基于地表水供应指数和SWAT模型的山区流域SSP情景水文干旱预测

IF 5.7 3区 环境科学与生态学 Q1 WATER RESOURCES
Omid Babamiri, Yagob Dinpashoh, Alireza Samavati, Faeze Shoja
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引用次数: 0

摘要

本研究旨在探讨气候变化对山地流域水文干旱的影响。利用耦合模式比对项目第6阶段(CMIP6)模型和水土评价工具(SWAT)径流模拟模型来实现研究目标。此外,采用地表水供应指数(SWSI)对水文干旱进行了评价。为了纠正所选CMIP6模型(ACCESS-CM2、CNRM-CM6-1、CNRM-ESM2-1、INM-CM4-8、INM-CM5-0、MIROC6和MIROC-ES2L)的偏差,将1990 - 2014年的历史时期作为基线。研究发现,在研究的山区盆地,即伊朗的Ekbatan流域,与其他选择的模型相比,microc - es2l模型显示出更高的准确性。采用序列不确定拟合第2版(SUFI-2)算法对SWAT模型进行定标和验证,定标期为2004 - 2017年,验证期为2018 - 2020年。结果表明,该模型能有效地模拟流域径流。在验证阶段,标准化均方根误差(NRMSE)测量的最高百分比误差为18.78%。使用Mann-Kendall检验对预测期间(2023-2042)的径流趋势分析的结果表明,在这一时间段内,径流预计不会出现显著的减少或增加趋势。此外,对预测期(2023-2042)径流不确定性的评估表明,最显著的变异或不确定性与4月份有关,其范围为0 ~ 9.55 m3/s。未来径流(2023-2042)与过去径流(2000-2020)的比较表明,在典型的干旱月份(8月、9月和10月),径流增加。这一增长在9月份尤为明显,在SSP2-4.5情景和表现最佳的模型(MIROC-ES2L)下,径流预计将高出近12倍。这一现象可归因于干旱季节受气候变化影响可能发生的强降雨事件。此外,由于这一时期的流量普遍较低,相对增加更为显著。通过比较2023-2042年和2000-2020年的干旱状况,SWSI评估结果表明,在12个月尺度上,在所有情景(SSP1-2.6、SSP2-4.5和SSP5-8.5)下,典型湿润月(2、3、4、5)的干旱状况都将加剧。换句话说,预计未来这几个月将变得更加干燥。在SSP5-8.5情景下,预计2月份干旱严重程度的增幅最大,达到86.84%。总体而言,研究结果表明,在湿润月份,山区盆地的水文干旱加剧。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Projection of hydrological drought based on SSP scenarios using surface water supply index and SWAT model in mountainous watershed

The objective of this research is to explore climate change impact on hydrological drought in mountain watersheds. The Coupled Model Intercomparison Project Phase 6 (CMIP6) models and the Soil and Water Assessment Tool (SWAT) runoff simulation model were utilized to attain the objective of the study. Moreover, the surface water supply index (SWSI) was employed to examine hydrological drought. To correct the bias of the selected CMIP6 models (ACCESS-CM2, CNRM-CM6-1, CNRM-ESM2-1, INM-CM4-8, INM-CM5-0, MIROC6, and MIROC-ES2L), the historical period from 1990 to 2014 was used as a baseline. It was found that the MIROC-ES2L model exhibited greater accuracy compared to the other chosen models in the context of the examined mountain basin, namely the Ekbatan watershed in Iran. The calibration and validation of the SWAT model were conducted using the Sequential Uncertainty Fitting version 2 (SUFI-2) algorithm, covering the calibration period from 2004 to 2017 and the validation period from 2018 to 2020. The results indicated that the model effectively simulates runoff in the watershed. The highest percentage error, as measured by the Normalized Root Mean Square Error (NRMSE), was 18.78% during the validation phase. Results from a trend analysis of runoff using the Mann–Kendall test for the projected period (2023–2042) indicate that runoff is not expected to exhibit a significant decreasing or increasing trend during this timeframe. Furthermore, an assessment of runoff uncertainty within the projected period (2023–2042) revealed that the most substantial variability or uncertainty is associated with the month of April, with a range of 0 to 9.55 m3/s. The comparison of future runoff (2023–2042) with past runoff (2000–2020) indicates an increase in runoff during typically dry months (August, September, and October). This increase is particularly pronounced in September, where, under the SSP2-4.5 scenario and the best-performing model (MIROC-ES2L), runoff is projected to be nearly twelve times higher. This phenomenon may be attributed to the potential occurrence of intense rainfall events influenced by climate change during the dry season. Additionally, due to the generally low streamflow in this period, the relative increase appears more significant. When comparing drought conditions between the periods of 2023–2042 and 2000–2020, as assessed by SWSI, the results show that, on a 12-month scale, drought conditions in the typically wet months (February, March, April, and May) are expected to intensify under all scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5). In other words, these months are projected to become drier in the future. The most significant increase in drought severity is anticipated in February under the SSP5-8.5 scenario, reaching a magnitude of 86.84%. Overall, results indicated an intensification of hydrological drought during the wet months in the mountainous basin.

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来源期刊
Applied Water Science
Applied Water Science WATER RESOURCES-
CiteScore
9.90
自引率
3.60%
发文量
268
审稿时长
13 weeks
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