Improved Algorithm of SCS-CN Model Parameters in Typical Inland River Basin in Central Asia

International Symposium on Earth Observation for One Belt and One Road

地球科学;政治学;社会学;经济学

Wang, Jin J.^1,2,3,4 ; Ding, Jian L.^1,3,4 ; Zhang, Zhe^1,3,4 ; Chen, Wen Q.^1,3,4

Ecological Postdoctoral Research Station, Xinjiang University, Urumqi

831401, China^1

Xinjiang Vocational and Technical College of Communications, Urumqi

831401, China^2

College of Resources and Environment Science, Xinjiang University, Urumqi

830046, China^3

Key Laboratory of Oasis Ecology, Ministry of Education, Xinjiang University, Urumqi

830046, China^4

关键词: Calibration and validations;    Earth observation satellites;    Landuse classifications;    Moisture holding capacity;    Rainfall-runoff relationship;    Remote sensing information;    Social and economic development;    Soil conservation service curve numbers;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/57/1/012051/pdf
DOI  :  10.1088/1755-1315/57/1/012051

来源: IOP

【 摘 要 】

Rainfall-runoff relationship is the most important factor for hydrological structures, social and economic development on the background of global warmer, especially in arid regions. The aim of this paper is find the suitable method to simulate the runoff in arid area. The Soil Conservation Service Curve Number (SCS-CN) is the most popular and widely applied model for direct runoff estimation. In this paper, we will focus on Wen-quan Basin in source regions of Boertala River. It is a typical valley of inland in Central Asia. First time to use the 16m resolution remote sensing image about high-definition earth observation satellite "Gaofen-1" to provide a high degree accuracy data for land use classification determine the curve number. Use surface temperature/vegetation index (TS/VI) construct 2D scatter plot combine with the soil moisture absorption balance principle calculate the moisture-holding capacity of soil. Using original and parameter algorithm improved SCS-CN model respectively to simulation the runoff. The simulation results show that the improved model is better than original model. Both of them in calibration and validation periods Nash-Sutcliffe efficiency were 0.79, 0.71 and 0.66,038. And relative error were3%, 12% and 17%, 27%. It shows that the simulation accuracy should be further improved and using remote sensing information technology to improve the basic geographic data for the hydrological model has the following advantages: 1) Remote sensing data having a planar characteristic, comprehensive and representative. 2) To get around the bottleneck about lack of data, provide reference to simulation the runoff in similar basin conditions and data-lacking regions.