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Title: Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau

Abstract

On the Tibetan Plateau, the limited ground-based rainfall information owing to a harsh environment has brought great challenges to hydrological studies. Satellite-based rainfall products, which allow for a better coverage than both radar network and rain gauges on the Tibetan Plateau, can be suitable alternatives for studies on investigating the hydrological processes and climate change. In this study, a newly developed daily satellite-based precipitation product, termed Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks $$-$$ Climate Data Record (PERSIANN-CDR), is used as input for a hydrologic model to simulate streamflow in the upper Yellow and Yangtze River basins on the Tibetan Plateau. The results show that the simulated streamflows using PERSIANN-CDR precipitation and the Global Land Data Assimilation System (GLDAS) precipitation are closer to observation than that using limited gauge-based precipitation interpolation in the upper Yangtze River basin. The simulated streamflow using gauge-based precipitation are higher than the streamflow observation during the wet season. In the upper Yellow River basin, gauge-based precipitation, GLDAS precipitation, and PERSIANN-CDR precipitation have similar good performance in simulating streamflow. Finally, the evaluation of streamflow simulation capability in this study partly indicates that the PERSIANN-CDR rainfall product has good potential to be a reliablemore » dataset and an alternative information source of a limited gauge network for conducting long-term hydrological and climate studies on the Tibetan Plateau.« less

Authors:
 [1];  [2];  [2];  [3];  [2]
  1. Chinese Academy of Sciences (CAS), Beijing (China). Key Lab. of Water Cycle & Related Land Surface Process, Inst. of Geographic Sciences and Natural Resources Research; Univ. of California, Irvine, CA (United States). Dept. of Civil and Environmental Engineering
  2. Univ. of California, Irvine, CA (United States). Dept. of Civil and Environmental Engineering
  3. Chinese Academy of Sciences (CAS), Beijing (China). Key Lab. of Water Cycle & Related Land Surface Process, Inst. of Geographic Sciences and Natural Resources Research
Publication Date:
Research Org.:
Univ. of California, Irvine, CA (United States)
Sponsoring Org.:
USDOE; National Natural Science Foundation of China (NSFC)
OSTI Identifier:
1366534
Grant/Contract Number:  
IA0000018
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Hydrology and Earth System Sciences (Online)
Additional Journal Information:
Journal Volume: 21; Journal Issue: 1; Journal ID: ISSN 1607-7938
Publisher:
European Geosciences Union (EGU)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Liu, Xiaomang, Yang, Tiantian, Hsu, Koulin, Liu, Changming, and Sorooshian, Soroosh. Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau. United States: N. p., 2017. Web. doi:10.5194/hess-21-169-2017.
Liu, Xiaomang, Yang, Tiantian, Hsu, Koulin, Liu, Changming, & Sorooshian, Soroosh. Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau. United States. https://doi.org/10.5194/hess-21-169-2017
Liu, Xiaomang, Yang, Tiantian, Hsu, Koulin, Liu, Changming, and Sorooshian, Soroosh. 2017. "Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau". United States. https://doi.org/10.5194/hess-21-169-2017. https://www.osti.gov/servlets/purl/1366534.
@article{osti_1366534,
title = {Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau},
author = {Liu, Xiaomang and Yang, Tiantian and Hsu, Koulin and Liu, Changming and Sorooshian, Soroosh},
abstractNote = {On the Tibetan Plateau, the limited ground-based rainfall information owing to a harsh environment has brought great challenges to hydrological studies. Satellite-based rainfall products, which allow for a better coverage than both radar network and rain gauges on the Tibetan Plateau, can be suitable alternatives for studies on investigating the hydrological processes and climate change. In this study, a newly developed daily satellite-based precipitation product, termed Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks $-$ Climate Data Record (PERSIANN-CDR), is used as input for a hydrologic model to simulate streamflow in the upper Yellow and Yangtze River basins on the Tibetan Plateau. The results show that the simulated streamflows using PERSIANN-CDR precipitation and the Global Land Data Assimilation System (GLDAS) precipitation are closer to observation than that using limited gauge-based precipitation interpolation in the upper Yangtze River basin. The simulated streamflow using gauge-based precipitation are higher than the streamflow observation during the wet season. In the upper Yellow River basin, gauge-based precipitation, GLDAS precipitation, and PERSIANN-CDR precipitation have similar good performance in simulating streamflow. Finally, the evaluation of streamflow simulation capability in this study partly indicates that the PERSIANN-CDR rainfall product has good potential to be a reliable dataset and an alternative information source of a limited gauge network for conducting long-term hydrological and climate studies on the Tibetan Plateau.},
doi = {10.5194/hess-21-169-2017},
url = {https://www.osti.gov/biblio/1366534}, journal = {Hydrology and Earth System Sciences (Online)},
issn = {1607-7938},
number = 1,
volume = 21,
place = {United States},
year = {Tue Jan 10 00:00:00 EST 2017},
month = {Tue Jan 10 00:00:00 EST 2017}
}

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Assessing reliability of precipitation data over the Mekong River Basin: A comparison of ground-based, satellite, and reanalysis datasets
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Spatiotemporal assessment of the PERSIANN family of satellite precipitation data over Fars Province, Iran
journal, May 2019


Evaluating the Performance of CHIRPS Satellite Rainfall Data for Streamflow Forecasting
journal, August 2019


Regional and Global Land Data Assimilation Systems: Innovations, Challenges, and Prospects
journal, April 2019


Generation of High Mountain Precipitation and Temperature Data for a Quantitative Assessment of Flow Regime in the Upper Yarkant Basin in the Karakoram
journal, August 2018


Spatiotemporal Changes in Extreme Temperature and Precipitation Events in the Three-Rivers Headwater Region, China
journal, June 2018


On the Attribution of Changing Reference Evapotranspiration in a Coastal Area of China
journal, January 2018


Flood Inundation Mapping of the Sparsely Gauged Large-Scale Brahmaputra Basin Using Remote Sensing Products
journal, March 2019


Reliability of Gridded Precipitation Products in the Yellow River Basin, China
journal, January 2020


Does the Complexity of Evapotranspiration and Hydrological Models Enhance Robustness?
journal, August 2018


A Hydroclimatological Analysis of Precipitation in the Ganges–Brahmaputra–Meghna River Basin
journal, September 2018


Variation of Aridity Index and the Role of Climate Variables in the Southwest China
journal, September 2017


Investigating water budget dynamics in 18 river basins across the Tibetan Plateau through multiple datasets
journal, January 2018


The PERSIANN family of global satellite precipitation data: a review and evaluation of products
journal, January 2018


Using Multiple Monthly Water Balance Models to Evaluate Gridded Precipitation Products over Peninsular Spain
journal, June 2018


A Hydroclimatological Analysis of Precipitation in the Ganges–Brahmaputra–Meghna River Basin
journal, September 2018


Investigating water budget dynamics in 18 river basins across the Tibetan Plateau through multiple datasets
journal, January 2018