Improved modeling of snow and glacier melting by a progressive two‐stage calibration strategy with GRACE and multisource data: How snow and glacier meltwater contributes to the runoff of the Upper Brahmaputra River basin?

Snow and glacier melting and accumulation are important processes of the hydrological cycle in the cryosphere, e.g., high-mountain areas. Glaciers and snow cover respond to climate change notably over the Tibetan Plateau (TP) as the Earth's Third Pole where complex topography and lack of ground-based observations result in knowledge gaps in hydrological processes and large uncertainties in model output. This study develops a snow and glacier melt model for a distributed hydrological model (Coupled Routing and Excess Storage model, CREST) using the Upper Brahmaputra River (UBR) basin in the TP as a case study. Satellite and ground-based precipitation and land surface temperature are jointly used as model forcing. A progressive two-stage calibration strategy is developed to derive model parameters, i.e., (1) snow melting processes (stage I) and (2) glacier melting and runoff generation and routing using multisource data (stage II). Stage-I calibration is performed using the MODIS snow cover area (SCA) product and a blending snow water equivalent (SWE) product combined with partial in situ measurements. Stage-II calibration is based on Gravity Recovery and Climate Experiment (GRACE) satellite-derived total water storage (TWS) changes and streamflow observed at a gauging station of the lower reach of the UBR. Results indicate that the developed two-stage calibration method provides more reliable streamflow, snow (both SCA and SWE), and TWS change simulations against corresponding observations than commonly used methods based on streamflow and/or SCA performance. The simulated TWS time series shows high consistency with GRACE counterparts for the study period 2003–2014, and overestimated melting rates and contributions of glacier meltwater to runoff in previous studies are improved to some degree by the developed model and calibration strategy. Snow and glacier runoff contributed 10.6% and 9.9% to the total runoff, and the depletion rate of glacier mass was ∼ −10 mm/a (∼ −2.4 Gt/a, Gt/a is gigaton (km3 of water) per year) over the UBR basin during the study period. This study is valuable in examining the impacts of climate change on hydrological processes of cryospheric regions and providing an improved approach for simulating more reliable hydrological variables over the UBR basin and potentially similar regions globally.

[1]  T. Jonas,et al.  Estimating the snow water equivalent from snow depth measurements in the Swiss Alps , 2009 .

[2]  D. Rowlands,et al.  Recent glacier mass changes in the Gulf of Alaska region from GRACE mascon solutions , 2008, Journal of Glaciology.

[3]  M. Watkins,et al.  Improved methods for observing Earth's time variable mass distribution with GRACE using spherical cap mascons , 2015 .

[4]  S. Attinger,et al.  Improving the realism of hydrologic model functioning through multivariate parameter estimation , 2016 .

[5]  Ezio Todini,et al.  TOPKAPI: a model for the representation of the rainfall‐runoff process at different scales , 2002 .

[6]  Yan Shen,et al.  Validation and comparison of a new gauge‐based precipitation analysis over mainland China , 2016 .

[7]  Morten Andreas Dahl Larsen,et al.  Calibration of a distributed hydrology and land surface model using energy flux measurements , 2016 .

[8]  Günter Blöschl,et al.  Spatio‐temporal combination of MODIS images – potential for snow cover mapping , 2008 .

[9]  Keith Beven,et al.  Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology , 2001 .

[10]  S. Hagemann,et al.  A modified monthly degree‐day model for evaluating glacier runoff changes in China. Part I: model development , 2012 .

[11]  Yang Hong,et al.  Refining a Distributed Linear Reservoir Routing Method to Improve Performance of the CREST Model , 2017 .

[12]  Annette Eicker,et al.  Satellites provide the big picture , 2015, Science.

[13]  K. Franz,et al.  Calibration of a distributed snow model using MODIS snow covered area data , 2013 .

[14]  Z. Pu,et al.  MODIS/Terra observed seasonal variations of snow cover over the Tibetan Plateau , 2007 .

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

[16]  Liangpei Zhang,et al.  Reconstructing MODIS LST Based on Multitemporal Classification and Robust Regression , 2015, IEEE Geoscience and Remote Sensing Letters.

[17]  Claudio Smiraglia,et al.  Prediction of future hydrological regimes in poorly gauged high altitude basins: the case study of the upper Indus, Pakistan , 2011 .

[18]  Douglas W. Burbank,et al.  Toward a complete Himalayan hydrological budget: Spatiotemporal distribution of snowmelt and rainfall and their impact on river discharge , 2010 .

[19]  Shunlin Liang,et al.  The altitudinal dependence of recent rapid warming over the Tibetan Plateau , 2009 .

[20]  Alain Royer,et al.  Improvement of springtime streamflow simulations in a boreal environment by incorporating snow-covered area derived from remote sensing data. , 2010 .

[21]  Stefan Dech,et al.  Remote sensing of snow – a review of available methods , 2012 .

[22]  M. R. van den Broeke,et al.  A Reconciled Estimate of Glacier Contributions to Sea Level Rise: 2003 to 2009 , 2013, Science.

[23]  M. Rodell,et al.  Assimilation of GRACE Terrestrial Water Storage Data into a Land Surface Model: Results for the Mississippi River Basin , 2008 .

[24]  B. Scanlon,et al.  Ground referencing GRACE satellite estimates of groundwater storage changes in the California Central Valley, USA , 2012 .

[25]  G. Senay,et al.  Climate science and famine early warning , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[26]  J. Refsgaard.  Parameterisation, calibration and validation of distributed hydrological models , 1997 .

[27]  Z. Wan.  New refinements and validation of the MODIS Land-Surface Temperature/Emissivity products , 2008 .

[28]  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 .

[29]  Liyun Dai,et al.  Inter-Calibrating SMMR, SSM/I and SSMI/S Data to Improve the Consistency of Snow-Depth Products in China , 2015, Remote. Sens..

[30]  T. Schmugge,et al.  Remote sensing in hydrology , 2002 .

[31]  Zhao Ren-jun,et al.  The Xinanjiang model applied in China , 1992 .

[32]  P. Burlando,et al.  Assessing the transferability and robustness of an enhanced temperature-index glacier-melt model , 2009, Journal of Glaciology.

[33]  John W. Nicklow,et al.  Multi-objective automatic calibration of SWAT using NSGA-II , 2007 .

[34]  David Mocko,et al.  Blending satellite‐based snow depth products with in situ observations for streamflow predictions in the Upper Colorado River Basin , 2015 .

[35]  J. Arnold,et al.  Development of a snowfall-snowmelt routine for mountainous terrain for the soil water assessment tool (SWAT) , 2002 .

[36]  Brian Menounos,et al.  Contribution of Alaskan glaciers to sea-level rise derived from satellite imagery , 2010 .

[37]  Yang Hong,et al.  Comprehensive evaluation of multi-satellite precipitation products with a dense rain gauge network and optimally merging their simulated hydrological flows using the Bayesian model averaging method , 2012 .

[38]  B. Scanlon,et al.  Global analysis of approaches for deriving total water storage changes from GRACE satellites , 2015 .

[39]  J. Caesar,et al.  Temperature and precipitation projections over Bangladesh and the upstream Ganges, Brahmaputra and Meghna systems. , 2015, Environmental science. Processes & impacts.

[40]  F. Landerer,et al.  Accuracy of scaled GRACE terrestrial water storage estimates , 2012 .

[41]  Y. Hong,et al.  Multi-scale evaluation of high-resolution multi-sensor blended global precipitation products over the Yangtze River , 2013 .

[42]  Yi-ping Fang,et al.  Spatio-Temporal Characteristics of Global Warming in the Tibetan Plateau during the Last 50 Years Based on a Generalised Temperature Zone - Elevation Model , 2013, PloS one.

[43]  Shahid Habib,et al.  Satellite Remote Sensing and Hydrologic Modeling for Flood Inundation Mapping in Lake Victoria Basin: Implications for Hydrologic Prediction in Ungauged Basins , 2009, IEEE Transactions on Geoscience and Remote Sensing.

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

[45]  J. Pulliainen,et al.  Evaluation of snow products over the Tibetan Plateau , 2015 .

[46]  Marc F. P. Bierkens,et al.  Consistent increase in High Asia's runoff due to increasing glacier melt and precipitation , 2014 .

[47]  Jouni Pulliainen,et al.  Mapping of snow water equivalent and snow depth in boreal and sub-arctic zones by assimilating space-borne microwave radiometer data and ground-based observations , 2006 .

[48]  Li Zhang,et al.  Hydrological response to future climate changes for the major upstream river basins in the Tibetan Plateau , 2016 .

[49]  B. Scanlon,et al.  GRACE Hydrological estimates for small basins: Evaluating processing approaches on the High Plains Aquifer, USA , 2010 .

[50]  J. Pu,et al.  Modeling the runoff and glacier mass balance in a small watershed on the Central Tibetan Plateau, China, from 1955 to 2008 , 2012 .

[51]  Shiqiang Zhang,et al.  Modeling Hydrologic Response to Climate Change and Shrinking Glaciers in the Highly Glacierized Kunma Like River Catchment, Central Tian Shan , 2015 .

[52]  S. Attinger,et al.  Multiscale parameter regionalization of a grid‐based hydrologic model at the mesoscale , 2010 .

[53]  Martin Funk,et al.  An enhanced temperature-index glacier melt model including the shortwave radiation balance: development and testing for Haut Glacier d'Arolla, Switzerland , 2005 .

[54]  William L. Quinton,et al.  The cold regions hydrological model: a platform for basing process representation and model structure on physical evidence , 2007 .

[55]  V. Singh,et al.  Computer Models of Watershed Hydrology , 1995 .

[56]  Qingyun Duan,et al.  An integrated hydrologic Bayesian multimodel combination framework: Confronting input, parameter, and model structural uncertainty in hydrologic prediction , 2006 .

[57]  Günter Blöschl,et al.  Estimating degree-day factors from MODIS for snowmelt runoff modeling , 2014 .

[58]  T. Blume,et al.  The value of satellite‐derived snow cover images for calibrating a hydrological model in snow‐dominated catchments in Central Asia , 2014 .

[59]  F. Göttsche,et al.  Influence of Land Surface Parameters and Atmosphere on METEOSAT Brightness Temperatures and Generation of Land Surface Temperature Maps by Temporally and Spatially Interpolating Atmospheric Correction , 2001 .

[60]  Junfeng Wei,et al.  Surface-area changes of glaciers in the Tibetan Plateau interior area since the 1970s using recent Landsat images and historical maps , 2014 .

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

[62]  P. Burlando,et al.  The value of glacier mass balance, satellite snow cover images, and hourly discharge for improving the performance of a physically based distributed hydrological model , 2011 .

[63]  Jian Wang,et al.  Snow depth and snow water equivalent estimation from AMSR-E data based on a priori snow characteristics in Xinjiang, China , 2012 .

[64]  G. Blöschl,et al.  The value of MODIS snow cover data in validating and calibrating conceptual hydrologic models , 2008 .

[65]  Regine Hock,et al.  Temperature index melt modelling in mountain areas , 2003 .

[66]  Roger L. King,et al.  Statistical Estimation of Daily Maximum and Minimum Air Temperatures from MODIS LST Data over the State of Mississippi , 2006 .

[67]  Zuhal Akyürek,et al.  Using MODIS snow cover maps in modeling snowmelt runoff process in the eastern part of Turkey , 2005 .

[68]  Dingbao Wang,et al.  Modeling interannual variability of seasonal evaporation and storage change based on the extended Budyko framework , 2013 .

[69]  Mahyar Shafii,et al.  Multi-objective calibration of a distributed hydrological model (WetSpa) using a genetic algorithm , 2009 .

[70]  N. Ward,et al.  Hydro‐meteorological variability in the greater Ganges–Brahmaputra–Meghna basins , 2004 .

[71]  Kuolin Hsu,et al.  Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using the particle filter , 2005 .

[72]  D. Hall,et al.  Accuracy assessment of the MODIS snow products , 2007 .

[73]  Yang Hong,et al.  Drought and flood monitoring for a large karst plateau in Southwest China using extended GRACE data , 2014 .

[74]  Yang Hong,et al.  Statistical and hydrological evaluation of TRMM-based Multi-satellite Precipitation Analysis over the Wangchu Basin of Bhutan: Are the latest satellite precipitation products 3B42V7 ready for use in ungauged basins? , 2013 .

[75]  Markus Neteler,et al.  Estimating Daily Land Surface Temperatures in Mountainous Environments by Reconstructed MODIS LST Data , 2010, Remote. Sens..

[76]  Yang Hong,et al.  Hydrologic evaluation of Multisatellite Precipitation Analysis standard precipitation products in basins beyond its inclined latitude band: A case study in Laohahe basin, China , 2010 .

[77]  M. Rodell,et al.  Assimilation of terrestrial water storage from GRACE in a snow‐dominated basin , 2011 .

[78]  Soroosh Sorooshian,et al.  Optimal use of the SCE-UA global optimization method for calibrating watershed models , 1994 .

[79]  P. Xie,et al.  A Gauge-Based Analysis of Daily Precipitation over East Asia , 2007 .

[80]  T. Barnett,et al.  Potential impacts of a warming climate on water availability in snow-dominated regions , 2005, Nature.

[81]  Sadiq I. Khan,et al.  The coupled routing and excess storage (CREST) distributed hydrological model , 2011 .

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

[83]  A. Roy,et al.  Snow cover estimation using blended MODIS and AMSR‐E data for improved watershed‐scale spring streamflow simulation in Quebec, Canada , 2014 .

[84]  D. Lettenmaier,et al.  Surface soil moisture parameterization of the VIC-2L model: Evaluation and modification , 1996 .

[85]  Yang Hong,et al.  Hydrology and Earth System Sciences Hydroclimatology of Lake Victoria Region Using Hydrologic Model and Satellite Remote Sensing Data , 2022 .

[86]  Z. Wan.  New refinements and validation of the collection-6 MODIS land-surface temperature/emissivity product , 2014 .

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

[88]  J. Oerlemans.  Glaciers as indicators of a carbon dioxide warming , 1986, Nature.

[89]  Soroosh Sorooshian,et al.  Toward improved calibration of hydrologic models: Multiple and noncommensurable measures of information , 1998 .

[90]  W. Tad Pfeffer,et al.  Recent contributions of glaciers and ice caps to sea level rise , 2012, Nature.

[91]  F. Giorgi,et al.  Climate change over the Yarlung Zangbo–Brahmaputra River Basin in the 21st century as simulated by a high resolution regional climate model , 2011 .

[92]  Hongyi Li,et al.  Simulation of snow distribution and melt under cloudy conditions in an Alpine watershed , 2010 .

[93]  R. Warrick,et al.  Trends and persistence in precipitation in the Ganges, Brahmaputra and Meghna river basins , 1998 .

[94]  S. Sorooshian,et al.  Effective and efficient global optimization for conceptual rainfall‐runoff models , 1992 .

[95]  Ning Wang,et al.  Evaluation of six land-surface diurnal temperature cycle models using clear-sky in situ and satellite data , 2012 .

[96]  Y. Hong,et al.  Global analysis of spatiotemporal variability in merged total water storage changes using multiple GRACE products and global hydrological models , 2017 .

[97]  Chris Derksen,et al.  Estimating Snow Water Equivalent Using Snow Depth Data and Climate Classes , 2010 .

[98]  Longwei Xiang,et al.  Groundwater storage changes in the Tibetan Plateau and adjacent areas revealed from GRACE satellite gravity data , 2016 .

[99]  M. Rodell,et al.  Assimilation of gridded terrestrial water storage observations from GRACE into a land surface model , 2016 .

[100]  Yiran Peng,et al.  Summer rainfall over the southwestern Tibetan Plateau controlled by deep convection over the Indian subcontinent , 2016, Nature Communications.

[101]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[102]  L. Thompson,et al.  Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings , 2012 .

[103]  Patrick M. Reed,et al.  When are multiobjective calibration trade‐offs in hydrologic models meaningful? , 2012 .

[104]  Martyn P. Clark,et al.  STEP WISE, MULTIPLE OBJECTIVE CALIBRATION OF A HYDROLOGIC MODEL FOR A SNOWMELT DOMINATED BASIN 1 , 2006 .

[105]  Y. Hong,et al.  Similarity and difference of the two successive V6 and V7 TRMM multisatellite precipitation analysis performance over China , 2013 .