Please wait a minute...
Journal of Arid Land  2018, Vol. 10 Issue (2): 169-182    DOI: 10.1007/s40333-018-0091-1
Orginal Article     
Model based decision support system for land use changes and socio-economic assessments
Yang YU1,*(), Xi CHEN1, HUTTNER Philipp2, HINNENTHAL Marie3, BRIEDEN Andreas3, Lingxiao SUN1, DISSE Markus2
1 Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
2 Chair of Hydrology and River Basin Management, Technical University of Munich, Munich 80333, Germany
3 Chair of Statistics and Risk Management, Universitaet der Bundeswehr Muenchen, Neubiberg D-85577, Germany
Download: HTML     PDF(939KB)
Export: BibTeX | EndNote (RIS)      

Abstract  

Hydrological models are often linked with other models in cognate sciences to understand the interactions among climate, earth, water, ecosystem, and human society. This paper presents the development and implementation of a decision support system (DSS) that links the outputs of hydrological models with real-time decision making on social-economic assessments and land use management. Discharge and glacier geometry changes were simulated with hydrological model,water availability in semi-arid environments. Irrigation and ecological water were simulated by a new commercial software MIKE HYDRO. Groundwater was simulated by MODFLOW. All the outputs of theses hydrological models were taken as inputs into the DSS in three types of links: regression equations, stationary data inputs, or dynamic data inputs as the models running parallel in the simulation periods. The DSS integrates the hydrological data, geographic data, social and economic statistical data, and establishes the relationships with equations, conditional statements and fuzzy logics. The programming is realized in C++. The DSS has four remarkable features: (1) editable land use maps to assist decision-making; (2) conjunctive use of surface and groundwater resources; (3) interactions among water, earth, ecosystem, and humans; and (4) links with hydrological models. The overall goal of the DSS is to combine the outputs of scientific models, knowledge of experts, and perspectives of stakeholders, into a computer-based system, which allows sustainability impact assessment within regional planning; and to understand ecosystem services and integrate them into land and water management.



Key wordsdecision support system      hydrological modeling      ecosystem services      land management      socio-economic indicator      Tarim River Basin     
Received: 28 August 2017      Published: 10 April 2018
Corresponding Authors:
About author:

The first and fourth authors contributed equally to this work.

Cite this article:

Yang YU, Xi CHEN, HUTTNER Philipp, HINNENTHAL Marie, BRIEDEN Andreas, Lingxiao SUN, DISSE Markus. Model based decision support system for land use changes and socio-economic assessments. Journal of Arid Land, 2018, 10(2): 169-182.

URL:

http://jal.xjegi.com/10.1007/s40333-018-0091-1     OR     http://jal.xjegi.com/Y2018/V10/I2/169

[1] Arnell N W, Lloyd-Hughes B.2014. The global-scale impacts of climate change on water resources and flooding under new climate and socio-economic scenarios. Climatic Change, 122(1-2): 127-140.
[2] Basso B, Ritchie J T.2015. Simulating crop growth and biogeochemical fluxes in response to land management using the SALUS model. In: Hamilton S K, Doll J E, Robertson G P. The Ecology of Agricultural Landscapes: Long-term Research on the Path to Sustainability. New York: Oxford University Press, 252-274.
[3] Biswas A K.2008. Integrated water resources management: is it working? International Journal ofWater Resources Development, 24(1): 5-22.
[4] Chen Y N, Li W H, Xu C C, et al.2015. Desert riparian vegetation and groundwater in the lower reaches of the Tarim River basin. Environmental Earth Sciences, 73(2): 547-558.
[5] Chenoweth T, Dowling K L, St. Louis R D.2004. Convincing DSS users that complex models are worth the effort. Decision Support Systems, 37(1): 71-82.
[6] Disse M.2016. Sustainable land and water management of River Oases along the Tarim River. Proceedings of the International Association of Hydrological Sciences, 373: 25-29.
[7] Doorenbos J, Kassam A H.1979. Yield Response to Water. Rome: FAO, 257.
[8] Duethmann D, Menz C, Jiang T, et al.2016. Projections for headwater catchments of the Tarim River reveal glacier retreat and decreasing surface water availability but uncertainties are large. Environmental Research Letters, 11(5): 054024.
[9] Feng Q, Endo K N, Cheng G D.2001. Towards sustainable development of the environmentally degraded arid rivers of China-a case study from Tarim River. Environmental Geology, 41(1-2): 229-238.
[10] Fl?rke M, Kynast E, B?rlund I, et al.2013. Domestic and industrial water uses of the past 60 years as a mirror of socio-economic development: a global simulation study. Global Environmental Change, 23(1): 144-156.
[11] Giordano M, Shah T.2014. From IWRM back to integrated water resources management. International Journal of Water Resources Development, 30(3): 364-376.
[12] Güntner A, Bronstert A.2004. Representation of landscape variability and lateral redistribution processes for large-scale hydrological modelling in semi-arid areas. Journal of Hydrology, 297(1-4): 136-161.
[13] Herrero M, Thornton P K, Bernués A, et al.2014. Exploring future changes in smallholder farming systems by linking socio-economic scenarios with regional and household models. Global Environmental Change, 24: 165-182.
[14] Jeffrey P, Gearey M.2006. Integrated water resources management: lost on the road from ambition to realisation? Water Science &Technology, 53(1): 1-8.
[15] Liu G L, Yin G, Kurban A, et al.2016. Spatiotemporal dynamics of land cover and their impacts on potential dust source regions in the Tarim Basin, NW China. Environmental Earth Sciences, 75(23): 1477.
[16] Liu X P, Meng M.2011. Sustainable land use and the coupling relation of ecological economic harmonious development: a case study of Tarim River Basin. Arid Land Geography, 34(1): 173-178. (in Chinese)
[17] Liu Y B, Chen Y N.2006. Impact of population growth and land-use change on water resources and ecosystems of the arid Tarim River Basin in Western China. The International Journal of Sustainable Development & World Ecology, 13(4): 295-305.
[18] Lv X, Liu X P, Li Z B.2016. Coupling of ecological economic system in Tarim River Watershed. In: Qu F T, Sun R M, Guo Z X, et al. Ecological Economics and Harmonious Society. Singapore: Springer, 197-208.
[19] McCown R L.2002. Locating agricultural decision support systems in the troubled past and socio-technical complexity of ‘models for management’. Agricultural Systems, 74(1): 11-25.
[20] Pedro-Monzonís M, Jiménez-Fernández P, Solera A, et al.2016. The use of AQUATOOL DSS applied to the System of Environmental-Economic Accounting for Water (SEEAW). Journal of Hydrology, 533: 1-14.
[21] Power D J, Sharda R, Burstein F.2015. Decision support systems. Volume 7. Management information systems. In: Cooper C L. Wiley Encyclopedia of Management. New York: John Wiley & Sons, Ltd, 1-11.
[22] Quevauviller P.2010. Is IWRM achievable in practice? Attempts to break disciplinary and sectoral walls through a science-policy interfacing framework in the context of the EU Water Framework Directive. Irrigation and drainage systems, 24(3-4): 177-189.
[23] Rumbaur C, Thevs N, Disse M, et al.2015. Sustainable management of river oases along the Tarim River (SuMaRiO) in Northwest China under conditions of climate change. Earth System Dynamics, 6(1): 83-107.
[24] Thomas F M, Jeschke M, Zhang X M, et al.2017. Stand structure and productivity of Populus euphratica along a gradient of groundwater distances at the Tarim River (NW China). Journal of Plant Ecology, 10(5): 753-764.
[25] Visconti P, Bakkenes M, Smith R J, et al.2015. Socio-economic and ecological impacts of global protected area expansion plans. Philosophical Transactions of the Royal Society B: Biological Sciences, 370(1681): 20140284.
[26] Wenkel K O, Berg M, Mirschel W, et al.2013. LandCaRe DSS-An interactive decision support system for climate change impact assessment and the analysis of potential agricultural land use adaptation strategies. Journal of Environmental Management, 127(Suppl.): S168-S183.
[27] West G G, Turner J A.2014. MyLand: a web-based and meta-model decision support system framework for spatial and temporal evaluation of integrated land use. Scandinavian Journal of Forest Research, 29(Suppl.): 108-120.
[28] Xu H L, Ye M, Li J M.2008. The water transfer effects on agricultural development in the lower Tarim River, Xinjiang of China. Agricultural Water Management, 95(1): 59-68.
[29] Yu Y, Disse M, Yu R D, et al.2015. Large-scale hydrological modeling and decision-making for agricultural water consumption and allocation in the main stem Tarim River, China. Water, 7(6): 2821-2839.
[30] Yue H L, Zhu Y P, Xue Y, et al.2014. Study on counties agricultural economic intelligent decision-making support system (IDSS) based on GIS and knowledge. Advanced Materials Research, 889-890: 1319-1322.
[31] Zadeh L A.1983. The role of fuzzy logic in the management of uncertainty in expert systems. Fuzzy Sets and Systems, 11(1-3): 199-227.
[32] Zhang Q, Sun P, Li J F, et al.2015. Assessment of drought vulnerability of the Tarim River basin, Xinjiang, China. Theoretical and Applied Climatology, 121(1-2): 337-347.
[33] Zhang Z, Hu H, Tian F, et al.2014. Groundwater dynamics under water-saving irrigation and implications for sustainable water management in an oasis: Tarim River basin of western China. Hydrology and Earth System Sciences, 18(10): 3951-3967.
[34] Zhao R F, Chen Y N, Li W H, et al.2009. Land cover change and landscape pattern in the mainstream of the Tarim River. ActaGeographicaSinica, 64(1): 95-106. (in Chinese)
[1] LIN Yanmin, HU Zhirui, LI Wenhui, CHEN Haonan, WANG Fang, NAN Xiongxiong, YANG Xuelong, ZHANG Wenjun. Response of ecosystem carbon storage to land use change from 1985 to 2050 in the Ningxia Section of Yellow River Basin, China[J]. Journal of Arid Land, 2024, 16(1): 110-130.
[2] WANG Jing, WEI Yulu, PENG Biao, LIU Siqi, LI Jianfeng. Spatiotemporal variations in ecosystem services and their trade-offs and synergies against the background of the gully control and land consolidation project on the Loess Plateau, China[J]. Journal of Arid Land, 2024, 16(1): 131-145.
[3] 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.
[4] Mohsen SHARAFATMANDRAD, Azam KHOSRAVI MASHIZI. Evaluation of restoration success in arid rangelands of Iran based on the variation of ecosystem services[J]. Journal of Arid Land, 2023, 15(11): 1290-1314.
[5] 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.
[6] 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.
[7] 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.
[8] CHEN Limei, Abudureheman HALIKE, YAO Kaixuan, WEI Qianqian. Spatiotemporal variation in vegetation net primary productivity and its relationship with meteorological factors in the Tarim River Basin of China from 2001 to 2020 based on the Google Earth Engine[J]. Journal of Arid Land, 2022, 14(12): 1377-1394.
[9] YU Yang, CHEN Xi, Ireneusz MALIK, Malgorzata WISTUBA, CAO Yiguo, HOU Dongde, TA Zhijie, HE Jing, ZHANG Lingyun, YU Ruide, ZHANG Haiyan, SUN Lingxiao. Spatiotemporal changes in water, land use, and ecosystem services in Central Asia considering climate changes and human activities[J]. Journal of Arid Land, 2021, 13(9): 881-890.
[10] BAI Jie, LI Junli, BAO Anmin, CHANG Cun. Spatial-temporal variations of ecological vulnerability in the Tarim River Basin, Northwest China[J]. Journal of Arid Land, 2021, 13(8): 814-834.
[11] SUN Chen, MA Yonggang, GONG Lu. Response of ecosystem service value to land use/cover change in the northern slope economic belt of the Tianshan Mountains, Xinjiang, China[J]. Journal of Arid Land, 2021, 13(10): 1026-1040.
[12] Ahmed M M HASOBA, Ahmed A H SIDDIG, Yousif E YAGOUB. Exploring tree diversity and stand structure of savanna woodlands in southeastern Sudan[J]. Journal of Arid Land, 2020, 12(4): 609-617.
[13] ZERAATPISHEH Mojtaba, AYOUBI Shamsollah, SULIEMAN Magboul, RODRIGO-COMINO Jesús. Determining the spatial distribution of soil properties using the environmental covariates and multivariate statistical analysis: a case study in semi-arid regions of Iran[J]. Journal of Arid Land, 2019, 11(4): 551-566.
[14] Alisher MIRZABAEV, Mohamed AHMED, Jutta WERNER, John PENDER, Mounir LOUHAICHI. Rangelands of Central Asia: challenges and opportunities[J]. Journal of Arid Land, 2016, 8(1): 93-108.
[15] Yue HUANG, Xi CHEN, YongPing LI, AnMing BAO, YongGang MA. A simulation-based two-stage interval-stochastic programming model for water resources management in Kaidu-Konqi watershed, China[J]. Journal of Arid Land, 2012, 4(4): 390-398.