Satellite-Based Precipitation Datasets Evaluation Using Gauge Observation and Hydrological Modeling in a Typical Arid Land Watershed of Central Asia
Open Access
- 11 January 2021
- journal article
- research article
- Published by MDPI AG in Remote Sensing
- Vol. 13 (2), 221
- https://doi.org/10.3390/rs13020221
Abstract
Hydrological modeling has always been a challenge in the data-scarce watershed, especially in the areas with complex terrain conditions like the inland river basin in Central Asia. Taking Bosten Lake Basin in Northwest China as an example, the accuracy and the hydrological applicability of satellite-based precipitation datasets were evaluated. The gauge-adjusted version of six widely used datasets was adopted; namely, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (CDR), Climate Hazards Group Infrared Precipitation with Stations (CHIRPS), Global Precipitation Measurement Ground Validation National Oceanic and Atmospheric Administration Climate Prediction Center (NOAA CPC) Morphing Technique (CMORPH), Integrated Multi-Satellite Retrievals for GPM (GPM), Global Satellite Mapping of Precipitation (GSMaP), the Tropical Rainfall Measuring Mission (TRMM) and Multi-satellite Precipitation Analysis (TMPA). Seven evaluation indexes were used to compare the station data and satellite datasets, the soil and water assessment tool (SWAT) model, and four indexes were used to evaluate the hydrological performance. The main results were as follows: 1) The GPM and CDR were the best datasets for the daily scale and monthly scale rainfall accuracy evaluations, respectively. 2) The performance of CDR and GPM was more stable than others at different locations in a watershed, and all datasets tended to perform better in the humid regions. 3) All datasets tended to perform better in the summer of a year, while the CDR and CHIRPS performed well in winter compare to other datasets. 4) The raw data of CDR and CMORPH performed better than others in monthly runoff simulations, especially CDR. 5) Integrating the hydrological performance of the uncorrected and corrected data, all datasets have the potential to provide valuable input data in hydrological modeling. This study is expected to provide a reference for the hydrological and meteorological application of satellite precipitation datasets in Central Asia or even the whole temperate zone.Funding Information
- National Natural Science Foundation of China (41761144079)
This publication has 63 references indexed in Scilit:
- The Global Precipitation Measurement MissionBulletin of the American Meteorological Society, 2014
- The climate of daily precipitation in the Alps: development and analysis of a high‐resolution grid dataset from pan‐Alpine rain‐gauge dataInternational Journal of Climatology, 2013
- Climate change impact on water resource extremes in a headwater region of the Tarim basin in ChinaHydrology and Earth System Sciences, 2011
- Hydrologic evaluation of satellite precipitation products over a mid-size basinJournal of Hydrology, 2011
- Real-time remote sensing driven river basin modeling using radar altimetryHydrology and Earth System Sciences, 2011
- Statistical Methods in the Atmospheric SciencesJournal of the American Statistical Association, 2007
- Using a geographic information system to improve Special Sensor Microwave Imager precipitation estimates over the Tibetan PlateauPublished by American Geophysical Union (AGU) ,2004
- Validation and Uncertainty Analysis of Satellite Rainfall AlgorithmsThe Professional Geographer, 2000
- Impact of small-scale spatial rainfall variability on runoff modelingJournal of Hydrology, 1995
- River flow forecasting through conceptual models part I — A discussion of principlesJournal of Hydrology, 1970