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
19 October 2011, Mexico City,
Mexico
Project Personnel's
Assefa Melesse (PI)
Francisco Nunez
Dale Webber
Jorge Ortiz
Felipe Vicioso
The presentation consists of






CCS - Core Science Objectives
Study area
Modeling tools
Modeling Results
Climate change projections
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
STUDY AREA
Caribbean Costal Regions

Puerto Rico
 Manate and Plata Basins

Dominican Republic
 Haina and Yuna watersheds

Jamaica
 Great River and Re Cobre
Islands of interest
Watershed Modeling
Overview of Watershed modelling

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.

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),
geographic information system (GIS),
embedded
within
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
impacts
enables
to
study
long-term
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).
Model Input Cont.
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 Calibration and Evaluation

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, R2,
MODELING RESULTS
Puerto Rico, Rio Manati
Time serious graph for calibration period – Rio Manati
Annual average water balance of the
Rio De Manati watershed
Water balance Component
Precipitation
Surface runoff
Lateral soil flow
Groundwater flow (shallow aquifer)
Revap (shallow aquifer => soil/plants)
Annual Average (mm)
1620
86
386
3
102
Deep aquifer recharge
5
Total aquifer recharge
94
Total water yield
Percolation out of soil
474
89
Actual evapotranspiration
1067
Potential evapotranspiration
1838
Average Monthly Basin Values of Manati watershed
MONTH RAIN,
SURF Q,
Water Yield,
ET,
PET,
S
(mm)
(mm)
LAT Q (mm)
(mm)
(mm)
1
108.76
4.17 32.9
38.29
67.41
101.33
2
3
88.83
101.83
5.01 26.28
4.81 22.5
32.13
27.64
76.37
118.21
121.58
184.68
4
151.33
7.36 23.39
30.89
116.1
172.32
5
118.01
3.19 26.49
29.68
118.83
188.35
6
61.9
0.93 19.67
20.61
98.55
203.88
7
76.59
0.97 14.98
15.94
76.01
204.73
8
145.36
2.99 20.23
23.2
73.26
172.56
9
187.47
7.18 32.94
40.08
87.54
148.13
10
272.15
29.28 56.65
85.78
87.8
129.2
11
178.87
13.44 61.68
75
79.9
117.38
12
131.44
6.57 48.81
55.29
69.08
97.17
Puerto Rico – Plata
Area (%)
0.003
4.141
28.387
1.295
0.225
0.612
51.078
0.107
13.015
0.011
1.127
Land use: Plata Watershed, PR
Time serious graph for calibration period – Rio Plata
Dominican Republic - Rio Haina
Area
1.279
46.922
17.800
10.244
0.027
4.916
0.012
0.296
17.568
0.936
Land use: Haina Watershed, DR
Days (1985-1987)
Dec/87
Nov/87
Oct/87
Sep/87
Aug/87
Jul/87
Jun/87
May/87
Apr/87
Mar/87
Feb/87
Jan/87
Dec/86
Nov/86
Oct/86
Sep/86
Obsreved
Aug/86
Jul/86
Jun/86
May/86
Apr/86
Mar/86
Feb/86
Jan/86
Dec/85
Nov/85
Oct/85
Sep/85
Aug/85
Jul/85
Jun/85
May/85
Apr/85
Mar/85
Feb/85
Jan/85
Discharge (m3/s)
Time serious graph for calibration period – Haina Watershed
Simulated
1200
1000
800
600
400
200
0
Annual average water balance of the
Haina watershed
Water balance Component
Precipitation
Surface runoff
Lateral soil flow
Groundwater flow (shallow aquifer)
Revap (shallow aquifer => soil/plants)
Annual Average (mm)
2101
927,63
21
215
17
Deep aquifer recharge
12.33
Total aquifer recharge
246.64
Total water yield
Percolation out of soil
1161.63
250.31
Actual evapotranspiration
890.6
Potential evapotranspiration
1702
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
Annual average water balance of the
Rio Cobre watershed (1997-2008).
Water balance Component
Precipitation
Annual Average (mm)
1953.0
Surface runoff
102.8
Lateral soil flow
427.7
Groundwater flow (shallow aquifer)
368.8
Revap (shallow aquifer => soil/plants)
9.0
Deep aquifer recharge
19.9
Total aquifer recharge
397.6
Total water yield
899.0
Percolation out of soil
393.5
Actual evapotranspiration
1028.3
Potential evapotranspiration
1579.8
Monthly mean and seasonal water balance components for
the Rio Cobre watershed
Seasons/months
Rainfall Surface
Lateral
Water
AET,
PET,
, mm
flow, mm
Yield,
mm
mm
runoff,
mm
Average (1997-2008)
mm
154.44
21.68
38.10
79.73
71.50 180.42
Dry (Jan-Mar)
57.72
4.20
11.67
28.24
68.12
180.33
Wet (Aug-Oct)
267.09
52.20
72.15 151.99
77.49
179.79
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
Climate Change Impact on Water Resources
Variability
• GCM’s are numerical coupled models that represent various earth
systems including the atmosphere, oceans, land surface and seaice and offer considerable potential for the study of climate change
and 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.
Center
Model
Atmospheric
resolution (approx)
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 1.875
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)
Australia's Commonwealth Scientific and Industrial Research
Organisation Australia (CSIRO)
Max-Planck-Institut for Meteorology Germany (MPI-M)
CSIRO Mark 3.0
1.9× 1.9
CSIRO Mark 3.5
1.9× 1.9
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)
Institute for Numerical Mathematics Russia (INM)
Institut Pierre Simon Laplace France (IPSL)
Meteorological Research Institute Japan (MRI)
National Centre for Atmospheric Research USA (NCAR)
CM2.1 - AOGCM
INMCM3.0
IPSL-CM4
MRI-CGCM2.3.2
Parallel Climate Model (PCM)
2.5× 2.0
5.0× 4.0
3.75× 2.5
2.8× 2.8
2.8× 2.8
National Centre for Atmospheric Research USA(NCAR)
Community Climate System Model, version
3.0 (CCSM3)
HadCM3
1.4× 1.4
NASA Goddard Institute for Space Studies (NASA/GISS), USA,
Hadley Centre for Climate Prediction and Research, Met Office, United
Kingdom - UK Met. Office UK (UKMO)
3.75× 2.5
Trends in Climate Change - Temperature
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
A2 (2011-2040)
A2 (2041-2070
A2 (2071-2100)
4
3
2
1
A1B (2011-2040)
0
A1B (2041-2070)
A1B (2071-2100)
3
2.5
2
1.5
1
0.5
0
B1 (2011-2040)
B1 (2041-2070)
B1 (2071-2100)
Trends in Climate Change - Rainfall
30
20
10
0
-10
-20
-30
-40
-50
-60
-70
30
20
10
0
-10
-20
-30
-40
-50
-60
-70
30
20
10
0
-10
-20
-30
-40
-50
A2 (2011-2040)
A2 (2041-2070)
A2 (2071-2100)
A1B (2011-2040)
A1B (2041-2070)
A1B (2071-2100)
B1 (2011-2040)
B1 (2041-2070)
B1 (2071-2100)
Projected Seasonal changes in Rainfall
Changes in stream flow due to changes in precipitation and
air temperature for the period 2046-2065 and 2080-2100
Changes in potential and actual evapotranspiration
(PET and AET) for the 2046-2065
Annual changes in potential and actual
evapotranspiration (PET and AET) for the 2080-2100
Annual changes in soil water storage for
2046-2065 and 2080-2100 period
Changes in surface and ground water for
2046-2065 and 2080-2100 periods
Changes in surface and ground water for
2046-2065 and 2080-2100 periods
Uncertainties in GCM model outputs
A2 (2011-2040)
1.8
bccr_bcm2_0
1.6
cccma_cgcm3_1
T change in °C
1.4
cnrm_cm3
1.2
1
csiro_mk3_0
0.8
csiro_mk3_5
0.6
gfdl_cm2_0
0.4
gfdl_cm2_1
0.2
giss_model_e_r
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
ingv_echam4
Rainfall changes in % - A2 (2011-2040)
Rainfall changes in %
100
bccr_bcm2_0
80
cccma_cgcm3_1
60
cnrm_cm3
40
20
csiro_mk3_0
0
csiro_mk3_5
-20
gfdl_cm2_0
-40
gfdl_cm2_1
-60
giss_model_e_r
-80
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
ingv_echam4
Thank You!
30 August 2010, Puerto Rico