流域尺度评估干旱对巴基斯坦印度河流域环境流量的影响

K. Rahman, S. Shang, Khaled S. Balkhair, H. Gabriel, K. Jadoon, Kifayat Zaman
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引用次数: 1

摘要

摘要。利用水文变化指标(IHAs)研究了 1980-2018 年间干旱对印度河流域 27 个集水区环境流量(EF)的影响。利用主成分分析 (PCA) 系统地将标准化降水蒸散指数 (SPEI) 从一个流域传播到另一个流域。阈值回归用于确定引发印度河流域低流量的干旱严重程度(情景 1,导致低流量的干旱严重程度)和月份(情景 2,干旱导致低流量的月份)。干旱对低 EFs 的影响通过变异范围分析 (RVA) 进行量化,RVA 是 IHA 的一个综合组成部分,用于研究环境流量成分 (EFCs) 的水文变化,方法是比较人为和/或气候干预对 EFCs 影响的前后时期。印度河流域的每个集水区都计算了水文变化系数 (HAF)。结果表明,大多数流域在 1984 至 1986 年、1991/1992 年、1997 至 2003 年、2007 至 2008 年、2012 至 2013 年和 2017 至 2018 年期间易受干旱影响。从更长的时间尺度来看(SPEI-12),下印度河流域(LIB)的干旱比上印度河流域(UIB)更为严重。国际水文局指出,干旱严重影响了 EFC 的分布,尤其是极低流量 (ELF) 和低流量 (LF)。随着干旱严重程度的增加,ELF 和 LF 事件的规模和频率也在增加。阈值回归提供了有用的见解,表明中度干旱可在较短的时间尺度(SPEI-1 和 SPEI-6)上引发印度河上游流域和印度河中游流域的 ELF 和 LF。相反,在印度河流域,严重和极端干旱会在较长的时间尺度上(SPEI-12)触发 ELF 和 LF。阈值回归还将整个研究期间(1980-2018 年)划分为不同的时间段(情景 2),这有助于利用 SPEI 系数量化干旱对低 EF 的影响。在 LIB 中观察到较高的 SPEI 系数,表明干旱对 EF 的改变较大。除 8 月和 9 月外,HAF 表明大多数流域全年的 EF 都有较高的变化。总体而言,本研究为分析干旱对 EF 的影响(尤其是在低流量期间)提供了有用的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Catchment-scale assessment of drought impact on environmental flow in the Indus Basin, Pakistan
Abstract. The impact of drought on environmental flow (EF) in 27 catchments of the Indus Basin is studied from 1980–2018 using indicators of hydrologic alterations (IHAs). The standardized precipitation evapotranspiration index (SPEI) was systematically propagated from one catchment to another using principal component analysis (PCA). Threshold regression is used to determine the severity of drought (scenario 1, drought severity that causes low flows) and the month (scenario 2, months where drought has resulted in low flows) that trigger low flows in the Indus Basin. The impact of drought on low EFs is quantified using range of variability analysis (RVA), which is an integrated component of the IHA used to study the hydrological alterations in environmental flow components (EFCs) by comparing the pre- and post-impact periods of human and/or climate interventions in EFCs. The hydrological alteration factor (HAF) is calculated for each catchment in the Indus Basin. The results show that most of the catchments were vulnerable to drought during the periods of 1984 to 1986, 1991/1992, 1997 to 2003, 2007 to 2008, 2012 to 2013, and 2017 to 2018. On a longer timescale (SPEI-12), drought is more severe in the lower Indus Basin (LIB) than in the upper Indus Basin (UIB). The IHA pointed out that drought significantly impacts the distribution of EFCs, particularly extremely low flow (ELF) and low flow (LF). The magnitude and frequency of the ELF and LF events increase as drought severity increases. The threshold regression provided useful insights, indicating that moderate drought can trigger ELF and LF at shorter timescales (SPEI-1 and SPEI-6) in the UIB and middle Indus Basin (MIB). Conversely, severe and extreme droughts trigger ELF and LF at longer timescales (SPEI-12) in the LIB. The threshold regression also divided the entire study period (1980–2018) into different time periods (scenario 2), which is useful for quantifying the impact of drought on low EFs using the SPEI coefficient. Higher SPEI coefficients are observed in the LIB, indicating high alterations in EF due to drought. HAF showed high alterations in EF in most of the catchments throughout the year except in August and September. Overall, this study provided useful insights for analysing the effects of drought on EF, especially during low flows.
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