Hydrological Simulation and Runoff Component Analysis over a Cold Mountainous River Basin in Southwest China

Assessment of water resources from mountainous catchments is crucial for the development of upstream rural areas and downstream urban communities. However, lack of data in these mountainous catchments prevents full understanding of the response of hydrology or water resources to climate change. Meanwhile, hydrological modeling is challenging due to parameter uncertainty. In this work, one tributary of the Yarlung Zangbo River Basin (the upper stream of the Brahmaputra River) was used as a case study for hydrological modeling. Tropical Rainfall Measuring Mission (TRMM 3B42V7) data were utilized as a substitute for gauge-based rainfall data, and the capability of simulating precipitation, snow, and groundwater contributions to total runoff by the Soil and Water Assessment Tool (SWAT) was investigated. The uncertainty in runoff proportions from precipitation, snowmelt, and groundwater was quantified by a batch-processing module. Hydrological signatures were finally used to help identify if the hydrological model simulated total runoff and corresponding proportions properly. The results showed that: (1) TRMM data were very useful for hydrological simulation in high and cold mountainous catchments; (2) precipitation was the primary contributor nearly all year round, reaching 56.5% of the total runoff on average; (3) groundwater occupied the biggest proportion during dry seasons, whereas snowmelt made a substantial contribution only in late spring and summer; and (4) hydrological signatures were useful for helping to evaluate the performance of the hydrological model.

[1]  Jeffrey G. Arnold,et al.  Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations , 2007 .

[2]  K. Abbaspour,et al.  A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model , 2015 .

[3]  S. Sorooshian,et al.  Evaluation of PERSIANN system satellite-based estimates of tropical rainfall , 2000 .

[4]  Jae-Pil Cho,et al.  Multi‐site evaluation of hydrology component of SWAT in the coastal plain of southwest Georgia , 2013 .

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

[6]  A. As-syakur,et al.  Validation of TRMM Precipitation Radar satellite data over Indonesian region , 2013, Theoretical and Applied Climatology.

[7]  K. Abbaspour,et al.  Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT , 2007 .

[8]  Magic components—why quantifying rain, snowmelt, and icemelt in river discharge is not easy , 2018 .

[9]  Jing Zhang,et al.  Determination of runoff components using path analysis and isotopic measurements in a glacier‐covered alpine catchment (upper Hailuogou Valley) in southwest China , 2015 .

[10]  Yang Hong,et al.  Comparison of PERSIANN and V7 TRMM Multi-satellite Precipitation Analysis (TMPA) products with rain gauge data over Iran , 2013 .

[11]  J. Olden,et al.  Redundancy and the choice of hydrologic indices for characterizing streamflow regimes , 2003 .

[12]  Vidhi Bharti,et al.  Evaluation of error in TRMM 3B42V7 precipitation estimates over the Himalayan region , 2015 .

[13]  A. Barros,et al.  From weather to climate—Seasonal and interannual variability of storms and implications for erosion processes in the Himalaya , 2006 .

[14]  Yang Hong,et al.  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? , 2017 .

[15]  S. Kampf,et al.  Estimating source regions for snowmelt runoff in a Rocky Mountain basin: tests of a data‐based conceptual modeling approach , 2014 .

[16]  A. Barros,et al.  Winter storms in the central Himalayas , 2003 .

[17]  G. Jia,et al.  Monitoring meteorological drought in semiarid regions using multi-sensor microwave remote sensing data , 2013 .

[18]  Tanvir Islam,et al.  Evaluation of TRMM rainfall for soil moisture prediction in a subtropical climate , 2014, Environmental Earth Sciences.

[19]  Yi-Bo Luo,et al.  Evaluating the performance of remote sensing precipitation products CMORPH, PERSIANN, and TMPA, in the arid region of northwest China , 2014, Theoretical and Applied Climatology.

[20]  Weihong Li,et al.  Analysis on the streamflow components of the typical inland river, Northwest China , 2016 .

[21]  Tobias Landmann,et al.  Spatial analysis of human-induced vegetation productivity decline over eastern Africa using a decade (2001-2011) of medium resolution MODIS time-series data , 2014, Int. J. Appl. Earth Obs. Geoinformation.

[22]  K. Abbaspour,et al.  Estimating Uncertain Flow and Transport Parameters Using a Sequential Uncertainty Fitting Procedure , 2004 .

[23]  Peter A. Vanrolleghem,et al.  Sensitivity analysis for hydrology and pesticide supply towards the river in SWAT , 2005 .

[24]  Z. Easton,et al.  Improving the spatial representation of soil properties and hydrology using topographically derived initialization processes in the SWAT model , 2016 .

[25]  D. Scherer,et al.  Precipitation seasonality and variability over the Tibetan plateau as resolved by the High Asia reanalysis , 2014 .

[26]  Soroosh Sorooshian,et al.  Status of Automatic Calibration for Hydrologic Models: Comparison with Multilevel Expert Calibration , 1999 .

[27]  Chungu Lu,et al.  World water tower: An atmospheric perspective , 2008 .

[28]  Linjing Qiu,et al.  SWAT-based runoff and sediment simulation in a small watershed, the loessial hilly-gullied region of China: capabilities and challenges , 2012 .

[29]  Yue-Ping Xu,et al.  Evaluation and hydrological application of precipitation estimates derived from PERSIANN‐CDR, TRMM 3B42V7, and NCEP‐CFSR over humid regions in China , 2016 .

[30]  Jing Yang,et al.  Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China , 2008 .

[31]  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 .

[32]  J. Arnold,et al.  Baseflow simulation using SWAT model in an inland river basin in Tianshan Mountains, Northwest China , 2011 .

[33]  Raghavan Srinivasan,et al.  Regional estimation of base flow and groundwater recharge in the Upper Mississippi river basin , 2000 .

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

[35]  G. Fu,et al.  Uncertainties in SWAT extreme flow simulation under climate change , 2014 .

[36]  Hoshin Vijai Gupta,et al.  A process‐based diagnostic approach to model evaluation: Application to the NWS distributed hydrologic model , 2008 .

[37]  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 .

[38]  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 .

[39]  Hoshin Vijai Gupta,et al.  Regionalization of constraints on expected watershed response behavior for improved predictions in ungauged basins , 2007 .

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

[41]  C. Jones,et al.  WRF simulations of two extreme snowfall events associated with contrasting extratropical cyclones over the western and central Himalaya , 2015 .

[42]  Kamil Kaygusuz Hydropower as clean and renewable energy source for electricity generation , 2016 .

[43]  Bart Nijssen,et al.  Effect of precipitation sampling error on simulated hydrological fluxes and states: Anticipating the Global Precipitation Measurement satellites , 2004 .

[44]  J. Janowiak,et al.  CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution , 2004 .

[45]  Y. Hong,et al.  Precipitation Estimation from Remotely Sensed Imagery Using an Artificial Neural Network Cloud Classification System , 2004 .

[46]  F. Ludwig,et al.  Global water resources affected by human interventions and climate change , 2013, Proceedings of the National Academy of Sciences.

[47]  Shi-yin Liu,et al.  Regimes of runoff components on the debris-covered Koxkar glacier in western China , 2015, Journal of Mountain Science.

[48]  Bryan A. Tolson,et al.  Optimizing hydrological consistency by incorporating hydrological signatures into model calibration objectives , 2015 .