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

2017 ◽  
Vol 8 (4) ◽  
pp. 627-640 ◽  
Author(s):  
Min Luo ◽  
Tie Liu ◽  
Fanhao Meng ◽  
Yongchao Duan ◽  
Yue Huang ◽  
...  

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.

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 253 ◽  
Author(s):  
Dandan Guo ◽  
Hantao Wang ◽  
Xiaoxiao Zhang ◽  
Guodong Liu

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.


2011 ◽  
Vol 84-85 ◽  
pp. 238-243
Author(s):  
Yu Jie Fang ◽  
Wen Bin Zhou ◽  
Ding Gui Luo

Hydrological simulation is the basis of water resources management and utilization. In this study, Soil and Water Assessment Tool (SWAT) model was applied to Jin River Basin for hydrological simulation on ArcView3.3 platform. The basic database of Jin river Basin was built using ArcGis9.2. Based on the LH-OAT parameter sensitivity analysis, the sensitive parameters of runoff were identified, including CN2, Gwqmn, rchrg_dp, ESCO, sol_z, SLOPE, SOL_AWC, sol_k, Gwrevap, and then model parameters related to runoff were calibrated and validated using data observed in weifang, yifeng, shanggao and gaoan hydrological stations during 2001-2008. The simulation showed that the simulated values were reasonably comparable to the observed data (Re<20%, R2 >0.7 and Nash-suttcliffe > 0.7), suggesting the validity of SWAT model in Jin River Basin.


Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1225 ◽  
Author(s):  
Xichao Gao ◽  
Qian Zhu ◽  
Zhiyong Yang ◽  
Hao Wang

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.


Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3243
Author(s):  
Qiang Wang ◽  
Jun Xia ◽  
Xiang Zhang ◽  
Dunxian She ◽  
Jie Liu ◽  
...  

The lack of meteorological observation data limits the hydro-climatic analysis and modeling, especially for the ungauged or data-limited regions, while satellite and reanalysis products can provide potential data sources in these regions. In this study, three daily products, including two satellite products (Tropic Rainfall Measuring Mission Multi-Satellite Precipitation Analysis, TMPA 3B42 and 3B42RT) and one reanalysis product (China Meteorological Assimilation Driving Datasets for the SWAT Model, CMADS), were used to assess the capacity of hydro-climatic simulation based on the statistical method and hydrological model in Ganjiang River Basin (GRB), a humid basin of southern China. CAMDS, TMPA 3B42 and 3B42RT precipitation were evaluated against ground-based observation based on multiple statistical metrics at different temporal scales. The similar evaluation was carried out for CMADS temperature. Then, eight scenarios were constructed into calibrating the Soil and Water Assessment Tool (SWAT) model and simulating streamflow, to assess their capacity in hydrological simulation. The results showed that CMADS data performed better in precipitation estimation than TMPA 3B42 and 3B42RT at daily and monthly scales, while worse at the annual scale. In addition, CMADS can capture the spatial distribution of precipitation well. Moreover, the CMADS daily temperature data agreed well with observations at meteorological stations. For hydrological simulations, streamflow simulation results driven by eight input scenarios obtained acceptable performance according to model evaluation criteria. Compared with the simulation results, the models driven by ground-based observation precipitation obtained the most accurate streamflow simulation results, followed by CMADS, TMPA 3B42 and 3B42RT precipitation. Besides, CMADS temperature can capture the spatial distribution characteristics well and improve the streamflow simulations. This study provides valuable insights for hydro-climatic application of satellite and reanalysis meteorological products in the ungauged or data-limited regions.


Land ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 291 ◽  
Author(s):  
Meilin Wang ◽  
Yaqi Shao ◽  
Qun’ou Jiang ◽  
Ling Xiao ◽  
Haiming Yan ◽  
...  

Guishui River Basin in northwestern Beijing has ecological significance and will be one of the venues of the upcoming Beijing Winter Olympic Games in 2022. However, accelerating climate change and human disturbance in recent decades has posed an increasing challenge to the sustainable use of water in the basin. This study simulated the runoff of the Guishui River Basin using the Soil and Water Assessment Tool (SWAT) model to reveal the spatio-temporal variations of runoff in the basin and the impacts of climate change and human activities on the runoff changes. The results showed that annual runoff from 2004 to 2018 was relatively small, with an uneven intra-annual runoff distribution. The seasonal trends in runoff showed a decreasing trend in spring and winter while an increasing trend in summer and autumn. There was a first increasing and then decreasing trend of average annual runoff depth from northwest to southeast in the study area. In addition, the contributions of climate change and human activities to changes in runoff of the Guishui River Basin were 60% and 40%, respectively, but with opposite effects. The results can contribute to the rational utilization of water resources in the Guishui River Basin.


Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3288
Author(s):  
Dandan Zhang ◽  
Mou Leong Tan ◽  
Sharifah Rohayah Sheikh Dawood ◽  
Narimah Samat ◽  
Chun Kiat Chang ◽  
...  

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.


Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1546
Author(s):  
Suresh Marahatta ◽  
Laxmi Prasad Devkota ◽  
Deepak Aryal

The soil and water assessment tool (SWAT) hydrological model has been used extensively by the scientific community to simulate varying hydro-climatic conditions and geo-physical environment. This study used SWAT to characterize the rainfall-runoff behaviour of a complex mountainous basin, the Budhigandaki River Basin (BRB), in central Nepal. The specific objectives of this research were to: (i) assess the applicability of SWAT model in data scarce and complex mountainous river basin using well-established performance indicators; and (ii) generate spatially distributed flows and evaluate the water balance at the sub-basin level. The BRB was discretised into 16 sub-basins and 344 hydrological response units (HRUs) and calibration and validation was carried out at Arughat using daily flow data of 20 years and 10 years, respectively. Moreover, this study carried out additional validation at three supplementary points at which the study team collected primary river flow data. Four statistical indicators: Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), ratio of the root mean square error to the standard deviation of measured data (RSR) and Kling Gupta efficiency (KGE) have been used for the model evaluation. Calibration and validation results rank the model performance as “very good”. This study estimated the mean annual flow at BRB outlet to be 240 m3/s and annual precipitation 1528 mm with distinct seasonal variability. Snowmelt contributes 20% of the total flow at the basin outlet during the pre-monsoon and 8% in the post monsoon period. The 90%, 40% and 10% exceedance flows were calculated to be 39, 126 and 453 m3/s respectively. This study provides additional evidence to the SWAT diaspora of its applicability to simulate the rainfall-runoff characteristics of such a complex mountainous catchment. The findings will be useful for hydrologists and planners in general to utilize the available water rationally in the times to come and particularly, to harness the hydroelectric potential of the basin.


2021 ◽  
Vol 13 (14) ◽  
pp. 7560
Author(s):  
Dinesh Singh Bhati ◽  
Swatantra Kumar Dubey ◽  
Devesh Sharma

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.


Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1548
Author(s):  
Suresh Marahatta ◽  
Deepak Aryal ◽  
Laxmi Prasad Devkota ◽  
Utsav Bhattarai ◽  
Dibesh Shrestha

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.


2021 ◽  
Vol 13 (4) ◽  
pp. 622
Author(s):  
Wan-Ru Huang ◽  
Pin-Yi Liu ◽  
Ya-Hui Chang ◽  
Cheng-An Lee

This study assesses the performance of satellite precipitation products (SPPs) from the latest version, V06B, Integrated Multi-satellitE Retrievals for Global Precipitation Mission (IMERG) Level-3 (including early, late, and final runs), in depicting the characteristics of typhoon season (July to October) rainfall over Taiwan within the period of 2000–2018. The early and late runs are near-real-time SPPs, while final run is post-real-time SPP adjusted by monthly rain gauge data. The latency of early, late, and final runs is approximately 4 h, 14 h, and 3.5 months, respectively, after the observation. Analyses focus on the seasonal mean, daily variation, and interannual variation of typhoon-related (TC) and non-typhoon-related (non-TC) rainfall. Using local rain-gauge observations as a reference for evaluation, our results show that all IMERG products capture the spatio-temporal variations of TC rainfall better than those of non-TC rainfall. Among SPPs, the final run performs better than the late run, which is slightly better than the early run for most of the features assessed for both TC and non-TC rainfall. Despite these differences, all IMERG products outperform the frequently used Tropical Rainfall Measuring Mission 3B42 v7 (TRMM7) for the illustration of the spatio-temporal characteristics of TC rainfall in Taiwan. In contrast, for the non-TC rainfall, the final run performs notably better relative to TRMM7, while the early and late runs showed only slight improvement. These findings highlight the advantages and disadvantages of using IMERG products for studying or monitoring typhoon season rainfall in Taiwan.


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