Citation: | Sai Wang, Bin Wu, Hai-xue Li, Min-min Zhao, Lei Yuan, Xi Wu, Tao Ma, Fu-cheng Li, Shuang-bao Han, 2024. Optimization of water-urban-agricultural-ecological land use pattern: A case study of Guanzhong Basin in the southern Loess Plateau of Shaanxi Province, China, China Geology, 7, 480-493. doi: 10.31035/cg2022068 |
Extensive land use will cause many environmental problems. It is an urgent task to improve land use efficiency and optimize land use patterns. In recent years, due to the flow decrease, the Guanzhong Basin in Shaanxi Province is confronted with the problem of insufficient water resources reserve. Based on the Coupled Ground-Water and Surface-Water Flow Model (GSFLOW), this paper evaluates the response of water resources in the basin to changes in land use patterns, optimizes the land use pattern, improves the ecological and economic benefits, and the efficiency of various spatial development, providing a reference for ecological protection and high-quality development of the Yellow River Basin. The research shows that the land use pattern in the Guanzhong Basin should be further optimized. Under the condition of considering ecological and economic development, the percentage change of the optimum area of farmland, forest, grassland, water area, and urban area compared with the current land use area ratio is +2.3, +2.4, −6.1, +0.2, and +1.6, respectively. The economic and ecological value of land increases by 14.1% and 3.1%, respectively, and the number of water resources can increase by 2.5%.
Carranza-García M, García-Gutiérrez J, Riquelme JC. 2019. A framework for evaluating land use and land cover classification using convolutional neural networks. Remote Sensing, 11(3), 274. doi: 10.3390/rs11030274. |
Chen C, Ahmad S, Kalra A. 2018. A conceptual framework for integration development of gsflow model: Concerns and issues identified and addressed for model development efficiency. Geoscientific Model Development Discussions, 1‒18. doi: 10.5194/gmd-2018-268. |
Clarke KC. 2018. Land Use Change Modeling with SLEUTH: Improving Calibration with a Genetic Algorithm//Geomatic Approaches for Modeling Land Change Scenarios. Switzerland, Springer Cham Press, 139‒161. doi: 10.1007/978-3-319-60801-3_8. |
Crystal Ng GH, Wickert AD, Somers LD, Saberi L, Cronkite-Ratcliff C, Niswonger RG, McKenzie JM. 2018. GSFLOW–GRASS v1. 0. 0:GIS-enabled hydrologic modeling of coupled groundwater-surface-water systems. Geoscientific Model Development, 11(12), 4755–4777. doi: 10.5194/gmd-11-4755-2018. |
Cosenza Z, Block DE. 2021. A generalizable hybrid search framework for optimizing expensive design problems using surrogate models. Engineering Optimization, 53(10), 1772–1785. doi: 10.1080/0305215X.2020.1826466. |
Dong Y, Song YG, Zhang MS, Lan MW, Fu XF, Liu HF, Ning QQ. 2019. Several key basic geological problems on the development of the Guanzhong urban agglomeration. Northwestern Geology, 52(2), 12–26 (in Chinese with English abstract). doi: 10.19751/j.cnki.61-1149/p.2019.02.002. |
Feng BP, Liang X, Zeng Z. 2018. Optimizing land usage in southern mountain areas of Jinan based on the SWAT model. Journal of Irrigation and Drainage, 37(5), 121–128 (in Chinese with English abstract). doi: 10.13522/j.cnki.ggps.2017.0546. |
Gao L, Shao M, Wang Y. 2012. Spatial scaling of saturated hydraulic conductivity of soils in a small watershed on the Loess Plateau, China. Journal of Soils and Sediments, 12(6), 863–875. doi: 10.1007/s11368-012-0511-3. |
Geng H, Wang ZM. 2000. Research on optimization of land use structure based on gray linear programming. Journal of Wuhan Technical University of Surveying and Mapping, 25(2), 167–171,182 (in Chinese with English abstract). |
He J. 2018. Analysis of coupling effect of surface water and groundwater in gneiss area based on GSFLOW. Shaanxi Water Resources, 221(6), 17–19, 22 (in Chinese with English abstract). |
Islam K, Rahman MF, Jashimuddin M. 2018. Modeling land use change using cellular automata and artificial neural network: The case of Chunati Wildlife Sanctuary, Bangladesh. Ecological indicators, 88, 439–453. doi: 10.1016/j.ecolind.2018.01.047. |
Jiang W, Chen Z, Lei X, Jia K, Wu Y. 2015. Simulating urban land use change by incorporating an autologistic regression model into a CLUE-S model. Journal of Geographical Sciences, 25(7), 836–850. doi: 10.1007/s11442-015-1205-8. |
Kucsicsa G, Popovici EA, Bălteanu D, Grigorescu I, Dumitraşcu M, Mitrică B. 2019. Future land use/cover changes in Romania: Regional simulations based on CLUE-S model and CORINE land cover database. Landscape and ecological engineering, 15(1), 75–90. doi: 10.1007/s11355-018-0362-1. |
Li B, Wang L, Hao XJ. 2021. Analysis of annual runoff distribution characteristics in Weihe River Basin from 1956 to 2015. Shaanxi Water Resources, 240(1), 34–38 (in Chinese with English abstract). |
Li H, Wang DP, Liu BY, Lin MS, Wang JY. 2018. Research on land use change based on Cellular Automata and Rough Set. Journal of Central China Normal University (Nat. Sci.), 52(6), 910–915 (in Chinese with English abstract). doi: 10.19603/j.cnki.1000-1190.2018.06.021. |
Li HX, Han SB, Wu X, Wang S, Liu WP, Ma T, Zhang MN, Wei YT, Yuan FQ, Yan L, Li FC, Wu B, Wang YS, Zhao MM, Yang HW, Wei SB. 2021. Distribution, characteristics and influencing factors of fresh groundwater resources in the Loess Plateau, China. China Geology, 4(3), 509–526. doi: 10.31035/cg2021057. |
Liang X, Liu X, Li X, Chen Y, Tian H, Yao Y. 2018. Delineating multi-scenario urban growth boundaries with a CA-based FLUS model and morphological method. Landscape and Urban Planning, 177, 47–63. doi: 10.1016/j.landurbplan.2018.04.016. |
Lin W, Sun Y, Nijhuis S, Wang Z. 2020. Scenario-based flood risk assessment for urbanizing deltas using future land-use simulation (FLUS): Guangzhou Metropolitan Area as a case study. Science of the Total Environment, 739, 139899. doi: 10.1016/j.scitotenv.2020.139899. |
Liu S, Qi Z, Li X, Yeh AGO. 2019. Integration of convolutional neural networks and object-based post-classification refinement for land use and land cover mapping with optical and SAR data. Remote Sensing, 11(6), 690. doi: 10.3390/rs11060690. |
Lu J H, Mei ZX, Zhao SF, Xiao YY. 2017. Land use optimization allocation based on chaos ant colony algorithm. Journal of Geo-information Science, 19(8), 1026–1035 (in Chinese with English abstract). doi: 10.3724/SP.J.1047.2017.01026. |
Luo YL, Huang FG, Zhang HM, Bian YL. 2010. Influence of water diversion in Guanzhong irrigation area on runoff from Weihe River into the Yellow River. Yellow River, 32(5), 19–20,22. doi: 10.3969/j.issn.1000-1379.2010.05.008. |
Ma BY, Huang J, Li SC. 2019. Optimal allocation of land use types in the Beijing-Tianjin-Hebei urban agglomeration based on ecological and economic benefits trade-offs. Progress in Geography, 38(1), 26–37 (in Chinese with English abstract). doi: 10.18306/dlkxjz.2019.01.003. |
Markstrom SL, Niswonger RG, Regan RS, Prudic DE, Barlow PM. 2008. GSFLOW‒coupled Ground-water and Surface-water FLOW model based on the integration of the Precipitation-Runoff Modeling System (PRMS) and the Modular Ground-Water Flow Model (MODFLOW-2005). US Geological Survey techniques and methods, 6, 240. doi: 10.13140/2.1.2741.9202. |
Niswonger RG. 2020. An agricultural water use package for MODFLOW and GSFLOW. Environmental Modelling & Software, 125, 104617. doi: 10.1016/j.envsoft.2019.104617. |
Regis RG, Shoemaker CA. 2013. Combining radial basis function surrogates and dynamic coordinate search in high-dimensional expensive black-box optimization. Engineering Optimization, 45(5), 529–555. doi: 10.1080/0305215X.2012.687731. |
Rimal B, Zhang L, Keshtkar H, Haack BN, Rijal S, Zhang P. 2018. Land use/land cover dynamics and modeling of urban land expansion by the integration of cellular automata and markov chain. ISPRS International Journal of Geo-Information, 7(4), 154. doi: 10.3390/ijgi7040154. |
Sobol IM. 2001. Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. Mathematics and Computers in Simulation, 55(1‒3), 271‒280. doi: 10.1016/S0378-4754(00)00270-6. |
Song YG, Lan MW, Liu HF, Zhang MS, Fu XF, Ning QQ. 2021. Cenozoic stratigraphic correlation and the lower limit of Quaternary in Cuanzhong Basin. Bulletin of Geological Science and Technology, 40(2), 24–35 (in Chinese with English abstract). doi: 10.19509/j.cnki.dzkq.2021.0204. |
Sun YZ, Yang J, Song SY, Zhu J, Dai JJ. 2020. Modeling of multilevel vector cellular automata and its simulation of land use change. Acta Geographica Sinica, 75(10), 2164–2179 (in Chinese with English abstract). doi: 10.11821/dlxb202010009. |
Tian H, Liang X, Li X, Liu XP, Ou JP, Hong Y, He ZJ. 2017. Simulating multiple land use scenarios in China during 2010‒2050 based on System Dynamic Model. Tropical Geography, 37(4), 547–561 (in Chinese with English abstract). doi: 10.13284/j.cnki.rddl.002939. |
Tu XS, Pu LJ, Yan X, Zhu M. 2009. Analysis of optimal allocation of land resources and soil quality regulation using system dynamics. Research of Environmental Sciences, 22(2), 221–226 (in Chinese with English abstract). |
Tian H, Wang WK, Cao YQ, Wang Z, Wang J. 2007. Tritium age calculation of groundwater in Guanzhong Basin. Journal of Xi’an University of Science and Technology, 27(3), 382–385,426 (in Chinese with English abstract). |
Wang BS, Liao JF, Zhu W, Qiu QY, Wang L, Tang LN. 2019. The weight of neighborhood setting of the FLUS model based on a historical scenario: A case study of land use simulation of urban agglomeration of the Golden Triangle of Southern Fujian in 2030. Acta Ecologica Sinica, 39(12), 4284–4298 (in Chinese with English abstract). doi: 10.5846/stxb201808021649. |
Wang J, Yan BJ, Li H, Wang GL. 2008. Optimized allocation for land resources and construction scales for regional highway network. Journal of Chang’an University (Social Science Edition), 10(3), 34–38 (in Chinese with English abstract). |
Wang Q, Liu R, Men C, Guo L. 2018. Application of genetic algorithm to land use optimization for non-point source pollution control based on CLUE-S and SWAT. Journal of Hydrology, 560, 86–96. doi: 10.1016/j.jhydrol.2018.03.022. |
Wei W, Xie YW, Wei XX, Xie BB, Zhang Q, Hao YY. 2017. Land use optimization based on CLUE-S model and ecological security scenario in Shiyang River Basin. Geomatics and Information Science of Wuhan University, 42(9), 1306–1315 (in Chinese with English abstract). doi: 10.13203/j.whugis20160051. |
Wu B, Zheng Y, Tian Y, Wu X, Yao Y, Han F, Liu J, Zheng C. 2014. Systematic assessment of the uncertainty in integrated surface water‐groundwater modeling based on the probabilistic collocation method. Water Resources Research, 50(7), 5848–5865. doi: 10.1002/2014WR015366. |
Wu B, Zheng Y, Wu X, Tian Y, Han F, Liu J, Zheng C. 2015. Optimizing water resources management in large river basins with integrated surface water-groundwater modeling: A surrogate-based approach. Water Resources Research, 51(4), 2153–2173. doi: 10.1002/2014WR016653. |
Wu B, Wang S, Wang WX, An YH. 2019. Impact of future climate change on water resources in the arid regions of Northwest China based on surface water-groundwater coupling model: A case study of the middle reaches of the Heihe River. Geology in China, 46(2), 369–380 (in Chinese with English abstract). doi: 10.12029/gc20190213. |
Xie GD, Lu CX, Leng YF, Zheng D, Li SC. 2003. Ecological assets valuation of the Tibetan Plateau. Journal of Natural Resources, 18(2), 189–196 (in Chinese with English abstract). doi: 10.11849/zrzyxb.2003.02.010. |
Xu RR, Gao P, Mu XM, Chai XK, Gu CJ. 2020. Dynamic of streamflow and sediment load and its response to human activities in the Weihe River Basin. Yellow River, 42(3), 17–24 (in Chinese with English abstract). doi: 10.3969/j.issn.1000-1379.2020.03.003. |
Yang L, Xie YW, Zong LL, Qiu T, Jiao JZ. 2020. Land use optimization configuration based on multi-objective genetic algorithm and FLUS model of agro-pastoral ecotone in Northwest China. Journal of Geo-information Science, 22(3), 568–579 (in Chinese with English abstract). doi: 10.12082/dqxxkx.2020.190531. |
Yuan M, Liu YL. 2014. Land use optimization allocation based on multi-agent genetic algorithm. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 30(1), 191–199 (in Chinese with English abstract). doi: 10.3969/j.issn.1002-6819.2014.01.025. |
Zhang HJ, Wu JF, Lin J, Wu M, Wu JC. 2015. Comparative analysis and coupling simulation of groundwater and surface water flow based on GSFLOW. Geotechnical Investigation and Surveying, 43(5), 34–38 (in Chinese with English abstract). |
Zhang HH, Zeng YN, Tan R, Liu HM. 2011. A model for regional land use optimization allocation based on multi-agent system and its application. Acta Geographica Sinica, 66(7), 972–984 (in Chinese with English abstract). doi: 10.11821/xb201107010. |
Zhang MS, Zhu LF, Wang XY. 2005. Groundwater systems and sustainable development countermeasures of groundwater resources in the Guanzhong Basin. Quaternary Sciences, 25(1), 15–22 (in Chinese with English abstract). |
Zhang WL, Liu Q, Wu CB, Yang GD. 2021. Annual change detection of land use status based on Siamese neural network. Bulletin of Surveying and Mapping, (3), 91–95,104 (in Chinese with English abstract). doi: 10.13474/j.cnki.11-2246.2021.0084. |
Zhang XR, Li AN, Nan X, Lei GB, Wang CB. 2020. Multi-scenario simulation of land use change along China-Pakistan Economic Corridor through coupling FLUS model with SD model. Journal of Geo-information Science, 22(12), 2393–2409 (in Chinese with English abstract). doi: 10.12082/dqxxkx.2020.190618. |
General situation of Guanzhong Basin in Shaanxi Province, China.
Geological conditions of Guanzhong Basin in Shaanxi Province, China.
Permeability coefficient and aquifer thickness. a‒permeability coefficient; b‒aquifer thickness.
Digital river and subbasins.
Measured and simulated monthly runoff at Huaxian station and Xianyang station. a‒Huaxian; b‒Xianyang.
Measured and simulated water level of groundwater level observation wells.
Sankey diagrams of land use structures before and after optimization. a‒ecological protection priority mode; b‒economic development priority mode; c‒ecology-economy equilibrium mode.
Spatial distribution pattern of land use before and after optimization. a‒initial condition; b‒ecological protection priority mode; c‒economic development priority mode; d‒ecology-economy equilibrium mode.