نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه محیط زیست، دانشکده محیط زیست، پردیس دانشکده های فنی دانشگاه تهران، تهران، ایران

2 دانشیار، گروه محیط زیست، دانشکده محیط زیست، پردیس دانشکده های فنی دانشگاه تهران، تهران، ایران

3 استاد، گروه محیط زیست، دانشکده محیط زیست، پردیس دانشکده‌های فنی دانشگاه تهران، تهران، ایران

4 استاد، گروه محیط زیست، دانشکده محیط زیست، پردیس دانشکده های فنی دانشگاه تهران، تهران، ایران

چکیده

منابع آب همیشه به‌عنوان یک عامل محدودکننده در برنامه­ریزی­ محیط­زیست نقش دارد. شناخت وضعیت این منبع مهم می­تواند تأثیر زیادی در برنامه­ریزی صحیح استفاده از سرزمین را داشته باشد. هدف از این پژوهش برآورد میزان عرضه و تقاضای آب به‌عنوان یک خدمت اکوسیستمی و شناسایی مناطق دارای تنش آبی در سطح حوضه آبریز مرزی سیروان بود. این کار با بهره­گیری از مفهوم خدمات اکوسیستمی که تفکری نوین در علوم زمین است و با استفاده از داده­های جغرافیایی، اقلیمی و تصاویر ماهواره­ای قابل انجام است. در این راستا ابتدا تصاویر ماهواره­ی لندست برای سال 2019 پس از انجام تصحیحات مختلف آماده­سازی و نقشه کاربری اراضی تولید شد. سپس اطلاعات بارش، تبخیر و تعرق، عمق ریشه، ضرایب تبخیر و تعرق پوشش زمین و جدول­های مربوطه آماده­سازی و در محیط نرم­افزار InVEST 3.8.9 مدل­سازی شد. نتایج نشان داد که مقدار تولید آب در این حوضه Mm3/yr 5380 است که زیرحوضه­های 5، 11 و 1 دارای بیش­ترین میزان تولید آب با 1426، 906 و Mm3/yr 631؛ و زیرحوضه شماره 2 با Mm3/yr 100 دارای کم­ترین تولید آب هستند. زیرحوضه شماره 5 با Mm3/yr 110 دارای بیش­ترین میزان مصرف و زیرحوضه شماره دو با Mm3/yr 7 دارای کم­ترین میزان مصرف است. بر اساس محاسبات تولید و مصرف، زیرحوضه 4 دارای بیش­ترین مشکلات در تأمین آب است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Water Resources Supply and Demand Modeling using the Concept of Ecosystem Services in Sirvan Transboundary Basin

نویسندگان [English]

  • Jahanbakhsh Balist 1
  • Bahram Malek Mohammadi 2
  • Hamid Reza Jafari 3
  • Ahmad Nohegar 4

1 Ph.D. Scholar, Department of Environment, Faculty of Engineering, University of Tehran, Tehran, Iran

2 Assoc. Professor, Department of Environment, Faculty of Engineering, University of Tehran, Tehran, Iran

3 Professor, Department of Environment, Faculty of Engineering, University of Tehran, Tehran, Iran

4 Professor, Department of Environment, Faculty of Engineering, University of Tehran, Tehran, Iran

چکیده [English]

Water resources have always been a limiting factor in environmental planning. Understanding the status of this critical resource can have a significant impact on proper land use planning. This study aimed to estimate the water supply and demand as an ecosystem service and to identify areas with water stress in the Sirvan transboundary basin. This goal could be achieved using the concept of ecosystem services, which is new thinking in the earth sciences, and using geographical, climatic data, and satellite images. After relative corrections, Landsat satellite images for 2019 were prepared, and the LULC map was produced. Then precipitation, evapotranspiration, and root depth layers were created. The latest inputs, including the Evapotranspiration coefficients of the land cover and related tables, were prepared and modeled in the InVEST 3.8.9 software environment. The results showed that the amount of water yield in this watershed is 5,381 million m3/yr, where the sub-basin 5, 11, and 1 have the highest water yield with 1426, 906, and 621 million m3/yr. and sub-basin 2 with 100 million m3/yr have the lowest water yield. The sub-basin 5 with 110 million m3/yr has the highest consumption, and the sub-basin 2 with 7 Mm3/yr has the lowest consumption. Sub-basin 4, where the city of Sanandaj is located, has the highest water stress.

کلیدواژه‌ها [English]

  • Ecosystem Services
  • InVEST
  • Land Use Planning
  • Sirvan Watershed
  • Water Resources
Akoko, G., Kato, T. and Tu, L. H. (2020). Evaluation of irrigation water resources availability and climate change impacts—A Case Study of Mwea Irrigation Scheme, Kenya. Water. 12, 2330.
Bonan, G. (2015). Ecological Climatology: Concepts and Applications; Cambridge University Press: Cambridge, UK. 68pp.
Brauman, K. A. (2015). Hydrologic ecosystem services: Linking ecohydrologic processes to human well-being in water research and watershed management. Water, 2, 345–358.
Brisbane Declaration. (2007). The Brisbane Declaration: Environmental flows are essential for freshwater ecosystem health and human well-being. In 10th International River Symposium, Brisbane, 3-6.
Brouziyne, Y., Abouabdillah, A., Chehbouni, A., Hanich, L., Bergaoui, K., McDonnell, R. and Benaabidate, L. (2020). Assessing hydrological vulnerability to future droughts in a mediterranean watershed: combined indices-based and distributed modeling approaches. Water, 12, 2333.
Brown, C. M., Lund, J. R., Cai, X., Reed, P. M., Zagona, E. A., Ostfeld, A., Hall, J., Characklis, G. W., Yu, W. and Brekke, L. (2015). The future of water resources systems analysis: Toward a scientific framework for sustainable water management. Water Resour. Res. 51 (8), 6110–6124. doi.org/10.1002/2015WR017114.
Canqiang, Z., Wenhua, L., Biao, Z. and Moucheng, L. (2012). Water yield of Xitiaoxi River Basin based on INVEST modeling. J. Resour. Ecol., 3(1), 50-54. DOI:10.5814/j.issn.1674764x.2012.01.008.
Chen, Y., Wang, K., Lin, Y., Shi, W., Song, Y. and He, X. (2015). Balancing green and grain trade. Nat. Geosci. 8, 739–741.
Coe, M. T. and Foley J. A. (2001), Human and natural impacts on the water resources of the Lake Chad basin, J. Geophys. Res. 106(D4), 3349–3356.
De Groot, R. S., Alkemade, R., Braat, L., Hein, L. and Willemen, L. (2010). Challenges in integrating the concept of ecosystem services and values in landscape planning. management and decision making. Ecol. Complex., 7(3), 260-272. doi.org/10.1016/j.ecocom.2009.10.006.
Donohue, R. J., Roderick, M. L. and McVicar, T. R. (2012). Roots, storms and soil pores: Incorporating key ecohydrological processes into Budyko’s hydrological model. J. Hydrol., 436, 35- 50. doi.org/10.1016/j.jhydrol.2012.02.033.
Emamifar, S., Davari, K., Ansari, H., Ghahraman, B., Hosseini, S., Nasseri, M. (2016). Uncertainty assessment DWB model by using GLUE method (Case study: Andrabi and Farvbrman catchments). Journal of Soil and Water Resources Conservation, 6(1), 125-143.
Furat, A. M., Al-Faraj. and Scholz, M. (2015). Impact of upstream anthropogenic river regulation on downstream water availability in transboundary river watersheds. Int. J. Wat Resour. Develop., 31(1), 28-49, DOI: 10.1080/07900627.2014.924395.
Gheewala, S., Silalertusksa, T., Nilsalab, P., Mungkung, R., Perret, S. R. and Chaiyawannakarn N. (2014). Water footprint and impact of water consumption for food, feed, fuel crops production in Thailand. Water, 6, 1698–1718.
Haiping, L., Yanan, Q. and Yunying, Q. (2018). Use a spatial analysis model to assess habitat quality in Lashihai watershed. J. Resour. Ecol., 9(6), 622–632.
Hu, W., Li, G., Gao, Z., Jia, G., Wang, Z. and Li, Y. (2020). Assessment of the impact of the Poplar Ecological Retreat Project on water conservation in the Dongting Lake wetland region using the InVEST model. Sci. Tot. Environ., 733, 139423. doi.org/10.1016/j.scitotenv.2020.139423.
Jewitt, G. (2020). Can integrated water resources management sustain the provision of ecosystem goods and services? Phys. Chem. Earth. 27, 887–895.
Gao J., Christensen, P. and Li, W. (2017). Application of the WEAP model in strategic environmental assessment: Experiences from a case study in an arid/semi-arid area in China. J. Environ. Manag., 198, 363-371,  doi.org/10.1016/j.jenvman.2017.04.068.
Kindu, M., Schneider, T., Teketay, D. and Knoke, T. (2016). Changes of ecosystem service values in response to land use/land cover dynamics in Munessa– Shashemene landscape of the Ethiopian highlands. Sci. Tot. Environ., 547, 137-147. doi.org/10.1016/j.scitotenv.2015.12.127.
Landell-Mills, N. and Porras, I. (2002). Silver bullets or fools’ gold? a global review of markets for forest environmental services and their impact on the poor. International Institute for Environment and Development, London, UK.
Lang, Y., Song, W., and Deng, X. (2017). Projected land use changes impacts on water yields in the karst mountain areas of China. Phys. Chem. Ear., 104, 66-75. DOI:10.1016/j.pce.2017.11.001.
Li, Y., Piao, S., Li, L. Z. X., Chen, A., Wang, X., Ciais, P., Huang, L., Lian, X., Peng, S. and Zeng, Z. (2018). Divergent hydrological response to large-scale afforestation and vegetation greening in China. Sci. Adv., 4(5), eaar4182.
Liang, X., Lettenmaier, D. P., Wood, E. F. and Burges, S. J. (1994). A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J. Geoph. Res. Atm., 99(14), 14415-14428. DOI: 10.1029/94JD00483.
Lu, N., Sun, G., Feng, X. M., and Fu, B. J. (2013). Water yield responses to climate change and variability across the North-South Transect of Eastern China (NSTEC). J. Hydrol., 481, 96–105.
Lalika, M. C. S., Meire, P., Ngaga, Y. M. and Chang’a, L. (2015), Understanding watershed dynamics and impacts of climate change and variability in the Pangani River Basin, Tanzania, Ecohydol. Hydrobio., 15, 26–38. doi.org/10.1016/j.ecohyd.2014.11.002.
McDonnel, R. A. (2008). Challenges for integrated water resources management: how do we provide the knowledge to support truly integrated thinking? Int. J. Water Resour. Develop., 24(1), 131–143.
Ndiaye, P.M., Bodian, A., Diop, L., Deme, A., Dezetter, A., Djaman, K., Ogilvie, A. Trend and Sensitivity Analysis of Reference Evapotranspiration in the Senegal River Basin Using NASA Meteorological Data. Water 2020, 12, 1957. https://doi.org/10.3390/w12071957
Nilsson, C., Reidy, C. A., Dynesius, M. and Revenga C. (2005). Fragmentation and flow regulation of the World’s large river systems. Sci.,  308, 405–408. doi:10.1126/science.1107887.
Pessacg, N., Flaherty, S., Brandizi, L., Solman, S. and Pascual, M. (2015). Getting water right: A case study in water yield modelling based on precipitation data. Sci. Tot. Environ., 537, 225-234. doi.org/10.1016/j.scitotenv.2015.07.148.
Petpongpan, C., Ekkawatpanit, C. and Kositgittiwong, D. (2020). Climate Change Impact on Surface Water and Groundwater Recharge in Northern Thailand. Water, 12, 1029.
Yariyan, P., Avand, M., Abbaspour, R. A.,  Karami, M. and Tiefenbachere, J. P. (2020), GIS-based spatial modeling of snow avalanches using four novel ensemble models. Sci. Tot. Environ., 745(25), 141008. doi.org/10.1016/j.scitotenv.2020.141008.
Piao, S., Ciais, P., Huang, Y., Shen, Z., Peng, S., Li, J., Zhou, L., Liu, H., Ma, Y. and Ding, Y. (2010). The impacts of climate change on water resources and agriculture in China. Nat., 467, 43–51.
Rahimi, L., Malekmohammadi, B. and Yavari, A. R. (2020). Assessing and modeling the impacts of wetland land cover changes on water provision and habitat quality ecosystem services. Nat. Resour. Res., 29, 3701–3718.10.1007/s11053- 020-09667-7.
Redhead, J. W., Stratford, C., Sharps, K., Jones, L., Ziv, G., Clarke, D., Oliver, T. H., Bullock, J. M. (2016). Empirical validation of the InVEST water yield ecosystem service model at a national scale. Sci. Tot. Environ., 569–570, 1418-1426.
Sallustio, L., De Toni, A., Strollo, A., Di Febbraro, M., Gissi, E., Casella, L., Geneletti, D., Munafò, M., Vizzarri M. and Marchetti M. (2017). Assessing habitat quality in relation to the spatial distribution of protected areas in Italy. J. Environ. Manage., 201, 129–137.
Schaller, J., Cramer, A., Carminati, A. and Zarebandkouki M. (2020). Biogenic amorphous silica as main driver for plant available water in soils. Sci Rep 10, 2424. https://doi.org/10.1038/s41598-020-59437
Sharp, R., Tallis, H. T., Ricketts, T., Guerry, A. D., Wood, S. A. and Chaplin-Kramer, R. (2019). InVEST 3.7.0 Users Guide. The Natural Capital Project. Stanford University, University of Minnesota, the Nature Conservancy. and World Wildlife Fund.
Sharp, R., Tallis, H. T., Ricketts, T., Guerry, A. D., Wood, S. A., Chaplin- Kramer, R., Nelson, E., Ennaanay, D., Wolny, S., Olwero, N. and Vigerstol, K. (2014). InVEST user’s guide. The Natural Capital Project. Stanford. 161pp.
Shrestha, M., Leigh, L. and Helder, D. (2018). Classification of north Africa for use as an extended pseudo invariant calibration sites (EPICS) for radiometric calibration and stability monitoring of optical satellite sensors. Remote Sens., 11, 875.
Solanes, M. and Gonzales-Villareal, F. (1999). The Dublin principles for water as reflected in a comparative assessment of institutional and legal arrangements for integrated water resources management. Global water partnership technical advisory committee Background Paper No. 3 48 pp.
Tao, J. I. N., Xiaoyu Q. and Liyan, H. (2016). Changes in grain production and the optimal spatial allocation of water resources in China. J. Resour. Ecol., 7(1), 28-35. DOI: 10.5814/j.issn.1674- 764X.2016.01.004.
Yang, X., Chen, R., Meadows, M. E., Ji, G. and Xu J. (2020). Modelling water yield with the InVEST model in a data scarce region of northwest China. Water Suppl., 20(3), 1035–1045. doi: https://doi.org/10.2166/ws.2020.026
Xu, X., Liu, W., Scanlon, B. R., Zhang, L. and Pan, M. (2013). Local and global factors controlling water‐energy balances within the Budyko framework. Geophys. Res. Lett., 40(23), 6123-6129. doi:10.1002/2013GL058324, 2013.
Yang, D., Liu, W., Tang, L., Chen, L., Li, X. and Xu, X. (2019). Estimation of water provision service for monsoon catchments of South China: Applicability of the InVEST model, Landscape Urban Plan., 182, 133-143. https://doi.org/10.1016/j.landurbplan.2018.10.011.
Ye, L. and Grimm, N. B. (2013). Modelling potential impacts of climate change on water and nitrate export from a mid-sized, semiarid watershed in the US Southwest. Clima. Change, 120(1–2), 419–431.
Yin, G., Wang, X., Zhang, X., Fu, Y., Hao, F. and Hu, Q. (2020). InVEST model-based estimation of water yield in north China and its sensitivities to climate variables. Water, 12, 1692.
Zhang, L., Hickel, K., Dawes, W. R., Chiew, F. H., Western, A. W. and Briggs, P. R. (2004). A rational function approach for estimating mean annual evapotranspiration. Water Resour. Res., 40(2), W02502. https://doi.org/10.1029/2003WR002710.
Zhang, L., Cheng, L., Chiew, F. and Fu, B. (2018). Understanding the impacts of climate and landuse change on water yield. Curr. Opin. Environ. Sustain., 33. 167–174.