EGU General Assembly 2020
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the Creative Commons Attribution 4.0 License.

Satellite Data Application to Cover Lack of In-situ Observations for Mapping Precipitation and Direct Runoff in Semi-arid Basin

Mahdi Akbari and Ali Torabi Haghighi
Mahdi Akbari and Ali Torabi Haghighi
  • Water, Energy and Environmental Engineering Research Unit, Department of Technology, University of Oulu, Finland

Hydrological modeling in arid basins located in developing countries often lacks sufficient hydrological data because, e.g., rain gauges are typically absent at high elevations and inflow to ungauged areas around large closed lakes such as Lake Urmia is difficult to estimate. We tried to improve precipitation and runoff estimation in Lake Urmia, Iran as an arid basin using satellite-based data. We estimated precipitation using interpolation of rain gauge data by kriging, downscaling Tropical Rainfall Measuring Mission (TRMM), and cokriging interpolation of in-situ records with Remote Sensing (RS)-based data. Using RS-based data in estimations gave more precise results, by compensating for lack of data at high elevations. Cokriging interpolation of rain gauges by TRMM and Digitized Elevation Model (DEM) gave 4–9 mm lower Root Mean Square Error (RMSE) in different years compared with kriging. Downscaling TRMM improved its accuracy by 14 mm. Using the most accurate precipitation model, we modeled annual direct runoff with Kennessey and Soil Conservation Service Curve Number (SCS-CN) models. These models use land use, permeability, slope maps and climatic parameter (Ia) to represent the annual climatic condition of modeled basin in sense of wetness or dryness. In runoff modeling, Kennessey gave higher accuracy in annual scale. It was found that classification of years to wet, dry and normal states in Kennessey by default assumptions on Ia is not accurate enough for semi-arid basins so by solving this issue and calibration Kennessey model parameters, we made this model applicable for Urmia Lake basin. Calibrating Kennessey reduced the Normalized RMSE (NRMSE) from 1 in the standard model to 0.44. Direct runoff coefficient map by 1 km spatial resolution was generated by calibrated Kennessey. Validation by the closest gauges to the lake gave a NRMSE of 0.41 which approved the accuracy of modeling.

How to cite: Akbari, M. and Torabi Haghighi, A.: Satellite Data Application to Cover Lack of In-situ Observations for Mapping Precipitation and Direct Runoff in Semi-arid Basin, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13666,, 2020

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Display material version 1 – uploaded on 28 Apr 2020
  • CC1: precipitation estimation, Sina Khatami, 04 May 2020

    Hi Mahdi and Ali, and thanks for your display. 

    I have a question about precipitation estimation. Did you evaluate the precip estimation for the overall period 2006-2011, or on an annual (or seasonal) basis? 

    Given the high rainfall variability in this basin (both inter-annually and intra-annually), I wonder if you evaluate your estimation over the entire period the positive and negative biases in different years/months may cancel out. 

    • AC2: Reply to CC1, Mahdi Akbari, 04 May 2020

      Thank you Sina for you comment. we calculated precipitation annually so error did not cancel out each other. 

    • AC3: Reply to CC1, Mahdi Akbari, 04 May 2020

      we estimated precipitation in wet, normal and dry years by our method and we found the best method (co kriging of TRMM and in situ data) will result in best accuracy. 

      • CC2: Reply to AC3, Sina Khatami, 04 May 2020

        Thanks Mahdi jan for clarification!

        • AC4: Reply to CC2, Mahdi Akbari, 04 May 2020

          Dear Sina

          Can I participate in chat presentation? I supposed that I should be available here not chat presentation environment. 


          • CC3: Reply to AC4, Sina Khatami, 04 May 2020

            You weren't available at the time conveners called for your name. Timeline is strict so they had to move to next displays. I think at the end of the block, if there's time they will call you again, keep an eye. 

            • AC5: Reply to CC3, Mahdi Akbari, 04 May 2020

              please call me again. I was here in my presentation page instead of chat section. I am availble now in chat presentation page.


  • AC1: Comment on EGU2020-13666, Mahdi Akbari, 04 May 2020

    we utilized satellite based data to cover lack of in situ data for modeling runoff and precipitation in Urmi Lake basin. We applied SCS and Kennessey for runoff modeing and co kriging for precipitation which helped us to enhace the accuracy of modeling.