基于SPEI的宁夏沿黄城市带干旱特征及驱动性分析

宁夏沿黄城市带气候变化敏感，生态环境脆弱，探究区域干旱驱动机制，对进一步研究黄河流域高质量发展，优化区域农业水资源管理具有重要意义。利用研究区1995—2015年的气象资料，采用彭曼蒙特斯模型(P-M模型)和标准降雨蒸散指数(SPEI)获得区域潜在蒸散发量和干旱指数，通过Mann-Kendall突变检测法、滑动t检验和Pettitt突变检验，分析了研究区干旱时间变化周期，利用冗余分析法定量分析宁夏沿黄城市带干旱驱动因素。结果表明：(1)研究区在季节尺度上，单季旱发生频繁，以春季和秋季发生为主，自北向南整体呈现由高到底的趋势，且主要发生在北部地区，整体以0.013/10 a速率呈湿润化趋势；(2)在年尺度上干旱的下降趋势具有全域性，自北向南呈现由高到底的趋势；(3)宁夏沿黄城市带SPEI-12值在研究时段呈现逐年下降的趋势，通过3种突变检测函数，确定2008年出现异常值，这与降水分布一致；(4)各环境因子对SPEI指数的解释率均在75%以上，降水量、温度、地表净辐射是驱动SPEI值主要环境因子。其中，降水量对SPEI的贡献率最高，呈显著正相关关系。

Analysis of Drought Characteristics and Driving Forces in the Urban Belt Along the Yellow River in Ningxia Based on SPEI

The urban belt along the Yellow River in Ningxia is sensitive to climate change and its ecological environment is fragile. Exploring the driving mechanism of regional drought is of great significance for further research on the high-quality development of the Yellow River Basin and optimize the management of regional agricultural water resources. Based on the meteorological data of the study area from 1995 to 2015, the Penman Montes model(PM model)and the standard rainfall evapotranspiration index(SPEI)were used to obtain the regional potential evapotranspiration and drought index, the Mann-Kendall mutation detection method, sliding t test and Pettitt mutation test were used to analyze the drought time change cycle in the study area, and the redundancy analysis method was used to quantitatively analyze the driving factors of drought in the urban belt along the Yellow River in Ningxia. The results show that:(1)on the seasonal scale, the single-season drought occurred frequently in the study area, mainly in spring and autumn; the overall trend from north to south was from high to bottom, and it mainly occurred in the northern region, a humidification trend was found with an overall rate of 0.013/decade;(2)the decreasing trend of drought on the annual scale was found in the entire belt, showing a trend from high to bottom from north to south;(3)the SPEI-12 value of the urban belt along the Yellow River in Ningxia showed the downward trend year by year during the study period; it was determined that there was an abnormal value in 2008 through three mutation detection functions, which was consistent with the precipitation distribution;(4)the interpretation rate of each environmental factor for the SPEI index was above 75%, and precipitation, temperature, and surface net radiation were the driving forces on SPEI value of major environmental factors; precipitation had the highest contribution rate to SPEI, and had a significant positive correlation with SPEI.