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Journal of Arid Land  2022, Vol. 14 Issue (4): 390-410    DOI: 10.1007/s40333-022-0054-4
Research article     
Scenario simulation of water retention services under land use/cover and climate changes: a case study of the Loess Plateau, China
SUN Dingzhao1,2,3, LIANG Youjia2,*(), PENG Shouzhang1
1State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Water and Soil Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, China
2School of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430070, China
3Institute of Surveying and Mapping, Guizhou Geology and Mineral Exploration Bureau, Guiyang 550018, China
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Abstract  

Comprehensive assessments of ecosystem services in environments under the influences of human activities and climate change are critical for sustainable regional ecosystem management. Therefore, integrated interdisciplinary modelling has become a major focus of ecosystem service assessment. In this study, we established a model that integrates land use/cover change (LUCC), climate change, and water retention services to evaluate the spatial and temporal variations of water retention services in the Loess Plateau of China in the historical period (2000-2015) and in the future (2020-2050). An improved Markov-Cellular Automata (Markov-CA) model was used to simulate land use/land cover patterns, and ArcGIS 10.2 software was used to simulate and assess water retention services from 2000 to 2050 under six combined scenarios, including three land use/land cover scenarios (historical scenario (HS), ecological protection scenario (EPS), and urban expansion scenario (UES)) and two climate change scenarios (RCP4.5 and RCP8.5, where RCP is the representative concentration pathway). LUCCs in the historical period (2000-2015) and in the future (2020-2050) are dominated by transformations among agricultural land, urban land and grassland. Urban land under UES increased significantly by 0.63×103 km2/a, which was higher than the increase of urban land under HS and EPS. In the Loess Plateau, water yield decreased by 17.20×106 mm and water retention increased by 0.09×106 mm in the historical period (2000-2015), especially in the Interior drainage zone and its surrounding areas. In the future (2020-2050), the pixel means of water yield is higher under RCP4.5 scenario (96.63 mm) than under RCP8.5 scenario (95.46 mm), and the pixel means of water retention is higher under RCP4.5 scenario (1.95 mm) than under RCP8.5 scenario (1.38 mm). RCP4.5-EPS shows the highest total water retention capacity on the plateau scale among the six combined scenarios, with the value of 1.27×106 mm. Ecological restoration projects in the Loess Plateau have enhanced soil and water retention. However, more attention needs to be paid not only to the simultaneous increase in water retention services and evapotranspiration but also to the type and layout of restored vegetation. Furthermore, urbanization needs to be controlled to prevent uncontrollable LUCCs and climate change. Our findings provide reference data for the regional water and land resources management and the sustainable development of socio-ecological systems in the Loess Plateau under LUCC and climate change scenarios.



Key wordswater retention      water yield      land use/cover change      climate change      representative concentration pathway      Markov-Cellular Automata model      Loess Plateau     
Received: 07 August 2021      Published: 30 April 2022
Corresponding Authors: LIANG Youjia     E-mail: yjliang@whut.edu.cn
Cite this article:

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. Journal of Arid Land, 2022, 14(4): 390-410.

URL:

http://jal.xjegi.com/10.1007/s40333-022-0054-4     OR     http://jal.xjegi.com/Y2022/V14/I4/390

Fig. 1 Overview of the Loess Plateau
Fig. 2 Integrated modelling framework in this study. HS, historical scenario; EPS, ecological protection scenario; UES, urban expansion scenario; LUCC, land use/cover change; FLUS, future land use simulation; RCP, representative concentration pathway.
Name Source Format Period Processing method
LULC European Space Agency (https://www.esa-landcover-cci.org) 300 m, grid 2000-2015 Reclassification and resampling
DEM Resource and Environment Data Cloud Platform, the Chinese Academy of Sciences (http://www.resdc.cn/Default.aspx) 1000 m, grid 2003 Slope, aspect, and catchment calculations by ArcGIS 10.2
Soil properties Environmental and Ecological Science Data Center for West China (http://westdc.westgis.ac.cn/) 30 s, grid 2013 Projection conversion and resampling
Precipitation China Meteorological Data Service Center (http://data.cma.cn/) Text 2000-2015 Data organization and interpolation
Format conversion and resampling
National Aeronautics and Space Administration (NASA) (https://nex.nasa.gov/nex/projects/1356/) 25 km, grid 2020-2050
Meteorological elements China Meteorological Data Service Center (http://data.cma.cn/) Text 2000-2015 Data organization and interpolation
LAI Land-Atmosphere Interaction Research Group at Sun Yat-sen University, China (http://globalchange.bnu.edu.cn/) 30 s, grid 2000-2015 Projection and resampling
Population, GDP Resource and Environment Data Cloud Platform, the Chinese Academy of Sciences (http://www.resdc.cn/Default.aspx) 1000 m, grid 2000-2015 Projection
Geographical elements Resource and Environment Data Cloud Platform, the Chinese Academy of Sciences (http://www.resdc.cn/Default.aspx) Vector Projection and data cropping
Catchment boundaries Resource and Environmental Science Data Center, the Chinese Academy of Sciences (http://www.resdc.cn/data.aspx) Vector Projection and data cropping
Table S1 Data sources and data processing used in this study
Fig. 3 Simulations of land use type patterns under historical scenario (HS), ecological protection scenario (EPS), and urban expansion scenario (UES) in the Loess Plateau in 2020 (a, e, i), 2030 (b, f, j), 2040 (c, g, k), and 2050 (d, h, l)
Fig. 4 Conversions of land use types under HS (a), EPS (b), and UES (c) in the Loess Plateau during 2020-2050
Fig. S1 Correlation of different land use types under HS (a), EPS (b), and UES (c) in the Loess Plateau. HS, historical scenario; EPS, ecological protection scenario; UES, urban expansion scenario.
Fig. 5 Time series changes of pixel mean of precipitation and pixel mean of reference evapotranspiration (ET0) in the Loess Plateau from 2000 to 2015
Fig. 6 Spatial distributions and changes of precipitation (a, b, c) and ET0 (d, e, f) in the Loess Plateau from 2000 to 2015
Fig. 7 Time series changes of total water yield (a) and total water retention (b) in the Loess Plateau from 2000 to 2015
Fig. 8 Spatial distributions and changes of water yield (a, b, c) and water retention (d, e, f) in the Loess Plateau from 2000 to 2015
Fig. 9 Spatial distributions and changes of water yield under different scenarios (RCP4.5-HS, RCP4.5-EPS, RCP4.5-UES, RCP8.5-HS, RCP8.5-EPS, and RCP8.5-UES) in the Loess Plateau from 2015 to 2050
Fig. 10 Spatial distributions and changes of water retention under different scenarios (RCP4.5-HS, RCP4.5-EPS, RCP4.5-UES, RCP8.5-HS, RCP8.5-EPS, and RCP8.5-UES) in the Loess Plateau from 2015 to 2050
Period Percentage of area with different importance levels of water retention services (%)
General
(0-3 mm)
More
(3-10 mm)
Moderate
(10-30 mm)
High
(30-80 mm)
Extreme
(80-330.2 mm)
Historical period (2000-2015) 81.29 12.92 5.20 0.59 0.05
Future (2020-2050) under RCP4.5 84.65 11.02 4.03 0.29 0.01
Future (2020-2050) under RCP8.5 88.54 9.36 1.91 0.18 0.01
Table 1 Percentage of area with different importance levels of water retention services in the Loess Plateau in the historical period (2000-2015) and in the future (2020-2050) under RCP4.5 and RCP8.5 scenarios
Fig. 11 Spatial distributions of different importance levels of water retention services in the Loess Plateau in the historical period (2000-2015; a) and in the future (2020-2050; b and c) under RCP4.5 and RCP8.5 scenarios. The importance of water retention services in the Loess Plateau in the historical period (2000-2015) and in the future (2020-2050) under RCP4.5 and RCP8.5 scenarios can be divided into five levels using natural breaks method: general, 0.00-3.00 mm; more, 3.00-10.00 mm; moderate, 10.00-30.00 mm; high, 30.00-80.00 mm; and extreme, 80.00-330.20 mm.
Fig. 12 Spatial distributions of water retention change in the Mu Us Sandy Land in 2000-2015 (a), and spatial distributions of predicted water retention in the Mu Us Sandy Land in 2050 under RCP4.5-EPS (b) and RCP8.5-EPS (c)
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