Sehgal Vinay Kumar, Dhakar Rajkumar
Division of Agricultural Physics, Indian Agricultural Research Institute, New Delhi, 110012, India.
Environ Monit Assess. 2016 Mar;188(3):197. doi: 10.1007/s10661-016-5187-5. Epub 2016 Feb 27.
The study presents a methodology to assess and map agricultural drought vulnerability during main kharif crop season at local scale and compare its intra-seasonal variations. A conceptual model of vulnerability based on variables of exposure, sensitivity, and adaptive capacity was adopted, and spatial datasets of key biophysical factors contributing to vulnerability were generated using remote sensing and GIS for Rajasthan State of India. Hazard exposure was based on frequency and intensity of gridded standardized precipitation index (SPI). Agricultural sensitivity was based on soil water holding capacity as well as on frequency and intensity of normalized difference vegetation index (NDVI)-derived trend adjusted vegetation condition index (VCITadj). Percent irrigated area was used as a measure of adaptive capacity. Agricultural drought vulnerability was derived separately for early, mid, late, and whole kharif seasons by composting rating of factors using linear weighting scheme and pairwise comparison of multi-criteria evaluation. The regions showing very low to extreme rating of hazard exposure, drought sensitivity, and agricultural vulnerability were identified at all four time scales. The results indicate that high to extreme vulnerability occurs in more than 50% of net sown area in the state and such areas mostly occur in western, central, and southern parts. The higher vulnerability is on account of non-irrigated croplands, moderate to low water holding capacity of sandy soils, resulting in higher sensitivity, and located in regions with high probability of rainfall deficiency. The mid and late season vulnerability has been found to be much higher than that during early and whole season. Significant correlation of vulnerability rating with food grain productivity, drought recurrence period, crop area damaged in year 2009 and socioeconomic indicator of human development index (HDI) proves the general soundness of methodology. Replication of this methodology in other areas is expected to lead to better preparedness and mitigation-oriented management of droughts.
该研究提出了一种方法，用于在地方尺度评估和绘制主要季风作物季期间的农业干旱脆弱性，并比较其季节内变化。采用了一个基于暴露、敏感性和适应能力变量的脆弱性概念模型，并利用遥感和地理信息系统（GIS）为印度拉贾斯坦邦生成了有助于评估脆弱性的关键生物物理因素的空间数据集。灾害暴露基于网格化标准化降水指数（SPI）的频率和强度。农业敏感性基于土壤持水能力以及归一化植被指数（NDVI）衍生的趋势调整植被状况指数（VCITadj）的频率和强度。灌溉面积百分比用作适应能力的衡量指标。通过使用线性加权方案对因素进行评分并进行多标准评价的成对比较，分别得出了季风早季、中季、晚季和全季的农业干旱脆弱性。在所有四个时间尺度上，都确定了灾害暴露、干旱敏感性和农业脆弱性评级从极低到极高的区域。结果表明，该邦超过50%的净播种面积存在高至极端的脆弱性，这些区域大多位于西部、中部和南部。较高的脆弱性是由于非灌溉农田、沙质土壤持水能力中等至较低导致更高的敏感性，以及位于降雨不足概率较高的地区。已发现季中及季末的脆弱性远高于季初和全季。脆弱性评级与粮食产量、干旱重现期、2009年作物受灾面积以及人类发展指数（HDI）社会经济指标之间的显著相关性证明了该方法总体上的合理性。预计在其他地区应用该方法将有助于更好地做好干旱应对准备并进行以减灾为导向的管理。
