A New and Simplified Approach for Estimating the Daily River Discharge of the Tibetan Plateau Using Satellite Precipitation: An Initial Study on the Upper Brahmaputra River

Collecting in situ observations from remote, high mountain rivers presents major challenges, yet real-time, high temporal resolution (e.g., daily) discharge data are critical for flood hazard mitigation and river management. In this study, we propose a method for estimating daily river discharge (RD) based on free, operational remote sensing precipitation data (Tropical Rainfall Measuring Mission (TRMM), since 2001). In this method, an exponential filter was implemented to produce a new precipitation time series from daily basin-averaged precipitation data to model the time lag of precipitation in supplying RD, and a linear-regression relationship was constructed between the filtered precipitation time series and observed discharge records. Because of different time lags in the wet season (rainfall-dominant) and dry season (snowfall-dominant), the precipitation data were processed in a segmented way (from June to October and from November to May). The method was evaluated at two hydrological gauging stations in the Upper Brahmaputra (UB) river basin, where Nash–Sutcliffe Efficiency (NSE) coefficients for Nuxia (>0.85) and Yangcun (>0.80) indicate good performance. By using the degree-day method to estimate the snowmelt and acquire the time series of new active precipitation (rainfall plus snowmelt) in the target basins, the discharge estimations were improved (NSE > 0.9 for Nuxia) compared to the original data. This makes the method applicable for most rivers on the Tibetan Plateau, which are fed mainly by precipitation (including snowfall) and are subject to limited human interference. The method also performs well for reanalysis precipitation data (Chinese Meteorological Forcing Dataset (CMFD), 1980–2000). The real-time or historical discharges can be derived from satellite precipitation data (or reanalysis data for earlier historical years) by using our method.

[1]  John D. Valiantzas,et al.  Investigation of the direct runoff generation mechanism for the analysis of the SCS-CN method applicability to a partial area experimental watershed , 2009 .

[2]  Lei Wang,et al.  The dependence of precipitation types on surface elevation and meteorological conditions and its parameterization , 2014 .

[3]  Luca Brocca,et al.  Toward the estimation of river discharge variations using MODIS data in ungauged basins , 2013 .

[4]  C. Albergel,et al.  From near-surface to root-zone soil moisture using an exponential filter: an assessment of the method based on in-situ observations and model simulations , 2008 .

[5]  Yan Yuping,et al.  Climate change over the yarlung zangbo river basin during 1961-2005 , 2007 .

[6]  Luca Brocca,et al.  River Discharge Estimation by Using Altimetry Data and Simplified Flood Routing Modeling , 2013, Remote. Sens..

[7]  M. Hansen,et al.  Estimating daily streamflow in the Congo Basin using satellite-derived data and a semi-distributed hydrological model , 2019, Hydrological Sciences Journal.

[8]  Z. Hao,et al.  The impacts of climate change and land cover/use transition on the hydrology in the upper Yellow River Basin, China , 2013 .

[9]  Russell G. Congalton,et al.  Evaluating the potential for measuring river discharge from space , 2003 .

[10]  Xiuping Li,et al.  New methods designed to estimate the daily discharges of rivers in the Tibetan Plateau , 2019, Science Bulletin.

[11]  K. Takara,et al.  Hydrological Stream Flow Modelling for Calibration and Uncertainty Analysis Using SWAT Model in the Xedone River Basin, Lao PDR , 2015 .

[12]  Lei Wang,et al.  Estimation of River Discharge Solely from Remote-Sensing Derived Data: An Initial Study Over the Yangtze River , 2018, Remote. Sens..

[13]  C. Kummerow,et al.  The Tropical Rainfall Measuring Mission (TRMM) Sensor Package , 1998 .

[14]  Toshio Koike,et al.  Assessment of a distributed biosphere hydrological model against streamflow and MODIS land surface temperature in the upper Tone River Basin , 2009 .

[15]  B. Parida,et al.  Evaluation of future climate using SDSM and secondary data (TRMM and NCEP) for poorly gauged catchments of Uganda: the case of Aswa catchment , 2018, Theoretical and Applied Climatology.

[16]  Fei Xiao,et al.  Monitoring river discharge with remotely sensed imagery using river island area as an indicator , 2012 .

[17]  J. Qiu.  China: The third pole , 2008, Nature.

[18]  Abdollah A. Jarihani,et al.  Evaluation of multiple satellite altimetry data for studying inland water bodies and river floods , 2013 .

[19]  M. Kummu,et al.  Future changes in Mekong River hydrology: impact of climate change and reservoir operation on discharge , 2012 .

[20]  D. Alsdorf,et al.  Water slope and discharge in the Amazon River estimated using the shuttle radar topography mission digital elevation model , 2005 .

[21]  H. Rezaei-Sadr.  Influence of coarse soils with high hydraulic conductivity on the applicability of the SCS-CN method , 2017 .

[22]  C. Gleason,et al.  Toward global mapping of river discharge using satellite images and at-many-stations hydraulic geometry , 2014, Proceedings of the National Academy of Sciences.

[23]  Lei Wang,et al.  Evaluation and application of a fine‐resolution global data set in a semiarid mesoscale river basin with a distributed biosphere hydrological model , 2011 .

[24]  Zhenchun Hao,et al.  Discharge regime and simulation for the upstream of major rivers over Tibetan Plateau , 2013 .

[25]  Zongxue Xu,et al.  Streamflow response to climate variability and human activities in the upper catchment of the Yellow River Basin , 2009 .

[26]  M. Bierkens,et al.  Climate Change Will Affect the Asian Water Towers , 2010, Science.

[27]  Zeyong Hu,et al.  Meteorological Forcing Datasets for Blowing Snow Modeling on the Tibetan Plateau: Evaluation and Intercomparison , 2017 .

[28]  Wenchao Sun,et al.  Prospects for calibrating rainfall‐runoff models using satellite observations of river hydraulic variables as surrogates for in situ river discharge measurements , 2012 .

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

[30]  Luca Brocca,et al.  Discharge estimation and forecasting by MODIS and altimetry data in Niger-Benue River , 2017 .

[31]  Douglas W. Burbank,et al.  Towards a complete Himalayan hydrologic budget : The spatiotemporal distribution of snowmelt and rainfall and their impact on river discharge , 2010 .

[32]  Delwyn Moller,et al.  Estimating discharge in rivers using remotely sensed hydraulic information , 2005 .

[33]  Marouane Temimi,et al.  A multi‐temporal analysis of AMSR‐E data for flood and discharge monitoring during the 2008 flood in Iowa , 2011 .

[34]  Tamlin M. Pavelsky,et al.  Using width‐based rating curves from spatially discontinuous satellite imagery to monitor river discharge , 2014 .

[35]  Chris Kilsby,et al.  Daily discharge estimation at ungauged river sites using remote sensing , 2014 .

[36]  Yang Hong,et al.  Microwave Satellite Data for Hydrologic Modeling in Ungauged Basins , 2012, IEEE Geoscience and Remote Sensing Letters.

[37]  Fan Yang,et al.  Evaluation of multiple forcing data sets for precipitation and shortwave radiation over major land areas of China , 2017 .

[38]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[39]  Richard B. Lammers,et al.  Increasing River Discharge to the Arctic Ocean , 2002, Science.

[40]  W. Wagner,et al.  A Method for Estimating Soil Moisture from ERS Scatterometer and Soil Data , 1999 .

[41]  Lei Wang,et al.  Estimating continental river basin discharges using multiple remote sensing data sets , 2016 .

[42]  Tandong Yao,et al.  Third Pole Environment (TPE) , 2012 .

[43]  Yang Hong,et al.  Discharge estimation in high-mountain regions with improved methods using multisource remote sensing: A case study of the Upper Brahmaputra River , 2018, Remote Sensing of Environment.

[44]  Cheng Wang,et al.  Constructing river stage-discharge rating curves using remotely sensed river cross-sectional inundation areas and river bathymetry , 2016 .

[45]  Nico Sneeuw,et al.  River discharge estimation at daily resolution from satellite altimetry over an entire river basin , 2017 .