Application of the InVEST model for assessing water yield and its response to precipitation and land use in the Weihe River Basin, China

doi:10.1007/s40333-022-0013-0

Journal of Arid Land

2022, Vol. 14

Issue (4): 426-440 DOI: 10.1007/s40333-022-0013-0 CSTR: 32276.14.s40333-022-0013-0

Research article

Application of the InVEST model for assessing water yield and its response to precipitation and land use in the Weihe River Basin, China

WU Changxue¹, QIU Dexun²^,³, GAO Peng¹^,²^,³^,^*(

), MU Xingmin¹^,²^,³^,^*(

), ZHAO Guangju¹^,²^,³

¹State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, China
²State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, China
³University of Chinese Academy of Sciences, Beijing 100000, China

Download:

HTML

PDF(2044KB)
Export: BibTeX | EndNote (RIS)

Abstract

With realizing the importance of ecosystem services to society, the efforts to evaluate the ecosystem services have increased. As the largest tributary of the Yellow River, the Weihe River has been endowed with many ecological service functions. Among which, water yield can be a measure of local availability of water and an index for evaluating the conservation function of the region. This study aimed to explore the temporal and spatial variation of water yield and its influencing factors in the Weihe River Basin (WRB), and provide basis for formulating reasonable water resources utilization schemes. Based on the InVEST (integrated valuation of ecosystem services and tradeoffs) model, this study simulated the water yield in the WRB from 1985 to 2019, and discussed the impacts of climatic factors and land use change on water yield by spatial autocorrelation analysis and scenario analysis methods. The results showed that there was a slight increasing trend in water yield in the WRB over the study period with the increasing rate of 4.84 mm/10a and an average depth of 83.14 mm. The main water-producing areas were concentrated along the mainstream of the Weihe River and in the southern basin. Changes in water yield were comprehensively affected by climate and underlying surface factors. Precipitation was the main factor affecting water yield, which was consistent with water yield in time. And there existed significant spatial agglomeration between water yield and precipitation. Land use had little impact on the amount of water yield, but had an impact on its spatial distribution. Water yield was higher in areas with wide distribution of construction land and grassland. Water yield of different land use types were different. Unused land showed the largest water yield capacity, whereas grassland and farmland contributed most to the total water yield. The increasing water yield in the basin indicates an enhanced water supply service function of the ecosystem. These results are of great significance to the water resources management of the WRB.

Key words： water yield InVEST model Weihe River Basin Geoda model scenario analysis

Received: 06 February 2022 Published: 30 April 2022

Corresponding Authors: *GAO Peng (E-mail: gaopeng@ms.iswc.ac.cn);MU Xingmin (E-mail: xmmu@ms.iswc.ac.cn)

	Service
	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	WU Changxue
	QIU Dexun
	GAO Peng
	MU Xingmin
	ZHAO Guangju

Cite this article:

WU Changxue, QIU Dexun, GAO Peng, MU Xingmin, ZHAO Guangju. Application of the InVEST model for assessing water yield and its response to precipitation and land use in the Weihe River Basin, China. Journal of Arid Land, 2022, 14(4): 426-440.

URL:

http://jal.xjegi.com/10.1007/s40333-022-0013-0 OR http://jal.xjegi.com/Y2022/V14/I4/426

Fig. 1 Elevation, and hydrological and meteorological stations in the Weihe River Basin, China

Table 1 Relevant basic data sources and description

Fig. 2 Spatial distributions of biophysical characteristics of the Weihe River Basin, China. (a), PAWC, plant available water capacity; (b), soil depth; (c), land use/land cover (LULC) in 2020.

Table 2 Biophysical table for the InVEST model

Fig. 3 Annual precipitation, actual evapotranspiration (AET), potential evapotranspiration (PET) and water yield of the Weihe River Basin, China during 1985-2019

Fig. 4 Spatial distribution of water yield in the Weihe River Basin, China. (a), 1985; (b), 2005; (c), 2015; (d), average.

Table 3 P and LULC under different scenarios

Fig. 5 Spatial distributions of annual precipitation (P, a-c) and water yield (d-f) in the Weihe River Basin, China under scenario 1

Fig. 6 Spatial distribution of the relationship between annual precipitation and water yield in the Weihe River Basin, China in 1997 (a), 2003 (b) and 2007 (c)

Fig. 7 Spatial distributions of LULC (land use/land cover) types (a-c) and water yield (d-f) in the Weihe River Basin, China under scenario 2

Fig. 8 Water yield of different LULC (land use/land cover) types in the Weihe River Basin, China

Table 4 Changes of LULC (land use/land cover) types of the Weihe River Basin, China from 1990 to 2020


[1]	Allen R G, Prtrits L D, Raes D, et al. 2006. Crop evapotranspiration-guidelines for computing crop water requirements. Fao Irrigation & Drainage Paper No. 56. FAO, Rome, Italy.

[2]	Anache J A A, Flanagan D C, Srivastava A, et al. 2017. Land use and climate change impacts on runoff and soil erosion at the hillslope scale in the Brazilian Cerrado. Science of the Total Environment, 622-623: 140-151. doi: 10.1016/j.scitotenv.2017.11.257

[3]	Baker T J, Miller S N. 2013. Using the soil and water assessment tool (SWAT) to assess land use impact on water resources in an East African watershed. Journal of Hydrology, 486: 100-111. doi: 10.1016/j.jhydrol.2013.01.041

[4]	Boumans R, Costanza R. 2008. The multiscale integrated Earth systems model (MIMES): The dynamics, modeling and valuation of ecosystem services. Issues in Global Water System Research, 2(2): 30-41.

[5]	Budyko M I. 1974. Climate and Life. Academic Press: San Diego, 508

[6]	Cara A, Slhb A, Capm . 2020. Modeling interactions among multiple ecosystem services. A critical review. Ecological Modelling, 429: 109103, doi: 10.1016/j.ecolmodel.2020.109103. doi: 10.1016/j.ecolmodel.2020.109103

[7]	Chen Z S, Chen Y N, Li B F. 2013. Quantifying the effects of climate variability and human activities on runoff for Kaidu River Basin in arid region of northwest China. Theoretical and Applied Climatology, 111(3-4): 537-545. doi: 10.1007/s00704-012-0680-4

[8]	Cheng B, Li H E, Yue S Y, et al. 2019. A conceptual decision-making for the ecological base flow of rivers considering the economic value of ecosystem services of rivers in water shortage area of Northwest China. Journal of Hydrology, 578: 124126, doi: 10.1016/j.jhydrol.2019.124126. doi: 10.1016/j.jhydrol.2019.124126

[9]	Cheng B, Li H. 2020. Impact of climate change and human activities on economic values produced by ecosystem service functions of rivers in water shortage area of Northwest China. Environmental Science and Pollution Research, 27(21): 26570-26578. doi: 10.1007/s11356-020-08963-2

[10]	Costanza R, Arge R, Groot R, et al. 1998. The value of the world's ecosystem services and natural capital. Ecological Economics, 25(1): 3-15. doi: 10.1016/S0921-8009(98)00020-2

[11]	Daneshi A, Brouwer R, Najafinejad A, et al. 2021. Modelling the impacts of climate and land use change on water security in a semi-arid forested watershed using InVEST. Journal of Hydrology, 593: 125621, doi: 10.1016/j.jhydrol.2020.125621. doi: 10.1016/j.jhydrol.2020.125621

[12]	Dennedy-Frank P J, Muenich R L, Chaubey I, et al. 2016. Comparing two tools for ecosystem service assessments regarding water resources decisions. Journal of Environmental Management, 177: 331-340. doi: 10.1016/j.jenvman.2016.03.012 pmid: 27111651

[13]	Donohue R J, Roderick M L, McVicar T R. 2012. Roots, storms and soil pores: Incorporating key ecohydrological processes into Budyko's hydrological model. Journal of Hydrology, 436-437: 35-50. doi: 10.1016/j.jhydrol.2012.02.033

[14]	Droogers P, Allen R G. 2002. Estimating reference evapotranspiration under inaccurate data conditions. Irrigation and Drainage Systems, 16(1): 33-45. doi: 10.1023/A:1015508322413

[15]	Ercin A E, Hoekstra A Y. 2014. Water footprint scenarios for 2050: A global analysis. Environment International, 65(1): 71-82.

[16]	Fu B P. 1981. On the calculation of the evaporation from land surface. Scientia Atmospherica Sinica, 5(1): 23-31. (in Chinese)

[17]	Gassman P W, Reyes M R, Green C H, et al. 2007. The soil and water assessment tool: Historical development, applications, and future research directions. Transactions of the Asabe, 50(4): 1211-1250. doi: 10.13031/2013.23637

[18]	Goldewijk K K, Ramankutty N. 2004. Land cover change over the last three centuries due to human activities: The availability of new global data sets. Geojournal, 61(4): 335-344. doi: 10.1007/s10708-004-5050-z

[19]	Gómez C M, Pérez-Blanco C D, Batalla R J. 2014. Tradeoffs in river restoration: Flushing flows vs. hydropower generation in the Lower Ebro River, Spain. Journal of Hydrology, 518: 130-139. doi: 10.1016/j.jhydrol.2013.08.029

[20]	Gusev E M, Nasonova O N, Kovalev E E, et al. 2019. Impact of possible climate change on extreme annual runoff from river basins located in different regions of the globe. Water Resources, 46: S126-S136.

[21]	Harries K. 2006. Extreme spatial variations in crime density in Baltimore County, MD. Geoforum, 37(3): 404-416. doi: 10.1016/j.geoforum.2005.09.004

[22]	Hassan R, Scholes R, Ash N. 2005. Ecosystems and human well-being: Current state and trends. Journal of Bacteriology, 1(5): 1387-1404.

[23]	He J, Shi X Y, Fu Y J. 2021. Identifying vegetation restoration effectiveness and driving factors on different micro-topographic types of hilly Loess Plateau: From the perspective of ecological resilience. Journal of Environmental Management, 289: 112562, doi: 10.1016/j.jenvman.2021.112562. doi: 10.1016/j.jenvman.2021.112562

[24]	Huang C H, Yang J, Zhang W J. 2013. Development of ecosystem services evaluation models: Research progress. Chinese Journal of Ecology, 32(12): 3360-3367. (in Chinese)

[25]	Jia X, Fu B, Feng X, et al. 2014. The tradeoff and synergy between ecosystem services in the Grain-for-Green areas in northern Shaanxi, China. Ecological Indicators, 43(1): 103-113. doi: 10.1016/j.ecolind.2014.02.028

[26]	Jiang C, Li D Q, Wang D W, et al. 2016. Quantification and assessment of changes in ecosystem service in the Three-River Headwaters Region, China as a result of climate variability and land cover change. Ecological Indicators, 199-211.

[27]	Jiang H Q, Wu W J, Wang J N, et al. 2021. Mapping global value of terrestrial ecosystem services by countries. Ecosystem Services, 52: 101361, doi: 10.1016/j.ecoser.2021.101361. doi: 10.1016/j.ecoser.2021.101361

[28]	Kendall M G. 1975. Rank correlation methods. Charles Griffin: London. British Journal of Psychology, 25(1): 86-91.

[29]	Kim S W, Jung Y Y. 2020. Application of the InVEST model to quantify the water yield of North Korean forests. Forests, 11(8): 804. doi: 10.3390/f11080804

[30]	Lambin E F, Geist H J, Lepers E. 2003. Dynamics of land-use and land-cover change in tropical regions. Annual Review of Environment and Resources, 28(1): 205-241. doi: 10.1146/annurev.energy.28.050302.105459

[31]	Lang Y, Song W, Zhang Y. 2017. Responses of the water-yield ecosystem service to climate and land use change in Sancha River Basin, China. Physics and Chemistry of the Earth, Parts A/B/C: 102-111.

[32]	Lewis C S, Allen L N. 2017. Potential crop evapotranspiration and surface evaporation estimates via a gridded weather forcing dataset. Journal of Hydrology, 546: 450-463. doi: 10.1016/j.jhydrol.2016.11.055

[33]	Li M Y, Liang D, Xia J, et al. 2021. Evaluation of water conservation function of Danjiang River Basin in Qinling Mountains, China based on InVEST model. Journal of Environmental Management, 286: 112212, doi: 10.1016/j.jenvman.2021.112212. doi: 10.1016/j.jenvman.2021.112212

[34]	Li X Y, Guo J M, Qi S Z. 2021. Forestland landscape change induced spatiotemporal dynamics of subtropical urban forest ecosystem services value in forested region of China: A case of Hangzhou City. Environmental Research, 193: 110618, doi: 10.1016/j.envres.2021.110926. doi: 10.1016/j.envres.2021.110926

[35]	Li Y Y, Yao S B, Deng Y J, et al. 2020. Spatio-temporal study on supply and demand matching of ecosystem water yield service-a case study of Wei River Basin. Polish Journal of Environmental Studies, 30(2): 1677-1693. doi: 10.15244/pjoes/126711

[36]	Liu J, Wu Y. 2012. Water sustainability for China and beyond. Science, 337(6095): 649-650. doi: 10.1126/science.1219471

[37]	Liu J X, Li Z G, Zhang X P, et al. 2013. Responses of vegetation cover to the Grain for Green program and their driving forces in the He-Long region of the middle reaches of the Yellow River. Journal of Arid Land, 5(4): 511-520. doi: 10.1007/s40333-013-0177-8

[38]	Liu Y, Hu A M. 2008. Study on spatial differentiation characteristics of water resources supply-demand and balance in Weihe Basin. Journal of Arid Land Resources and Environment, 22(3): 81-85.

[39]	Ma Z M, Kang S Z, Zhang L, et al. 2008. Analysis of impacts of climate variability and human activity on streamflow for a river basin in arid region of northwest China. Journal of Hydrology, 352(3-4): 239-249. doi: 10.1016/j.jhydrol.2007.12.022

[40]	Mann H B. 1945. Nonparametric test against trend. Econometrica, 13(3): 245-259. doi: 10.2307/1907187

[41]	Maurya S, Srivastava P K, Gupta M, et al. 2016. Integrating soil hydraulic parameter and micro wave precipitation with morphometric analysis for watershed prioritization. Water Resources Management, 30(14): 5385-5405. doi: 10.1007/s11269-016-1494-4

[42]	Mekonnen M M, Hoekstra A Y. 2016. Four billion people facing severe water scarcity. Science Advances, 2(2): e1500323, doi: 10.1126/sciadv.1500323. doi: 10.1126/sciadv.1500323

[43]	Milliman J D, Farnsworth K L, Jones P D, et al. 2008. Climatic and anthropogenic factors affecting river discharge to the global ocean, 1951-2000. Global and Planetary Change, 62(3-4): 187-194. doi: 10.1016/j.gloplacha.2008.03.001

[44]	Moran P A P. 1950. Notes on continuous stochastic phenomena. Biometrika, 37(1-2): 17-23. doi: 10.1093/biomet/37.1-2.17

[45]	Mu X M, Zhang L, McVicar T R, et al. 2007. Analysis of the impact of conservation measures on stream flow regime in catchments of the Loess Plateau, China. Hydrological Processes, 21(16): 2124-2134. doi: 10.1002/hyp.6391

[46]	Natalia P, Silvia F, Laura B, et al. 2015. Getting water right: A case study in water yield modelling based on precipitation data. Science of the Total Environment, 537: 225-234. doi: 10.1016/j.scitotenv.2015.07.148

[47]	Nie W, Yuan Y, Kepner W, et al. 2011. Assessing impacts of land use and land cover changes on hydrology for the upper San Pedro watershed. Journal of Hydrology, 407(1-4): 105-114. doi: 10.1016/j.jhydrol.2011.07.012

[48]	Qiang Z, Xu C Y, Tao Y. 2009. Scaling properties of the runoff variations in the arid and semi-arid regions of China: A case study of the Yellow River basin. Stochastic Environmental Research & Risk Assessment, 23(8): 1103-1111.

[49]	Qiu J. 2010. China faces up to groundwater crisis. Nature, 466(7304): 308-308. doi: 10.1038/466308a

[50]	Rientjes T, Perera B, Haile A T, et al. 2011. Regionalisation for lake level simulation-the case of Lake Tana in the upper Blue Nile, Ethiopia. Hydrology and Earth System Sciences Discussions, 15(14): 1167-1183.

[51]	Scordo F, Lavender T M, Seitz C, et al. 2018. Modeling water yield: Assessing the role of site and region-specific attributes in determining model performance of the InVEST seasonal water yield model. Water, 10(11): 1496, doi: 10.3390/w10111496. doi: 10.3390/w10111496

[52]	Sharp R, Douglass J, Wolny S, et al. 2020. InVEST 3.9.0 User's Guide. The Natural Capital Project, Stanford University, University of Minnesota, the Nature Conservancy and World Wildlife Fund.

[53]	Sheng Y, Paul P. 2004. A comparison of the power of the t test, Mann-Kendall and bootstrap tests for trend detection: Detecting change in hydrological data. International Association of Scientific Hydrology Bulletin, 49(1): 21-37.

[54]	Sherrouse B C, Clement J M, Semmens D J. 2011. A GIS application for assessing, mapping, and quantifying the social values of ecosystem services. Applied Geography, 31(2): 748-760. doi: 10.1016/j.apgeog.2010.08.002

[55]	Sterling S M, Ducharne A, Polcher J. 2013. The impact of global land-cover change on the terrestrial water cycle. Nature Climate Change, 3(4): 385-390. doi: 10.1038/nclimate1690

[56]	Symmank L, Natho S, Scholz M, et al. 2020. The impact of bioengineering techniques for riverbank protection on ecosystem services of riparian zones. Ecological Engineering, 158: 106040, doi: 10.1016/j.ecoleng.2020.106040. doi: 10.1016/j.ecoleng.2020.106040

[57]	Tepanosyan G, Sahakyan L, Zhang C S, et al. 2019. The application of local Moran's I to identify spatial clusters and hot spots of Pb, Mo and Ti in urban soils of Yerevan. Applied Geochemistry, 104: 116-123. doi: 10.1016/j.apgeochem.2019.03.022

[58]	Tu J, Xia Z G. 2008. Examining spatially varying relationships between land use and water quality using geographically weighted regression I: Model design and evaluation. Science of the Total Environment, 407(1): 358-378. doi: 10.1016/j.scitotenv.2008.09.031

[59]	Vorosmarty C J, Green P, Salisbury J, et al. 2000. Global water resources: Vulnerability from climate change and population growth. Science, 289(5477): 284-288. doi: 10.1126/science.289.5477.284

[60]	Vose J M, Sun G, Ford C R, et al. 2011. Forest ecohydrological research in the 21^st century: What are the critical needs? Ecohydrology, 4(2): 146-158. doi: 10.1002/eco.193

[61]	Wang B, Gao P, Niu X, et al. 2017. Policy-driven China's Grain to Green program: Implications for ecosystem services. Ecosystem Services, 27: 38-47. doi: 10.1016/j.ecoser.2017.07.014

[62]	Wu N, Song X Y, Kang W H, et al. 2018. Standard of payment for ecosystem services in a watershed based on InVEST model under different standpoints: A case study of the Weihe River in Gansu Province. Acta Ecologica Sinica, 38(7): 2512-2522. (in Chinese)

[63]	Xia J, Qiao Y F, Song X F, et al. 2007. Analysis about effect rules of underlying surface change to the relationship between rainfall and runoff in the Chabagou Catchment. Resources Science, 29(1): 70-76. (in Chinese)

[64]	Xu K, Milliman J D, Hui X. 2010. Temporal trend of precipitation and runoff in major Chinese rivers since 1951. Global and Planetary Change, 73(3-4): 219-232. doi: 10.1016/j.gloplacha.2010.07.002

[65]	Xu Y X, Zhu G F, Wan Q Z, et al. 2021. Effect of terrace construction on soil moisture in rain-fed farming area of Loess Plateau. Journal of Hydrology: Regional Studies, 37: 100889, doi: 10.1016/j.ejrh.2021.100889. doi: 10.1016/j.ejrh.2021.100889

[66]	Yang D, Liu W, Tang L, et al. 2019. Estimation of water provision service for monsoon catchments of South China: Applicability of the InVEST model. Landscape and Urban Planning, 182: 133-143. doi: 10.1016/j.landurbplan.2018.10.011

[67]	Yang H B, Yang D W, Lei Z D, et al. 2008. New analytical derivation of the mean annual water-energy balance equation. Water Resources Research, 44(3): 893-897.

[68]	Yang J, Xie B P, Zhang D G. 2020. Spatio-temporal variation of water yield and its response to precipitation and land use change in the Yellow River Basin based on InVEST model. Chinese Journal of Applied Ecology, 31(8): 2731-2739. (in Chinese) doi: 10.13287/j.1001-9332.202008.015 pmid: 34494796

[69]	Yang X, Chen R S, Meadows M E, et al. 2020. Modelling water yield with the InVEST model in a data scarce region of northwest China. Water Supply, 20(3): 1035-1045. doi: 10.2166/ws.2020.026

[70]	Yin G D, Wang X, Zhang X, et al. 2020. InVEST model-based estimation of water yield in North China and its sensitivities to climate variables. Water, 12(6): 1692, doi: 10.3390/w12061692. doi: 10.3390/w12061692

[71]	Yue S Y, Li H E, Zhao L. 2021. Impact of climate and land use changes on water scarcity in the Wei River Basin. Research of Soil and Water Conservation, 28(5): 95-101. (in Chinese)

[72]	Zhang H, Huang Q, Zhang Q, et al. 2016. Changes in the long-term hydrological regimes and the impacts of human activities in the main Wei River, China. Hydrological Sciences Journal, 61(6): 1054-1068. doi: 10.1080/02626667.2015.1027708

[73]	Zhang L, Hickel K, Dawes W R, et al. 2004. A rational function approach for estimating mean annual evapotranspiration. Water Resources Research, 40(2): W02502, doi: 10.1029/2003WR002710. doi: 10.1029/2003WR002710

[74]	Zhao Y, Hu C H, Zhang X M, et al. 2018. Analysis on runoff and sediment regimes and its causes of the Yellow River in recent 70 years. Transactions of the Chinese Society of Agricultural Engineering, 34(21): 112-119. (in Chinese)

[75]	Zhou W, Liu G, Pan J, et al. 2005. Distribution of available soil water capacity in China. Journal of Geographical Sciences, 15(1): 3-12. doi: 10.1007/BF02873101

[1]	ZHENG Guoqiang, Li Cunxiu, LI Runjie, LUO Jing, FAN Chunxia, ZHU Hailing. Spatio-temporal evolution analysis of landscape pattern and habitat quality in the Qinghai Province section of the Yellow River Basin from 2000 to 2022 based on InVEST model[J]. Journal of Arid Land, 2024, 16(9): 1183-1196.

[2]	ZUBAIDA Muyibul. Trade-offs and synergies between ecosystem services in Yutian County along the Keriya River Basin, Northwest China[J]. Journal of Arid Land, 2024, 16(7): 943-962.

[3]	CHEN Jiazhen, KASIMU Alimujiang, REHEMAN Rukeya, WEI Bohao, HAN Fuqiang, ZHANG Yan. Temporal and spatial variation and prediction of water yield and water conservation in the Bosten Lake Basin based on the PLUS-InVEST model[J]. Journal of Arid Land, 2024, 16(6): 852-875.

[4]	ZHU Haiqiang, WANG Jinlong, TANG Junhu, DING Zhaolong, GONG Lu. Spatiotemporal variations of ecosystem services and driving factors in the Tianchi Bogda Peak Natural Reserve of Xinjiang, China[J]. Journal of Arid Land, 2024, 16(6): 816-833.

[5]	WU Jingyan, LUO Jungang, ZHANG Han, YU Mengjie. Driving forces behind the spatiotemporal heterogeneity of land-use and land-cover change: A case study of the Weihe River Basin, China[J]. Journal of Arid Land, 2023, 15(3): 253-273.

[6]	CAO Yijie, MA Yonggang, BAO Anming, CHANG Cun, LIU Tie. Evaluation of the water conservation function in the Ili River Delta of Central Asia based on the InVEST model[J]. Journal of Arid Land, 2023, 15(12): 1455-1473.

[7]	YAN Xue, LI Lanhai. Spatiotemporal characteristics and influencing factors of ecosystem services in Central Asia[J]. Journal of Arid Land, 2023, 15(1): 1-19.

[8]	SUN Dingzhao, LIANG Youjia, PENG Shouzhang. Scenario simulation of water retention services under land use/cover and climate changes: a case study of the Loess Plateau, China[J]. Journal of Arid Land, 2022, 14(4): 390-410.

[9]	WANG Hongwei, QI Yuan, LIAN Xihong, ZHANG Jinlong, YANG Rui, ZHANG Meiting. Effects of climate change and land use/cover change on the volume of the Qinghai Lake in China[J]. Journal of Arid Land, 2022, 14(3): 245-261.

[10]	HE Bing, CHANG Jianxia, GUO Aijun, WANG Yimin, WANG Yan, LI Zhehao. Assessment of river basin habitat quality and its relationship with disturbance factors: A case study of the Tarim River Basin in Northwest China[J]. Journal of Arid Land, 2022, 14(2): 167-185.

[11]	LI Feng, LI Yaoming, ZHOU Xuewen, YIN Zun, LIU Tie, XIN Qinchuan. Modeling and analyzing supply-demand relationships of water resources in Xinjiang from a perspective of ecosystem services[J]. Journal of Arid Land, 2022, 14(2): 115-138.

[12]	WU Changxue, Xu Ruirui, QIU Dexun, DING Yingying, GAO Peng, MU Xingmin, ZHAO Guangju. Runoff characteristics and its sensitivity to climate factors in the Weihe River Basin from 2006 to 2018[J]. Journal of Arid Land, 2022, 14(12): 1344-1360.

[13]	Shanhu JIANG, Liliang REN, Meng ZHOU, Bin YONG, Yu ZHANG, Mingwei MA. Drought monitoring and reliability evaluation of the latest TMPA precipitation data in the Weihe River Basin, Northwest China[J]. Journal of Arid Land, 2017, 9(2): 256-269.

Viewed

Full text

Abstract

Cited

Shared

Discussed