ISI Document Delivery No.: AB0BS Times Cited: 0 Cited Reference Count: 40 Cited References: Alsdorf DE, 2007, REV GEOPHYS, V45, DOI 10.1029/2006RG000197 Application of Climate Forecasts in the Agriculture Sector, 2002, APPL CLIM FOR AGR SE Bakker MH, 2009, J AM WATER RESOUR AS, V45, P553, DOI 10.1111/j.1752-1688.2009.00325.x Balthrop C, 2010, WATER POLICY, V12, P635, DOI 10.2166/wp.2009.117 Biancamaria S, 2011, GEOPHYS RES LETT, V38, DOI 10.1029/2011GL047290 Birkett CM, 2002, J GEOPHYS RES-ATMOS, V107, DOI 10.1029/2001JD000609 Bjerklie DM, 2005, J HYDROL, V309, P191, DOI 10.1016/j.jhydrol.2004.11.022 Box GEP, 1976, TIME SERIES ANAL FOR Brakenridge G. R., 2005, EOS T AM GEOPHYS UNI, V86 Brakenridge G. R., 2007, WATER RESOURCES RES, V43 Calmant S, 2013, ADV SPACE RES, V51, P1551, DOI 10.1016/j.asr.2012.07.033 Davis CH, 1997, IEEE T GEOSCI REMOTE, V35, P974, DOI 10.1109/36.602540 Durand D., 2008, GEOPHYS RES LETT, V35, DOI [10.1029/2008GL034150, DOI 10.1029/2008GL034150] Evans S. G., 2011, LECT NOTES EARTH SCI, V133, P543, DOI [10.1007/978-3-642-04764-0_22, DOI 10.1007/978-3-642-04764-0_] Frappart F, 2006, REMOTE SENS ENVIRON, V100, P252, DOI 10.1016/j.rse.2005.10.027 Hossain F., 2006, EOS T AGU, V87, P49, DOI DOI 10.1029/2006EO050001 Hossain F, 2007, WATER INT, V32, P376 Jung H. C., 2010, EARTH SURF PROCESSES, DOI DOI 10.1002/ESPL Kalyanapu AJ, 2011, ENVIRON MODELL SOFTW, V26, P1009, DOI 10.1016/j.envsoft.2011.02.014 Khan SI, 2011, IEEE T GEOSCI REMOTE, V49, P85, DOI 10.1109/TGRS.2010.2057513 Kouraev AV, 2004, REMOTE SENS ENVIRON, V93, P238, DOI 10.1016/j.rse.2004.07.007 Lee H, 2008, J GEODYN, V46, P182, DOI 10.1016/j.jog.2008.05.001 Lee H., 2011, AGU FALL M Lee H, 2009, MAR GEOD, V32, P284, DOI 10.1080/01490410903094767 LeFavour G, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2005GL023836 MARTIN TV, 1983, J GEOPHYS RES-OC ATM, V88, P1608, DOI 10.1029/JC088iC03p01608 Misra AK, 2007, ENVIRON GEOL, V51, P1361, DOI 10.1007/s00254-006-0434-7 Moffitt CB, 2011, INT J APPL EARTH OBS, V13, P165, DOI 10.1016/j.jag.2010.11.003 Nishat B, 2009, J AM WATER RESOUR AS, V45, P1313, DOI 10.1111/j.1752-1688.2009.00374.x Paudyal GN, 2002, HYDROLOG SCI J, V47, pS5 Pielke R., 2009, EOS T AM GEOPHYS UN, V90, P453, DOI DOI 10.1029/2009EO480001 Pingel N., 2005, NAT HAZARDS REV, V6, P60, DOI DOI 10.1061/(ASCE)1527-6988(2005)6:2(60) Prestininzi P, 2011, ADV WATER RESOUR, V34, P38, DOI 10.1016/j.advwatres.2010.09.016 Siddique-E-Akbor AHM, 2011, REMOTE SENS ENVIRON, V115, P1522, DOI 10.1016/j.rse.2011.02.011 Temimi M., 2011, HYDROLOGICAL PROCESS, V25, P2623 Thibaut P., 2010, COMMUNICATION Vorosmarty CJ, 2009, B ATOM SCI, V65, P31, DOI 10.2968/065002005 Wingham D., 1986, P IEEE IGARSS, V3, P1339 Woldemichael A. T., 2010, IEEE SPECIAL TOPICS, DOI [10.1109/JSTARS.2010. 2050579, DOI 10.1109/JSTARS.2010.2050579] Wolf A T, 1999, INT J WATER RESOUR D, V15, P387, DOI DOI 10.1080/07900629948682 Hossain, Faisal Siddique-E-Akbor, A. H. Mazumder, Liton Chandra ShahNewaz, Sardar M. Biancamaria, Sylvain Lee, Hyongki Shum, C. K. NASA Physical Oceanography progr...

The Ganges-Brahmaputra-Meghna (GBM) river basins exhibit extremes in surface water availability at seasonal to annual time scales. However, because of a lack of basinwide hydrological data from in situ platforms, whether they are real time or historical, water management has been quite challenging for the 630 million inhabitants. Under such circumstances, a large-scale and spatially distributed hydrological model, forced with more widely available satellite meteorological data, can be useful for generating high resolution basinwide hydrological state variable data [streamflow, runoff, and evapotranspiration (ET)] and for decision making on water management. The Variable Infiltration Capacity (VIC) hydrological model was therefore set up for the entire GBM basin at spatial scales ranging from 12.5 to 25 km to generate daily fluxes of surface water availability (runoff and streamflow). Results indicate that, with the selection of representative gridcell size and application of correction factors to evapotranspiration calculation, it is possible to significantly improve streamflow simulation and overcome some of the insufficient sampling and data quality issues in the ungauged basins. Assessment of skill of satellite precipitation forcing datasets revealed that the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) product of 3B42RT fared comparatively better than the Climate Prediction Center (CPC) morphing technique (CMORPH) product for simulation of streamflow. The general conclusion that emerges from this study is that spatially distributed hydrologic modeling for water management is feasible for the GBM basins under the scenario of inadequate in situ data availability. Satellite precipitation forcing datasets provide the necessary skill for water balance studies at interannual and interseasonal scales. However, further improvement in skill may be required if these datasets are to be used for flood management at daily to weekly time scales and within a data assimilation framework.

No abstract

No abstract

No abstract