宁夏中部干旱带潜在蒸散量变化及影响因素

潜在蒸散量(PE,Potential Evapotranspiration)的估算与分析对于研究气候变化、监测农业旱情、提高农业水资源利用率具有十分重要的意义。在利用FAO Penman-Monteith(FPM)公式计算研究区1975—2012年PE日值的基础上,采用去趋势预置白Mann-Kendall检验法及敏感性分析探讨了历年来PE的变化规律和影响因素,将Matlab与Arc GIS相结合,研究了PE及其时序趋势的空间特征。结果显示:研究区多年平均PE月值呈现倒U形的变化规律,最大值和最小值分别出现在7月和1月;多年来,同心县PE具有明显的增长趋势,盐池和海原县则表现为微弱的减少。就影响因素而言,年际尺度上,同心县PE的主导因素为温度和风速,海原县为风速和水汽压,盐池县则以风速为主;月际水平上,温度的变化幅度最大,特别是在植物的生长季节(5—9月份)明显高于其他因素。研究区内PE具有明显的空间变化规律,盐池县表现为沿经向递减,同心和海原县则表现为沿纬向递增;就PE变化趋势的空间特征而言,盐池县大部分区域的PE变化不明显,显著增加的区域仅占该县总面积的2.52%,同心县显著和极显著增加的区域占全县面积的61.98%,海原县PE则以微弱减少和微弱增加为主,显著增加的区域面积比例小于30.00%。

Dynamic change and influencing factors of potential evapotranspiration in the middle arid region of Ningxia

Evapotranspiration consists of soil evaporation and plant transpiration. It is the main mechanism of the transfer and conversion of energy and moisture occurring in the soil-vegetation-atmosphere system. Potential evapotranspiration (PE) is the theoretical upper limit value of evapotranspiration, reflecting the land surface evapotranspiration capacity under the existing weather conditions. A reasonable estimate of PE is very important for studying climate change, monitoring agricultural drought, improving the utilization rate of agricultural water resources, and for many other purposes. At present, the input parameters of PE calculation models are based mostly on meteorological data. Among the models, the FAO Penman-Monteith (FPM) formula is suitable for both humid and arid/semiarid areas. Thus, FPM is often used as the standard method for calculating PE. This paper is based on daily meteorological data, collected from 28 sites of the study area and the surrounding area in 1975-2012, to estimate potential evapotranspiration by using FPM. The trend-free pre-whitening Mann-Kendall (TFPW-MK) test and sensitivity analysis were used to examine the change law and the factors influencing PE through the years. The spatial distribution characteristics of pixel-based PE and its variation trend were studied using Matlab and ArcGIS. The goal of the study was to provide methods and data support for ecological evaluation, disaster prevention, and agricultural structure adjustment. The conclusions of the study are as follows: 1) The change of average monthly PE from 1975 to 2012 was an inverted U-shaped curve, and the maximum and minimum values appeared in July and January, respectively. The average annual PE of Yanchi and Haiyuan counties showed a slight decreasing trend in 1975-2012, but the average annual PE of Tongxin County grew significantly, with an outstanding PE increase in March, April, and June. 2) In terms of influencing factors, in addition to net radiation, the sensitivity coefficients of various meteorological elements changed little during the study period in Yanchi County. Temperature in Yanchi County increased through the years, but wind speed decreased significantly, which is the main reason for the weak reduction of PE. In Tongxin County, the increase of wind speed, temperature, and its sensitivity coefficient would promote an increase of PE, but the increase of vapor pressure and the decrease of its sensitivity coefficient would help decrease PE. The combined result of both aspects led to significantly increased PE at the interannual scale, which shows that temperature and wind speed play a dominant role for PE in the region. In Haiyuan County, although temperature increased significantly through the years, wind speed decreased significantly, vapor pressure increased, and the temperature sensitivity coefficient decreased, resulting in slightly reduced PE. At the monthly scale, the change of temperature reached its maximum, especially in the growing season of plants (from May to September), and the influence of temperature was significantly higher than those of other factors. 3) PE in the study area had an obvious spatial variation law. PE in Yanchi County showed a decreasing trend with increasing longitude, and PE in Tongxin and Haiyuan counties showed an increasing trend with increasing latitude. For the spatial characteristics of the PE variation trend, the range of Z value calculated by the Mann-Kendall test for each pixel was -1.65-2.47 in Yanchi County, but the change of PE in most of the region was not obvious. Regions with significantly increased PE accounted for only 2.52% of the total area of the county. In Tongxin County, the range of Z value was 0.50-3.70, and significantly and extremely significantly increased areas accounted for 61.98% of the county. The range of Z value in Haiyuan County was from -0.70 to 3.73, and the PE variation trend of the county was a slight decrease or weak increase. The ratio of significantly increased areas was less than 30.00%.