基于Landsat数据的开都河两岸绿洲地下水遥感监测及影响因素分析

发布时间：2018-05-20 16:35

本文选题：Landsat + 干旱指数　；参考：《自然灾害学报》2017年04期

【摘要】：为了研究干旱区绿洲地下水位时空变化特征及其归因,以新疆开都河两岸绿洲为研究对象,利用实测地下水埋深数据和Landsat数据计算得到的改进型温度植被干旱指数(MTVDI)相结合,建立了地下水位监测关系模型(R2=0.82)。对研究区1999年到2016年地下水的时空分布进行了监测,利用2005年和2003年两年实测数据对模型进行了验证。结果表明:1)两年实测地下水位和监测水位相关系数(R2)分别为0.75和0.77,均方根误差(RMSE)分别为0.17和0.27,平均相对误差(RME)分别为11.4%和16.7%,研究结果符合研究区实际情况;利用MTVDI建立的地下水位监测模型对干旱区绿洲一定深度的地下水位监测是可行的;2)开都河两岸绿洲1999年到2016年地下水位年际变化逐渐降低,年内地下水位升降显著;3)地下水位年际降低的主要原因是耕地面积的增加和灌溉方式向高效节水方式转变,增加了地下水开采量和降低了补给量。在年内随着渠系灌溉水的作用,使地下水位在季节性里变化较大。
[Abstract]:In order to study the temporal and spatial variation characteristics and attribution of oasis groundwater in arid area, taking the oasis on both banks of Kaidu River in Xinjiang as the research object, the modified temperature vegetation drought index (MTVDII) was calculated by using the measured groundwater depth data and Landsat data. The monitoring model of groundwater level is established. The temporal and spatial distribution of groundwater in the study area from 1999 to 2016 was monitored and the model was verified by the data measured in 2005 and 2003. The results show that the correlation coefficient of groundwater level and monitored water level is 0.75 and 0.77, the RMSE is 0.17 and 0.27, and the average relative error is 11.4% and 16.7g, respectively. The results agree with the actual situation in the study area. Using the groundwater level monitoring model established by MTVDI, it is feasible to monitor the groundwater level at a certain depth in the oasis in arid area.) the interannual variation of groundwater level in the oasis on both sides of the Kaidu River from 1999 to 2016 decreases gradually. The main reasons for the interannual decrease of groundwater level are the increase of cultivated land area and the transformation of irrigation mode to high efficiency and water saving mode, which increases the groundwater exploitation and reduces the recharge. During the year, with the effect of irrigation water in canal system, the groundwater level changes greatly in seasonal.
【作者单位】：新疆师范大学地理科学与旅游学院/流域信息集成与生态安全实验室;新疆干旱区湖泊环境与资源重点实验室;
【基金】：新疆自治区青年科技创新人才培养工程(QN2015YX009) 国家自然科学基金(41161007,41461006)~~
【分类号】：P641;TP79

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