Evaluation of Satellite Precipitation Products and Their Potential Influence on Hydrological Modeling over the Ganzi River Basin of the Tibetan Plateau

In the last few years, satellite-based precipitation datasets are believed to be a potential source for forcing inputs in driving hydrological models, which are important especially in complex terrain areas or ungauged basins where ground gauges are generally sparse or nonexistent. This study aims to comprehensively evaluate the satellite precipitation products, CMORPH-CRT, PERSIANN-CDR, 3B42RT, and 3B42 against gauge-based datasets and to infer their relative potential impacts on hydrological processes simulation using the HEC-HMS model in the Ganzi River Basin (GRB) of the Tibetan Plateau. Results from a quantitative statistical comparison reveal that, at annual and seasonal scales, both CMORPH-CRT and 3B42 perform better than PERSIANN-CDR and 3B42RT. The CMORPH-CRT and 3B42 tend to underestimate values at the medium and high precipitation intensities ranges, whereas the opposite tendency is found for PERSIANN-CDR and 3B42RT. Overall, 3B42 exhibits the best performance for streamflow simulations over GRB and even outperforms simulation driven by gauge data during the validation period. PERSIANN-CDR shows the worst overall performance. After recalibrating with input-specific precipitation data, the performance of all satellite precipitation forced simulations is substantially improved, except for PERSIANN-CDR. Furthermore, 3B42 is more suitable to drive hydrological models and can be a potential alternative source of sparse data in Tibetan Plateau basins.

[1]  Faisal Hossain,et al.  Satellite Precipitation Data–Driven Hydrological Modeling for Water Resources Management in the Ganges, Brahmaputra, and Meghna Basins , 2014 .

[2]  Kenneth R. Knapp,et al.  Scientific data stewardship of international satellite cloud climatology project B1 global geostationary observations , 2008 .

[3]  Pietro Ceccato,et al.  Validation and Intercomparison of Satellite Rainfall Estimates over Colombia , 2010 .

[4]  Guangtao Fu,et al.  Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations , 2015 .

[5]  Jian Zhang,et al.  National mosaic and multi-sensor QPE (NMQ) system description, results, and future plans , 2011 .

[6]  Huiling Yuan,et al.  Evaluation of the latest satellite–gauge precipitation products and their hydrologic applications over the Huaihe River basin , 2016 .

[7]  Jeffrey G. Arnold,et al.  Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations , 2007 .

[8]  Y. Hong,et al.  Global View Of Real-Time Trmm Multisatellite Precipitation Analysis: Implications For Its Successor Global Precipitation Measurement Mission , 2015 .

[9]  Robert J. Joyce,et al.  CMORPH: A “Morphing” Approach for High Resolution Precipitation Product Generation , 2010 .

[10]  Y. Mohamoud,et al.  Effect of Temporal and Spatial Rainfall Resolution on HSPF Predictive Performance and Parameter Estimation , 2012 .

[11]  L. Douglas James,et al.  Developing an Efficient Auto-Calibration Algorithm for HEC-HMS Program , 2016, Water Resources Management.

[12]  S. Herath,et al.  Modeling of Event and Continuous Flow Hydrographs with HEC–HMS: Case Study in the Kelani River Basin, Sri Lanka , 2014 .

[13]  W. Briggs Statistical Methods in the Atmospheric Sciences , 2007 .

[14]  A. Feldman,et al.  Hydrologic Modeling System , 1996 .

[15]  Soroosh Sorooshian,et al.  Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau , 2016 .

[16]  Witold F. Krajewski,et al.  New paradigm for statistical validation of satellite precipitation estimates: Application to a large sample of the TMPA 0.25° 3‐hourly estimates over Oklahoma , 2009 .

[17]  Y. Hong,et al.  The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales , 2007 .

[18]  K. Ibrahim-Bathis,et al.  Rainfall-runoff modelling of Doddahalla watershed—an application of HEC-HMS and SCN-CN in ungauged agricultural watershed , 2016, Arabian Journal of Geosciences.

[19]  Mauricio Zambrano-Bigiarini,et al.  Hydrological evaluation of satellite-based rainfall estimates over the Volta and Baro-Akobo Basin , 2013 .

[20]  Daqing Yang,et al.  Precipitation bias variability versus various gauges under different climatic conditions over the Third Pole Environment (TPE) region , 2015 .

[21]  Y. Hong,et al.  Multi-scale evaluation of high-resolution multi-sensor blended global precipitation products over the Yangtze River , 2013 .

[22]  Kuolin Hsu,et al.  Hydrologic evaluation of satellite precipitation products over a mid-size basin , 2011 .

[23]  Pingping Xie A 15-Year High - Resolution Gauge – Satellite Merged Analysis of Precipitation , 2013 .

[24]  Aljosja Hooijer,et al.  Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia , 2011 .

[25]  Mekonnen Gebremichael,et al.  Evaluation of High-Resolution Satellite Rainfall Products through Streamflow Simulation in a Hydrological Modeling of a Small Mountainous Watershed in Ethiopia , 2012 .

[26]  Peter Bauer-Gottwein,et al.  Evaluation of Remotely Sensed Precipitation and Its Performance for Streamflow Simulations in Basins of the Southeast Tibetan Plateau , 2015 .

[27]  Zhenchun Hao,et al.  Tibetan Plateau precipitation as depicted by gauge observations, reanalyses and satellite retrievals , 2014 .

[28]  S. Sorooshian,et al.  Evaluation of PERSIANN system satellite-based estimates of tropical rainfall , 2000 .

[29]  S. Sorooshian,et al.  Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks , 1997 .

[30]  J. Janowiak,et al.  CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution , 2004 .

[31]  Jiaping Wu,et al.  Simulating the regional water balance through hydrological model based on TRMM satellite rainfall data , 2015 .

[32]  Liliang Ren,et al.  Evaluation of latest TMPA and CMORPH satellite precipitation products over Yellow River Basin , 2016 .

[33]  Y.‐C. Gao,et al.  Evaluation of high-resolution satellite precipitation products using rain gauge observations over the Tibetan Plateau , 2012 .

[34]  C. Kummerow,et al.  The Tropical Rainfall Measuring Mission (TRMM) Sensor Package , 1998 .

[35]  Mekonnen Gebremichael,et al.  Evaluation of satellite rainfall products through hydrologic simulation in a fully distributed hydrologic model , 2011 .

[36]  Assessment of hydrologic impacts of climate change on the runoff trend in Klang Watershed, Malaysia , 2014, Environmental Earth Sciences.

[37]  Yang Hong,et al.  Comprehensive evaluation of multi-satellite precipitation products with a dense rain gauge network and optimally merging their simulated hydrological flows using the Bayesian model averaging method , 2012 .

[38]  Faisal Hossain,et al.  Understanding the Scale Relationships of Uncertainty Propagation of Satellite Rainfall through a Distributed Hydrologic Model , 2010 .

[39]  Jiancheng Shi,et al.  Evaluation of TRMM Multisatellite Precipitation Analysis (TMPA) Products and Their Potential Hydrological Application at an Arid and Semiarid Basin in China , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[40]  Chris Sweetapple,et al.  Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations (discussion paper) , 2015 .

[41]  K. D. Sharma,et al.  Hydrological Modelling in Arid and Semi-Arid Areas: Preface , 2007 .

[42]  Emmanouil N. Anagnostou,et al.  Effects of Resolution of Satellite-Based Rainfall Estimates on Hydrologic Modeling Skill at Different Scales , 2014 .

[43]  Chong-yu Xu,et al.  Assessing the influence of rain gauge density and distribution on hydrological model performance in a humid region of China , 2013 .

[44]  David W. Watkins,et al.  Continuous Hydrologic Modeling of Snow-Affected Watersheds in the Great Lakes Basin Using HEC-HMS , 2013 .

[45]  G. Huffman,et al.  The TRMM Multi-Satellite Precipitation Analysis (TMPA) , 2010 .

[46]  Shaofeng Jia,et al.  Potential Impacts of Climate Change on Water Resources in the Kunhar River Basin, Pakistan , 2016 .

[47]  Kuolin Hsu,et al.  Assessing the Efficacy of High-Resolution Satellite-Based PERSIANN-CDR Precipitation Product in Simulating Streamflow , 2016 .

[48]  S. Sorooshian,et al.  PERSIANN-CDR: Daily Precipitation Climate Data Record from Multisatellite Observations for Hydrological and Climate Studies , 2015 .

[49]  G. Huffman,et al.  TRMM and Other Data Precipitation Data Set Documentation , 2015 .

[50]  S. Sorooshian,et al.  Evaluation of the PERSIANN-CDR Daily Rainfall Estimates in Capturing the Behavior of Extreme Precipitation Events over China , 2014 .

[51]  Yang Hong,et al.  Statistical and hydrological evaluation of TRMM-based Multi-satellite Precipitation Analysis over the Wangchu Basin of Bhutan: Are the latest satellite precipitation products 3B42V7 ready for use in ungauged basins? , 2013 .