Large-Scale Hydrological Modelling of the Upper Paraná River Basin

The Upper Paraná River Basin (UPRB) has undergone many rapid land use changes in recent decades, due to accelerating population growth. Thus, the prediction of water resources has crucial importance in improving planning and sustainable management. This paper presents a large-scale hydrological modelling of the UPRB, using the Soil and Water Assessment Tool (SWAT) model. The model was calibrated and validated for 78 outlets, over a 32-year simulation period between 1984 and 2015. The results and the comparison between observed and simulated values showed that after the calibration process, most of the outlets performed to a satisfactory level or better in all objective functions analyzed with 86%, 92%, 76%, 88%, and 74% for Percent bias, Coefficient of determination, Nash-Sutcliffe efficiency, Kling-Gupta efficiency, and the Ratio of Standard deviation of observations to root mean square error, respectively. The model output provided in this work could be used in further simulations, such as the evaluation of the impacts of land use change or climate change on river flows of the Upper Paraná Basin.

[1]  H. Diaz,et al.  Contributions of different time scales to extreme Paraná floods , 2016, Climate Dynamics.

[2]  Tammo S. Steenhuis,et al.  A multi basin SWAT model analysis of runoff and sedimentation in the Blue Nile, Ethiopia , 2010 .

[3]  Leonardo Campos de Assis,et al.  The Contribution of Conservation Practices in Reducing Runoff, Soil Loss, and Transport of Nutrients at the Watershed Level , 2012, Water Resources Management.

[4]  Lijing Wang,et al.  Using the SWAT model to assess impacts of land use changes on runoff generation in headwaters , 2014 .

[5]  Mauricio N. Capucim,et al.  The Impact of Rainfall and Land Cover Changes on the Flow of a Medium-sized River in the South of Brazil , 2016 .

[6]  Carol J. Miller,et al.  Anthropogenic impacts to the sediment budget of São Francisco River navigation channel using SWAT , 2015 .

[7]  Raghavan Srinivasan,et al.  A parallelization framework for calibration of hydrological models , 2012, Environ. Model. Softw..

[8]  C. Kiang,et al.  Sedimentation of the Cretaceous Bauru Group in São Paulo, Paraná Basin, Brazil , 2009 .

[9]  Mauricio Zambrano-Bigiarini,et al.  Hydrological evaluation of satellite-based rainfall estimates over the Volta and Baro-Akobo Basin , 2013 .

[10]  Karim C. Abbaspour,et al.  Sensitivity of Calibrated Parameters and Water Resource Estimates on Different Objective Functions and Optimization Algorithms , 2017 .

[11]  Ann van Griensven,et al.  Effect of Single and Multisite Calibration Techniques on the Parameter Estimation, Performance, and Output of a SWAT Model of a Spatially Heterogeneous Catchment , 2017 .

[12]  J. Hamlett,et al.  Hydrologic calibration of the SWAT model in a watershed containing fragipan soils , 1998 .

[13]  V. Barros,et al.  Extreme discharge events in the Paraná River and their climate forcing , 2003 .

[14]  Hoshin Vijai Gupta,et al.  Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling , 2009 .

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

[16]  G. Ghaffari,et al.  SWAT‐simulated hydrological impact of land‐use change in the Zanjanrood basin, Northwest Iran , 2010 .

[17]  Edzer J. Pebesma,et al.  Multivariable geostatistics in S: the gstat package , 2004, Comput. Geosci..

[18]  R. Srinivasan,et al.  Hydrological modelling of the Vistula and Odra river basins using SWAT , 2017 .

[19]  Jeffrey G. Arnold,et al.  The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions , 2007 .

[20]  Eike Luedeling,et al.  Climate change sensitivity assessment of a highly agricultural watershed using SWAT , 2009 .

[21]  Xuesong Zhang,et al.  Multi-Site Calibration of the SWAT Model for Hydrologic Modeling , 2008 .

[22]  J. McNair,et al.  COMPARISON OF PROCESS‐BASED AND ARTIFICIAL NEURAL NETWORK APPROACHES FOR STREAMFLOW MODELING IN AN AGRICULTURAL WATERSHED 1 , 2006 .

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

[24]  A. Grimm Interannual climate variability in South America: impacts on seasonal precipitation, extreme events, and possible effects of climate change , 2011 .

[25]  Anthony Lehmann,et al.  Water resources of the Black Sea Basin at high spatial and temporal resolution , 2014 .

[26]  Edmilson Dias de Freitas,et al.  South America Land Use and Land Cover Assessment and Preliminary Analysis of Their Impacts on Regional Atmospheric Modeling Studies , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[27]  C. Johnston,et al.  Hydrologic response to climatic variability in a Great Lakes Watershed: A case study with the SWAT model , 2007 .

[28]  H. K. Chang,et al.  The South American retroarc foreland system: The development of the Bauru Basin in the back-bulge province , 2016 .

[29]  J. Michael Fritsch,et al.  Mesoscale Convective Complexes in the Americas , 1987 .

[30]  B. Narsimlu,et al.  Assessment of Future Climate Change Impacts on Water Resources of Upper Sind River Basin, India Using SWAT Model , 2013, Water Resources Management.

[31]  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 .

[32]  John R. Williams,et al.  LARGE AREA HYDROLOGIC MODELING AND ASSESSMENT PART I: MODEL DEVELOPMENT 1 , 1998 .

[33]  M. Jha,et al.  CLIMATE CHHANGE SENSITIVITY ASSESSMENT ON UPPER MISSISSIPPI RIVER BASIN STREAMFLOWS USING SWAT 1 , 2006 .

[34]  Shengtian Yang,et al.  Coupling Xinanjiang model and SWAT to simulate agricultural non-point source pollution in Songtao watershed of Hainan, China , 2011 .

[35]  Denis Ruelland,et al.  Sensitivity of a lumped and semi-distributed hydrological model to several methods of rainfall interpolation on a large basin in West Africa , 2008 .

[36]  Edward J. Zipser,et al.  Mesoscale Convective Systems over Southeastern South America and Their Relationship with the South American Low-Level Jet , 2007 .

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

[38]  M. Brea,et al.  The Paraná-Paraguay Basin: Geology and Paleoenvironments , 2011 .

[39]  Jeffrey G. Arnold,et al.  Soil and Water Assessment Tool (SWAT) Model: Current Developments and Applications , 2010 .

[40]  P. Willems,et al.  Large-scale hydrological simulations using the soil water assessment tool, protocol development, and application in the danube basin. , 2014, Journal of environmental quality.

[41]  The Importance of Open Data and Software for Large Scale Hydrological Modelling , 2013 .

[42]  C. Jones,et al.  The South American Monsoon System and the 1970s climate transition , 2011 .

[43]  Aditya Sood,et al.  MODELING RAPPAHANNOCK RIVER BASIN USING SWAT - PILOT FOR CHESAPEAKE BAY WATERSHED , 2010 .

[44]  S. Sorooshian,et al.  Automatic calibration of conceptual rainfall-runoff models: sensitivity to calibration data , 1996 .