Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 529-541, 2015
https://doi.org/10.5194/isprsarchives-XL-1-W5-529-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
11 Dec 2015
ASSESSMENT OF RAINFALL-RUNOFF SIMULATION MODEL BASED ON SATELLITE ALGORITHM
A. R. Nemati1, M. Zakeri Niri1, and S. Moazami2 1Young Researchers and Elite Club, Islamshahr Branch, Islamic Azad University, Islamshahr, Iran
2Department of Civil Engineering, Islamshahr branch, Islamic Azad University, Islamshahr, Iran
Keywords: Tamar station, Simulation runoff, satellite rainfall data, Data-driven models, Conceptual models, Svr Abstract. Simulation of rainfall-runoff process is one of the most important research fields in hydrology and water resources. Generally, the models used in this section are divided into two conceptual and data-driven categories. In this study, a conceptual model and two data-driven models have been used to simulate rainfall-runoff process in Tamer sub-catchment located in Gorganroud watershed in Iran. The conceptual model used is HEC-HMS, and data-driven models are neural network model of multi-layer Perceptron (MLP) and support vector regression (SVR). In addition to simulation of rainfall-runoff process using the recorded land precipitation, the performance of four satellite algorithms of precipitation, that is, CMORPH, PERSIANN, TRMM 3B42 and TRMM 3B42RT were studied. In simulation of rainfall-runoff process, calibration and accuracy of the models were done based on satellite data. The results of the research based on three criteria of correlation coefficient (R), root mean square error (RMSE) and mean absolute error (MAE) showed that in this part the two models of SVR and MLP could perform the simulation of runoff in a relatively appropriate way, but in simulation of the maximum values of the flow, the error of models increased.
Conference paper (PDF, 1632 KB)


Citation: Nemati, A. R., Zakeri Niri, M., and Moazami, S.: ASSESSMENT OF RAINFALL-RUNOFF SIMULATION MODEL BASED ON SATELLITE ALGORITHM, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 529-541, https://doi.org/10.5194/isprsarchives-XL-1-W5-529-2015, 2015.

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