马莲河下游产水量时空演变特征

doi:10.13866/j.azr.2024.05.06

Abstract

Abstract:

This study examines water yield patterns in the lower reaches of the Malian River Basin, which are typical loess plateau gully areas in eastern Gansu Province, China. These areas are crucial for regional ecosystem health and understanding the temporal and spatial characteristics and response of water yield considering climate and land-use changes. Employing the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, we quantitatively assess the spatial and temporal patterns of water yields across four years: 1990, 2000, 2010, and 2020. Spatial heterogeneity in water yield across the lower reaches of the Malian River Basin was assessed using geographic detection techniques. Analysis revealed a fluctuating trend in total water yield from 1990 to 2020, characterized by an initial decrease, followed by an increase, and finally another decrease. Compared to 1990, total water yield in 2020 declined by 5.9×10⁷ m³ (25.43% reduction). Furthermore, spatial analysis revealed a distinct pattern in water yield distribution across the basin. Higher water yield was observed in the southern and marginal areas, whereas lower yield characterized the northern and central regions. Land-use type significantly influenced water yield capacity. Ranked from highest to lowest, the order was as follows: construction land>bare land>agricultural land>low-coverage grassland>high-coverage grassland>shrub land>forest land>open water. Moreover, a significant positive correlation was identified between water yield and precipitation, suggesting that precipitation plays a key role in water production. Conversely, a negative correlation emerged between actual evapotranspiration and altitude. Our analysis identified precipitation and actual evapotranspiration as the primary drivers of spatial variations and temporal changes in water yield, with q values ranging from 0.616 to 0.735 and 0.517 to 0.653, respectively. These findings provide valuable scientific evidence to support the development, utilization, and management of soil and water resources in the loess plateau of eastern Gansu.

Key words: InVEST model, water yield, spatiotemporal evolution, lower Malian River Basin

GAO Yayu, SONG Yu, ZHAO Tinghong, GAO Jinfang, HE Wenbo, LI Zexia. Spatiotemporal evolution of water yield in the lower Malian River Basin[J].Arid Zone Research, 2024, 41(5): 776-787.

Figures/Tables 13

Fig. 1

Tab. 1

Tab. 2

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Tab. 3

Fig. 6

Fig. 7

Fig. 8

Fig. 9

Tab. 4

References 33

[1]	Liu J, Li J, Qin K, et al. Changes in land-uses and ecosystem services under multi-scenarios simulation[J]. Science of the Total Environment, 2017, 586, 522-526.
[2]	Lang Y, Song W, Deng X. Projected land use changes impacts on water yields in the karst mountain areas of China[J]. Physics and Chemistry of the Earth, Parts A/B/C, 2018, 104: 66-75.
[3]	戴尔阜, 王晓莉, 朱建佳, 等. 生态系统服务权衡/协同研究进展与趋势展望[J]. 地球科学进展, 2015, 30(11): 1250-1259. doi: 10.11867/j.issn.1001-8166.2015.11.1250
	[Dai Erfu, Wang Xiaoli, Zhu Jianjia, et al. Progress and perspective on ecosystem services trade-offs[J]. Advances in Earth Science, 2015, 30(11): 1250-1259.] doi: 10.11867/j.issn.1001-8166.2015.11.1250
[4]	Wang Y, Ye A, Peng D, et al. Spatiotemporal variations in water conservation function of the Tibetan Plateau under climate change based on InVEST model[J]. Journal of Hydrology: Regional Studies, 2022, 41: 101064.
[5]	Sun S, Sun G, Cohen E, et al. Projecting water yield and ecosystem productivity across the United States by linking an ecohydrological model to WRF dynamically downscaled climate data[J]. Hydrology and Earth System Sciences, 2016, 20(2): 935-952.
[6]	孙琪, 徐长春, 任正良, 等. 塔里木河流域产水量时空分布及驱动因素分析[J]. 灌溉排水学报, 2021, 40(8): 114-122.
	[Sun Qi, Xu Changchun, Ren Zhengliang, et al. Spatiotemporal variation in water yield and their underlying mechanisms in Tarim River Basin[J]. Journal of Irrigation and Drainage, 2021, 40(8): 114-122.]
[7]	吴健, 李英花, 黄利亚, 等. 东北地区产水量时空分布格局及其驱动因素[J]. 生态学杂志, 2017, 36(11): 3216-3223.
	[Wu Jian, Li Yinghua, Huang Liya, et al. Spatiotemporal variation of water yield and its driving factors in Northeast China[J]. Chinese Journal of Ecology, 2017, 36(11): 3216-3223.]
[8]	Nahib I, Ambarwulan W, Rahadiati A, et al. Assessment of the impacts of climate and LULC changes on the water yield in the Citarum River Basin, West Java Province, Indonesia[J]. Sustainability, 2021, 13(7): 3919.
[9]	Pérez-Cutillas P, Banos Paez P, Banos-González I. Variability of water balance under climate change scenarios. Implications for sustainability in the Rhône River Basin[J]. Sustainability, 2020, 12(16): 6402.
[10]	Wang X, Liu G, Lin D, et al. Water yield service influence by climate and land use change based on InVEST model in the monsoon hilly watershed in South China[J]. Geomatics, Natural Hazards and Risk, 2022, 13(1): 2024-2048.
[11]	赵美亮, 曹广超, 赵青林, 等. 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[J]. 干旱区研究, 2023, 40(3): 381-391.
	[Zhao Meiliang, Cao Guangchao, Zhao Qinglin, et al. 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.]
[12]	刘斯文, 刘海隆, 王玲. MIKE SHE模型的发展与应用研究[J]. 水文, 2018, 38(5): 23-28.
	[Liu Siwen, Liu Hailong, Wang Ling. Development and application of MIKE SHE model[J]. Journal of China Hydrology, 2018, 38(5): 23-28.]
[13]	Zhou S, Wang Y, Guo A, et al. Impacts of changes in the watershed partitioning level and optimization algorithm on runoff simulation: Decomposition of uncertainties[J]. Stochastic Environmental Research and Risk Assessment, 2020, 34: 1909-1923.
[14]	雷馨, 海新权. 祁连山地区土地利用变化对碳储量的影响及经济价值估算[J]. 干旱区研究, 2023, 40(11): 1845-1854.
	[Lei Xin, Hai Xinquan. Impacts of land use change on carbon storage and estimation of economic value in Qilian Mountain region[J]. Arid Zone Research, 2023, 40(11): 1845-1854.]
[15]	Redhead J W, Stratford C, Sharps K, et al. Empirical validation of the InVEST water yield ecosystem service model at a national scale[J]. Science of the Total Environment, 2016, 569: 1418-1426.
[16]	Belete M, Deng J, Wang K, et al. Evaluation of satellite rainfall products for modeling water yield over the source region of Blue Nile Basin[J]. Science of the Total Environment, 2020, 708: 134834.
[17]	Wang Y, Wang H, Zhang J, et al. Exploring interactions in water-related ecosystem services nexus in Loess Plateau[J]. Journal of Environmental Management, 2023, 336: 117550.
[18]	包玉斌, 李婷, 柳辉, 等. 基于InVEST模型的陕北黄土高原水源涵养功能时空变化[J]. 地理研究, 2016, 35(4): 664-676. doi: 10.11821/dlyj201604006
	[Bao Yubin, Li Ting, Liu Hui, et al. Spatial and temporal changes of water conservation of Loess Plateau in northern Shaanxi Province by InVEST model[J]. Geographical Research, 2016, 35(4): 664-676.] doi: 10.11821/dlyj201604006
[19]	刘宥延, 刘兴元, 张博, 等. 基于InVEST模型的黄土高原丘陵区水源涵养功能空间特征分析[J]. 生态学报, 2020, 40(17): 6161-6170.
	[Liu Youyan, Liu Xingyuan, Zhang Bo, et al. Spatial features analysis of water conservation function in the hilly areas of the Loess Plateau based on InVEST model[J]. Acta Ecologica Sinica, 2020, 40(17): 6161-6170.]
[20]	王雨山, 程旭学, 张梦南. 马莲河流域河水化学特征和化学风化过程分析[J]. 地球与环境, 2018, 46(1): 15-22.
	[Wang Yushan, Cheng Xuxue, Zhang Mengnan. Hydrochemistry and chemical weathering processes of Malian River Basin[J]. Earth and Environment, 2018, 46(1): 15-22.]
[21]	彭世想, 郭相秦, 刘卓, 等. 马莲河流域水沙变化与水土保持成效分析[J]. 中国水土保持, 2020 (11): 29-31, 48.
	[Peng Shixiang, Guo Xiangqin, Liu Zuo, et al. Analysis on water and sediment change and soil and water conservation effect in Malian River Watershed[J]. Soil and Water Conservation in China, 2020(11): 29-31, 48.]
[22]	龚诗涵, 肖洋, 郑华, 等. 中国生态系统水源涵养空间特征及其影响因素[J]. 生态学报, 2017, 37(7): 2455-2462.
	[Gong Shihan, Xiao Yang, Zheng Hua, et al. Spatial patterns of ecosystem water conservation in China and its impact factors analysis[J]. Acta Ecologica Sinica, 2017, 37(7): 2455-2462.]
[23]	Hu W, Li G, Li Z. Spatial and temporal evolution characteristics of the water conservation function and its driving factors in regional lake wetlands—Two types of homogeneous lakes as examples[J]. Ecological Indicators, 2021, 130: 108069.
[24]	Yan F, Shangguan W, Zhang J, et al. Depth-to-bedrock map of China at a spatial resolution of 100 meters[J]. Scientific Data, 2020, 7(1): 2.
[25]	周文佐. 基于GIS的我国主要土壤类型土壤有效含水量研究[D]. 南京: 南京农业大学, 2003.
	[Zhou Wenzuo. A Study on Available Water Capacity of Main Soil Types in China Based on Geographic Information System[D]. Nanjing: Nanjing Agricultural University, 2003.]
[26]	王劲峰, 徐成东. 地理探测器: 原理与展望[J]. 地理学报, 2017, 72(1): 116-134. doi: 10.11821/dlxb201701010
	[Wang Jinfeng, Xu Chengdong. Geodetector: Principle and prospective[J]. Acta Geographica Sinica, 2017, 72(1): 116-134.] doi: 10.11821/dlxb201701010
[27]	Moriasi D N, Gitau M W, Pai N, et al. Hydrologic and water quality models: Performance measures and evaluation criteria[J]. Transactions of the ASABE, 2015, 58(6): 1763-1785.
[28]	郑续, 魏乐民, 郭建军, 等. 基于地理探测器的干旱区内陆河流域产水量驱动力分析——以疏勒河流域为例[J]. 干旱区地理, 2020, 43(6): 1477-1485.
	[Zheng Xu, Wei Lemin, Guo Jianjun, et al. Driving force analysis of water yield in inland river basins of arid areas based on geo-detectors: A case of the Shule River[J]. Arid Land Geography, 2020, 43(6): 1477-1485.]
[29]	郭倩. 全球气候变化背景下土地利用和流域水生态系统响应研究[D]. 兰州: 兰州大学, 2022.
	[Guo Qian. The Responses of Land Use and Watershed Water-related Ecosystem under Global Climate Change[D]. Lanzhou: Lanzhou University, 2022.]
[30]	杨洁, 谢保鹏, 张德罡. 基于InVEST模型的黄河流域产水量时空变化及其对降水和土地利用变化的响应[J]. 应用生态学报, 2020, 31(8): 2731-2739. doi: 10.13287/j.1001-9332.202008.015
	[Yang Jie, Xie Baopeng, Zhang Degang. Spatio-temporal variation of water yield and its response to precipitation and land use change in the Yellow River Basin based on InVEST model[J]. Chinese Journal of Applied Ecology, 2020, 31(8): 2731-2739.] doi: 10.13287/j.1001-9332.202008.015
[31]	赖明, 陈仁升, 刘玖芬, 等. 雅鲁藏布江下游产水量时空演变及对气候和土地利用变化的响应[J]. 草业科学, 2022, 39(12): 2516-2526.
	[Lai Ming, Chen Rensheng, Liu Jiufen, et al. Temporal and spatial evolution of water yield in the lower reaches of the Yarlung Zangbo River and its response to climate and land use change[J]. Pratacultural Science, 2022, 39(12): 2516-2526.]
[32]	刘美娟, 仲俊涛, 王蓓, 等. 基于InVEST模型的青海湖流域产水功能时空变化及驱动因素分析[J]. 地理科学, 2023, 43(3): 411-422. doi: 10.13249/j.cnki.sgs.2023.03.004
	[Liu Meijuan, Zhong Juntao, Wang Bei, et al. Spatiotemporal change and driving factor analysis of the Qinghai Lake Basin based on InVEST model[J]. Scientia Geographica Sinica, 2023, 43(3): 411-422.] doi: 10.13249/j.cnki.sgs.2023.03.004
[33]	董玉婷, 穆兴民, 王双银, 等. 产流及其研究进展[J]. 华北水利水电大学学报(自然科学版), 2022, 43(2): 21-29.
	[Dong Yuting, Mu Xingmin, Wang Shuangyin, et al. Runoft ceneration and its research progress[J]. Journal of North China University of Water Resources and Electric Power (Natural Science Edition), 2022, 43(2): 21-29.]

土地利用编号	土地利用类型	植被蒸散系数	植物最大根系深度/mm	属性类别
1	耕地	0.65	400	1
2	有林地	0.95	3000	1
3	灌木林	0.9	2500	1
4	高覆盖度草地	0.65	500	1
5	低覆盖度草地	0.6	450	1
6	水域	0.9	1	0
7	城镇用地	0.3	1	0
8	未利用地	0.5	100	0

	年份
	1990年	2000年	2010年	2020年
实测径流量/mm	42.71	25.68	36.01	31.76
模拟产水量/mm	43.29	26.66	37.52	32.31

土地利用类型	1990—2000年		2000—2010年		2010—2020年		1990—2020年
土地利用类型	面积变化/km²	变化率/%	面积变化/km²	变化率/%	面积变化/km²	变化率/%	面积变化/km²	变化率/%
耕地	-10.39	-0.53	-226.47	-11.65	-32.5	-1.89	-269.36	-13.79
有林地	1.07	0.23	17.14	3.72	-0.39	-0.08	17.82	3.88
灌木林	0.16	0.02	4.87	0.63	1.68	0.22	6.71	0.87
高覆盖度草地	0.12	0.04	137.95	51.27	-85.56	-21.02	52.51	19.52
低覆盖度草地	-0.06	0.01	31.08	1.74	92.39	5.09	123.41	6.91
水域	-0.89	-7.21	-0.9	-7.86	0.12	1.14	-1.67	-13.53
城镇用地	9.16	9.02	33.93	30.64	19.29	13.33	62.38	61.41
未利用地	0.78	0.39	0.4	0.14	0.93	0.29	2.11	1.07

年份	降水	实际蒸散发	海拔	土地利用类型
1990年	0.616	0.517	0.344	0.196
2000年	0.722	0.653	0.370	0.135
2010年	0.714	0.618	0.367	0.135
2020年	0.735	0.625	0.376	0.114

Spatiotemporal evolution of water yield in the lower Malian River Basin

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 13

References 33

Related Articles 15

Metrics

Comments

Recommended 0

[1]	WU Zhaoqiao, LIN Fei, NIU Junjie, GENG Tianwei. Response of ecosystem service to land use pattern change in the Shanxi central urban agglomeration [J]. Arid Zone Research, 2024, 41(7): 1153-1166.
[2]	LI Bingjie, FAN Zhitao, QU Zhicheng, YAO Shunyu, SU Xiashu, LIU Dongwei, WANG Lixin. Evaluation and prediction of ecosystem carbon storage in the Inner Mongolia section of the Yellow River Basin based on the InVEST-PLUS model [J]. Arid Zone Research, 2024, 41(7): 1217-1227.
[3]	ZHANG Shunxin, WU Zihao, YAN Qingwu, LI Gui’e, MU Shouguo. Spatiotemporal changes in the ecosystem carbon storage on the northern slope of the Tianshan Mountains and simulations based on the PLUS-InVEST model [J]. Arid Zone Research, 2024, 41(7): 1228-1237.
[4]	JIAN Zhengbo, LUO Hao, SHAN Nana. A study on the spatial and temporal evolution and carbon effects of production-living-ecological in Xinjiang under carbon peak and carbon neutrality goals [J]. Arid Zone Research, 2024, 41(7): 1238-1248.
[5]	LIU Rulong, ZHAO Yuanyuan, CHEN Guoqing, CHI Wenfeng, LIU Zhengjia. Assessment of habitat quality in the Yellow River Basin in Inner Mongolia from 1990 to 2020 [J]. Arid Zone Research, 2024, 41(4): 674-683.
[6]	LI Jiake, SHAO Zhanlin. Spatiotemporal evolution and prediction of carbon stock in Urumqi City based on PLUS and InVEST models [J]. Arid Zone Research, 2024, 41(3): 499-508.
[7]	YAO Junqiang. Change in atmospheric and surface water resource in Xinjiang [J]. Arid Zone Research, 2024, 41(2): 181-190.
[8]	YAN Li, CAO Guangchao, KANG Ligang, LIU Menglin, YE Deli. Analysis of spatial and temporal changes in habitat quality and driving factors in Gonghe County using the InVEST model [J]. Arid Zone Research, 2024, 41(2): 314-325.
[9]	SHEN Cao,REN Zongping,LI Peng,WANG Kaibo,LU Kexin,REN Zhengyan,WEI Xiaoyan. Identification of priority areas for ecological compensation under soil and water conservation in Ningxia [J]. Arid Zone Research, 2023, 40(9): 1527-1536.
[10]	ZHANG Xiaomin, ZHANG Dongmei, ZHANG Wei. Effects of human activities on carbon storage in the Irtysh River Basin [J]. Arid Zone Research, 2023, 40(8): 1333-1345.
[11]	BAO Yubin,WANG Yaozong,LU Feng,LIU Zizeng,MA Dawei,YANG Yong,WU Juan,ZHANG Yongkang. Construction of an ecological security pattern and zoning optimization for territorial space in the Liupan Mountain Area [J]. Arid Zone Research, 2023, 40(7): 1172-1183.
[12]	WANG Peng, QIN Sitong, HU Huirong. Spatial-temporal evolution characteristics of land use change and habitat quality in the Lhasa River Basin over the past three decades [J]. Arid Zone Research, 2023, 40(3): 492-503.
[13]	CHEN Shi, HUANG Yinlan, JIN Yunxiang. Spatiotemporal changes of habitat quality before and after the implementation of Grain for Green Project in the middle reaches of the Yellow River [J]. Arid Zone Research, 2023, 40(3): 456-468.
[14]	LEI Xin, HAI Xinquan. Impacts of land use change on carbon storage and estimation of economic value in Qilian Mountain region [J]. Arid Zone Research, 2023, 40(11): 1845-1854.
[15]	JI Qianqian, PAN Huanhuan, WU Shurong, WU Zhitao, DU Ziqiang. Effect of spatial reconstruction of “production-living-ecology” space and precipitation changes on water yield services in the Yellow River Basin in Shanxi Province [J]. Arid Zone Research, 2023, 40(1): 132-142.