19 October 2011, Mexico City, Mexico Hydrological Modeling and Impact of Climate changes in the Caribbean Islands of Dominican Republic, Puerto Rico and Jamaica Shimelis G Setegn, Ph.D. Postdoctoral Research Scientist Florida International University, Dep. of Earth and Environment Project Personnel's Assefa Melesse (PI) Francisco Nunez Dale Webber Jorge Ortiz Felipe Vicioso

The presentation consists of CCS - CCS - Core Science Objectives Study area Study area Modeling tools Modeling tools Modeling Results Modeling Results Climate change projections Climate change projections Impact of climate change on water resources Impact of climate change on water resources

Caribbean Coastal Scenarios Core Science Objectives Determine spatial and temporal variability in climate across the region. Determine geographic & demographic characteristics of catchments – – topography, land cover, geology, soil, land management techniques, population, roads and infrastructure, urban systems, etc. Consider present & future trends in the nature & distribution of dynamic characteristics – – e.g. land cover, management techniques, population, infrastructure, urban systems.

Caribbean Coastal Scenarios Core Science Objectives (cont.) Simulate seasonal and inter-annual fluxes of fresh water, sediments, and dissolved loads to coastal zones as a function of climate and catchment characteristics. Montego Bay

Caribbean Costal Regions Puerto Rico Puerto Rico Manate and Plata Basins Manate and Plata Basins Dominican Republic Dominican Republic Haina and Yuna watersheds Haina and Yuna watersheds Jamaica Jamaica Great River and Re Cobre Great River and Re Cobre STUDY AREA

Islands of interest

Watershed Modeling

Many hydrological models are developed to describe the hydrology, erosion and sedimentation processes. Many hydrological models are developed to describe the hydrology, erosion and sedimentation processes. They describe the physical processes controlling the transformation of precipitation to runoff and detachment and transport of sediments. They describe the physical processes controlling the transformation of precipitation to runoff and detachment and transport of sediments. Overview of Watershed modelling

Watershed models are used to implement alternative management strategies in the areas of Watershed models are used to implement alternative management strategies in the areas of –water resources allocation –flood control –impact of land use change –impact of climate change –environmental pollution control

SWAT (Soil water Assessment Tool)  SWAT is a river basin scale developed to predict the impact of land management practices on water, sediment and agricultural chemical yields  It is a public domain model actively supported by the USDA Agricultural Research Service at the Grassland, Soil and Water Research Laboratory in Temple, Texas, USA.  The SWAT system (ArcSWAT), embedded within geographic information system (GIS),  can integrate various spatial environmental data, including soil, land cover, climate, and topographic features.

SWAT cont.  The model is physically based  i.e., it requires specific information  It is computationally efficient  Simulation of very large basins  SWAT enables to study long-term impacts

Phases of hydrologic cycle simulated by SWAT Land phase Water phase Courtesy: SWAT Manual

Model Input  GIS input files needed for the SWAT model include  the digital elevation model (DEM),  land cover, and  soil layers  The DEM can be utilized by ArcSWAT to delineate basin and subbasin boundaries, calculate subbasin average slopes and delineate the stream network.  The land use, soil and Slope layers are used to creat and define Hydrological response units (HRU’s).

Metrological Data  The weather variables for driving the hydrological balance are –precipitation, –air temperature, –solar radiation, –wind speed and –relative humidity. Model Input Cont.

Hydrological data  River Discharge and Suspended sediment load Land Management  Management input files include planting, harvest, tillage operations, and pesticide and fertilizer application. Model Input Cont.

Model Calibration and Evaluation The ability of a watershed model is evaluated through sensitivity analysis, model calibration, and model validation. The ability of a watershed model is evaluated through sensitivity analysis, model calibration, and model validation. For model evaluation we used the goodness of measures such as NSE, R 2, For model evaluation we used the goodness of measures such as NSE, R 2,

MODELING RESULTS

Puerto Rico, Rio Manati

Time serious graph for calibration period – Rio Manati

Water balance ComponentAnnual Average (mm) Precipitation1620 Surface runoff 86 Lateral soil flow 386 Groundwater flow (shallow aquifer)3 Revap (shallow aquifer => soil/plants)102 Deep aquifer recharge5 Total aquifer recharge94 Total water yield474 Percolation out of soil89 Actual evapotranspiration1067 Potential evapotranspiration1838 Annual average water balance of the Rio De Manati watershed

MONTH S RAIN, (mm) SURF Q, (mm)LAT Q Water Yield, (mm) ET, (mm) PET, (mm) Average Monthly Basin Values of Manati watershed

Area (%) Land use: Plata Watershed, PR Puerto Rico – Plata

Time serious graph for calibration period – Rio Plata

Area Land use: Haina Watershed, DR Dominican Republic - Rio Haina

Time serious graph for calibration period – Haina Watershed

Water balance ComponentAnnual Average (mm) Precipitation2101 Surface runoff927,63 Lateral soil flow21 Groundwater flow (shallow aquifer)215 Revap (shallow aquifer => soil/plants)17 Deep aquifer recharge12.33 Total aquifer recharge Total water yield Percolation out of soil Actual evapotranspiration890.6 Potential evapotranspiration1702 Annual average water balance of the Haina watershed

Jamaica, Great River Basin

Time series of observed and simulated monthly flow for calibration (top) and validation (bottom) period at Lethe station of Great River

Jamaica, Rio Cobre Watershed

The time-series comparison between measured and simulated monthly flow at Rio Cobre Watershed

Water balance ComponentAnnual Average (mm) Precipitation Surface runoff102.8 Lateral soil flow427.7 Groundwater flow (shallow aquifer)368.8 Revap (shallow aquifer => soil/plants)9.0 Deep aquifer recharge19.9 Total aquifer recharge397.6 Total water yield899.0 Percolation out of soil393.5 Actual evapotranspiration Potential evapotranspiration Annual average water balance of the Rio Cobre watershed ( ).

Seasons/months Rainfall, mm Surface runoff, mm Lateral flow, mm Water Yield, mm AET, mm PET, mm Average ( ) Dry (Jan-Mar) Wet (Aug-Oct) Monthly mean and seasonal water balance components for the Rio Cobre watershed

Spatial distribution of actual evapotranspiration in the Rio Cobre Watershed, Jamaica.

Spatial distribution of water yield in the Rio Cobre Watershed, Jamaica.

Climate Change 30 August 2010, Gran Melia, Puerto Rico, photo by Shimelis S

GCM’s are numerical coupled models that represent various earth systems including the atmosphere, oceans, land surface and sea- ice and offer considerable potential for the study of climate change and variability. Climate Change Impact on Water Resources Variability Climate change scenarios Scenarios are images of the future, or alternative futures. They are neither predictions nor forecasts. The Special Report on Emissions Scenarios (SRES) are grouped into four scenario families (A1, A2, B1 and B2) that explore alternative development pathways, covering a wide range of demographic, economic and technological driving forces and resulting GHG emissions.

CenterModelAtmospheric resolution (approx) NASA Goddard Institute for Space Studies (NASA/GISS), USA, AOM 4x3 4  x 3  Goddard Institute for Space Studies (GISS), NASA, USA GISS _ ModelE-H 4  x 5  Canadian Centre for Climate Modelling and Analysis (CCCma)Coupled Global Climate Model (CGCM3) Hadley Centre for Climate Prediction and Research, Met Office United Kingdom Hadley Centre Global Environmental Model, version 1 (HadGEM1) 1.25  x  Bjerknes Centre for Climate Research Norway (BCCR)Bergen Climate Model (BCM2.0) 2.8  ×2.8  Canadian Center for Climate Modelling and Analysis Canada (CCCMA)Coupled Global Climate Model (CGCM3) 3.75  × 3.7  Centre National de Recherches Meteorologiques France(CNRM)CNRM-CM3 2.8  × 2.8  Australia's Commonwealth Scientific and Industrial Research Organisation Australia (CSIRO) CSIRO Mark  × 1.9  Australia's Commonwealth Scientific and Industrial Research Organisation Australia (CSIRO) CSIRO Mark  × 1.9  Max-Planck-Institut for Meteorology Germany (MPI-M)ECHAM5/MPI-OM 1.9  × 1.9  Meteorological Institute of the University of Bonn (Germany), (MIUB)ECHO-G 3.75  × 3.7  Geophysical Fluid Dynamics Laboratory USA ( GFDL)CM2.0 - AOGCM 2.5  × 2.0  Geophysical Fluid Dynamics Laboratory USA (GFDL)CM2.1 - AOGCM 2.5  × 2.0  Institute for Numerical Mathematics Russia (INM)INMCM  × 4.0  Institut Pierre Simon Laplace France (IPSL)IPSL-CM  × 2.5  Meteorological Research Institute Japan (MRI)MRI-CGCM  × 2.8  National Centre for Atmospheric Research USA (NCAR) Parallel Climate Model (PCM) 2.8  × 2.8  National Centre for Atmospheric Research USA(NCAR) Community Climate System Model, version 3.0 (CCSM3) 1.4  × 1.4  Hadley Centre for Climate Prediction and Research, Met Office, United Kingdom - UK Met. Office UK (UKMO) HadCM  × 2.5 

Trends in Climate Chan ge - Temperature

Trends in Climate Chan ge - Rainfall

Projected Seasonal changes in Rainfall

Changes in stream flow due to changes in precipitation and air temperature for the period and

Changes in potential and actual evapotranspiration (PET and AET) for the

Annual changes in potential and actual evapotranspiration (PET and AET) for the

Annual changes in soil water storage for and period

Changes in surface and ground water for and periods

Uncertainties in GCM model outputs

Thank You! 30 August 2010, Puerto Rico