Land use and climate change impacts on runoff and soil erosion at the hillslope scale in the Brazilian Cerrado.

Land use and climate change can influence runoff and soil erosion, threatening soil and water conservation in the Cerrado biome in Brazil. The adoption of a process-based model was necessary due to the lack of long-term observed data. Our goals were to calibrate the WEPP (Water Erosion Prediction Project) model for different land uses under subtropical conditions in the Cerrado biome; predict runoff and soil erosion for these different land uses; and simulate runoff and soil erosion considering climate change. We performed the model calibration using a 5-year dataset (2012-2016) of observed runoff and soil loss in four different land uses (wooded Cerrado, tilled fallow without plant cover, pasture, and sugarcane) in experimental plots. Selected soil and management parameters were optimized for each land use during the WEPP model calibration with the existing field data. The simulations were conducted using the calibrated WEPP model components with a 100-year climate dataset created with CLIGEN (weather generator) based on regional climate statistics. We obtained downscaled General Circulation Model (GCM) projections, and runoff and soil loss were predicted with WEPP using future climate scenarios for 2030, 2060, and 2090 considering different Representative Concentration Pathways (RCPs). The WEPP model had an acceptable performance for the subtropical conditions. Land use can influence runoff and soil loss rates in a significant way. Potential climate changes, which indicate the increase of rainfall intensities and depths, may increase the variability and rates of runoff and soil erosion. However, projected climate changes did not significantly affect the runoff and soil erosion for the four analyzed land uses at our location. Finally, the runoff behavior was distinct for each land use, but for soil loss we found similarities between pasture and wooded Cerrado, suggesting that the soil may attain a sustainable level when the land management follows conservation principles.

[1]  Simone Fatichi,et al.  Environmental stochasticity controls soil erosion variability , 2016, Scientific Reports.

[2]  E. López-Granados,et al.  Runoff, soil loss, and nutrient depletion under traditional and alternative cropping systems in the Transmexican Volcanic Belt, Central Mexico , 2009 .

[3]  W. J. Elliot,et al.  A Compendium of soil erodibility data from WEPP cropland soil field erodibility experiments 1987 and 88 , 1990 .

[4]  S. Filoso,et al.  Expansion of sugarcane ethanol production in Brazil: environmental and social challenges. , 2008, Ecological applications : a publication of the Ecological Society of America.

[5]  David J. Dahlstrom Calibration and Uncertainty Analysis for Complex Environmental Models , 2015 .

[6]  E. E. Alberts,et al.  Variability of Runoff and Soil Loss from Fallow Experimental Plots , 1986 .

[7]  Christopher B. Field,et al.  Direct impacts on local climate of sugar-cane expansion in Brazil , 2011 .

[8]  V. Jetten,et al.  Calibration of Erosion Models , 2011 .

[9]  T. Vanwalleghem,et al.  Impact of historical land use and soil management change on soil erosion and agricultural sustainability during the Anthropocene , 2017 .

[10]  X. Zhang,et al.  A comparison of explicit and implicit spatial downscaling of GCM output for soil erosion and crop production assessments , 2007 .

[11]  C. Hughes Are there many different routes to becoming a global biodiversity hotspot? , 2017, Proceedings of the National Academy of Sciences.

[12]  H. A. Mooney,et al.  Maximum rooting depth of vegetation types at the global scale , 1996, Oecologia.

[13]  F. F. Pruski,et al.  Expected climate change impacts on soil erosion rates: A review , 2004 .

[14]  Keith C. Clarke,et al.  Converting Brazil's pastures to cropland: An alternative way to meet sugarcane demand and to spare forestlands , 2015 .

[15]  Karl Auerswald,et al.  Rates of sheet and rill erosion in Germany — A meta-analysis , 2009 .

[16]  A. Avelar,et al.  Soil erosion as a function of different agricultural land use in Rio de Janeiro , 2014 .

[17]  G. Bocco,et al.  Hydrological implications of land use and land cover change: spatial analytical approach at regional scale in the closed basin of the Cuitzeo Lake, Michoacan, Mexico. , 2010 .

[18]  J. A. Anache,et al.  Performance of evaporation estimation methods compared with standard 20 m2 tank , 2016 .

[19]  Alfredo Huete,et al.  Assessing the seasonal dynamics of the Brazilian Cerrado vegetation through the use of spectral vegetation indices , 2004 .

[20]  A. Thompson,et al.  Estimating Sediment Delivery Ratios for Grassed Waterways using WEPP , 2017 .

[21]  Gerrit Hoogenboom,et al.  An evaluation of the statistical methods for testing the performance of crop models with observed data , 2014 .

[22]  Reto Knutti,et al.  The use of the multi-model ensemble in probabilistic climate projections , 2007, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[23]  Kristof Van Oost,et al.  The impact of agricultural soil erosion on biogeochemical cycling , 2010 .

[24]  M. E. Ferreira,et al.  Pervasive transition of the Brazilian land-use system , 2014 .

[25]  A. Guerra,et al.  The implications of general circulation model estimates of rainfall for future erosion: a case study from Brazil , 1999 .

[26]  S. Hagemann,et al.  Projected climate change impacts in rainfall erosivity over Brazil , 2017, Scientific Reports.

[27]  E. Panachuki,et al.  Effect of sugarcane waste in the control of interrill erosion , 2016 .

[28]  E. Wendland,et al.  Experimental evaluation of sediment yield in the first year after replacement of pastures by sugarcane , 2016 .

[29]  E. Davidson,et al.  Deep root function in soil water dynamics in cerrado savannas of central Brazil , 2005 .

[30]  D. Montgomery Soil erosion and agricultural sustainability , 2007, Proceedings of the National Academy of Sciences.

[31]  E. Davidson,et al.  Estimating Seasonal Changes in Volumetric Soil Water Content at Landscape Scales in a Savanna Ecosystem Using Two-Dimensional Resistivity Profiling , 2008 .

[32]  Baoyuan Liu,et al.  Rates of soil erosion in China: A study based on runoff plot data , 2015 .

[33]  L. J. Lane,et al.  Chapter 2. WEATHER GENERATOR , 1995 .

[34]  Corinne Le Quéré,et al.  Climate Change 2013: The Physical Science Basis , 2013 .

[35]  S. Dabney,et al.  Changes in Erosion and Runoff due to Replacement of Pasture Land with Sugarcane Crops , 2016 .

[36]  L. Vázquez-selem,et al.  Human impact on natural systems modeled through soil erosion in GeoWEPP: A comparison between pre-Hispanic periods and modern times in the Teotihuacan Valley (Central Mexico) , 2017 .

[37]  Bernard A. Engel,et al.  A Simple Technique for Obtaining Future Climate Data Inputs for Natural Resource Models , 2016 .

[38]  F. Zheng,et al.  Assessing the site-specific impacts of climate change on hydrology, soil erosion and crop yields in the Loess Plateau of China , 2011 .

[39]  D. Flanagan,et al.  Comparative Study of Different Stochastic Weather Generators for Long-Term Climate Data Simulation , 2017 .

[40]  John E. Gilley,et al.  Water Erosion Prediction Project (WEPP): Development History, Model Capabilities, and Future Enhancements , 2007 .

[41]  D. Mullan,et al.  Soil erosion under the impacts of future climate change: assessing the statistical significance of future changes and the potential on-site and off-site problems , 2013 .

[42]  Ashish Pandey,et al.  Physically based soil erosion and sediment yield models revisited , 2016 .

[43]  J. Stone,et al.  Curve number estimation from Brazilian Cerrado rainfall and runoff data , 2016, Journal of Soil and Water Conservation.

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

[45]  Spatial patterns over a 24-year period show an increase in native vegetation cover and decreased fragmentation in Andean temperate landscapes, Chile , 2016 .

[46]  James C. Ascough,et al.  The Water Erosion Prediction Project ( WEPP ) Model , 2001 .

[47]  D. Flanagan,et al.  Runoff and soil erosion plot-scale studies under natural rainfall: A meta-analysis of the Brazilian experience , 2017 .

[48]  Jack Chertok Conservação do solo , 2008 .

[49]  Keith Beven,et al.  Macropores and water flow in soils revisited , 2013 .

[50]  James C. Ascough,et al.  WEPP: Model Use, Calibration, and Validation , 2012 .

[51]  Jean Paolo Gomes Minella,et al.  The expansion of Brazilian agriculture: Soil erosion scenarios , 2013, International Soil and Water Conservation Research.

[52]  G. R. Foster,et al.  A Process-Based Soil Erosion Model for USDA-Water Erosion Prediction Project Technology , 1989 .

[53]  J. A. Gomez,et al.  Analysis of sources of variability of runoff volume in a 40 plot experiment using a numerical model , 2001 .

[54]  Jurgen D. Garbrecht,et al.  Soil Erosion from Winter Wheat Cropland under Climate Change in Central Oklahoma , 2015 .

[55]  S. Sorooshian,et al.  Shuffled complex evolution approach for effective and efficient global minimization , 1993 .

[56]  Peter G. Jones,et al.  Generating downscaled weather data from a suite of climate models for agricultural modelling applications , 2013 .

[57]  Mark A. Nearing,et al.  Variability in Soil Erosion Data from Replicated Plots , 1999 .

[58]  James W. Jones,et al.  Climate change impacts on sugarcane attainable yield in southern Brazil , 2013, Climatic Change.

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

[60]  Jurandy Almeida,et al.  Using phenological cameras to track the green up in a cerrado savanna and its on-the-ground validation , 2014, Ecol. Informatics.

[61]  Zhiying Li,et al.  Impacts of climate change on water erosion: A review , 2016 .

[62]  J. Stape,et al.  Köppen's climate classification map for Brazil , 2013 .

[63]  Ewald Schnug,et al.  Runoff mapping using WEPP erosion model and GIS tools , 2005, Comput. Geosci..

[64]  P. Kinnell,et al.  A comparison of the abilities of the USLE-M, RUSLE2 and WEPP to model event erosion from bare fallow areas. , 2017, The Science of the total environment.

[65]  Mark A. Nearing,et al.  EVALUATION OF WEPP AND ITS COMPARISON WITH USLE AND RUSLE , 2000 .

[66]  M. Nearing,et al.  Orders of magnitude increase in soil erosion associated with land use change from native to cultivated vegetation in a Brazilian savannah environment , 2015 .

[67]  Robert L. Wilby,et al.  A review of climate risk information for adaptation and development planning , 2009 .

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