Prediction of future hydrological drought risk in the Yarkant River Basin based on CMIP6 models
Received date: 2023-10-01
Revised date: 2023-11-22
Online published: 2024-05-30
Global warming has led to the increased frequency of extreme events such as droughts, posing significant threats to ecological security and sustainable socioeconomic development, particularly in arid regions, which are highly sensitive and responsive to climate changes. This paper employs the distributed hydrological model HEC-HMS, utilizing observed meteorological and hydrological data from basin stations and global climate model data from the Sixth International Coupled Model Intercomparison Program (CMIP6), to simulate and forecast the historical (1986—2014) and future (2015—2100) runoff trends and hydrological drought risks in the Yarkant River Basin (an essential tributary of the Tarim River), Xinjiang, China. The findings indicate that: (1) The HEC-HMS model is well-suited for arid basin areas. Under the three shared socioeconomic pathways (SSPs) scenarios, the runoff and standardized runoff index (SRI) in the Yarkant River Basin are projected to significantly increase (P<0.1), with the SRI growth rate estimated at approximately 0.13-0.27·(10a)-1. (2) A comparative analysis of the marginal distributions of four drought characteristic variables in the basin for both historical and future periods reveals that the duration and intensity of future droughts will exceed those in the historical record, with a continuous rise in drought event magnitudes. (3) Moreover, the joint probability of future hydrological droughts in the Yarkant River Basin is expected to decrease relative to the historical period, leading to a prolonged return period for future droughts. The outcomes of this study offer valuable scientific references for water resource management and the development of strategies to mitigate hydrological drought risks in the basin.
Key words： hydrological drought; risk prediction; CMIP6; climate change
XIANG Yanyun , WANG Yi , CHEN Yaning , ZHANG Qifei , ZHANG Yujie . Prediction of future hydrological drought risk in the Yarkant River Basin based on CMIP6 models[J]. Arid Land Geography, 2024 , 47(5) : 798 -809 . DOI: 10.12118/j.issn.1000-6060.2023.536
| [1] | Ahmed K, Shahid S, Nawaz N. Impacts of climate variability and change on seasonal drought characteristics of Pakistan[J]. Atmospheric Research, 2018, 214: 364-374. |
| [2] | Damberg L A. Global trends and patterns of drought from space[J]. Theoretical and Applied Climatology, 2013, 117(3-4): 441-448. |
| [3] | 周波涛, 钱进. IPCCAR6报告解读: 极端天气气候事件变化[J]. 气候变化研究进展, 2021, 17(6): 713-718. |
| [Zhou Botao, Qian Jin. Changes of weather and climate extremes in the IPCC AR6[J]. Climate Change Research, 2021, 17(6): 713-718. ] | |
| [4] | Dai A. Characteristics and trends in various forms of the Palmer drought severity index during 1900—2008[J]. Journal of Geophysical Research, 2011, 116: D12115, doi: 10.1029/2010JD015541. |
| [5] | Dai A. Drought under global warming: A review[J]. Wiley Interdisciplinary Reviews: Climate Change, 2011, 2(1): 45-65. |
| [6] | Oloruntade A J, Mohammad T A, Ghazali A H, et al. Analysis of meteorological and hydrological droughts in the Niger-South Basin, Nigeria[J]. Global and Planetary Change, 2017, 155: 225-233. |
| [7] | 陈亚宁, 李玉朋, 李稚, 等. 全球气候变化对干旱区影响分析[J]. 地球科学进展, 2022, 37(2): 111-119. |
| [Chen Yaning, Li Yupeng, Li Zhi, et al. Analysis of the impact of global climate change on dryland areas[J]. Advances in Earth Science, 2022, 37(2): 111-119. ] | |
| [8] | Taskiris G. Drought risk assessment and management[J]. Water Resources Management, 2017, 31(10): 3083-3095. |
| [9] | Van L, Laaha G. Hydrological drought severity explained by climate and catchment characteristics[J]. Journal of Hydrology, 2015, 526: 3-14. |
| [10] | Williams A P, Seager R, Abatoglou J T, et al. Contribution of anthropogenic warming to California drought during 2012—2014[J]. Geophysical Research Letters, 2015, 42(16): 6819-6828. |
| [11] | 丁一汇. 构建全球气候变化早期预警和防御系统[J]. 可持续发展经济导刊, 2020, 11(增刊1): 44-45. |
| [Ding Yihui. Build an early warning and defense system for global climate change[J]. China Sustainability Tribune, 2020, 11(Suppl. 1): 44-45. ] | |
| [12] | 袁星, 马凤, 李华, 等. 全球变化背景下多尺度干旱过程及预测研究进展[J]. 大气科学学报, 2020, 43(1): 225-237. |
| [Yuan Xing, Ma Feng, Li Hua, et al. A review on multi-scale drought processes and prediction under global change[J]. Transactions of Atmospheric Sciences, 43(1): 225-237. ] | |
| [13] | 向燕芸, 王志成, 张辉, 等. 干旱区融雪径流模拟的研究进展与展望[J]. 冰川冻土, 2017, 39(4): 892-901. |
| [Xiang Yanyun, Wang Zhicheng, Zhang Hui, et al. Study of snowmelt runoff simulation in arid regions: Progress and prospect[J]. Journal of Glaciology and Geocryology, 2017, 39(4): 892-901. ] | |
| [14] | Azmat M, Choi M, Kim T W, et al. Hydrological modeling to simulate streamflow under changing climate in a scarcely gauged cryosphere catchment[J]. Environmental Earth Sciences, 2016, 75(3): 186, doi: 10.1007/s12665-015-5059-2. |
| [15] | Xu H, Liu L, Wang Y, et al. Assessment of climate change impact and difference on the river runoff in four basins in China under 1.5 and 2.0?℃ global warming[J]. Hydrology and Earth System Sciences, 2019, 23(10): 4219-4231. |
| [16] | Kong Q, Guerreiro S B, Blenkinsop S, et al. Increases in summertime concurrent drought and heatwave in eastern China[J]. Weather and Climate Extremes, 2020, 28: 100242, doi: 10.1016/j.wace.2019.100242. |
| [17] | Laurent L, Buoncristiani J F, Pohl B, et al. Landscape pattern change research of Yarkant irrigated area[J]. Scientific Reports, 2020, 10: 10420, doi: 10.1038/s41598-020-67379-7. |
| [18] | Han H, Wang R. Landscape pattern change research of Yarkant irrigated area[C]// International Symposium on Geomatics for Integrated Water Resources Management. IEEE, 2012. |
| [19] | 王晨鹏, 黄萌田, 翟盘茂. IPCC AR6 报告关于不同类型干旱变化研究的新进展与启示[J]. 气象学报, 2022, 80(1): 168-175. |
| [Wang Chenpeng, Huang Mengtian, Zhai Panmao. New progress and enlightenment on different types of drought changes from IPCC Sixth Assessment Report[J]. Acta Meteorologica Sinica, 2022, 80(1): 168-175. ] | |
| [20] | 周天军, 邹立维, 陈晓龙. 第六次国际耦合模式比较计划(CMIP6)评述[J]. 气候变化研究进展, 2019, 15(5): 455-456. |
| [Zhou Tianjun, Zou Liwei, Chen Xiaolong. Commentary on the Coupled Model Intercomparison Project Phase 6 (CMIP6)[J]. Climate Change Research, 2019, 15(5): 445-456. ] | |
| [21] | Kan B, Su F, Xu B, et al. Generation of high mountain precipitation and temperature data for a quantitative assessment of flow regime in the upper Yarkant Basin in the Karakoram[J]. Journal of Geophysical Research: Atmospheres, 2018, 123(16): 8462-8486. |
| [22] | 刘蛟, 刘铁, 黄粤, 等. 基于遥感数据的叶尔羌河流域水文过程模拟与分析[J]. 地理科学进展, 2017, 36(6): 753-761. |
| [Liu Jiao, Liu Tie, Huang Yue, et al. Simulation and analysis of the hydrological processes in the Yarkant River Basin based on remote sensing data[J]. Progress in Geography, 2017, 36(6): 753-761. ] | |
| [23] | 任才, 龙爱华, 於嘉闻, 等. 气候与下垫面变化对叶尔羌河源流径流的影响[J]. 干旱区地理, 2021, 44(5): 1373-1383. |
| [Ren Cai, Long Aihua, Yu Jiawen, et al. Effects of climate and underlying surface changes on runoff of Yarkant River source[J]. Arid Land Geography, 2021, 44(5): 1373-1383. ] | |
| [24] | Xiang Y, Wang Y, Chen Y, et al. Impact of climate change on the hydrological regime of the Yarkant River Basin, China: An assessment using three SSP scenarios of CMIP6 GCMs[J]. Remote Sensing, 2021, 14(1): 115, doi: 10.3390/rs14010115. |
| [25] | 田昊玮, 陈伏龙, 龙爱华, 等. 博尔塔拉河源流区径流对气候变化的响应及预测[J]. 干旱区地理, 2023, 46(9): 1432-1442. |
| [Tian Haowei, Chen Fulong, Long Aihua, et al. Response and prediction of runoff to climate change in the headwaters of the Bortala River[J]. Arid Land Geography, 2023, 46(9): 1432-1442. ] | |
| [26] | 李昱, 席佳, 张弛, 等. 气候变化对澜湄流域气象水文干旱时空特性的影响[J]. 水科学进展, 2021, 32(4): 508-519. |
| [Li Yu, Xi Jia, Zhang Chi, et al. Impact of climate change on the spatio-temporal characteristics of meteorological and hydrological drought over the Lancang-Mekong River Basin[J]. Advances in Water Science, 2021, 32(4): 508-519. ] | |
| [27] | Xiang Y, Wang Y, Chen Y, et al. Hydrological drought risk assessment using a multidimensional Copula function approach in arid inland basins, China[J]. Water, 2020, 12(7): 1888, doi: 10.3390/w12071888. |
| [28] | Sklar A. Fonctions de Repartition a n Dimensions et Leurs Marges[J]. Publications de l’Institut de statistique de l’Université de Paris, 1959(8): 229-231. |
| [29] | Hao Z, Aghakouchak A, Nakhjiri N, et al. Global integrated drought monitoring and prediction system[J]. Science Data, 2014, 1: 140001, doi: 10.1038/sdata.2014.1. |
| [30] | Bushra N, Trepanier J C, Rohli R V. Joint probability risk modelling of storm surge and cyclone wind along the coast of bay of Bengal using a statistical Copula[J]. International Journal of Climatology, 2019, 39(11): 4206-4217. |
| [31] | Das J, Jha S, Goyal M K. Non-stationary and Copula-based approach to assess the drought characteristics encompassing climate indices over the Himalayan states in India[J]. Journal of Hydrology, 2020, 580: 124356, doi: 10.1016/j.jhydrol.2019.124356. |
| [32] | Lü J Q, Shen B, Li H E. Dynamics of major hydro-climatic variables in the headwater catchment of the Tarim River Basin, Xinjiang, China[J]. Quaternary International, 2015, 380-381: 143-148. |
| [33] | Gao X, Yang B S, Zhang S Q, et al. Glacier runoff variation and its influence on river runoff during 1961—2006 in the Tarim River Basin, China[J]. Science China Earth Sciences, 2010, 40(5): 544-565. |
| [34] | Duethmann D T, Bolch D, Farinotti D, et al. Attribution of streamflow trends in snow and glacier melt-dominated catchments of the Tarim River, Central Asia[J]. Water Resources Research, 2015, 51: 4727-4750. |
| [35] | 张久丹, 李均力, 包安明, 等. 2013—2020年塔里木河流域胡杨林生态恢复成效评估[J]. 干旱区地理, 2022, 45(6): 1824-1835. |
| [Zhang Jiudan, Li Junli, Bao Anming, et al. Effectiveness assessment of ecological restoration of Populus euphratica forest in the Tarim River Basin during 2013—2020[J]. Arid Land Geography, 2022, 45(6): 1824-1835. ] |
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