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Application of Remotely-Sensed Data to Estimate a Water Budget for Data-Scarce Endorheic Basins: A Case Study of Lake Urmia basin, Iran

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Abstract

Estimating the water budgets of large basins is a challenge because of the lack of data and information. It becomes more complicated in endorheic basins that consist of separate land and water phases. The application of remotely-sensed data is one solution in this regard. The present study addresses this issue and develops a modeling framework to evaluate a water budget based on remotely-sensed data for endorheic basins. To explore the methodology, Lake Urmia basin was selected as a case study. The lake water level has declined steeply since 1995 and stakeholders have agreed to allocate 3100 MCM of water per year to the lake. This makes it necessary to monitor river inflow into the lake to fulfill the agreement. Gauging stations have been employed around the lake, but they could not account for shortages such as water uptake below the stations. To do this, separate water budgets for the water body and the land were required. More specifically, it was necessary to estimate actual evapotranspiration (ET a ) from freshwater (E f ) and saltwater (E s ) estimated using the SEBAL model. Different methods were applied to estimate soil moisture, groundwater exploitation, and surface-groundwater inflow into the lake. A comparison of the observed and estimated amounts showed good agreement. For instance, the coefficient of determination for the observed/reported and estimated ET a and E f were 0.83 and 0.84, respectively. The average annual inflow was estimated to be 2.2 BCM/year for 2002–2008 using the RS model, which is about 84 % of the total inflow from the last recording stations before the lake and shows influence of water exploitation after these stations. Future study should focus on increasing temporal and spatial resolution of the method

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References

  • Abouali, R. (2012). Personal communication with the East Azarbaijan Regional Water Company, Tabriz.

  • Ahmad, M.D. (2002). Estimation of net groundwater use in irrigated river basins using geo-information techniques: A case study in Rechna Doab, Pakistan. PhD Thesis, Wageningen University, Wageningen, p 144.

  • Ahmad, M. D., & Bastiaanssen, W. (2003). Retrieving soil moisture storage in the unsaturated zone using satellite imagery and bi-annual phreatic surface fluctuations. Journal of Irrigation and Drainage Engineering, 17(3), 141–161.

    Article  Google Scholar 

  • Ahmad, M. D., Bastiaanssen, W. G., & Feddes, R. A. (2005). A new technique to estimate net groundwater use across large irrigated areas by combining remote sensing and water balance approaches, Rechna Doab, Pakistan. Hydrogeology Journal, 13(5–6), 653–664.

    Article  Google Scholar 

  • Allen, R.G., & Tasumi, M. (2005). Evaporation from American Falls Reservoir in Idaho via a combination of Bowen ratio and eddy covariance. Proceedings of the EWRI World Water and Environmental Resources Congress, 15–19.

  • Anderson, M. C., Norman, J., Diak, G., Kustas, W., & Mecikalski, J. (1997). A two-source time-integrated model for estimating surface fluxes using thermal infrared remote sensing. Remote Sensing of Environment, 60(2), 195–216.

    Article  Google Scholar 

  • Bagheri, M.H. (2012). Assessment of remote sensing technique for estimation of water balance components in basin scale, emphasizing on net groundwater exploitation: a case study on Urmia lake basin. Master of Science Thesis, Universityof Tarbiat Modares, p 126.

  • Bagheri, M. H., Arshad, S., Majnuni, A., & Morid, S. (2012). A comparison of single-source and two-source energy fluxes models to estimate actual evapotranspiration in Tabriz Plain. Iranian Journal of RS and GIS, 4(1), 81–96.

    Google Scholar 

  • Bagheri, M. H., Morid, S., & Arshad, S. (2015). Assessment of remote sensing SEBAL algorithm to estimate actual evapotranspiration in different land uses: a case study in Urmia Lake basin. Iranian Water Research Journal, 4(7), 11.

    Google Scholar 

  • Bastiaanssen, W. (2000). SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin, Turkey. Journal of Hydrology, 229(1), 87–100.

    Article  Google Scholar 

  • Bastiaanssen, W., Menenti, M., Feddes, R., & Holtslag, A. (1998). A remote sensing surface energy balance algorithm for land (SEBAL): 1. Formulation. Journal of Hydrology, 212, 198–212.

    Article  Google Scholar 

  • Bastiaanssen, W. G., Molden, D. J., & Makin, I. W. (2000). Remote sensing for irrigated agriculture: examples from research and possible applications. Agricultural Water Management, 46(2), 137–155.

    Article  Google Scholar 

  • Bastiaanssen, W., Noordman, E., Pelgrum, H., Davids, G., Thoreson, B., & Allen, R. (2005). SEBAL model with remotely sensed data to improve water-resources management under actual field conditions. Journal of Irrigation and Drainage Engineering, 131(1), 85–93.

    Article  Google Scholar 

  • Burba, G., Verma, S., & Kim, J. (1999). Surface energy fluxes of Phragmites australis in a prairie wetland. Agricultural and Forest Meteorology, 94(1), 31–51.

    Article  Google Scholar 

  • CIWP (2009) Conservation of Iranian Wetlands Project UNDP/GEF, Annual Progress Report, URL: http://wetlandsproject.ir/English/enshowfiles.aspx?attachid=1345

  • Eimanifar, A., & Mohebbi, F. (2007). Urmia Lake (Northwest Iran): a brief review. Saline Systems, 3, 5. doi:10.1186/1746-1448-3-5.

    Article  Google Scholar 

  • Eltahir, E. A. (1998). A soil moisture–rainfall feedback mechanism: 1. Theory and observations. Water Resources Research, 34(4), 765–776.

    Article  Google Scholar 

  • Farrokhnia, A. & Morid, S. (2013). Study of landuse change in the lake urmia basin base on landsat-tm images and pixel-based and object-based classification methods. Iranian Journal of Watershed Management Research, 13 (In Press).

  • Findell, K. L., & Eltahir, E. A. (1997). An analysis of the soil moisture-rainfall feedback based on direct observations from Illinois. Water Resources Research, 33(4), 725–735.

    Article  Google Scholar 

  • Food and Agriculture Organization of the United Nations. (1995). Digital soil map of the world and derived soil properties. Version 3.5. Rome: FAO.

    Google Scholar 

  • Gafurov, A. (2010). Water balance modeling using remote sensing information: focus on Central Asia. Ph. D Thesis, University of Stuttgart, Stuttgart, p. 153.

  • Gillies, R. R., & Carlson, T. N. (1995). Thermal remote sensing of surface soil water content with partial vegetation cover for incorporation into climate models. Journal of Applied Meteorology, 34(4), 745–756.

    Article  Google Scholar 

  • Iranian Ministry of Energy (IME) (2005). Environmental consequences of water resources development projects of Urmia basin on Urmia Lake, Volume 2: Urmia Lake water balance. Research Report No.36280-123. (In Persian).

  • Iranian Ministry of Energy (IME) (2005). Environmental consequences of water resources development projects of Urmia basin on Urmia Lake, Volume 1: Estimation of inflows to the lake. Research Report No.36280-123. (In Persian).

  • Iranian Ministry of Energy (IME) (2011). Updating the integrated water plan, agricultural and economic study of the lake Urmia basin. Research Report No. 3385070-4140. (In Persian).

  • Jayawickreme, D.H., Van Dam, R.L., & Hyndman, D.W. (2008). Subsurface imaging of vegetation, climate, and root zone moisture interactions. Geophysical Research Letters, 35(18). doi:10.1029/2008GL034690.

  • Khatami, S., & Berndtsson, R. (2013). Urmia Lake watershed restoration in Iran: short-and long-term perspectives. In 6th International Perspective on Water Resources & the Environment conference (IPWE 2013). Environmental & Water Resources Institute (EWRI)/American Society of Civil Engineers (ASCE).

  • Machiwal, D., Jha, M. K., & Mal, B. C. (2011). Assessment of groundwater potential in a semi-arid region of India using remote sensing, GIS and MCDM techniques. Water Resources Management, 25(5), 1359–1386.

    Article  Google Scholar 

  • Muthuwatta, L., Bos, M., & Rientjes, T. (2010). Assessment of water availability and consumption in the Karkheh River basin, Iran using remote sensing and geo-statistics. Water Resources Management, 24(3), 459–484.

    Article  Google Scholar 

  • Nichols, S., Zhang, Y., & Ahmad, A. (2011). Review and evaluation of remote sensing methods for soil-moisture estimation. Journal of Photonics for Energy, 2(1), 18.

    Google Scholar 

  • Norman, J. M., Kustas, W. P., & Humes, K. S. (1995). Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature. Agricultural and Forest Meteorology, 77(3), 263–293.

    Article  Google Scholar 

  • Roerink, G., Jacobs, C., & Hammani, A. (2009). Assessment of groundwater extraction in the Tadla irrigated perimeter (Morocco) using the SSEBI remote sensing algorithm. Presented at the 23rd European Regional Conference of the ICID, 18–24 May 2009, Lviv, Ukraine.

  • Schmugge, T. J., Kustas, W. P., Ritchie, J. C., Jackson, T. J., & Rango, A. (2002). Remote sensing in hydrology. Advances in Water Resources, 25(8), 1367–1385.

    Article  Google Scholar 

  • Scott, C. A., Bastiaanssen, W. G., & Ahmad, M. D. (2003). Mapping root zone soil moisture using remotely sensed optical imagery. Journal of Irrigation and Drainage Engineering, 129(5), 326–335.

    Article  Google Scholar 

  • Šimůnek, J. K., Huang, A. M. T., & Genuchten, V. (1998). The HYDRUS code for simulating the one-dimensional movement of water, heat, and multiple solutes in variably-saturated media. Version 6.0. Research Report No. 144 (p. 164). Riverside: U.S. Salinity Laboratory, USDA, ARS.

    Google Scholar 

  • Su, Z. (2002). The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes. Hydrology and Earth System Sciences (HESS), 6(1), 85–100.

    Article  Google Scholar 

  • Taghvaeian, S., & Neale, C. M. (2011). Water balance of irrigated areas: a remote sensing approach. Hydrolical Processes, 25(26), 4132–4141.

    Article  Google Scholar 

  • UNEP, GEAS. (2012). The drying of Iran’s Lake Urmia and its environmental consequences. Journal of Environmental Development, 2, 128–137.

    Article  Google Scholar 

  • Waters, R., Allen, R., Tasumi, M., Trezza, R., & Bastiaanssen, W. (2002). SEBAL: Surface Energy Balance Algorithms for Land Idaho implementation, advance training and users manual. Boise: Department of Water Resources.

    Google Scholar 

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Authors and Affiliations

  1. Department of Water Resources Engineering, Tarbiat Modares University, Tehran, Iran

    MohammadHossein Bagheri

  2. Department of Water Resources Engineering, Tarbiat Modares University, P.O.Box 14115-336, Tehran, Iran

    Saeid Morid

  3. Department of Water Engineering, Gilan University, Rasht, Iran

    Saleh Arshad

Authors
  1. MohammadHossein Bagheri
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  2. Saeid Morid
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  3. Saleh Arshad
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Correspondence to Saeid Morid.

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Bagheri, M., Morid, S. & Arshad, S. Application of Remotely-Sensed Data to Estimate a Water Budget for Data-Scarce Endorheic Basins: A Case Study of Lake Urmia basin, Iran. J Indian Soc Remote Sens 45, 101–112 (2017). https://doi.org/10.1007/s12524-015-0522-9

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  • DOI: https://doi.org/10.1007/s12524-015-0522-9

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