气候变化下泾河流域蓝绿水变化趋势及预测

doi:10.13866/j.azr.2024.12.07

干旱区研究 ›› 2024, Vol. 41 ›› Issue (12): 2045-2055.doi: 10.13866/j.azr.2024.12.07 cstr: 32277.14.AZR.20241207

气候变化下泾河流域蓝绿水变化趋势及预测

张嘉琪¹^,²^,³(), 刘招¹^,²^,³(), 韩忠青¹^,²^,³, 王丽霞⁴, 张晋霞¹^,²^,³, 岳甲寅¹^,²^,³, 管子隆⁵

1.长安大学水利与环境学院，陕西西安 710054
2.长安大学旱区地下水文与生态效应教育部重点实验室，陕西西安 710054
3.长安大学水利部旱区生态水文与水安全重点实验室，陕西西安 710054
4.长安大学地质工程与测绘学院，陕西西安 710054
5.中国电建集团西北勘测设计研究院有限公司，陕西西安 710065

收稿日期:2024-04-21 修回日期:2024-09-21 出版日期:2024-12-15 发布日期:2024-12-20
通讯作者: 刘招. E-mail: lz975@163.com
作者简介:张嘉琪（2001-），女，博士研究生，主要从事水文学及水资源研究. E-mail: zjq18991324073@163.com
基金资助:
陕西省自然科学基础研究计划(2023-JC-QN-0372);国家自然科学基金(42207084)

Trend change and prediction of blue-green water in the Jinghe River Basin under climate change

ZHANG Jiaqi¹^,²^,³(), LIU Zhao¹^,²^,³(), HAN Zhongqing¹^,²^,³, WANG Lixia⁴, ZHANG Jinxia¹^,²^,³, YUE Jiayin¹^,²^,³, GUAN Zilong⁵

1. School of Water and Environment, Chang’an University, Xi’an 710054, Shaanxi, China
2. Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of the Ministry of Education, Chang’an University, Xi’an 710054, Shaanxi, China
3. Key Laboratory of Eco-hydrology and Water Security in Arid and Semi-arid Regions of Ministry of Water Resources, Chang’an University, Xi’an 710054, Shaanxi, China
4. College of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, Shaanxi, China
5. Powerchina Northwest Engineering Corporation Limited, Xi’an 710065, Shaanxi, China

Received:2024-04-21 Revised:2024-09-21 Published:2024-12-15 Online:2024-12-20

摘要/Abstract

摘要：

基于泾河流域1980—2020年气象站点实测数据、水文站点实测径流数据及CMIP6未来气候模式，通过Delta降尺度的方法处理CMIP6气候数据，耦合SWAT（Soil and Water Assessment Tool）水文模型，探究流域内气候变化下蓝绿水的变化特征。结果表明：在SSP1-2.6路径下，研究区的蓝绿水量均呈现不显著上升趋势，在SSP3-7.0路径下，研究区蓝水量为不显著下降趋势，绿水量为显著上升趋势；在SSP5-8.5路径下，蓝水量为不显著下降趋势，绿水量为不显著上升趋势。3种路径下的多年平均蓝水量均较历史时期有所减小，多年平均蓝水量分别为128.8 mm、117.2 mm、126 mm，多年平均绿水量都有所增加，绿水量分别为372.7 mm、369.3 mm、372.1 mm，并且绿水系数均大于历史时期。蓝绿水空间分布特征均为从西北向东南地区递增，各路径之间蓝绿水的空间分布特征基本完全相同。

关键词: SWAT模型, Delta降尺度, 气候变化, CMIP6气候模式, 蓝绿水, 泾河流域

Abstract:

In this study, we analyzed meteorological data from 1980 to 2020, hydrological runoff data, and future climate models from CMIP6 in the Jinghe River Basin. The CMIP6 climate data was processed using the delta downscaling method and coupled with the Soil and Water Assessment Tool hydrological model to investigate the variations in blue-green water due to climate change in the basin. The results showed that under the SSP1-2.6 pathway, the blue-green water content in the study area exhibited an insignificant upward trend. Under the SSP3-7.0 pathway, the blue water content showed an insignificant downward trend, while the green water content showed a significant upward trend. Similarly, under the SSP5-8.5 pathway, the blue water content showed an insignificant downward trend, and the green water content also exhibited an insignificant upward trend. The average annual blue water volume under the three pathways decreased compared to the historical period, with annual averages of 128.8 mm, 117.2 mm, and 126 mm, respectively. Conversely, the average annual green water volume increased, recording values of 372.7 mm, 369.3 mm, and 372.1 mm, resulting in a green water coefficient higher than that of the historical period. The spatial distribution of blue-green water increased from northwest to southeast, with consistent spatial distribution characteristics across each pathway.

Key words: SWAT model, Delta downscaling, climate change, CMIP6 climate model, blue-green water, Jinghe River Basin

张嘉琪, 刘招, 韩忠青, 王丽霞, 张晋霞, 岳甲寅, 管子隆. 气候变化下泾河流域蓝绿水变化趋势及预测[J]. 干旱区研究, 2024, 41(12): 2045-2055.

ZHANG Jiaqi, LIU Zhao, HAN Zhongqing, WANG Lixia, ZHANG Jinxia, YUE Jiayin, GUAN Zilong. Trend change and prediction of blue-green water in the Jinghe River Basin under climate change[J]. Arid Zone Research, 2024, 41(12): 2045-2055.

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数据名称	数据年份	分辨率	数据来源	网址
DEM数据	2020年	30 m	地理空间数据云	https://www.gscloud.cn
土地利用数据	1980年、2000年、2020年	30 m	中国科学院资源环境数据中心	https://www.resdc.cn
土壤类型	2020年	1 km	世界土壤数据库	https://data.tpdc.ac.cn/zh-hans/
实测气象数据	1980—2020年	日值	中国气象数据网	https://data.cma.cn
实测径流数据	1980—2020年	日值	黄河水利委员会
未来气候数据	1975—2014年（基准期）	日值	CMCC-ESM2模式	https://aims.llnl.gov/search/cmip6/
未来气候数据	2021—2050年（未来期）	日值	CMCC-ESM2模式	https://aims.llnl.gov/search/cmip6/

因子	相关系数R²	均方根误差RMSE
月平均降水量	0.643	3.3 mm
月均最高气温	0.955	2.92 ℃
月均最低气温	0.981	1.78 ℃

序号	参数	最优值	序号	参数	最优值
1	V_EVRCH	0.337	18	V_REVAPMN	472.001
2	V_TRNSRCH	0.427	19	V_RCHRG_DP	0.365
3	V_ESCO	1.200	20	V_SLSUBBSN	37.204
4	V_EPCO	0.439	21	V_FFCB	0.786
5	V_SURLAG	55.711	22	V_SHALLST	23562.256
6	V_CH_K1	93.200	23	V_DEEPST	34715.676
7	V_CH_N1	-3.083	24	V_SFTMP	-13.548
8	V_CH_N2	-0.019	25	V_SMTMP	-0.338
9	V_CH_K2	123.386	26	V_SMFMX	-2.317
10	V_ALPHA_BNK	0.346	27	V_SMFMN	7.732
11	V_CN2	81.835	28	V_TIMP	0.308
12	V_CANMX	-1.538	29	V_SOL_AWC	0.244
13	V_OV_N	18.574	30	V_TLAPS	-0.926
14	V_GW_DELAY	16.481	31	V_HRU_SLP	0.599
15	V_ALPHA_BF	0.500	32	V_SOL_BD	3.356
16	V_GWQMN	1084.731	33	V_SOL_K	1367.089
17	V_GW_REVAP	0.131

气候变化下泾河流域蓝绿水变化趋势及预测

Trend change and prediction of blue-green water in the Jinghe River Basin under climate change

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