Statistical and SWAT Model-Based Performance Evaluation of RCMs in Modeling Streamflow and Sediment Yield at Upper Awash Sub-Basin, Ethiopia

IF 2.1 Q3 SOIL SCIENCE
Bekan Chelkeba Tumsa
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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.
基于统计和SWAT模型的RCM在埃塞俄比亚阿瓦什河上游次流域流量和产沙建模中的性能评估
本研究的重点是评估区域气候模型在模拟流量、产沙量、降水量和温度方面的性能。人们认识到,在模拟气候变量时,随机对照模型并非没有偏见和不确定性。评估是通过统计工具模拟气候变量的年度气候学、年度周期和年度变化,并通过SWAT模型输出模拟流量和产沙量。该研究使用网格点RACMO22T、RCA4、CCLM4-8-17和HIRHAM5模型的观测和CORDEX Africa-44气象数据。对夏季平均年降雨量周期的分析表明,所有的随机对照模型都被低估了。然而,RACMO22T和RCA4更适合模拟气候变量。较高的误差与集水区最高地形区域的最高和最低温度模拟有关。气候学的统计分析表明,除季节性视角外,所有RCM的执行方式基本相同。在这种情况下,RACMO22T最能模拟流量和产沙量,PBIAS分别为0.14、NSE为0.91、R2为0.82、R2为0.72、NSE值为0.78和PBIAS值为−2.61%。RCA4较好地模拟了径流,但低估了模拟产沙量。结果表明,RACMO22T和RCA4在上漫滩地区表现较好。气候模型的性能因集水区、位置和地形而异。该统计和SWAT模型的输出表明,气候模型不能准确模拟水文气候变量。最后,这项研究表明,气候模型比旱季更适合模拟雨季。这种将统计工具和SWAT模型相结合来分析RCM的性能,是一种独特的方法,可以提高其在维持水平衡和减沙方面的输出质量。
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来源期刊
Applied and Environmental Soil Science
Applied and Environmental Soil Science Earth and Planetary Sciences-Earth-Surface Processes
CiteScore
4.00
自引率
4.50%
发文量
55
审稿时长
18 weeks
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
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