Investigating Uncertainty of Future Predictions of Temperature and Precipitation in The Kerman Plain under Climate Change Impacts

IF 3.1 Q2 WATER RESOURCES

Hydrology Pub Date : 2023-12-25 DOI:10.3390/hydrology11010002

M. Goodarzi, Mahnaz Heydaripour, Vahid Jamali, Maryam Sabaghzadeh, M. Niazkar

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引用次数: 0

Abstract

Climate change affects hydroclimatic variables, and assessing the uncertainty in future predictions is crucial. This study aims to explore variations in temperature and precipitation in the Kerman Plain under climate change impacts between 2023 and 2054. For this purpose, two climate models, MRI-ESM-2 and BCC-CSM2-MR, were used to simulate precipitation and temperature under two different scenarios. The Mann–Kendall test was employed to analyze the annual time series in the future period. The results indicated an increase in the average temperature of about 1.5 degrees Celsius based on both scenarios in the coming years. Furthermore, an average annual increase of 6.37 mm of precipitation was predicted under the SSP585 scenario. Meanwhile, under the SSP585 scenario, an increase was estimated using the MRI-ESM-2 model, and a decrease was predicted with the BCC-CSM2-MR model. The Mann–Kendall test revealed a downward trend in the BCC-CSM2-MR model under both scenarios and an upward trend in the MRI-ESM-2 model under both scenarios. The bootstrap method and the R-factor index were exploited in this study with a 95% confidence interval to estimate the uncertainty of the predicted data. The results demonstrated that the predicted precipitation is more uncertain than the temperature. Finally, it is postulated that the obtained results provide necessary information for water resource management under a changing climate in the study area.

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调查气候变化影响下克曼平原未来气温和降水预测的不确定性

气候变化会影响水文气候变量，评估未来预测的不确定性至关重要。本研究旨在探讨 2023 年至 2054 年期间，克尔曼平原在气候变化影响下的气温和降水变化。为此，研究人员使用 MRI-ESM-2 和 BCC-CSM2-MR 两种气候模型模拟了两种不同情景下的降水和温度。采用 Mann-Kendall 检验法对未来时期的年时间序列进行分析。结果表明，根据两种方案，未来几年的平均气温将上升约 1.5 摄氏度。此外，根据 SSP585 情景预测，年平均降水量将增加 6.37 毫米。同时，在 SSP585 情景下，使用 MRI-ESM-2 模型估计了降水量的增加，而使用 BCC-CSM2-MR 模型预测了降水量的减少。Mann-Kendall 检验显示，在两种情景下，BCC-CSM2-MR 模型都呈下降趋势，而 MRI-ESM-2 模型则呈上升趋势。本研究利用自举法和 R 因子指数，以 95% 的置信区间来估计预测数据的不确定性。结果表明，预测降水量的不确定性要大于温度。最后，推测所得结果可为研究区域气候变化下的水资源管理提供必要信息。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Hydrology Earth and Planetary Sciences-Earth-Surface Processes

CiteScore

4.90

自引率

21.90%

发文量

192

审稿时长

6 weeks

期刊介绍： Journal of Hydrology publishes original research papers and comprehensive reviews in all the subfields of the hydrological sciences, including water based management and policy issues that impact on economics and society. These comprise, but are not limited to the physical, chemical, biogeochemical, stochastic and systems aspects of surface and groundwater hydrology, hydrometeorology, hydrogeology and hydrogeophysics. Relevant topics incorporating the insights and methodologies of disciplines such as climatology, water resource systems, ecohydrology, geomorphology, soil science, instrumentation and remote sensing, data and information sciences, civil and environmental engineering are within scope. Social science perspectives on hydrological problems such as resource and ecological economics, sociology, psychology and behavioural science, management and policy analysis are also invited. Multi-and interdisciplinary analyses of hydrological problems are within scope. The science published in the Journal of Hydrology is relevant to catchment scales rather than exclusively to a local scale or site. Studies focused on urban hydrological issues are included.