Understanding the basin-scale hydrology and the spatiotemporal distribution of regional precipitation requires high precision, as well as high-resolution precipitation data. We have made an attempt to develop an Integrated Downscaling and Calibration (IDAC) framework to generate high-resolution (1km×1km) gridded precipitation data over high altitude mountain region of Indus Basin. Traditionally, GWR (Geographical weighted regression) model has widely been applied to generate high-resolution precipitation data for regional scales. The GWR model generally assumes a spatially varied relationships between precipitation and its associated environmental variables, however, the relationships need to remain constant (fixed) for some variables over space. In this study, a Mixed Geographically Weighted Regression (MGWR) model, capable of dealing with the fixed and spatially varied environmental variables, is proposed to downscale the Original-TRMM precipitation data from a coarse resolution (0.25 deg × 0.25 deg) to a high-resolution (1 km × 1 km) for the period of 2000–2018 over the Upper Indus Basin (UIB).
The comparison between the spatial precipitation patterns obtained from different datasets for the dry period (2002), normal period (2005), wet period (2010) and average of entire period (2000–2018). First, second and third columns represent the precipitation obtained from the Original-TRMM, downscaled data by the GWR model and downscaled data by the MGWR model respectively
Precipitation profile along the transect line (~750 km) drawn over the Original-TRMM and downscaled precipitation grids shows a very strong similarity in both datasets. However, spatial variations depicted by the downscaled precipitation data are obviously showing much clearer and variable trend along the line of transect which could be seen as uniform in the Original-TRMM precipitation
Conclusions: In general, the proposed IDAC approach is suitable for retrieving high spatial resolution gridded data for annual, monthly, and daily time scales over the UIB with varying climate and complex topography
Limitations and future directions: In general, the current research primarily focused on mainly improving the spatial (horizontal) information of precipitation from coarse resolution satellite observation over the high-altitude UIB; however, further work is needed to investigate the vertical distribution of precipitation, which is important in hydrological modeling studies over the upper glaciered catchments. Secondly, in most of the upper catchments with complex topography and sparse rain gauge stations, the observed precipitation is unreliable or unavailable; hence, poses a limitation to the application of remote sensing precipitation datasets in such regions. Therefore, the orographic correction of precipitation based on the vertical gradients along with glacier mass balance is required to retrieve an accurate precipitation dataset in high-altitude mountain regions.
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