Watershed

Oral

393023 - EVALUATION OF SATELLITE-BASED PRECIPITATION ESTIMATES OVER AN AGRICULTURAL WATERSHED OF INDIA

Monday, June 4
4:00 PM - 5:30 PM
Location: Greenway IJ
Co-Authors: Ashish Pandey, ROORKEE – IIT ROORKEE; DEEN DAYAL, ROORKEE – IIT ROORKEE

Due to lack of watershed-wide hydrologic data from in situ platforms, whether they are real time or historical, water management has been quite challenging. Benefiting from the high spatio-temporal resolution and near-global coverage, satellite-based precipitation estimates (SPEs) provide an opportunity to enhance present hydrologic prediction capability for a watershed or river basin. In the present study, three different SPEs i.e., PERSIANN, CMORPH and TRMM precipitation datasets have been assessed over gauge-based India Meteorological Department (IMD) gridded dataset employing statistical and contingency table methods for an agricultural watershed of India. The detailed evaluation has been carried out for the years 1998–2013 on daily, monthly, seasonal and yearly basis with a spatial resolution of 0.25° × 0.25° latitude/longitude. SPEs performed reasonably well with the IMD gauge-based gridded dataset, although significant biases were observed. In general, the rainfall detection capability of SPEs were found better during monsoon season than non-monsoon season and annual time scale. A good correlation was found between watershed-averaged monthly precipitations of TRMM dataset against IMD gauge-based gridded dataset (R2 = 0.77) as compared to CMORPH (R2 = 0.63) and PERSIANN (R2 = 0.56) datasets. Overall, performance of TRMM precipitation dataset was found superior over CMORPH and PERSIANN datasets, however, due to error and bias in SPEs considerable inter-annual and seasonal variations were observed. The analysis indicates that the use of SPEs can be a compensating approach after suitable bias correction and it has potential for hydrologic simulation in data-sparse regions.

Sushil Kumar. Himanshu

RESEARCH SCHOLAR
IIT ROORKEE

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393023 - EVALUATION OF SATELLITE-BASED PRECIPITATION ESTIMATES OVER AN AGRICULTURAL WATERSHED OF INDIA



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