This paper integrates drought and soil erosion problems of Puruliya district of West Bengal. The space-time dynamics of vegetative drought is assessed based on the mean monthly time-series MODIS data for the period of 2000–2013. The drought recurrence ranges from 0 to 29 months, and the mean frequency was assessed to be 7.09 months for the entire period under deliberation. The potential soil disintegration of the district was estimated using the Revised Universal Soil Loss Equation in the geo-spatial environment. The locale has been arranged into six potential soil erosion classes ranging from low-to-severe risk depending upon the computed soil erosion amount. The mean soil erosion rate of the district was anticipated as 76.29 t ha−1 year−1. The erosion amount is high in gently sloping grounds covering mainly harvested agricultural fields and open fields. These areas contribute mostly the soil erosion in this district. It is found that in this area the slope length-steepness factor is the major erosion-controlling factor. About one-fourth of the total area comes under the threat of a very high-to-severe erosion zone. Also, it was observed that the drought condition of the district is strongly correlated with the soil moisture condition in the drought-affected months and the precipitation amount. The study likewise distinguished the conceivable interrelationship between the soil erosion problem and drought frequency for better monitoring and policy decision making. A considerable increasing trend is observed in mean soil erosion with increasing frequency of drought-affected months for the study period.

中文翻译：

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印度西孟加拉邦普鲁利亚地区的时空干旱动力学和土壤侵蚀：概念设计

本文综合了西孟加拉邦普鲁利亚地区的干旱和水土流失问题。基于 2000-2013 年期间的月平均时间序列 MODIS 数据评估了植物性干旱的时空动态。干旱复发的范围为 0 至 29 个月，整个审议期间的平均频率估计为 7.09 个月。使用地理空间环境中修订的通用土壤流失方程估计该地区潜在的土壤分解。根据计算的土壤侵蚀量，该地区已被分为六个潜在的土壤侵蚀等级，从低到严重的风险。该地区的平均土壤侵蚀速率预计为 76.29 t ha-1 year-1。平缓坡地的侵蚀量高，主要覆盖收获的农田和开阔地。这些地区是该地区水土流失的主要贡献者。研究发现，在该地区边坡长度陡度因子是主要的侵蚀控制因子。总面积的大约四分之一受到非常高到严重侵蚀区的威胁。此外，还观察到该地区的干旱状况与受干旱影响月份的土壤水分状况和降水量密切相关。该研究还区分了土壤侵蚀问题与干旱频率之间可能存在的相互关系，以便更好地进行监测和决策。