Applicability Evaluation of Multisource Satellite Precipitation Data for Hydrological Research in Arid Mountainous Areas

Global Satellite Mapping of Precipitation (GSMaP), Climate Hazards Group InfraRed Preconception with Station data (CHIRPS), Tropical Rain Measurement Mission Multisatellite Precipitation Analysis (TRMM 3B42 V7) and Rainfall Estimation from Soil Moisture Observations (SM2RAIN) are satellite precipitation products with high applicability, but their applicability in hydrological research in arid mountainous areas is not clear. Based on precipitation and runoff data, this study evaluated the applicability of each product to hydrological research in a typical mountainous basin (the Qaraqash River basin) in an arid region by using two methods: a statistical index and a hydrological model (Soil and Water Assessment Tool, SWAT). Simulation results were evaluated by Nash efficiency coefficient (NS), relative error (PBIAS) and determination coefficient (R2). The results show that: (1) The spatial distributions of precipitation estimated by these four products in the Qaraqash River basin are significantly different, and the multi-year average annual precipitation of GSMaP is 97.11 mm, which is the closest to the weather station interpolation results. (2) On the annual and monthly scales, GSMaP has the highest correlation (R ≥ 0.82) with the observed precipitation and the smallest relative error (BIAS 0.6). In daily runoff simulation, GSMaP has the greatest ability to reproduce runoff changes. The study provides a reference for the optimization of precipitation image data and hydrological simulation in data-scarce areas.

[1]  Zed Zulkafli,et al.  Satellite Rainfall (TRMM 3B42-V7) Performance Assessment and Adjustment over Pahang River Basin, Malaysia , 2018, Remote. Sens..

[2]  Ming Xu,et al.  Accuracy Evaluation of Two High-Resolution Satellite-Based Rainfall Products: TRMM 3B42V7 and CMORPH in Shanghai , 2018 .

[3]  Weizhen Wang,et al.  Evaluation and integration of the top-down and bottom-up satellite precipitation products over mainland China , 2020 .

[4]  Lei Wu,et al.  Comparison of TMPA-3B42RT Legacy Product and the Equivalent IMERG Products over Mainland China , 2018, Remote. Sens..

[5]  Dongdong Zhang,et al.  Evaluation of the GSMaP_Gauge products using rain gauge observations and SWAT model in the Upper Hanjiang River Basin , 2019, Atmospheric Research.

[6]  J. McDonnell,et al.  Debates—The future of hydrological sciences: A (common) path forward? A call to action aimed at understanding velocities, celerities and residence time distributions of the headwater hydrograph , 2014 .

[7]  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 .

[8]  Naser El-Sheimy,et al.  Performance Assessment of Sub-Daily and Daily Precipitation Estimates Derived from GPM and GSMaP Products over an Arid Environment , 2019, Remote. Sens..

[9]  Jeffrey G. Arnold,et al.  Inclusion of glacier processes for distributed hydrological modeling at basin scale with application to a watershed in Tianshan Mountains, northwest China , 2013 .

[10]  Hui Lu,et al.  Ground validation of GPM IMERG and TRMM 3B42V7 rainfall products over southern Tibetan Plateau based on a high‐density rain gauge network , 2017 .

[11]  Zongxue Xu,et al.  Analysis of parameter uncertainty in semi-distributed hydrological models using bootstrap method: a case study of SWAT model applied to Yingluoxia watershed in northwest China. , 2010 .

[12]  T. Tadesse,et al.  Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia , 2017 .

[13]  Yang Hong,et al.  Early assessment of Integrated Multi-satellite Retrievals for Global Precipitation Measurement over China , 2016 .

[14]  Changjiang Xu,et al.  Error analysis and correction of the daily GSMaP products over Hanjiang River Basin of China , 2018, Atmospheric Research.

[15]  Assefa M. Melesse,et al.  Performance of High Resolution Satellite Rainfall Products over Data Scarce Parts of Eastern Ethiopia , 2015, Remote. Sens..

[16]  Mengru Li,et al.  Hydroclimate assessment of gridded precipitation products for the Tibetan Plateau. , 2019, The Science of the total environment.

[17]  Xin Jin,et al.  Effects of land-use data resolution on hydrologic modelling, a case study in the upper reach of the Heihe River, Northwest China , 2019, Ecological Modelling.

[18]  Kuolin Hsu,et al.  Intercomparison of PERSIANN-CDR and TRMM-3B42V7 precipitation estimates at monthly and daily time scales , 2017 .

[19]  David B. Wolff,et al.  Ground Validation for the Tropical Rainfall Measuring Mission (TRMM) , 2005 .

[20]  Daniel Vila,et al.  Precipitation comparison for the CFSR, MERRA, TRMM3B42 and Combined Scheme datasets in Bolivia , 2015 .

[21]  Franklin Paredes-Trejo,et al.  Assessment of SM2RAIN-Derived and State-of-the-Art Satellite Rainfall Products over Northeastern Brazil , 2018, Remote. Sens..

[22]  G. Jewitt,et al.  An evaluation of how downscaled climate data represents historical precipitation characteristics beyond the means and variances , 2016 .

[23]  Muhammad Shahid,et al.  Performance Assessment of SM2RAIN-CCI and SM2RAIN-ASCAT Precipitation Products over Pakistan , 2019, Remote. Sens..

[24]  Walter Collischonn,et al.  Daily hydrological modeling in the Amazon basin using TRMM rainfall estimates , 2008 .

[25]  S. Gabriele,et al.  Assessment of GPM and SM2RAIN-ASCAT rainfall products over complex terrain in southern Italy , 2018, Atmospheric Research.

[26]  Anzhi Wang,et al.  Comprehensive precipitation evaluation of TRMM 3B42 with dense rain gauge networks in a mid-latitude basin, northeast, China , 2016, Theoretical and Applied Climatology.

[27]  J. Michaelsen,et al.  The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes , 2015, Scientific Data.

[28]  I. Ahmad,et al.  Satellite precipitation product: Applicability and accuracy evaluation in diverse region , 2020 .

[29]  A. J. Farias,et al.  Intercomparison of improved satellite rainfall estimation with CHIRPS gridded product and rain gauge data over Venezuela , 2016 .

[30]  Feng Gao,et al.  Comparison of two long-term and high-resolution satellite precipitation datasets in Xinjiang, China , 2018, Atmospheric Research.

[31]  T. Skaugen,et al.  Simulated precipitation fields with variance-consistent interpolation , 2010 .

[32]  Zhiyong Wu,et al.  Improvement of a combination of TMPA (or IMERG) and ground-based precipitation and application to a typical region of the East China Plain. , 2018, The Science of the total environment.

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

[34]  Yang Hong,et al.  Have satellite precipitation products improved over last two decades? A comprehensive comparison of GPM IMERG with nine satellite and reanalysis datasets , 2020 .

[35]  Bin Guo,et al.  Systematical Evaluation of GPM IMERG and TRMM 3B42V7 Precipitation Products in the Huang-Huai-Hai Plain, China , 2019, Remote. Sens..

[36]  B. Cao,et al.  The spatial distribution of precipitation and topography in the Qilian Shan Mountains, northeastern Tibetan Plateau , 2017 .

[37]  Z. Duan,et al.  Evaluation of precipitation input for SWAT modeling in Alpine catchment: A case study in the Adige river basin (Italy). , 2016, The Science of the total environment.

[38]  Jeffrey J. McDonnell,et al.  On the dialog between experimentalist and modeler in catchment hydrology: Use of soft data for multicriteria model calibration , 2002 .

[39]  Bin Yong,et al.  A Preliminary Assessment of the Gauge-Adjusted Near-Real-Time GSMaP Precipitation Estimate over Mainland China , 2020, Remote. Sens..

[40]  Yared A. Bayissa,et al.  Evaluation of satellite rainfall products for modeling water yield over the source region of Blue Nile Basin. , 2019, The Science of the total environment.

[41]  Yang Hong,et al.  Evaluation of latest TMPA and CMORPH precipitation products with independent rain gauge observation networks over high-latitude and low-latitude basins in China , 2016, Chinese Geographical Science.

[42]  David A. Newell,et al.  The Global Precipitation Measurement (GPM) Microwave Imager (GMI): Instrument Overview and Early On-Orbit Performance , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[43]  A. Ghorbani,et al.  Comprehensive comparison of daily IMERG and GSMaP satellite precipitation products in Ardabil Province, Iran , 2018, International Journal of Remote Sensing.

[44]  W. Wagner,et al.  SM2RAIN–ASCAT (2007–2018): global daily satellite rainfall data from ASCAT soil moisture observations , 2019, Earth System Science Data.

[45]  Zhenchun Hao,et al.  Evaluation of satellite precipitation retrievals and their potential utilities in hydrologic modeling over the Tibetan Plateau , 2014 .

[46]  Yawar Hussain,et al.  Reliability of SM2RAIN precipitation datasets in comparison to gauge observations and hydrological modelling over arid regions , 2020, International Journal of Climatology.

[47]  Y. Hong,et al.  Comparison analysis of six purely satellite-derived global precipitation estimates , 2020 .

[48]  F. Miura,et al.  Evaluation of GSMaP Daily Rainfall Satellite Data for Flood Monitoring: Case Study—Kyushu Japan , 2016 .