Please wait a minute...
Journal of Arid Land  2012, Vol. 4 Issue (4): 390-398    DOI: 10.3724/SP.J.1227.2012.00390
Research Articles     
A simulation-based two-stage interval-stochastic programming model for water resources management in Kaidu-Konqi watershed, China
Yue HUANG1,2, Xi CHEN2, YongPing LI3, AnMing BAO2, YongGang MA2,4
1 College of Urban and Environmental Sciences, Peking University, Beijing 100871, China;
2 State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of
Sciences, Urumqi 830011, China;
3 MOE Key Laboratory of Regional Energy Systems Optimization, Sino-Canada Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206, China;
4 Xinjiang Remote Sensing Center, Urumqi 830011, China
Download:   PDF(1495KB)
Export: BibTeX | EndNote (RIS)      

Abstract  This study presented a simulation-based two-stage interval-stochastic programming (STIP) model to support water resources management in the Kaidu-Konqi watershed in Northwest China. The modeling system coupled a distributed hydrological model with an interval two-stage stochastic programing (ITSP). The distributed hydrological model was used for establishing a rainfall-runoff forecast system, while random parameters were pro-vided by the statistical analysis of simulation outcomes. The developed STIP model was applied to a real case of water resources management planning in Kaidu-Konqi watershed, where three scenarios with different water re-sources management policies were analyzed. The results indicated that water shortage mainly occurred in agri-culture, ecology and forestry sectors. In comparison, the water demand from municipality, industry and stock-breeding sectors can be satisfied due to their lower consumptions and higher economic values. Different policies for ecological water allocation can result in varied system benefits, and can help to identify desired water allocation plans with a maximum economic benefit and a minimum risk of system disruption under uncertainty.

Key wordsEvapotranspiration (ET)      arid areas      SEBS model      remote sensing      Central Asia      Xinjiang of China     
Received: 09 February 2012      Published: 15 December 2012

The National Basic Research Pro-gram of China (2010CB951002), the Dr. Western-funded Project of Chinese Academy of Science (XBBS201010 and XBBS¬201005), the National Natural Sciences Foundation of China (51190095), and the Open Research Fund Program of State Key Laboratory of Hydro-science and Engineering (sklhse-2012-A- 03).

Corresponding Authors:
Cite this article:

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. Journal of Arid Land, 2012, 4(4): 390-398.

URL:     OR

Abbott M B, Bathurst J C, Cunge J A, et al. 1986. An introduction to the European hydrological system—Systeme Hydrologique Eu-ropeen (SHE), 2: Structure of a physically-based, distributed mod-eling system. Journal of Hydrology, 87: 61–77.

Bronster A, Jaegr A, Ciintner A, et al. 2000. Integrated modeling of water availability and water use in the semi-arid northeast of Brazil. Physics and Chemistry of the Earth, 25: 227–232.

Danish Hydraulic Institute. 2007. MIKE 11 User’s and Reference Manual, Horsholm: DHI Water & Environment, Denmark.

Huang G H, Loucks D P. 2000. An inexact two-stage stochastic pro-gramming model for water resources management under uncer-tainty. Civil Engineering Environment System, 17: 95–118.

Huang G H, Cao M F. 2011. Analysis of solution methods for interval linear programming. Journal of Environmental Informatics, 17(2): 54–64.

Huang Y, Chen X, Li Y P, et al. 2010a. Integrated modeling system for water resources management of Tarim River Basin. Environmental Engineering Science, 27(3): 255–269.

Huang Y, Chen X, Li Y P, et al. 2010b. A fuzzy-based simulation method for modelling hydrological processes under uncertainty. Hydrological Processes, 24(25): 3718–3732.

Jing L, Chen B. 2011. Field investigation and hydrological modelling of a subarctic wetland: the deer river watershed. Journal of Envi-ronmental Informatics, 17(1): 36–45.

Li Y P, Huang G H, Nie S L. 2006. An interval-parameter multistage stochastic programming model for water resources management under uncertainty. Advances in Water Resources, 29(5): 776–789.

Li Y P, Huang G H, Nie S L, et al. 2008. Inexact multistage stochastic integer programming for water resources management under uncer-tainty. Journal of Environmental Management, 88: 93–107.

Li W, Li Y P, Li C H, et al. 2010. An inexact two-stage water man-agement model for planning agriculture irrigation under uncertainty.

Agriculture Water Management, 97: 1905–1914.

Luo B, Li J B, Huang G H, et al. 2006. A simulation-based interval two-stage stochastic model for agricultural nonpoint source pollu-tion control through land retirement. Science of the Total Environ-ment, 361: 38–56.

Maqsood I, Huang G H, Huang Y F, et al. 2005. ITOM: an inter-val-parameter two-stage optimization model for stochastic planning of water resources systems. Stochastic Environment Research Risk Assessment, 19: 125–133.

Nash J E, Sutcliffe J V. 1970. River flow forecasting through concep-tual models part Ι: a discussion of principles. Journal of Hydrology, 10(3): 282–290.

Paturel J E, Barrau C, Mahé G, et al. 2007. Modelling the impact of climatic variability on water resources in West and Central Africa from a non-calibrated hydrological model. Hydrological Sciences Journal, 52(1): 38–48.

Qin X S, Huang G H, Yu H. 2009. Enhancing remediation of LNAPL recovery through a response-surface-based optimization approach. Journal of Environmental Engineering, 135(10): 999–1008.

Statistical Bureau of Bayangol Mongol Autonomous Prefecture. 2000–2009. Statistical Yearbook of Bayangol. Beijing: China Sta-tistic Press.

Wang J, Yang H, Li L, et al. 2011. The coupled routing and excess storage (CREST) distributed hydrological model. Hydrological Sciences Journal, 56(1): 84–98.

Xu Y, Huang G H, Qin X S. 2009. An inexact two-stage stochastic robust optimization model for water resources management under uncer-tainty. Environmental Engineering Science, 26(12): 1765–1767.

Yang Y H, Chen Y N, Li W H, et al. 2010. Impacts of climatic change on river runoff in Northern Xinjiang of China over last fifty years. Chinese Geographical Science, 20(3): 193–201.

Zhang Y C. 2006. A study on hydrological process response to envi-ronmental change in Kaidu Watershed. Ph.D Dissertation, Beijing: Chinese Academy of Sciences.

[1] ZHAO Xiaohan, HAN Dianchen, LU Qi, LI Yunpeng, ZHANG Fangmin. Spatiotemporal variations in ecological quality of Otindag Sandy Land based on a new modified remote sensing ecological index[J]. Journal of Arid Land, 2023, 15(8): 920-939.
[2] WANG Min, CHEN Xi, CAO Liangzhong, KURBAN Alishir, SHI Haiyang, WU Nannan, EZIZ Anwar, YUAN Xiuliang, Philippe DE MAEYER. Correlation analysis between the Aral Sea shrinkage and the Amu Darya River[J]. Journal of Arid Land, 2023, 15(7): 757-778.
[3] Orhan DENGİZ, İnci DEMİRAĞ TURAN. Soil quality assessment for desertification based on multi-indicators with the best-worst method in a semi-arid ecosystem[J]. Journal of Arid Land, 2023, 15(7): 779-796.
[4] LI Wen, MU Guijin, YE Changsheng, XU Lishuai, LI Gen. Aeolian activity in the southern Gurbantunggut Desert of China during the last 900 years[J]. Journal of Arid Land, 2023, 15(6): 649-666.
[5] LONG Yi, JIANG Fugen, DENG Muli, WANG Tianhong, SUN Hua. Spatial-temporal changes and driving factors of eco- environmental quality in the Three-North region of China[J]. Journal of Arid Land, 2023, 15(3): 231-252.
[6] 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.
[7] SUN Liquan, GUO Huili, CHEN Ziyu, YIN Ziming, FENG Hao, WU Shufang, Kadambot H M SIDDIQUE. Check dam extraction from remote sensing images using deep learning and geospatial analysis: A case study in the Yanhe River Basin of the Loess Plateau, China[J]. Journal of Arid Land, 2023, 15(1): 34-51.
[8] HUANG Xiaoran, BAO Anming, GUO Hao, MENG Fanhao, ZHANG Pengfei, ZHENG Guoxiong, YU Tao, QI Peng, Vincent NZABARINDA, DU Weibing. Spatiotemporal changes of typical glaciers and their responses to climate change in Xinjiang, Northwest China[J]. Journal of Arid Land, 2022, 14(5): 502-520.
[9] YAO Linlin, ZHOU Hongfei, YAN Yingjie, LI Lanhai, SU Yuan. Projection of hydrothermal condition in Central Asia under four SSP-RCP scenarios[J]. Journal of Arid Land, 2022, 14(5): 521-536.
[10] YAO Kaixuan, Abudureheman HALIKE, CHEN Limei, WEI Qianqian. Spatiotemporal changes of eco-environmental quality based on remote sensing-based ecological index in the Hotan Oasis, Xinjiang[J]. Journal of Arid Land, 2022, 14(3): 262-283.
[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] WANG Jinjie, DING Jianli, GE Xiangyu, QIN Shaofeng, ZHANG Zhe. Assessment of ecological quality in Northwest China (2000-2020) using the Google Earth Engine platform: Climate factors and land use/land cover contribute to ecological quality[J]. Journal of Arid Land, 2022, 14(11): 1196-1211.
[13] MA Xiumei, ZHOU Kefa, WANG Jinlin, CUI Shichao, ZHOU Shuguang, WANG Shanshan, ZHANG Guanbin. Optimal bandwidth selection for retrieving Cu content in rock based on hyperspectral remote sensing[J]. Journal of Arid Land, 2022, 14(1): 102-114.
[14] WU Shupu, GAO Xin, LEI Jiaqiang, ZHOU Na, GUO Zengkun, SHANG Baijun. Ecological environment quality evaluation of the Sahel region in Africa based on remote sensing ecological index[J]. Journal of Arid Land, 2022, 14(1): 14-33.
[15] SONG Yujia, LIU Xijun, XIAO Wenjiao, ZHANG Zhiguo, LIU Pengde, XIAO Yao, LI Rui, WANG Baohua, LIU Lei, HU Rongguo. Neoproterozoic I-type granites in the Central Tianshan Block (NW China): geochronology, geochemistry, and tectonic implications[J]. Journal of Arid Land, 2022, 14(1): 82-101.