{"title":"Statistical and SWAT Model-Based Performance Evaluation of RCMs in Modeling Streamflow and Sediment Yield at Upper Awash Sub-Basin, Ethiopia","authors":"Bekan Chelkeba Tumsa","doi":"10.1155/2022/9193516","DOIUrl":null,"url":null,"abstract":"The focus of this study was to evaluate the performance of the regional climate models with regard to simulating streamflow, sediment yield, precipitation, and temperatures. It is recognized that RCMs are not free of bias and uncertainty when simulating climate variables. The evaluation was about simulating annual climatology, annual cycles, and annual variability of climate variables by statistical tools and streamflow and sediment yield by SWAT model output. The study used observed and CORDEX Africa-44 meteorological data for RACMO22T, RCA4, CCLM4-8-17, and HIRHAM5 models using grid points. This analysis of the mean annual rainfall cycle in the summer season shows that all RCMs were underestimated. However, RACMO22T and RCA4 are better suited for simulating climate variables. The higher errors were associated with the simulations of maximum and minimum temperatures in the highest terrain area of the catchment. The statistical analysis with climatology indicates that all RCM was performed in much the same way, except for the seasonal perspective. In this case, RACMO22T was best able to simulate streamflow and sediment yield with PBIAS of 0.14, NSE of 0.91, R2 of 0.82, R2 of 0.72, NSE of 0.78, and PBIAS of −2.61%, respectively. RCA4 simulated streamflow better, but it underestimated the simulated sediment yield. The result proved that RACMO22T and RCA4 performed better in the upper floodplain area. The performance of the climate model varied with catchments, locations, and terrains. The output of this statistical and SWAT model shows that climate models do not accurately simulate hydro-climatological variables. Finally, this study showed that climate models were better at simulating the rainy season than the dry season. This integration of statistical tools and the SWAT model to analyze the RCM’s performance is a unique method to improve the quality of the output for its implementation in maintaining water balance and sediment load reduction.","PeriodicalId":38438,"journal":{"name":"Applied and Environmental Soil Science","volume":" ","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied and Environmental Soil Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2022/9193516","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"SOIL SCIENCE","Score":null,"Total":0}
引用次数: 1
Abstract
The focus of this study was to evaluate the performance of the regional climate models with regard to simulating streamflow, sediment yield, precipitation, and temperatures. It is recognized that RCMs are not free of bias and uncertainty when simulating climate variables. The evaluation was about simulating annual climatology, annual cycles, and annual variability of climate variables by statistical tools and streamflow and sediment yield by SWAT model output. The study used observed and CORDEX Africa-44 meteorological data for RACMO22T, RCA4, CCLM4-8-17, and HIRHAM5 models using grid points. This analysis of the mean annual rainfall cycle in the summer season shows that all RCMs were underestimated. However, RACMO22T and RCA4 are better suited for simulating climate variables. The higher errors were associated with the simulations of maximum and minimum temperatures in the highest terrain area of the catchment. The statistical analysis with climatology indicates that all RCM was performed in much the same way, except for the seasonal perspective. In this case, RACMO22T was best able to simulate streamflow and sediment yield with PBIAS of 0.14, NSE of 0.91, R2 of 0.82, R2 of 0.72, NSE of 0.78, and PBIAS of −2.61%, respectively. RCA4 simulated streamflow better, but it underestimated the simulated sediment yield. The result proved that RACMO22T and RCA4 performed better in the upper floodplain area. The performance of the climate model varied with catchments, locations, and terrains. The output of this statistical and SWAT model shows that climate models do not accurately simulate hydro-climatological variables. Finally, this study showed that climate models were better at simulating the rainy season than the dry season. This integration of statistical tools and the SWAT model to analyze the RCM’s performance is a unique method to improve the quality of the output for its implementation in maintaining water balance and sediment load reduction.
期刊介绍:
Applied and Environmental Soil Science is a peer-reviewed, Open Access journal that publishes research and review articles in the field of soil science. Its coverage reflects the multidisciplinary nature of soil science, and focuses on studies that take account of the dynamics and spatial heterogeneity of processes in soil. Basic studies of the physical, chemical, biochemical, and biological properties of soil, innovations in soil analysis, and the development of statistical tools will be published. Among the major environmental issues addressed will be: -Pollution by trace elements and nutrients in excess- Climate change and global warming- Soil stability and erosion- Water quality- Quality of agricultural crops- Plant nutrition- Soil hydrology- Biodiversity of soils- Role of micro- and mesofauna in soil