Abstract

Agriculture in hill and mountain ecosystems is predominantly rainfed with common occurrence of moisture stress. It is a natural disaster which evolves in time and its impacts last for a long time. In the present investigation, long-term monthly precipitation data for 40 years (1980–2019) were used for characterizing agricultural drought in Almora and Nainital districts of Uttarakhand in India. Different drought indices based on meteorological data like standard precipitation index (SPI), percentage of departure (P_d) and percent of normal (P_n) were used. Percentage of departure is calculated from deviation of monthly precipitation from the long-term average monthly precipitation. Percent of normal is calculated by dividing the precipitation by normal precipitation for time being considered. SPI values were calculated based on gamma distribution of long-term monthly precipitation data. The Pearson’s correlation coefficient between monthly percentage of departure and different SPI time scales (1, 3 and 6 months) were analyzed. SPI-1 (July and August) for both the stations showed very strong correlation with the corresponding monthly percentage of departure (r > 0.97) than SPI-3 and SPI-6. Therefore, it is suggested that SPI as a stand-alone indicator should not be interpreted to identify drought in a hilly region.

Research highlights

• Meteorological drought indices have been used to identify agricultural drought.

• SPI-1 showed very strong correlation with percentage of departure.

• Meteorological based SPI was well correlated with satellite based drought indices.

• Study suggest to use multiple drought indices for drought Identification.

中文翻译：

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利用气象数据识别北阿坎德邦 Kumaon 地区的农业干旱

摘要

丘陵和山区生态系统中的农业主要靠雨养，经常发生水分胁迫。它是一种随时间演变的自然灾害，其影响持续很长时间。在本调查中，40 年（1980-2019 年）的长期月降水数据用于表征印度北阿坎德邦阿尔莫拉和奈尼塔尔地区的农业干旱。基于气象数据的不同干旱指数，如标准降水指数 (SPI)、偏离百分比 ( P _d ) 和正常百分比 ( P _n) 被使用。偏离百分比是根据月降水量与长期平均月降水量的偏差计算的。正常百分比的计算方法是将降水量除以所考虑的时间的正常降水量。SPI 值是根据长期月降水数据的伽马分布计算的。分析了每月离港百分比与不同 SPI 时间尺度（1、3 和 6 个月）之间的 Pearson 相关系数。与SPI-3 和 SPI-6 相比，两个站点的 SPI-1（7 月和 8 月）与相应的月离港百分比 ( r > 0.97)显示出非常强的相关性。因此，建议不应将 SPI 作为独立指标解释为识别丘陵地区的干旱。

研究亮点

• 气象干旱指数已被用于识别农业干旱。

• SPI-1 与偏离百分比显示出非常强的相关性。

• 基于气象的 SPI 与基于卫星的干旱指数密切相关。

• 研究建议使用多个干旱指数进行干旱识别。