Suitability of the TRMM satellite rainfalls in driving a distributed hydrological model for water balance computations in Xinjiang catchment, Poyang lake basin Xiang-Hu Li a , Qi Zhang a,⇑ , Chong-Yu Xu b,c a State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China b Department of Geosciences, University of Oslo, Oslo, Norway c School of Geographic and Oceanographic Sciences, Nanjing University, China article info Article history: Received 8 September 2011 Received in revised form 21 November 2011 Accepted 8 January 2012 Available online 24 January 2012 This manuscript was handled by Konstantine P. Georgakakos, Editor-in-Chief, with the assistance of Hervé Andrieu, Associate Editor Keywords: Rainfall TRMM Hydrological process Water balance Distributed hydrological model Xinjiang catchment summary Spatial rainfall is a key input to distributed hydrological models, and its precisions heavily affect the accu- racy of stream flow predictions from a hydrological model. Traditional interpolation techniques which obtain the spatial rainfall distribution from rain gauge data have some limitations caused by data scarcity and bad quality, especially in developing countries or remote locations. Satellite-based precipitation products are expected to offer an alternative to ground-based rainfall estimates in the present and the foreseeable future. For this purpose, the quality and usefulness of satellite-based precipitation products need to be evaluated. The present study compares the difference of Tropical Rainfall Measuring Mission (TRMM) rainfall with rain gauges data at different time scales and evaluates the usefulness of the TRMM rainfall for hydrological processes simulation and water balance analysis at the Xinjiang catchment, located in the lower reaches of the Yangtze River in China. The results show at daily time step TRMM rainfall data are better at determining rain occurrence and mean values than at determining the rainfall extremes, and larger difference exists for the maximal daily and maximal 5-day rainfalls. At monthly time scale, good linear relationships between TRMM rainfall and rain gauges rainfall data are received with the determination coefficients (R 2 ) varying between 0.81 and 0.89 for the individual stations and 0.88 for areal average rainfall data, respectively. But the slope of regression line ranges between 0.74 for Yingtan and 0.94 for Yushan, indicating that the TRMM satellite is inclined to underestimate the monthly rainfall in this area. The simulation of daily hydrological processes shows that the Water Flow Model for Lake Catchment (WATLAC) model using conventional rain gauge data produces an overall good fit, but the simulation results using TRMM rainfall data are discontented. The evaluation results imply that the TRMM rainfall data are unsuited for daily stream flow simulation in this study area with desired preci- sions. However, good performance can be received using TRMM rainfall data for monthly stream flow simulations. The comparison of the simulated annual water balance components shows that the different rainfall data sources can change the volume value and proportion of water balance components to some extent, but it generally meets the need of practical use. Ó 2012 Elsevier B.V. All rights reserved. 1. Introduction Distributed hydrological models have become the main tool to understand the hydrological processes and solve practical hydro- logical and water resources problems. Physically-based distributed hydrological models can fulfill the necessity of describing spatial heterogeneity, assessing the impact of natural and human induced changes and providing detailed descriptions of the hydrological processes in watersheds to satisfy various needs in spatial model- ling (Abbott and Refsgaard, 1996). However, these models require the spatially distributed data as input to reflect the heterogeneity of base information in the watersheds. The spatial rainfall is one of the key inputs for these models, and the accuracy of stream flow predictions from a hydrological model is heavily dependent on the accuracy of rainfall inputs (Gourley and Vieux, 2006), therefore, accurate estimate of the rainfall patterns over a catchment and a region is a great concern (Kurtzman et al., 2009). Conventional estimates of daily areal rainfall can be obtained by spatial interpolation of rain gauges’ data (Kurtzman et al., 2009). Various interpolation techniques have been proposed for areal rainfall estimations. The isohyetal and Thiessen polygon tech- niques are commonly used techniques of this kind (Guillermo et al., 1985). However, direct application of these techniques may produce inaccurate results because of the effects of topographical 0022-1694/$ - see front matter Ó 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.jhydrol.2012.01.013 ⇑ Corresponding author. Address: Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, 73 East Beijing Road, Nanjing 210008, PR China. Tel.: +86 25 86882102; fax: +86 25 57714759. E-mail addresses: lxh8010@yahoo.com.cn (X.-H. Li), qzhang@niglas.ac.cn (Q. Zhang), c.y.xu@geo.uio.no (C.-Y. Xu). Journal of Hydrology 426–427 (2012) 28–38 Contents lists available at SciVerse ScienceDirect Journal of Hydrology journal homepage: www.elsevier.com/locate/jhydrol