地下水和干旱指数对植被指数空间分布的联合影响:以鄂尔多斯高原为例

发布时间：2019-05-08 22:23

【摘要】：鄂尔多斯高原无定河与都思兔河之间的地段属于我国西北地区典型的干旱-半干旱过渡带,覆盖毛乌素沙地,存在大量的地下水浅埋区,为植被生长创造了有利条件。前人研究表明鄂尔多斯高原沙地植被的盖度随着地下水埋深的减小而增大,但没有充分考虑气候梯度的影响。本研究依托大量井孔调查资料建立了研究区地下水埋深的高分辨率栅格数据,与区内增强型植被指数EVI的遥感数据和气候数据进行相关分析,并建立地下水埋深与干旱指数双因素坐标系来确定区域植被指数对地下水和气候背景的联合响应。研究结果表明:干旱指数和地下水埋深的增大都会导致植被指数的概率统计值减小。干旱指数介于3~5时,地下水埋深对植被指数的影响比较显著,且地下水埋深介于1~3m最有利于高盖度植被的出现。地下水显著影响植被分布的临界埋深约为7m。这一结果改进了前人关于鄂尔多斯生态水文地质特征的认识。
[Abstract]:The section between Wudin River and Dusibunhe River in Ordos Plateau belongs to the typical arid-semi-arid transitional zone in northwest China, which covers the Maowusu Sandy Land and has a large number of shallow groundwater buried areas, which creates favorable conditions for the growth of vegetation. Previous studies have shown that the vegetation coverage of sandy land in Ordos Plateau increases with the decrease of groundwater depth, but the influence of climate gradient is not fully considered. Based on a large number of well-hole survey data, the high-resolution grid data of groundwater depth in the study area was established, and the correlation analysis was carried out with the remote sensing data and climate data of enhanced vegetation index (EVI) in the area. The two-factor coordinate system of groundwater depth and drought index is established to determine the joint response of regional vegetation index to groundwater and climate background. The results show that the probability and statistic values of vegetation index decrease with the increase of drought index and groundwater depth. When the drought index is between 3 and 5, the influence of groundwater depth on vegetation index is significant, and the groundwater depth of 1 m is the most favorable for the occurrence of high coverage vegetation. The critical depth of groundwater significantly affecting vegetation distribution is about 7 m. This result improves the previous understanding of the eco-hydrogeological characteristics of Ordos.
【作者单位】：中国地质大学(北京)水资源与环境学院;中国地质调查局西安地质调查中心;
【基金】：国土资源部国土资源公益性行业科研专项基金项目(201311076) 全国优秀博士学位论文作者专项资金项目(201457)
【分类号】：Q948;P641

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