Improved Remotely Sensed Total Basin Discharge and Its Seasonal Error Characterization in the Yangtze River Basin

Total basin discharge is a critical component for the understanding of surface water exchange at the land–ocean interface. A continuous decline in the number of global hydrological stations over the past fifteen years has promoted the estimation of total basin discharge using remote sensing. Previous remotely sensed total basin discharge of the Yangtze River basin, expressed in terms of runoff, was estimated via the water balance equation, using a combination of remote sensing and modeled data products of various qualities. Nevertheless, the modeled data products are presented with large uncertainties and the seasonal error characteristics of the remotely sensed total basin discharge have rarely been investigated. In this study, we conducted total basin discharge estimation of the Yangtze River Basin, based purely on remotely sensed data. This estimation considered the period between January 2003 and December 2012 at a monthly temporal scale and was based on precipitation data collected from the Tropical Rainfall Measuring Mission (TRMM) satellite, evapotranspiration data collected from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite, and terrestrial water storage data collected from the Gravity Recovery and Climate Experiment (GRACE) satellite. A seasonal accuracy assessment was performed to detect poor performances and highlight any deficiencies in the modeled data products derived from the discharge estimation. Comparison of our estimated runoff results based purely on remotely sensed data, and the most accurate results of a previous study against the observed runoff revealed a Pearson correlation coefficient (PCC) of 0.89 and 0.74, and a root-mean-square error (RMSE) of 11.69 mm/month and 14.30 mm/month, respectively. We identified some deficiencies in capturing the maximum and the minimum of runoff rates during both summer and winter, due to an underestimation and overestimation of evapotranspiration, respectively.

[1]  Chris Kilsby,et al.  Using satellite altimetry data to augment flow estimation techniques on the Mekong River , 2010 .

[2]  Zhongyuan Chen,et al.  Yangtze River of China: historical analysis of discharge variability and sediment flux , 2001 .

[3]  James S. Famiglietti,et al.  Remote Sensing of Terrestrial Water Storage, Soil Moisture and Surface Waters , 2013 .

[4]  N. Fohrer,et al.  Spatial and temporal characteristics of wet spells in the Yangtze River Basin from 1961 to 2003 , 2009 .

[5]  Narendra Singh Raghuwanshi,et al.  Spatial and Temporal Variation of Manning’s Roughness Coefficient in Furrow Irrigation , 2008 .

[6]  Michael Durand,et al.  Assessing the potential global extent of SWOT river discharge observations , 2014 .

[7]  Anny Cazenave,et al.  Ob' river discharge from TOPEX/Poseidon satellite altimetry (1992–2002) , 2004 .

[8]  R. Reynolds,et al.  The NCEP/NCAR 40-Year Reanalysis Project , 1996, Renewable Energy.

[9]  Minha Choi,et al.  Stand-alone uncertainty characterization of GLEAM, GLDAS and MOD16 evapotranspiration products using an extended triple collocation approach , 2018 .

[10]  Florian Pappenberger,et al.  A data assimilation approach to discharge estimation from space , 2009 .

[11]  Taikan Oki,et al.  Global atmospheric water balance and runoff from large river basins , 1995 .

[12]  Xiufeng He,et al.  Estimating Total Discharge in the Yangtze River Basin Using Satellite-Based Observations , 2013, Remote. Sens..

[13]  S. Running,et al.  A continuous satellite‐derived global record of land surface evapotranspiration from 1983 to 2006 , 2010 .

[14]  Chong-Yu Xu,et al.  Sediment and runoff changes in the Yangtze River basin during past 50 years , 2006 .

[15]  Tong Jiang,et al.  Recent trends in observed temperature and precipitation extremes in the Yangtze River basin, China , 2006 .

[16]  Kevin E. Trenberth,et al.  Estimates of Freshwater Discharge from Continents: Latitudinal and Seasonal Variations , 2002 .

[17]  J. Peixoto,et al.  Physics of climate , 1984 .

[18]  K. Tockner,et al.  A global boom in hydropower dam construction , 2014, Aquatic Sciences.

[19]  Patrick Matgen,et al.  Integration of SAR-derived river inundation areas, high-precision topographic data and a river flow model toward near real-time flood management , 2007, Int. J. Appl. Earth Obs. Geoinformation.

[20]  Xixi Lu,et al.  NDVI and its Relationships with Hydrological Regimes in the Upper Yangtze , 2000 .

[21]  Mekonnen Gebremichael,et al.  Upstream satellite remote sensing for river discharge forecasting: Application to major rivers in South Asia , 2013 .

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

[23]  Qi Zhang,et al.  GRACE-Based Hydrological Drought Evaluation of the Yangtze River Basin, China , 2016 .

[24]  L. B. Leopold,et al.  The hydraulic geometry of stream channels and some physiographic implications , 1953 .

[25]  J. Milliman,et al.  Seasonal variations of sediment discharge from the Yangtze River before and after impoundment of the Three Gorges Dam , 2009 .

[26]  Luca Brocca,et al.  River discharge estimation through MODIS data , 2011, Remote Sensing.

[27]  Douglas A. Miller,et al.  GCIP water and energy budget synthesis (WEBS) , 2002 .

[28]  David T. Bolvin,et al.  Real-Time TRMM Multi-Satellite Precipitation Analysis Data Set Documentation , 2015 .

[29]  Feifei Pan,et al.  Remote sensing of river stage using the cross‐sectional inundation area‐river stage relationship (IARSR) constructed from digital elevation model data , 2013 .

[30]  James S. Famiglietti,et al.  GRACE-Based Estimates of Terrestrial Freshwater Discharge from Basin to Continental Scales , 2007 .

[31]  P. Ciais,et al.  Contributions of Climate Change, CO2, Land-Use Change, and Human Activities to Changes in River Flow across 10 Chinese Basins , 2018, Journal of Hydrometeorology.

[32]  R. Dickinson,et al.  A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability , 2011 .

[33]  Frédéric Frappart,et al.  WATER VOLUME CHANGE IN THE LOWER MEKONG FROM SATELLITE ALTIMETRY AND IMAGERY DATA , 2006 .

[34]  C. Shum,et al.  Satellite radar altimetry for monitoring small rivers and lakes in Indonesia , 2014 .

[35]  Daniela Jacob,et al.  A note to the simulation of the annual and inter-annual variability of the water budget over the Baltic Sea drainage basin , 2001 .

[36]  Y. Hong,et al.  The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales , 2007 .

[37]  B. Ye,et al.  Contributions of climate and human activities to changes in runoff of the Yellow and Yangtze rivers from 1950 to 2008 , 2013, Science China Earth Sciences.

[38]  Shuanggen Jin,et al.  Lake level change and total water discharge in East Africa Rift Valley from satellite-based observations , 2014, GPC 2014.

[39]  Xianyou Ren,et al.  Analysis of historical floods on the Yangtze River, China: Characteristics and explanations , 2009 .

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

[41]  T. Pavelsky,et al.  Estimation of river discharge, propagation speed, and hydraulic geometry from space: Lena River, Siberia , 2008 .

[42]  L. Smith Satellite remote sensing of river inundation area, stage, and discharge: a review , 1997 .

[43]  Sonia I. Seneviratne,et al.  Inferring changes in terrestrial water storage using ERA-40 reanalysis data: The Mississippi River Basin , 2004 .

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

[45]  Matthew Rodell,et al.  Analysis of terrestrial water storage changes from GRACE and GLDAS , 2008 .

[46]  Chao Wang,et al.  Characterization of spatio-temporal patterns for various GRACE- and GLDAS-born estimates for changes of global terrestrial water storage , 2013 .

[47]  Peter Salamon,et al.  Surface Freshwater Limitation Explains Worst Rice Production Anomaly in India in 2002 , 2018, Remote. Sens..

[48]  Dennis P. Lettenmaier,et al.  Tracking Fresh Water from Space , 2003, Science.

[49]  S. Seneviratne,et al.  Basin scale estimates of evapotranspiration using GRACE and other observations , 2004 .

[50]  K. Taylor Summarizing multiple aspects of model performance in a single diagram , 2001 .

[51]  J. Milliman,et al.  Temporal trend of precipitation and runoff in major Chinese Rivers since 1951 , 2010 .

[52]  A. Hoekstra,et al.  Analysis of Long-term Terrestrial Water Storage Variations in the Yangtze River Basin , 2014 .

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

[54]  Valentina Krysanova,et al.  Impact of Intensive Irrigation Activities on River Discharge Under Agricultural Scenarios in the Semi-Arid Aksu River Basin, Northwest China , 2014, Water Resources Management.

[55]  George J. Huffman,et al.  Estimates of Root-Mean-Square Random Error for Finite Samples of Estimated Precipitation , 1997 .

[56]  V. Singh,et al.  Contribution of multiple climatic variables and human activities to streamflow changes across China. , 2017 .

[57]  B. Scanlon,et al.  Uncertainty in evapotranspiration from land surface modeling, remote sensing, and GRACE satellites , 2014 .

[58]  S. Becker,et al.  Precipitation, temperature and runoff analysis from 1950 to 2002 in the Yangtze basin, China / Analyse des précipitations, températures et débits de 1950 à 2002 dans le bassin du Yangtze, en Chine , 2005 .

[59]  M. Cheng,et al.  Variations in the Earth's oblateness during the past 28 years , 2004 .

[60]  S. Swenson,et al.  Post‐processing removal of correlated errors in GRACE data , 2006 .

[61]  Weixin Xu,et al.  Correlation Analysis of Mackenzie River Discharge and NDVI Relationship , 2016 .

[62]  B. Cao,et al.  Dynamics Change of Honghu Lake's Water Surface Area and Its Driving Force Analysis Based on Remote Sensing Technique and TOPMODEL model , 2014 .

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

[64]  Lu Zhang,et al.  Response of mean annual evapotranspiration to vegetation changes at catchment scale , 2001 .

[65]  W. Yue,et al.  The relationship between land surface temperature and NDVI with remote sensing : application to Shanghai Landsat 7 ETM + data , 2009 .

[66]  Zhongyuan Chen,et al.  Impact on the Yangtze (Changjiang) Estuary from its drainage basin: Sediment load and discharge , 2001 .

[67]  S. Kanae,et al.  Global Hydrological Cycles and World Water Resources , 2006, Science.

[68]  S. F. Shih,et al.  Seasonal Variations of Manning's Roughness Coefficient in a Subtropical Marsh , 1982 .

[69]  Sang-Il Lee,et al.  Total Discharge Estimation in the Korean Peninsula Using Multi-Satellite Products , 2017 .

[70]  T. Jiang,et al.  Changes in monthly precipitation and flood hazard in the Yangtze River Basin, China , 2008 .

[71]  Y. Lyu,et al.  Effects of Three Gorges Dam operation on spatial distribution and evolution of channel thalweg in the Yichang-Chenglingji Reach of the Middle Yangtze River, China , 2018, Journal of Hydrology.

[72]  Yang Zhifeng Spatio-temporal changes of NDVI and their relations with precipitation and runoff in the Yellow River Basin , 2004 .

[73]  D. Chambers,et al.  Estimating Geocenter Variations from a Combination of GRACE and Ocean Model Output , 2008 .

[74]  S. Walsh,et al.  Modeling floodplain inundation using an integrated GIS with radar and optical remote sensing , 1998 .

[75]  Frédéric Frappart,et al.  Time variations of land water storage from an inversion of 2 years of GRACE geoids , 2005 .

[76]  F. Bryan,et al.  Time variability of the Earth's gravity field: Hydrological and oceanic effects and their possible detection using GRACE , 1998 .

[77]  M. Watkins,et al.  GRACE Measurements of Mass Variability in the Earth System , 2004, Science.

[78]  Steven Kempler,et al.  Tropical Rainfall Measuring Mission (TRMM) Precipitation Data and Services for Research and Applications , 2012 .

[79]  J. Chan,et al.  The East Asian summer monsoon: an overview , 2005 .

[80]  Nico Sneeuw,et al.  Estimating Runoff Using Hydro-Geodetic Approaches , 2014, Surveys in Geophysics.

[81]  Animesh K. Gain,et al.  Daily GRACE gravity field solutions track major flood events in the Ganges–Brahmaputra Delta , 2017 .

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

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

[84]  Petra Döll,et al.  Global water data: A newly endangered species , 2001 .

[85]  Chiara Corbari,et al.  Calibration and Validation of a Distributed Energy-Water Balance Model Using Satellite Data of Land Surface Temperature and Ground Discharge Measurements , 2014 .

[86]  Maosheng Zhao,et al.  Improvements to a MODIS global terrestrial evapotranspiration algorithm , 2011 .

[87]  農業土木学会応用水文研究部会,et al.  応用水文 = Applied hydrology , 1991 .

[88]  Matthew Rodell,et al.  Total basin discharge for the Amazon and Mississippi River basins from GRACE and a land‐atmosphere water balance , 2005 .

[89]  Chong-Yu Xu,et al.  Possible influence of ENSO on annual maximum streamflow of the Yangtze River, China , 2007 .