Adequacy of TRMM satellite rainfall data in driving the SWAT modeling of Tiaoxi catchment (Taihu lake basin, China)

Spatial rainfall data is an essential input to Distributed Hydrological Models (DHM), and a significant contributor to hydrological model uncertainty. Model uncertainty is higher when rain gauges are sparse, as is often the case in practice. Currently, satellite-based precipitation products increasingly provide an alternative means to ground-based rainfall estimates, in which case a rigorous product assessment is required before implementation. Accordingly, the twofold objective of this work paper was the real-world assessment of both (a) the Tropical Rainfall Measuring Mission (TRMM) rainfall product using gauge data, and (b) the TRMM product’s role in forcing data for hydrologic simulations in the area of the Tiaoxi catchment (Taihu lake basin, China). The TRMM rainfall products used in this study are the Version-7 real-time 3B42RT and the post-real-time 3B42. It was found that the TRMM rainfall data showed a superior performance at the monthly and annual scales, fitting well with surface observation-based frequency rainfall distributions. The Nash-Sutcliffe Coefficient of Efficiency (NSCE) and the relative bias ratio (BIAS) were used to evaluate hydrologic model performance. The satisfactory performance of the monthly runoff simulations in the Tiaoxi study supports the view that the implementation of real-time 3B42RT allows considerable room for improvement. At the same time, post-real-time 3B42 can be a valuable tool of hydrologic modeling, water balance analysis, and basin water resource management, especially in developing countries or at remote locations in which rainfall gauges are scarce.

[1]  Yang Hong,et al.  Intercomparison of the Version-6 and Version-7 TMPA precipitation products over high and low latitudes basins with independent gauge networks: Is the newer version better in both real-time and post-real-time analysis for water resources and hydrologic extremes? , 2014 .

[2]  M. Kanamitsu,et al.  The Key Role of Heavy Precipitation Events in Climate Model Disagreements of Future Annual Precipitation Changes in California , 2013 .

[3]  Enrique R. Vivoni,et al.  Utility of Quantitative Precipitation Estimates for high resolution hydrologic forecasts in mount , 2012 .

[4]  Dawen Yang,et al.  Accuracy and spatio-temporal variation of high resolution satellite rainfall estimate over the Ganjiang River Basin , 2013 .

[5]  Liliang Ren,et al.  Evaluation of high-resolution satellite precipitation products with surface rain gauge observations from Laohahe Basin in northern China , 2010 .

[6]  Patrick Willems,et al.  Evaluation of TRMM 3B42 precipitation estimates and WRF retrospective precipitation simulation over the Pacific-Andean region of Ecuador and Peru , 2014 .

[7]  Y. Lü,et al.  Comparison of Four Spatial Interpolation Methods for Estimating Soil Moisture in a Complex Terrain Catchment , 2013, PloS one.

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

[9]  S. Jain,et al.  Validation of a new meteorological forcing data in analysis of spatial and temporal variability of precipitation in India , 2014, Stochastic Environmental Research and Risk Assessment.

[10]  Chaopeng Shen,et al.  A process-based, distributed hydrologic model based on a large-scale method for surface–subsurface coupling , 2010 .

[11]  K. Abbaspour,et al.  Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT , 2007 .

[12]  Wei Zhang,et al.  Temporal and spatial variability of annual extreme water level in the Pearl River Delta region, China , 2009 .

[13]  Y. Liu,et al.  Combining the SWAT model with sequential uncertainty fitting algorithm for streamflow prediction and uncertainty analysis for the Lake Dianchi Basin, China , 2014 .

[14]  U. Schneider,et al.  GPCC's new land surface precipitation climatology based on quality-controlled in situ data and its role in quantifying the global water cycle , 2013, Theoretical and Applied Climatology.

[15]  F. Turk,et al.  Component analysis of errors in satellite-based precipitation estimates , 2009 .

[16]  Yudong Tian,et al.  A global map of uncertainties in satellite‐based precipitation measurements , 2010 .

[17]  S. J. Connor,et al.  Validation of high‐resolution satellite rainfall products over complex terrain , 2008 .

[18]  Zhenchun Hao,et al.  Suitability of TRMM satellite rainfall in driving a distributed hydrological model in the source region of Yellow River , 2014 .

[19]  Lotta Andersson,et al.  Estimating rainfall and water balance over the Okavango River Basin for hydrological applications , 2006 .

[20]  Vladimir U. Smakhtin,et al.  Assessing the Impact of Areal Precipitation Input on Streamflow Simulations Using the SWAT Model 1 , 2011 .

[21]  Jing Yang,et al.  Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China , 2008 .

[22]  Chandranath Chatterjee,et al.  Evaluation of TRMM rainfall estimates over a large Indian river basin (Mahanadi) , 2014 .

[23]  Anders Moberg,et al.  HOMOGENIZATION OF SWEDISH TEMPERATURE DATA. PART I: HOMOGENEITY TEST FOR LINEAR TRENDS , 1997 .

[24]  Ming Lu,et al.  Analysing the uncertainty of estimating forest carbon stocks in China , 2015 .

[25]  G. Christakos,et al.  Spatiotemporal Interpolation of Rainfall by Combining BME Theory and Satellite Rainfall Estimates , 2015 .

[26]  H. Alexandersson.  A homogeneity test applied to precipitation data , 1986 .

[27]  George Christakos,et al.  Random Field Models in Earth Sciences , 1992 .

[28]  Emad Habib,et al.  Validation of NEXRAD multisensor precipitation estimates using an experimental dense rain gauge network in south Louisiana. , 2009 .

[29]  Anton Schleiss,et al.  Can satellite based pattern-oriented memory improve the interpolation of sparse historical rainfall records? , 2013 .

[30]  Christian Onof,et al.  A Comparative Analysis of TRMM-Rain Gauge Data Merging Techniques at the Daily Time Scale for Distributed Rainfall-Runoff Modeling Applications , 2015 .

[31]  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.

[32]  Assefa M. Melesse,et al.  SWAT model application and prediction uncertainty analysis in the Lake Tana Basin, Ethiopia , 2009 .

[33]  Chen Zhe,et al.  Quality Control Procedures for Hourly Precipitation Data from Automatic Weather Stations in China , 2010 .

[34]  Chulsang Yoo,et al.  On the sampling errors from raingauges and microwave attenuation measurements , 2000 .

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

[36]  Christian D. Kummerow,et al.  Beamfilling Errors in Passive Microwave Rainfall Retrievals. , 1998 .

[37]  Hongjing Wu,et al.  Evaluating uncertainty estimates in distributed hydrological modeling for the Wenjing River watershed in China by GLUE, SUFI-2, and ParaSol methods , 2015 .

[38]  M. Gebremichael,et al.  Estimating actual rainfall from satellite rainfall products , 2009 .

[39]  U. Schneider,et al.  Terrestrial Precipitation Analysis: Operational Method and Required Density of Point Measurements , 1994 .

[40]  Denis A. Hughes,et al.  Comparison of satellite rainfall data with observations from gauging station networks , 2006 .

[41]  Emmanouil N. Anagnostou,et al.  Evaluation of Global Satellite Rainfall Products over Continental Europe , 2012 .

[42]  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 .

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

[44]  Chong-Yu Xu,et al.  Suitability of the TRMM satellite rainfalls in driving a distributed hydrological model for water balance computations in Xinjiang catchment, Poyang lake basin , 2012 .

[45]  Yang Hong,et al.  Evaluation of TRMM Multisatellite Precipitation Analysis (TMPA) and Its Utility in Hydrologic Prediction in the La Plata Basin , 2008 .

[46]  Shiliang Su,et al.  Farmland fragmentation due to anthropogenic activity in rapidly developing region , 2014 .

[47]  S. Sorooshian,et al.  Evaluation and comparison of satellite precipitation estimates with reference to a local area in the Mediterranean Sea , 2014 .

[48]  Luigi J. Renzullo,et al.  Evaluating geostatistical methods of blending satellite and gauge data to estimate near real-time daily rainfall for Australia , 2013 .

[49]  T. Steenhuis,et al.  Comparison of rainfall estimations by TRMM 3B42, MPEG and CFSR with ground-observed data for the Lake Tana basin in Ethiopia , 2014 .

[50]  John R. Williams,et al.  LARGE AREA HYDROLOGIC MODELING AND ASSESSMENT PART I: MODEL DEVELOPMENT 1 , 1998 .