Investigating Spatial and Temporal Variation of Hydrological Processes in Western China Driven by CMADS

Yun Li,Jianghua Zheng,Mingxiang Yang,Yuejian Wang

doi:10.3390/w11030435

Abstract

The performance of hydrological models in western China has been restricted due to the scarcity of meteorological observation stations in the region. In addition to improving the quality of atmospheric input data, the use hydrological models to analyze Hydrological Processes on a large scale in western China could prove to be of key importance. The Jing and Bortala River Basin (JBR) was selected as the study area in this research. The China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) is used to drive SWAT model, in order to greatly improve the accuracy of SWAT model input data. The SUFI-2 algorithm is also used to optimize 26 sensitive parameters within the SWAT-CUP. After the verification of two runoff observation and control stations (located at Jing and Hot Spring) in the study area, the temporal and spatial distribution of soil moisture, snowmelt, evaporation and precipitation were analyzed in detail. The results show that the CMADS can greatly improve the performance of SWAT model in western China, and minimize the uncertainty of the model. The NSE efficiency coefficients of calibration and validation are controlled between 0.659–0.942 on a monthly scale and between 0.526–0.815 on a daily scale. Soil moisture will reach its first peak level in March and April of each year in the JBR due to the snow melting process in spring in the basin. With the end of the snowmelt process, precipitation and air temperature increased sharply in the later period, which causes the soil moisture content to fluctuate up and down. In October, there was a large amount of precipitation in the basin due to the transit of cold air (mainly snowfall), causing soil moisture to remain constant and increase again until snowmelt in early spring the following year. This study effectively verifies the applicability of CMADS in western China and provides important scientific and technological support for the spatio-temporal variation of soil moisture and its driving factor analysis in western China.

Highlights

In recent years, there have been a number of serious ecological and water crises in the world, with changes to the land surface process in arid areas having a significant influence on the whole inland river water cycle and the ecological environment of vast areas
The China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) is a datasetsdeveloped developed by Prof.Xianyong
The CMADS+SWAT model was used to export the monthly runoff of the two hydrological stations (Jinghe mountain station and Hot Spring station), and the parameters were calibrated

Summary

Introduction

There have been a number of serious ecological and water crises in the world, with changes to the land surface process in arid areas having a significant influence on the whole inland river water cycle and the ecological environment of vast areas. Due to the sharp decline in water resources, the lake’s salinity has greatly increased, the wetland area has become smaller, and the lake’s role in climate regulation has reduced, which is devastating to both the ecosystem and local residents The impact of this makes the already very fragile ecological environment of the JBR further deteriorate, resulting in a biological chain chasm, reduced biological diversity, intensified desertification and other ecological problems. The uncertainty of the atmospheric-related data will lead to a significant increase in the uncertainty of the region’s analog output [1]

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Methods

Conclusion