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在印度古吉拉特邦不同气候条件下的多尺度干旱指数的比较评估。

Comparative evaluation of multiscaler drought indices under different climatic conditions in Gujarat state of India.

机构信息

Department of Agricultural Meteorology, Anand Agricultural University, Anand, 388110, India.

出版信息

Environ Monit Assess. 2024 Oct 7;196(11):1028. doi: 10.1007/s10661-024-13187-9.

Abstract

The Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI), two drought indices, have been compared for interchangeability and reliability under various climatic conditions in Gujarat, India. As the quality of the input is crucial for the accuracy of the index, weather records from surface observatories are preferable over grid and reanalysis data. This study found that on a short timescale (1-3 months), SPEI diagnosed mild and moderate droughts more frequently than SPI, particularly in stations with relatively heavy rainfall. The indices in all timescales at all sites throughout the monsoon months displayed strong positive associations (r > 0.8). The correlation decreases but remains positive as the temporal scale is extended up to 8 months. On a 9-months or longer scales that encompassed active monsoon rainfall months at all stations, correlation coefficients were between 0.8 and 0.9 for all months of the year. During monsoon months, high fractional matches were observed on a short scale. The months after the monsoon show a generalized diagonal pattern of high fractional match with the timescale for all stations. The kappa statistic followed a broad pattern comparable to the match fractions. The instances with poor agreements (R, Match and kappa < 0.3) had proportional bias between the indices. SPEI recognized more drought events at all stations in the short time periods, while the agreements increased with longer time scales. However, SPI detects high intensities in the subhumid.

摘要

标准化降水蒸散指数(SPEI)和标准化降水指数(SPI)是两种干旱指数,在印度古吉拉特邦的各种气候条件下,对它们的互换性和可靠性进行了比较。由于输入质量对指数的准确性至关重要,因此表面观测站的天气记录优于网格和再分析数据。本研究发现,在短时间尺度(1-3 个月)内,SPEI 比 SPI 更频繁地诊断出轻度和中度干旱,尤其是在降雨量相对较大的站点。在季风月份,所有时间尺度和所有站点的指数都显示出强烈的正相关(r>0.8)。随着时间尺度的延长,相关系数虽然降低,但仍然为正。在 9 个月或更长时间尺度上,涵盖所有站点活跃季风降雨月份,所有月份的相关系数在 0.8 到 0.9 之间。在季风期间,短时间尺度上观察到高分数匹配。季风过后的月份,所有站点的分数匹配具有广义对角线模式。kappa 统计量遵循与匹配分数相似的广泛模式。具有较差一致性(R、匹配和 kappa<0.3)的实例,两个指数之间存在比例偏差。在短时间内,SPEI 在所有站点识别出更多的干旱事件,而随着时间尺度的延长,一致性会增加。然而,SPI 在次湿润地区检测到高强度干旱。

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