气候及土地利用变化对大通河源区水文要素空间分布的影响

doi:10.13866/j.azr.2023.03.05

Abstract

Abstract:

Water shortage has become a major resource and environmental challenge worldwide. Climate and land use change have made the evolution of current hydrological factors complex and uncertain. Exploring the spatial distribution characteristics of hydrological factors under dynamic scenarios is of vital theoretical and practical significance for the sustainable development of regional economy and society. The meteorological and hydrological data of the Datong River source region from 1960 to 2019 were used in this study to quantitatively analyze the spatial distribution characteristics of hydrological elements under climate and land use change scenarios based on model simulation and scenario segmentation. The results showed that: (1) After calibration and verification of the SWAT model, the coefficient of determination, Nash coefficient, and percentage bias (PBIAS) all met the model requirements of 0.81%, 0.79%, and -0.8% in the rate period, and 0.81%, 0.75%, and 15.8% in the validation period, respectively, which indicated that the model had good applicability in the headwaters of the Chase River. (2) Obvious spatial heterogeneity of hydrological elements was detected in the headwater area of Datong River, and a single hydrological element could not represent the overall spatial distribution. Precipitation, potential evapotranspiration, and soil water content decreased with the increase in altitude, while surface runoff and water yield increased with the increase in altitude. (3) The spatial distribution of hydrological factors under the three scenarios were generally consistent, while the spatial distribution of water yield was greatly affected by the land use change. Under the climate change scenario, the actual evapotranspiration and soil water content showed a downward trend, while the surface runoff and water yield showed an upward trend. Under the land use change scenario, the changes of hydrological elements were contrary to these observations.

Key words: hydrological elements, spatial distribution, SWAT model, Datong River

ZHAO Meiliang, CAO Guangchao, ZHAO Qinglin, CAO Shengkui. Effects of climate and land use change on the spatial distribution of hydrological factors in the source region of Datong River[J].Arid Zone Research, 2023, 40(3): 381-391.

Figures/Tables 12

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References 33

[1]	Siqueira P P, Oliveira P T S, Bressiani D, et al. Effects of climate and land cover changes on water availability in a Brazilian Cerrado basin[J]. Journal of Hydrology: Regional Studies, 2021, 37: 100931. doi: 10.1016/j.ejrh.2021.100931
[2]	董晓光. 浅谈水资源利用与保护[J]. 水利科技与经济, 2011, 17(5): 35-36.
	[Dong Xiaoguang. On the utilization and protection of water resources[J]. Water Conservancy Science and Technology and Economy, 2011, 17(5): 35-36.]
[3]	张利平, 夏军, 胡志芳. 中国水资源状况与水资源安全问题分析[J]. 长江流域资源与环境, 2009, 18(2): 116-120.
	[Zhang Liping, Xia Jun, Hu Zhifang. Situation and problem analysis of water resources security in China[J]. Resources and Environment in the Yangtze Basin, 2009, 18(2): 116-120.]
[4]	胡宏韬, 林学钰, 蔡青勤. 中国的水环境状况及对策[J]. 干旱环境监测, 2001, 15(1): 41-44.
	[Hu Hongtao, Lin Xueyu, Cai Qingqin. State of water environment and countermeasure in China[J]. Arid Environmental Monitoring, 2001, 15(1): 41-44.]
[5]	王正, 黄粤, 刘铁, 等. 近60 a巴尔喀什湖水量平衡变化及其影响因素[J]. 干旱区研究, 2022, 39(2): 400-409.
	[Wang Zheng, Huang Yue, Liu Tie, et al. Analyzing the water balance of Lake Balkhash and its influencing factors[J]. Arid Zone Research, 2022, 39(2): 400-409.]
[6]	盖美, 翟羽茜. 中国水资源-能源-粮食-支撑系统安全测度及协调发展[J]. 生态学报, 2021, 41(12): 4746-4756.
	[Gai Mei, Zhai Yuqian. Measurement and coordinated development of water resources, energy, food and support security in China[J]. Acta Ecologica Sinica, 2021, 41(12): 4746-4756.]
[7]	李文娟, 覃志豪, 林绿. 农业旱灾对国家粮食安全影响程度的定量分析[J]. 自然灾害学报, 2010, 19(3): 111-118.
	[Li Wenjuan, Qin Zhihao, Lin Lv. Quantitative analysis of agro-drought impact on food security in China[J]. Journal of Natural Disasters, 2010, 19(3): 111-118.]
[8]	Guo W, Hu J, Wang H. Analysis of runoff variation characteristics and influencing factors in the Wujiang River Basin in the past 30 Years[J]. Environmental Research and Public Health, 2022, 19(1): 19010372.
[9]	Xue D X, Zhou J J, Zhao X, et al. Impacts of climate change and human activities on runoff change in a typical arid watershed, NW China[J]. Ecological Indicators, 2021, 121: 107013. doi: 10.1016/j.ecolind.2020.107013
[10]	IPCC. Climate Change 2013: The Physical Science Basis[M]. Cambridge: Cambridge University Press, 2013.
[11]	唐国利, 丁一汇, 王绍武, 等. 中国近百年温度曲线的对比分析[J]. 气候变化研究进展, 2009, 5(2): 71-78.
	[Tang Guoli, Ding Yihui, Wang Shaowu, et al. Comparative analysis of the time series of surface air temperature over China for the last 100 years[J]. Advances in Climate Change Research, 2009, 5(2): 71-78.]
[12]	张莉, 丁一汇, 吴统文, 等. CMIP5模式对21世纪全球和中国年平均地表气温变化和2 ℃升温阈值的预估[J]. 气象学报, 2013, 71(6): 1047-1060.
	[Zhang Li, Ding Yihui, Wu Tongwen, et al. The 21st century annual mean surface air temperature change and the 2 ℃ warming threshold over the globe and China as projected by the CMIP5 models[J]. Acta Meteorologica Sinica, 2013, 71(6): 1047-1060.]
[13]	Immerzeel W W, van Beek L P, Bierkens M F. Climate change will affect the Asian water towers[J]. Science, 2010, 328(5984): 1382-1385. doi: 10.1126/science.1183188 pmid: 20538947
[14]	Wu J K, Li H Y, Zhou J X, et al. Variation of runoff and runoff components of the upper Shule River in the northeastern Qinghai-Tibet Plateau under Climate Change[J]. Water 2021, 13(23): 3357. doi: 10.3390/w13233357
[15]	Wu Y Y, Fang H W, Huang L, et al. Changing runoff due to temperature and precipitation variations in the dammed Jinsha River[J]. Journal of Hydrology, 2019, 582: 124500. doi: 10.1016/j.jhydrol.2019.124500
[16]	田晶, 郭生练, 刘德地, 等. 气候与土地利用变化对汉江流域径流的影响[J]. 地理学报, 2020, 75(11): 2307-2318. doi: 10.11821/dlxb202011003
	[Tian Jing, Guo Shenglian, Liu Dedi, et al. Impacts of climate and land use/cover changes on runoff in the Hanjiang River basin[J]. Acta Geographica Sinica, 2020, 75(11): 2307-2318.] doi: 10.11821/dlxb202011003
[17]	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.]
[18]	霍军军, 伊明启, 王静, 等. 拉萨河流域径流对土地利用和气候变化的响应分析[J]. 长江科学院院报, 2021, 38(10): 33-39.
	[Huo Junjun, Yi Mingqi, Wang Jing, et al. Response of runoff in Lhasa River Basin to land use and climate change[J]. Journal of Yangtze River Scientific Research Institute, 2021, 38(10): 33-39.]
[19]	黄维东, 牛最荣, 刘彦娥, 等. 梯级水电开发对大通河流域洪水过程的影响分析[J]. 水文, 2016, 36(4): 58-65.
	[Huang Weidong, Niu Zuirong, Liu Yan’e, et al. Effect of cascade hydroelectric development on flood process in Datonghe River basin[J]. Journal of China Hydrology, 2016, 36(4): 58-65.]
[20]	董军, 胡进宝, 魏国孝. 大通河流域径流变化及特征分析[J]. 水资源与水工程学报, 2018, 29(6): 75-80, 87.
	[Dong Jun, Hu Jinbao, Wei Guoxiao. Analysis of runoff variation and characteristics in Datong River basin[J]. Journal of Water Resources and Water Engineering, 2018, 29(6): 75-80, 87.]
[21]	王大超, 杜丽芳, 路贺, 等. 大通河流域近60年径流变化特征和趋势分析[J]. 水利水电快报, 2019, 40(4): 17-21.
	[Wang Dachao, Du Lifang, Lu He, et al. Variation characteristics and trend analysis of runoff in Datong River basin in recent 60 years[J]. Express Water Resources & Hydropower Information, 2019, 40(4): 17-21.]
[22]	刘赛艳, 黄强, 解阳阳, 等. 大通河流域上游径流变化特征与突变分析[J]. 西北农林科技大学学报(自然科学版), 2016, 44(3): 219-226.
	[Liu Saiyan, Huang Qiang, Xie Yangyang, et al. Abrupt change and variation characteristics of runoff in the upper reaches of Datong River basin[J]. Journal of Northwest A & F University (Natural Science Edition), 2016, 44(3): 219-226.]
[23]	Wu Jun, Deng Guoning, Zhou Dongmei, et al. Effects of climate change and land-use changes on spatiotemporal distributions of blue water and green water in Ningxia, Northwest China[J]. Journal of Arid Land, 2021, 13(7): 674-687. doi: 10.1007/s40333-021-0074-5
[24]	窦小东, 黄玮, 易琦, 等. LUCC及气候变化对澜沧江流域径流的影响[J]. 生态学报, 2019, 39(13): 4687-4696.
	[Dou Xiaodong, Huang Wei, Yi Qi, et al. Impacts of LUCC and climate change on runoff in Lancang River Basin[J]. Acta Ecologica Sinica, 2019, 39(13): 4687-4696.]
[25]	Arnold J G, Srinivasan R, Muttiah R S, et al. Large area hydrologic modeling and assessment(Part 1): Model development[J]. Journal of American Water Resource Association, 1998, 34(1): 73-89. doi: 10.1111/jawr.1998.34.issue-1
[26]	宋玉鑫, 左其亭, 马军霞. 基于SWAT模型的开都河流域水文干旱变化特征及驱动因子分析[J]. 干旱区研究, 2021, 38(3): 610-617.
	[Song Yuxin, Zuo Qiting, Ma Junxia. Variation and dynamic drivers of drought in Kaidu River Basin based on the SWAT model[J]. Arid Zone Research, 2021, 38(3): 610-617.]
[27]	郭伟, 陈兴伟, 林炳青. SWAT模型参数对土地利用变化的响应及其对不同时间尺度径流模拟的影响[J]. 生态学报, 2021, 41(16): 6373-6383.
	[Guo Wei, Chen Xingwei, Lin Bingqing. Response of SWAT model parameters to land use change and its effects on the simulation of runoff with different time scales[J]. Acta Ecologica Sinica, 2021, 41(16): 6373-6383.]
[28]	Wang Z Y, Cao J S. Spatial-temporal pattern study on water conservation function using the SWAT model[J]. Water Supply, 2021, 21(7): 3629-3642. doi: 10.2166/ws.2021.127
[29]	祖拜代·木依布拉, 师庆东, 普拉提·莫合塔尔, 等. 基于SWAT模型的乌鲁木齐河上游土地利用和气候变化对径流的影响[J]. 生态学报, 2018, 38(14): 5149-5157.
	[Zubaidai Muyibul, Shi Qingdong, Pulati Muhtar, et al. Land use and climate change effects on runoff in the upper Urumqi River watershed: A SWAT model based analysis[J]. Acta Ecologica Sinica, 2018, 38(14): 5149-5157.]
[30]	王钰双, 陈芸芝, 卢文芳, 等. 闽江流域不同土地利用情景下的径流响应研究[J]. 水土保持学报, 2020, 34(6): 30-36.
	[Wang Yushuang, Chen Yunzhi, Lu Wenfang, et al. The hydrological response to different land use scenarios in the Minjiang River basin[J]. Journal of Soil and Water Conservation, 2020, 34(6): 30-36.]
[31]	邹凯波, 张玉虎, 刘晓伟, 等. 气候变化下乌伦古河流域农业面源污染负荷响应[J]. 干旱区研究, 2022, 39(2): 625-637.
	[Zou Kaibo, Zhang Yuhu, Liu Xiaowei, et al. Response of agricultural nonpoint source pollution load in the Ulungur River basin under climate change[J]. Arid Zone Research, 2022, 39(2): 625-637.]
[32]	田义超, 王世杰, 白晓永. 桐梓河流域径流对气候和人类活动的响应[J]. 水土保持研究, 2020, 27(3): 76-82.
	[Tian Yichao, Wang Shijie, Bai Xiaoyong. Response of runoff to climate and human activities in Tongzi Tiver Basin[J]. Research of Soil and Water Conservation, 2020, 27(3): 76-82.]
[33]	Yang L S, Feng Q, Yin Z L, et al. Identifying separate impacts of climate and land use/cover change on hydrological processes in upper stream of Heihe River, Northwest China[J]. Hydrological Process, 2017, 31(5): 1100-1112. doi: 10.1002/hyp.v31.5

数据名称	数据来源	数据描述
DEM	地理空间数据云（http://www.gscloud.cn）	数字高程模型，30 m×30 m
土地利用	资源环境科学与数据中心（https://www.resdc.cn）	1980年、2020年土地利用类型图，1000 m×1000 m
土壤数据	联合国粮食及农业组织（FAO）	土地利用空间分布数据，1:1 000 000
气象数据	中国气象数据网（http://data.cma.cn/）	1960—2019年祁连、门源、野牛沟、刚察、托勒气象站气温、降水、日照、风速、湿度观测数据，逐日
水文数据	青海省水文与水资源局	1960—2016年青石嘴水文站径流观测数据，逐日

情景	情景类别	气候数据时段	土地利用数据
S0	基础情景	1962—1980年	1980年
S1	气候变化情景	1981—2019年	1980年
S2	土地利用变化情景	1962—1980年	2020年
S3	协同变化情景	1981—2019年	2020年

时间段	观测平均值/（m³·s^-1)	模拟平均值/（m³·s^-1)	NS	R²	PBIAS/%
率定期	50.56	50.96	0.79	0.81	-0.8
验证期	59.33	49.97	0.75	0.81	15.8

海拔/m	降水/mm	潜在蒸散发/mm	实际蒸散发/mm	土壤含水量/mm	地表径流/mm	产流量/mm	干旱指数	蒸发系数
2884~3427	568.01	737.38	378.89	63.29	84.86	180.41	1.30	0.67
3427~3704	546.87	769.00	368.72	61.73	116.44	188.36	1.41	0.67
3704~3935	535.94	745.05	336.06	52.99	138.11	204.11	1.39	0.63
3935~4177	536.65	744.37	334.63	52.53	136.26	203.01	1.39	0.62
4177~5067	535.81	749.81	332.99	51.92	134.83	203.12	1.40	0.62

		2020年
		草地	耕地	居民区	林地	裸地	其他建设用地	湿地	水域	永久性冰川雪地	总计
1980年	草地	3701.71	4.5	1.62	66.3	52.4	38.92	49.52	64.57	0.07	3979.61
	耕地	0.7	8.87	0.07	0.45	-	-	-	0.07	-	10.16
	居民区	0.13	0.06	0.95	0.04	-	-	-	0.03	-	1.21
	林地	65.32	1.33	0.9	991.19	8.83	0.17	0.64	24.82	-	1093.2
	裸地	116.7	-	-	4.33	1228.33	3.29	9.57	1.67	0.37	1364.26
	其他建设用地	2.13	-	-	0.11	-	1.84	-	-	-	4.08
	湿地	60.55		0.01	0.54	15.84	0.92	1027.49	7.11	-	1112.46
	水域	22.8	0.07	-	5.63	1.48	1.61	6.7	254.88	0.03	293.2
	永久性冰川雪地	-	-	-	-	8.3	-	-	-	4.81	13.11
	总计	3970.04	14.83	3.55	1068.59	1315.18	46.75	1093.92	353.15	5.28	7871.29

Effects of climate and land use change on the spatial distribution of hydrological factors in the source region of Datong River

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子流域编码	实际蒸散发/mm	土壤含水量/mm	地表径流/mm	产水量/mm	草地转林地/km²	林地转草地/km²	裸地转草地/km²
4	26.93	11.89	-41.43	-27.81	0.00	0.00	14.61
6	24.04	11.30	-45.95	-28.59	0.00	0.00	2.53
7	38.39	19.11	-76.58	-48.23	0.00	0.00	6.37
36	68.87	5.31	7.78	9.62	0.17	0.24	0.00

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[9]	SONG Yuxin,ZUO Qiting,MA Junxia. Variation and dynamic drivers of drought in Kaidu River Basin based on the SWAT model [J]. Arid Zone Research, 2021, 38(3): 610-617.
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[12]	LI Zhe-hua, , LI Sheng-yu, LI Bing-wen, FAN Jing-long, JIANG Jin, LI Ya-ping , , SONG Chun-wu. Spatial Variation of Soil Chemical Properties of Longitudinal Dunes with Different Vegetation Coverage Levels [J]. Arid Zone Research, 2020, 37(1): 160-167.
[13]	YU Xiu-xiu, ZHANG Ming-jun, WANG Sheng-jie, QIU Xue, DU Ming-xia, ZHOU Sue, MENG Hong-fei. Contribution of Moisture Recycling to Precipitation in the Arid Region in Northwest China Based on LMDZ Model [J]. Arid Zone Research, 2019, 36(1): 29-43.
[14]	LUO Kai-sheng，TAO Fu-lu. Sensitivity of Runoff to LUCC and Climate Change in the Heihe River Basin [J]. , 2018, 35(4): 753-760.
[15]	LIANG Shu-Min, YU Zhi-Yuan. Global runoff field calculated by empirical runoff coefficient [J]. , 2018, 35(01): 1-11.