performance. The CMADS reanalysis dataset is more accurate than CFSR in NEC and is a suitable input for hydrological simulations.

scholarly journals Comparison of NCEP-CFSR and CMADS for Hydrological Modelling Using SWAT in the Muda River Basin, Malaysia

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3288
Author(s):  
Dandan Zhang ◽  
Mou Leong Tan ◽  
Sharifah Rohayah Sheikh Dawood ◽  
Narimah Samat ◽  
Chun Kiat Chang ◽  
...  
Keyword(s):  
River Basin ◽  
Assessment Tool ◽  
Swat Model ◽  
Time Lag ◽  
Hydrological Modelling ◽  
Climate Forecast System Reanalysis ◽  
Monthly Streamflow ◽  
Gauge Station ◽  
Environmental Prediction ◽  
Gauged Basins

Identification of reliable alternative climate input data for hydrological modelling is important to manage water resources and reduce water-related hazards in ungauged or poorly gauged basins. This study aims to evaluate the capability of the National Centers for Environmental Prediction Climate Forecast System Reanalysis (NCEP-CFSR) and China Meteorological Assimilation Driving Dataset for the Soil and Water Assessment Tool (SWAT) model (CMADS) for simulating streamflow in the Muda River Basin (MRB), Malaysia. The capability was evaluated in two perspectives: (1) the climate aspect—validation of precipitation, maximum and minimum temperatures from 2008 to 2014; and (2) the hydrology aspect—comparison of the accuracy of SWAT modelling by the gauge station, NCEP-CFSR and CMADS products. The results show that CMADS had a better performance than NCEP-CFSR in the climate aspect, especially for the temperature data and daily precipitation detection capability. For the hydrological aspect, the gauge station had a “very good” performance in a monthly streamflow simulation, followed by CMADS and NCEP-CFSR. In detail, CMADS showed an acceptable performance in SWAT modelling, but some improvements such as bias correction and further SWAT calibration are needed. In contrast, NCEP-CFRS had an unacceptable performance in validation as it dramatically overestimated the low flows of MRB and contains time lag in peak flows estimation.

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

Water ◽  
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.

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

2019 ◽  
Vol 23 (2) ◽  
pp. 1113-1144 ◽  
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.

Integrated numerical model for irrigated area water resources management

2019 ◽  
Vol 11 (4) ◽  
pp. 980-991 ◽  
Author(s):  
Aidi Huo ◽  
Xiaofan Wang ◽  
Yan Liang ◽  
Cheng Jiang ◽  
Xiaolu Zheng
Keyword(s):  
River Basin ◽  
Water Resource Management ◽  
Assessment Tool ◽  
Swat Model ◽  
Hydrologic Model ◽  
Heihe River Basin ◽  
Irrigation District ◽  
Heihe River ◽  
Model Parameters ◽  
Long Term Effects

Abstract The likelihood of future global water shortages is increasing and further development of existing operational hydrologic models is needed to maintain sustainable development of the ecological environment and human health. In order to quantitatively describe the water balance factors and transformation relations, the objective of this article is to develop a distributed hydrologic model that is capable of simulating the surface water (SW) and groundwater (GW) in irrigation areas. The model can be used as a tool for evaluating the long-term effects of water resource management. By coupling the Soil and Water Assessment Tool (SWAT) and MODFLOW models, a comprehensive hydrological model integrating SW and GW is constructed. The hydrologic response units for the SWAT model are exchanged with cells in the MODFLOW model. Taking the Heihe River Basin as the study area, 10 years of historical data are used to conduct an extensive sensitivity analysis on model parameters. The developed model is run for a 40-year prediction period. The application of the developed coupling model shows that since the construction of the Heihe reservoir, the average GW level in the study area has declined by 6.05 m. The model can accurately simulate and predict the dynamic changes in SW and GW in the downstream irrigation area of Heihe River Basin and provide a scientific basis for water management in an irrigation district.

scholarly journals Model Uncertainty Analysis Methods for Semi-Arid Watersheds with Different Characteristics: A Comparative SWAT Case Study

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1177 ◽  
Author(s):  
Lufang Zhang ◽  
Baolin Xue ◽  
Yuhui Yan ◽  
Guoqiang Wang ◽  
Wenchao Sun ◽  
...  
Keyword(s):  
Uncertainty Analysis ◽  
River Basin ◽  
Model Uncertainty ◽  
Assessment Tool ◽  
Rapid Development ◽  
Swat Model ◽  
Observation Data ◽  
Hydrological Models ◽  
Distributed Hydrological Models ◽  
Different Characteristics

Distributed hydrological models play a vital role in water resources management. With the rapid development of distributed hydrological models, research into model uncertainty has become a very important field. When studying traditional hydrological model uncertainty, it is very common to use multisite observation data to evaluate the performance of the model in the same watershed, but there are few studies on uncertainty in watersheds with different characteristics. This study is based on the Soil and Water Assessment Tool (SWAT) model, and uses two common methods: Sequential Uncertainty Fitting Version 2 (SUFI-2) and Generalized Likelihood Uncertainty Estimation (GLUE) for uncertainty analysis. We compared these methods in terms of parameter uncertainty, model prediction uncertainty, and simulation effects. The Xiaoqing River basin and the Xinxue River basin, which have different characteristics, including watershed geography and scale, were used for the study areas. The results show that the GLUE method had better applicability in the Xiaoqing River basin, and that the SUFI-2 method provided more reasonable and accurate analysis results in the Xinxue River basin; thus, the applicability was higher. The uncertainty analysis method is affected to some extent by the characteristics of the watershed.

scholarly journals Assessing the Uncertainties of Four Precipitation Products for Swat Modeling in Mekong River Basin

2019 ◽  
Vol 11 (3) ◽  
pp. 304 ◽  
Author(s):  
Xiongpeng Tang ◽  
Jianyun Zhang ◽  
Chao Gao ◽  
Gebdang Ruben ◽  
Guoqing Wang
Keyword(s):  
River Basin ◽  
Assessment Tool ◽  
Model Performance ◽  
Mekong River ◽  
Distributed Hydrological Model ◽  
Parameter Uncertainties ◽  
Mekong River Basin ◽  
Daily Streamflow ◽  
Precipitation Estimates ◽  
Better Than

Using hydrological simulation to evaluate the accuracy of satellite-based and reanalysis precipitation products always suffer from a large uncertainty. This study evaluates four widely used global precipitation products with high spatial and temporal resolutions [i.e., AgMERRA (AgMIP modern-Era Retrospective Analysis for Research and Applications), MSWEP (Multi-Source Weighted-Ensemble Precipitation), PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record), and TMPA (Tropical Rainfall Measuring Mission 3B42 Version7)] against gauge observations with six statistical metrics over Mekong River Basin (MRB). Furthermore, the Soil and Water Assessment Tool (SWAT), a widely used semi-distributed hydrological model, is calibrated using different precipitation inputs. Both model performance and uncertainties of parameters and prediction have been quantified. The following findings were obtained: (1) The MSWEP and TMPA precipitation products have good accuracy with higher CC, POD, and lower ME and RMSE, and the AgMERRA precipitation estimates perform better than PERSIANN-CDR in this rank; and (2) out of the six different climate regions of MRB, all six metrics are worse than that in the whole MRB. The AgMERRA can better reproduce the occurrence and contributions at different precipitation densities, and the MSWEP has the best performance in Cwb, Cwa, Aw, and Am regions that belong to the low latitudes. (3) Daily streamflow predictions obtained using MSWEP precipitation estimates are better than those simulated by other three products in term of both the model performance and parameter uncertainties; and (4) although MSWEP better captures the precipitation at different intensities in different climatic regions, the performance can still be improved, especially in the regions with higher altitude.

Impact of landscape pattern change on runoff processes in catchment area of the Ulungur River Basin

2020 ◽  
Vol 20 (3) ◽  
pp. 1046-1058
Author(s):  
Fan Gao ◽  
Bing He ◽  
Songsong Xue ◽  
Yizhen Li
Keyword(s):  
Land Use ◽  
River Basin ◽  
Landscape Pattern ◽  
Water Conservation ◽  
Catchment Area ◽  
Positive Impact ◽  
Swat Model ◽  
Land Use Types ◽  
Monthly Runoff ◽  
Better Than

Abstract Based on the Soil and Water Assessment Tool (SWAT) model, the monthly runoff processes of two land-use types in 2000 and 2015 were simulated in this paper. The relationship between runoff and landscape pattern was analyzed, and the spatial correlation between runoff and landscape pattern analyzed using the geographic weighted regression model combined with the change of landscape pattern in the study area from 2000 to 2015. The results show the following. (1) The SWAT model can simulate the monthly runoff processes in the catchment area of the Ulungur River Basin (URB) under different land-use types for 2000 and 2015, but the simulation effect in 2000 was found to be better than that in 2015. (2) From 2000 to 2015, the area of woodland and grassland decreased. Runoff was positively correlated with woodland, grassland, largest patch index, mean patch area (AREA_MN), and contagion index, and negatively correlated with others. This indicates that the landscape fragmentation of URB was aggravated in 2000–2015, the landscape balance was destroyed, and the ability of rainfall interception and water conservation was weakened. (3) Landscape pattern indicators of grassland had a negative spatial impact on URB runoff, and the northern region of URB was more severely affected in 2015 than in 2000. AREA_MN landscape pattern index had a positive impact on runoff in the northern part of URB, and the positive impact in northern URB in 2000 was better than that in 2015.

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