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Discussion papers | Copyright
https://doi.org/10.5194/hess-2018-318
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 25 Jul 2018

Research article | 25 Jul 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).

Quantifying the impacts of human water use and climate variations on recent drying of Lake Urmia basin: the value of different sets of spaceborne and in-situ data for calibrating a hydrological model

Seyed-Mohammad Hosseini-Moghari1, Shahab Araghinejad1, Mohammad J. Tourian2, Kumars Ebrahimi1, and Petra Döll3,4 Seyed-Mohammad Hosseini-Moghari et al.
  • 1Department of Irrigation and Reclamation Engineering, University of Tehran, Karaj, Iran
  • 2University of Stuttgart, Institute of Geodesy (GIS), Stuttgart, Germany
  • 3Institute of Physical Geography, Goethe University Frankfurt, Frankfurt am Main, Germany
  • 4Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Frankfurt am Main, Germany

Abstract. During the last decades, the endorheic Lake Urmia basin in northwestern Iran has suffered from decreased precipitation, groundwater levels and a very strong reduction in the volume and more recently also in the extent of Lake Urmia. Human water use has exacerbated the desiccating impact of climatic variations. This study quantifies the contribution of human water use to the reduction of inflow into Lake Urmia, to the loss of lake water volume and to the loss of groundwater and total water storage in the entire Lake Urmia basin during 2003–2013. To this end, the WaterGAP Global Hydrology Model (WGHM) was manually calibrated specifically for the basin against multiple in-situ and spaceborne data, and the best-performing calibration variant was run with or without taking into account water use. Observation data encompass remote-sensing based time series of annual irrigated area in the basin from MODIS, monthly total water storage anomaly (TWSA) from GRACE satellites and monthly lake volume. In-situ observations include time series of annual inflow into the lake and basin averages of groundwater level variations based on 284 wells. In addition, local estimates of sectoral water withdrawals in 2009 and return flow fractions were utilized. Four calibration variants were set up in which the number of considered observation types was increased in a stepwise fashion. The best fit to each and all observations is achieved if the maximum amount of observations is used for calibration. Calibration against GRACE TWSA improves simulated inflow into Lake Urmia but still overestimates it by 90%; it results in an overestimation of lake volume loss, underestimation of groundwater loss and a shifted seasonality of groundwater storage. Lake and groundwater dynamics can only be simulated well if calibration against groundwater levels leads to adjusting the fractions of human water use from groundwater and surface water. According to our study, human water use was the reason for 50% of the total basin water loss of about 10km3 during 2003–2013, for 40% of the Lake Urmia water loss of about 8km3 and for up to 90% of the groundwater loss. Lake inflow was 40% less than it would have been without human water use. We found that even without human water use, Lake Urmia would not have recovered from the significant loss of lake water volume caused by the drought year 2008. These findings may serve to support water management in the basin and more specifically Lake Urmia restoration plans.

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This paper studies the value of different datasets in calibration of a hydrological model for determining the role of human water use and climate variations regarding recent loss of water storage in Lake Urmia basin, Iran. Based on the results, for a holistic modeling, at least remote sensing, discharge and groundwater levels data are required. We found that even without human water use, Lake Urmia could not recover after the significant loss of lake volume caused by the drought in year 2008.
This paper studies the value of different datasets in calibration of a hydrological model for...
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