抚河流域农业干旱特征及其驱动因子分析

Analyzing the droughts and their determinants in the Fuhe River Basin using the SWAT model

[目的]探究抚河流域农业干旱特征及其驱动因子。[方法]基于SWAT模型模拟抚河流域1962-2019年逐月土壤含水率,在此基础上计算标准化土壤湿度指数(SSI),利用游程理论分析农业干旱变化特征,运用地理探测器模型定量评估农业干旱的驱动因子。[结果]SWAT模型率定与验证的决定系数(R^(2))、纳什效率系数(ENS)均高于0.80,土壤含水率模拟值与实测值之间的R~2为0.52;干旱历时范围在各子流域间介于3.60~4.31个月,干旱烈度范围介于4.91~5.61,二者均呈南北高、中部低的空间分布格局;气温、太阳辐射量和风速对农业干旱空间异质性的影响程度(q)均超过0.30,不同环境因子对农业干旱空间异质性的影响均具有双因子增强或非线性增强特征。[结论]SSI能够有效表征抚河流域农业干旱状况,流域农业干旱具有明显的空间分异特征,气温、太阳辐射量和风速是决定流域农业干旱空间异质性的主要驱动因子。

【Objective】The Fuhe River Basin is an important food production region in Northwestern China.It is increasingly affected by droughts.This paper analyses the occurrence of droughts and their key determinants in this region.【Method】The analysis was based on modelling.We simulated the changes in monthly soil water content from 1962 to 2019 using the SWAT model.The resulting data were then used to calculate the standardized soil moisture index.The characteristics of agricultural droughts were analyzed using the theory of runs,and the key determinants of the droughts were analyzed using the geographical detector.【Result】①The coefficient of determination(R^(2))and the Nash efficiency coefficient(ENS)between the modelled and measured results in the calibration are both higher than 0.80;the coefficient of determination between the predicted soil moisture content and the measured soil moisture content is 0.52.②The duration of droughts in different regions in the basin varied from 3.60 to 4.31 months,and the drought intensity ranged from 4.91 to 5.61,both varying spatially,higher in the North and South and lower in the center.③The influence of temperature,solar radiation,and wind speed on spatial variation in the droughts,characterized by the q-value,exceeds 0.30.Other environmental factors are nonlinearly interacted in their influence on the droughts.【Conclusion】The standardized soil moisture index can quantitatively characterize droughts in the Fuhe River Basin.Droughts in the basin vary spatially,with temperature,solar radiation and wind speed being the main contributing factors.