Hydrological evaluation of satellite and reanalysis precipitation products in the glacier-fed river basin (Gilgit)

Weather conditions and flow are frequently analyzed using the multisource precipitation products, where rain gauge network is not available or dispersed. This study has been designed to evaluate the precipitation and flow using rain gauges, satellite, and reanalysis data (TRMM 3B42RT v-7 and ERA-Int...

Full description

Saved in:
Bibliographic Details
Published in:Arabian journal of geosciences 2020-07, Vol.13 (14), Article 631
Main Authors: Abro, Mohammad Ilyas, Wei, Ming, Zhu, Dehua, Elahi, Ehsan, Ali, Gohar, Khaskheli, Murad Ali, Shah, Abid Raza, Nkunzimana, Athanase
Format: Article
Language:English
Subjects:
Atmospheric precipitations
Catchment area
Earth and Environmental Science
Earth science
Earth Sciences
Flood control
Food security
Gauges
Glaciers
Hydrologic data
Hydrology
Original Paper
Precipitation
Rain
Rain gauges
Rainfall
River basins
Rivers
Root-mean-square errors
Satellites
Spatial distribution
Sustainable development
TRMM satellite
Weather
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Weather conditions and flow are frequently analyzed using the multisource precipitation products, where rain gauge network is not available or dispersed. This study has been designed to evaluate the precipitation and flow using rain gauges, satellite, and reanalysis data (TRMM 3B42RT v-7 and ERA-Interim) over Gilgit (glacier fed), a river basin of northern Pakistan. Statistical matrices, such as Bias, Mean Absolute Error (MAE), Root Mean Square Error (RMSE), coefficient of determination ( R 2 ), and percentage (%) difference, were used to report the discrepancies in the precipitation and flow. Moreover, the spatial distribution, rain occurrence, and volume precipitation were used for further analysis. However, both sources showed ability to capture the pattern well. In the rain occurrence, light precipitation (< 1 mm/h) contributes more than 60% (October–March) and heavy precipitation (> 10 mm/h) shares more than 40% in total volume (April–September). Overall, the TRMM outperforms for precipitation estimation in the catchment. Moreover, the findings of the study would be helpful in controlling flood-causing disaster in this particular area and provide important information for sustainable development and to overcome food security and energy issues in the country. These findings indicate the potential of satellite and reanalysis data as alternative to rain gauge in many applications where data are not available or very limited.
ISSN:1866-7511
1866-7538
DOI:10.1007/s12517-020-05621-2