Assessing Hydrological Modelling Driven by Different Precipitation Datasets via the SMAP Soil Moisture Product and Gauged Streamflow Data

To compare the effectivenesses of different precipitation datasets on hydrological modelling, five precipitation datasets derived from various approaches were used to simulate a two-week runoff process after a heavy rainfall event in the Wangjiaba (WJB) watershed, which covers an area of 30,000 km2 in eastern China. The five precipitation datasets contained one traditional in situ observation, two satellite products, and two predictions obtained from the Numerical Weather Prediction (NWP) models. They were the station observations collected from the China Meteorological Administration (CMA), the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG), the merged data of the Climate Prediction Center Morphing (merged CMORPH), and the outputs of the Weather Research and Forecasting (WRF) model and the WRF four-dimensional variational (4D-Var) data assimilation system, respectively. Apart from the outlet discharge, the simulated soil moisture was also assessed via the Soil Moisture Active Passive (SMAP) product. These investigations suggested that (1) all the five precipitation datasets could yield reasonable simulations of the studied rainfall-runoff process. The Nash-Sutcliffe coefficients reached the highest value (0.658) with the in situ CMA precipitation and the lowest value (0.464) with the WRF-predicted precipitation. (2) The traditional in situ observation were still the most reliable precipitation data to simulate the study case, whereas the two NWP-predicted precipitation datasets performed the worst. Nevertheless, the NWP-predicted precipitation is irreplaceable in hydrological modelling because of its fine spatiotemporal resolutions and ability to forecast precipitation in the future. (3) Gauge correction and 4D-Var data assimilation had positive impacts on improving the accuracies of the merged CMORPH and the WRF 4D-Var prediction, respectively, but the effectiveness of the latter on the rainfall-runoff simulation was mainly weakened by the poor quality of the GPM IMERG used in the study case. This study provides a reference for the applications of different precipitation datasets, including in situ observations, remote sensing estimations and NWP simulations, in hydrological modelling.

[1]  G. Grell,et al.  A generalized approach to parameterizing convection combining ensemble and data assimilation techniques , 2002 .

[2]  F. Brissette,et al.  Performance and uncertainty evaluation of empirical downscaling methods in quantifying the climate change impacts on hydrology over two North American river basins , 2013 .

[3]  Emmanouil N. Anagnostou,et al.  Decomposing the satellite precipitation error propagation through the rainfall-runoff processes , 2017 .

[4]  Zhong Liu,et al.  Comparison of Integrated Multisatellite Retrievals for GPM (IMERG) and TRMM Multisatellite Precipitation Analysis (TMPA) Monthly Precipitation Products: Initial Results , 2016 .

[5]  F. Pappenberger,et al.  Assessment of a 1-hour gridded precipitation dataset to drive a hydrological model: A case study of the summer 2007 floods in the upper severn, UK , 2013 .

[6]  Jimy Dudhia,et al.  A collaborative effort towards a future community mesoscale model (WRF) [presentation] , 1998 .

[7]  María Carolina Rogelis,et al.  Streamflow forecasts from WRF precipitation for flood early warning in mountain tropical areas , 2018 .

[8]  Xin Li,et al.  Effects of 4D-Var Data Assimilation Using Remote Sensing Precipitation Products in a WRF Model over the Complex Terrain of an Arid Region River Basin , 2017, Remote. Sens..

[9]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

[10]  E. Dilek Taylan,et al.  Isparta Bölgesi Yağış Değerlerinin IDW ve Kriging Enterpolasyon Yöntemleri ile Tahmini , 2016 .

[11]  Y. Hong,et al.  Evaluation of GPM Day-1 IMERG and TMPA Version-7 legacy products over Mainland China at multiple spatiotemporal scales , 2015 .

[12]  Vimal Mishra,et al.  Uncertainty and Bias in Satellite-Based Precipitation Estimates over Indian Subcontinental Basins: Implications for Real-Time Streamflow Simulation and Flood Prediction* , 2016 .

[13]  B. Merz,et al.  Evaluation of areal precipitation estimates based on downscaled reanalysis and station data by hydrological modelling , 2012 .

[14]  Andrew C. Lorenc,et al.  Modelling of error covariances by 4D‐Var data assimilation , 2003 .

[15]  Yuan Yong.  Spatial and Temporal Variations of Precipitation in Huaihe River Basin in Recent 50 Years , 2012 .

[16]  Desamsetti Srinivas,et al.  Implications of vortex initialization and model spin-up in tropical cyclone prediction using Advanced Research Weather Research and Forecasting Model , 2014, Natural Hazards.

[17]  P. Gleick,et al.  Sensitivity of streamflow in the Colorado Basin to climatic changes , 1991 .

[18]  J. Janowiak,et al.  The Global Precipitation Climatology Project (GPCP) combined precipitation dataset , 1997 .

[19]  John Derber,et al.  The National Meteorological Center's spectral-statistical interpolation analysis system , 1992 .

[20]  François Brissette,et al.  Can Precipitation and Temperature from Meteorological Reanalyses Be Used for Hydrological Modeling , 2016 .

[21]  Rodrigo Proença de Oliveira,et al.  Validation of remote‐sensing precipitation products for Angola , 2015 .

[22]  Y. Kerr,et al.  A first assessment of the SMOS data in southwestern France using in situ and airborne soil moisture estimates: The CAROLS airborne campaign , 2011 .

[23]  Lili Lei,et al.  A hybrid nudging‐ensemble Kalman filter approach to data assimilation in WRF/DART , 2011 .

[24]  Augusto Getirana,et al.  Hydrological modeling of the Peruvian-Ecuadorian Amazon basin using GPM-IMERG satellite-based precipitation dataset. , 2016, Hydrology and earth system sciences.

[25]  J. Dudhia,et al.  A New Vertical Diffusion Package with an Explicit Treatment of Entrainment Processes , 2006 .

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

[27]  Song-You Hong,et al.  Development of an Effective Double-Moment Cloud Microphysics Scheme with Prognostic Cloud Condensation Nuclei (CCN) for Weather and Climate Models , 2010 .

[28]  Chris Sweetapple,et al.  An ensemble-based dynamic Bayesian averaging approach for discharge simulations using multiple global precipitation products and hydrological models. , 2018 .

[29]  Emmanouil N. Anagnostou,et al.  Using NWP Simulations in Satellite Rainfall Estimation of Heavy Precipitation Events over Mountainous Areas , 2013 .

[30]  Harald Kunstmann,et al.  The Hydrological Cycle in Three State-of-the-Art Reanalyses: Intercomparison and Performance Analysis , 2012 .

[31]  A. Hou,et al.  The Global Precipitation Measurement Mission , 2014 .

[32]  Quansheng Ge,et al.  High-resolution precipitation data derived from dynamical downscaling using the WRF model for the Heihe River Basin, northwest China , 2017, Theoretical and Applied Climatology.

[33]  William C. Skamarock,et al.  A time-split nonhydrostatic atmospheric model for weather research and forecasting applications , 2008, J. Comput. Phys..

[34]  Christian D. Kummerow,et al.  The Joanne Simpson Special Issue on the Tropical Rainfall Measuring Mission (TRMM) , 2000 .

[35]  R. Leconte,et al.  Uncertainty of downscaling method in quantifying the impact of climate change on hydrology , 2011 .

[36]  Vahid Nourani,et al.  Using self-organizing maps and wavelet transforms for space–time pre-processing of satellite precipitation and runoff data in neural network based rainfall–runoff modeling , 2013 .

[37]  Melissa Bukovsky,et al.  Precipitation Simulations Using WRF as a Nested Regional Climate Model , 2009 .

[38]  Neill E. Bowler,et al.  Comparison of Hybrid-4DEnVar and Hybrid-4DVar Data Assimilation Methods for Global NWP , 2015 .

[39]  Matti Kummu,et al.  Using Reanalysis and Remotely Sensed Temperature and Precipitation Data for Hydrological Modeling in Monsoon Climate: Mekong River Case Study , 2014 .

[40]  Jefferson S. Wong,et al.  Evaluation of Integrated Multisatellite Retrievals for GPM (IMERG) over Southern Canada against Ground Precipitation Observations: A Preliminary Assessment , 2017 .

[41]  Pierre Baguis,et al.  Soil Moisture Data Assimilation in a Hydrological Model: A Case Study in Belgium Using Large-Scale Satellite Data , 2017, Remote. Sens..

[42]  Wei Huang,et al.  A Three-Dimensional Variational Data Assimilation System for MM5: Implementation and Initial Results , 2004 .

[43]  Jens Christian Refsgaard,et al.  Spatial-scale characteristics of precipitation simulated by regional climate models and the implications for hydrological modeling , 2012 .

[44]  Matthias Steiner,et al.  Effect of bias adjustment and rain gauge data quality control on radar rainfall estimation , 1999 .

[45]  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.

[46]  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 .

[47]  Antonio Parodi,et al.  Sensitivity of Precipitation Statistics to Resolution, Microphysics, and Convective Parameterization: A Case Study with the High-Resolution WRF Climate Model over Europe , 2015 .

[48]  S. Stisen,et al.  Inter-comparison of three distributed hydrological models with respect to seasonal variability of soil moisture patterns at a small forested catchment , 2016 .

[49]  Jimy Dudhia,et al.  Four-Dimensional Variational Data Assimilation for WRF : Formulation and Preliminary Results , 2009 .

[50]  F. Molteni,et al.  The ECMWF Ensemble Prediction System: Methodology and validation , 1996 .

[51]  Olivier Thomas,et al.  Impacts of rainfall events on runoff water quality in an agricultural environment in temperate areas. , 2011, The Science of the total environment.

[52]  András Bárdossy,et al.  Downscaling precipitation using regional climate models and circulation patterns toward hydrology , 2011 .

[53]  Yong-Run Guo,et al.  The Weather Research and Forecasting Model's Community Variational/Ensemble Data Assimilation System: WRFDA , 2012 .

[54]  Pedro M. A. Miranda,et al.  WRF high resolution simulation of Iberian mean and extreme precipitation climate , 2013 .

[55]  Torben Schmith,et al.  Statistical and dynamical downscaling of precipitation: An evaluation and comparison of scenarios for the European Alps , 2007 .

[56]  Jun Xia,et al.  Spatio-temporal trend and statistical distribution of extreme precipitation events in Huaihe River Basin during 1960–2009 , 2012, Journal of Geographical Sciences.

[57]  D. Vidal-Madjar,et al.  Assimilation of soil moisture inferred from infrared remote sensing in a hydrological model over the HAPEX-MOBILHY region , 1994 .

[58]  E. Anagnostou,et al.  Precipitation: Measurement, remote sensing, climatology and modeling , 2009 .

[59]  Yang Yang,et al.  Atmospheric-hydrological modeling of severe precipitation and floods in the Huaihe River Basin, China , 2006 .

[60]  K. Lee,et al.  Influence of storm magnitude and watershed size on runoff nonlinearity , 2016, Journal of Earth System Science.

[61]  A. Holtslag,et al.  Evaluation of the Weather Research and Forecasting Mesoscale Model for GABLS3: Impact of Boundary-Layer Schemes, Boundary Conditions and Spin-Up , 2014, Boundary-Layer Meteorology.

[62]  M. Buehner,et al.  Intercomparison of Variational Data Assimilation and the Ensemble Kalman Filter for Global Deterministic NWP. Part I: Description and Single-Observation Experiments , 2010 .

[63]  Toshio Koike,et al.  Decision support for dam release during floods using a distributed biosphere hydrological model driven by quantitative precipitation forecasts , 2010 .

[64]  Alejandro N. Flores,et al.  Dynamical Precipitation Downscaling for Hydrologic Applications Using WRF 4D-Var Data Assimilation: Implications for GPM Era , 2015 .

[65]  Emmanouil N. Anagnostou,et al.  Error Analysis of Satellite Precipitation-Driven Modeling of Flood Events in Complex Alpine Terrain , 2016, Remote. Sens..

[66]  Wade T. Crow,et al.  Assessment of the SMAP Level-4 surface and root-zone soil moisture product using in situ measurements , 2017 .

[67]  T. Flesch,et al.  Verification of the WRF model for simulating heavy precipitation in Alberta , 2014 .

[68]  Vahid Naeimi,et al.  Temporal variation of soil moisture over the Wuding River basin assessed with an eco-hydrological model, in-situ observations and remote sensing , 2008 .

[69]  Kai Wang,et al.  Evaluation of Heavy Precipitation Simulated by the WRF Model Using 4D-Var Data Assimilation with TRMM 3B42 and GPM IMERG over the Huaihe River Basin, China , 2018, Remote. Sens..

[70]  Hidde Leijnse,et al.  First-year evaluation of GPM rainfall over the Netherlands : IMERG day 1 final run (V03D) , 2016 .

[71]  Cheng Chen,et al.  Multiscale Comparative Evaluation of the GPM IMERG v5 and TRMM 3B42 v7 Precipitation Products from 2015 to 2017 over a Climate Transition Area of China , 2018, Remote. Sens..

[72]  Dawen Yang,et al.  Comparison of different distributed hydrological models for characterization of catchment spatial variability , 2000 .

[73]  Jiajia Liu,et al.  Evaluation of TRMM precipitation and its application to distributed hydrological model in Naqu River Basin of the Tibetan Plateau , 2017 .

[74]  M. Buehner,et al.  Intercomparison of Variational Data Assimilation and the Ensemble Kalman Filter for Global Deterministic NWP. Part II: One-Month Experiments with Real Observations , 2010 .

[75]  Claudia Notarnicola,et al.  Estimation of soil moisture patterns in mountain grasslands by means of SAR RADARSAT2 images and hydrological modeling , 2014 .

[76]  Seokhyeon Kim,et al.  Catchment scale simulations of soil moisture dynamics using an equivalent cross-section based hydrological modelling approach , 2018, Journal of Hydrology.

[77]  J. Dudhia,et al.  Coupling an Advanced Land Surface–Hydrology Model with the Penn State–NCAR MM5 Modeling System. Part I: Model Implementation and Sensitivity , 2001 .

[78]  Chong-Yu Xu,et al.  Evaluation of reanalysis and satellite-based precipitation datasets in driving hydrological models in a humid region of Southern China , 2015, Stochastic Environmental Research and Risk Assessment.

[79]  Kazuo Saito,et al.  The Operational JMA Nonhydrostatic Mesoscale Model , 2006 .

[80]  Anna Balenzano,et al.  Inter-comparison of hydrological model simulations with time series of SAR-derived soil moisture maps , 2012 .

[81]  P. Courtier,et al.  A strategy for operational implementation of 4D‐Var, using an incremental approach , 1994 .

[82]  E. Mlawer,et al.  Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave , 1997 .

[83]  Jia Xu,et al.  Soil Moisture Mapping from Satellites: An Intercomparison of SMAP, SMOS, FY3B, AMSR2, and ESA CCI over Two Dense Network Regions at Different Spatial Scales , 2017, Remote. Sens..

[84]  Qixiang Lei,et al.  Does watershed size affect simple mathematical relationships between flow velocity and discharge rate at watershed outlets on the Loess Plateau of China , 2012 .

[85]  Emanuele Santi,et al.  Comparison between SAR Soil Moisture Estimates and Hydrological Model Simulations over the Scrivia Test Site , 2013, Remote. Sens..

[86]  Robert Leconte,et al.  Analysis of the hydrological response of a distributed physically-based model using post-assimilation (EnKF) diagnostics of streamflow and in situ soil moisture observations , 2014 .

[87]  M. J. Booij,et al.  The Skill of Seasonal Ensemble Low-Flow Forecasts in the Moselle River for Three Different Hydrological Models , 2015 .

[88]  Zong-Liang Yang,et al.  A simple TOPMODEL-based runoff parameterization (SIMTOP) for use in global climate models , 2005 .

[89]  Chengguang Lai,et al.  Evaluation of the GPM IMERG satellite-based precipitation products and the hydrological utility , 2017 .

[90]  M. Bierkens,et al.  The benefits of using remotely sensed soil moisture in parameter identification of large‐scale hydrological models , 2013 .

[91]  Ehsan Sharifi,et al.  Assessment of GPM-IMERG and Other Precipitation Products against Gauge Data under Different Topographic and Climatic Conditions in Iran: Preliminary Results , 2016, Remote. Sens..

[92]  Dawei Han,et al.  Hydrological modeling using Effective Rainfall routed by the Muskingum method (ERM) , 2013 .

[93]  J. P. Matos,et al.  Comparison and evaluation of satellite derived precipitation products for hydrological modeling of the Zambezi River Basin , 2011 .

[94]  F. Veerse,et al.  Multiple‐truncation incremental approach for four‐dimensional variational data assimilation , 1998 .

[95]  Wanchang Zhang,et al.  A modified topographic index that incorporates the hydraulic and physical properties of soil , 2017 .

[96]  N. Davidson,et al.  Evaluation of TRMM 3B42 precipitation estimates of tropical cyclone rainfall using PACRAIN data , 2013 .

[97]  Chong-Yu Xu,et al.  Evaluating Consistency between the Remotely Sensed Soil Moisture and the Hydrological Model-Simulated Soil Moisture in the Qujiang Catchment of China , 2018 .

[98]  Amirhossein Mazrooei,et al.  Decomposition of Sources of Errors in Seasonal Streamflow Forecasting Over the US Sunbelt Using Multiple Land Surface Models. , 2014 .

[99]  T. Black.  The new NMC mesoscale Eta Model: description and forecast examples , 1994 .

[100]  Jiancheng Shi,et al.  The Future of Earth Observation in Hydrology. , 2017, Hydrology and earth system sciences.

[101]  Konstantine P. Georgakakos,et al.  Precipitation analysis, modeling, and prediction in hydrology , 1987 .

[102]  Vahid Nourani,et al.  Hydrological model parameterization using NDVI values to account for the effects of land cover change on the rainfall-runoff response , 2017 .

[103]  A. Speranza,et al.  Sensitivity of Precipitation Forecast Skill Scores to Bilinear Interpolation and a Simple Nearest-Neighbor Average Method on High-Resolution Verification Grids , 2003 .

[104]  Wolfgang Wagner,et al.  Assimilation of ASCAT near-surface soil moisture into the SIM hydrological model over France , 2011 .

[105]  Yudong Tian,et al.  Evaluation of Quantitative Precipitation Estimations through Hydrological Modeling in IFloodS River Basins , 2017 .

[106]  Peter E. Black,et al.  Hydrograph responses to watershed model size and similitude relations , 1975 .

[107]  Faisal Hossain,et al.  Understanding the Dependence of Satellite Rainfall Uncertainty on Topography and Climate for Hydrologic Model Simulation , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[108]  J. P. Matos,et al.  Evaluation of precipitation products over the Zambezi Basin , 2011 .

[109]  Adil N. Godrej,et al.  Watershed size effects on applicability of regression‐based methods for fluvial loads estimation , 2013 .

[110]  Jaap Schellekens,et al.  Improved large-scale hydrological modelling through the assimilation of streamflow and downscaled satellite soil moisture observations , 2015 .

[111]  Pieter van der Zaag,et al.  Validating Rainfall-Runoff Modelling Using Satellite-Based and Reanalysis Precipitation Products in the Sre Pok Catchment, the Mekong River Basin , 2018 .

[112]  Andrew W. Western,et al.  The Tarrawarra project: high resolution spatial measurement, modelling and analysis of soil moisture and hydrological response , 1999 .

[113]  J. Dudhia.  Numerical Study of Convection Observed during the Winter Monsoon Experiment Using a Mesoscale Two-Dimensional Model , 1989 .

[114]  J. Refsgaard,et al.  Operational Validation and Intercomparison of Different Types of Hydrological Models , 1996 .

[115]  F. Brissette,et al.  Hydrological modelling using proxies for gauged precipitation and temperature , 2017 .

[116]  Tadashi Tsuyuki,et al.  Assimilation of Precipitation Data to the JMA Mesoscale Model with a Four-dimensional Variational Method and its Impact on Precipitation Forecasts , 2005 .