Multi-station calibration strategy for evaluation and sensitivity analysis of the snowmelt runoff model using MODIS satellite images

Abstract

In this study, the snowmelt runoff model (SRM) was employed to estimate the effect of snow on the surface flow of Aji-Chay basin, northwest Iran. Two calibration techniques were adopted to enhance the calibration. The multi-station calibration (MSC) and single-station calibration (SSC) strategies applied to investigate their effects on the modeling accuracy. The runoff coefficients (cs and cr) were selected as calibration parameters because of their uncertainty in such an extended basin. To determine the most substantial input of the model which is the snow-covered area (SCA) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor imagery, MOD10A2 images were collected with spatial and temporal resolutions of 500 meters and 8 days, respectively. The results show an average of 15% improvement in the model performance in the MSC strategy from the data period of 2008–2012. Also, an appropriate agreement with physical characteristics of the study area could be seen for the calibration parameters. The contribution of snowmelt in the river flow reaches its peak in April and May, then with increasing temperature, the contribution decreased gradually. Furthermore, analysis of parameters indicates that the SRM is sensitive to recession coefficient and runoff coefficients. HIGHLIGHTS Conceptual SRM was employed to estimate the effect of snow on the surface flow.; Calibration performed via both single and multi-station methods.; MOD10A2 images were used to estimate snow cover of the basin.; The results show 15% improvement in modeling performance when using multistation calibration strategy.;

Keywords

• aji-chay
• modis snow-cover
• multi-station calibration
• remote sensing (rs)
• snowmelt runoff model (srm)