Title: Evaluation of the Impact of Climate Change on Water Storage and Ground Water Recharge

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Summary Tropical Islands have unique conditions These conditions create problems for society A study is needed We propose to do The model will provide

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TABLE OF CONTENTS TABLE OF CONTENTS...... 2 LIST OF FIGURES...... 2 PROJECT DESCRIPTION...... 3 Introduction...... 3 Atmosphere/Land Modeling...... 4 Objectives...... 7 Work Plan...... 8 Calibrate the models for regional/local conditions...... 12 Model Validation...... 12 Conduct simulation studies of the hydrological cycle on Puerto Rico...... 14 PROJECT SIGNIFICANCE AND LINKAGES...... 15 EXPECTED RESEARCH PRODUCTS...... 15 Time Frame...... 15 Personnel...... 15 Project Assessment and Management...... 16 REFERENCES...... 18 BIOGRAPHICAL SCHETCHES...... 23 PROPOSED BUDGET...... 24 CURRENT AND PENDING SUPPORT...... 25 FACILITIES, EQUIPMENT AND OTHER RESOURCES...... 26

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LIST OF FIGURES

Figure 1. Coupling of RAMS, LEAF-2 and TOPMODEL...... 5 Figure 2. RAMS-estimated accumulated total precipitation (mm) for Puerto Rico during April 1998 (contour inc. 10 mm)...... 6 Figure 3. RAMS-estimated monthly-accumulated precipitation for 15 stations in Puerto Rico during April 1998...... 6 Figure 4. Flow of project activities and sources of data for the model configuration, calibration and validation...... 8 Figure 5. Flowchart of numerical models used to simulate Puerto Rico water balance...... 9 Figure 6. Locations of Groundwater Resource and Modeling Studies in Puerto Rico...... 11

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PROJECT DESCRIPTION

Simulating the Hydrologic Water Balance of Puerto Rico Using a Coupled RAMS/LEAF-2/TOPMODEL/MODFLOW Modeling System

Introduction The quantitative investigation of the hydrological balance on tropical islands is required to understand and manage water resources. This study proposes the use of advanced numerical modeling techniques to better understand the hydrologic processes in Puerto Rico (PR). The methodology and expertise gained from this study should make an invaluable contribution to hydrological studies of tropical islands that have large populations and intense pressure on their water resources. PR is an ideal location for a case study because it is one of the best environmentally observed tropical islands with a dense network of U.S. Geological Service (USGS) hydrological stream gauges and stations, and U.S. National Oceanic and Atmospheric Administration (NOAA) cooperating observer and weather stations. PR’s dense population (400 people/km2 average), and the economic impact that water supply represents is also another major reason for this study. The hydrological cycle is determined by a unique set of external (e.g., storms, cold fronts, or high pressure systems from maritime and continental sources) and local factors (e.g., convective cloud formations, localized land/air interaction and the transport of moisture fluxes from and to the lower boundary layer). In tropical regions the cycle is often exasperated by extreme flooding, hurricanes, drought, dense populations and destructive land-use practices. Currently the countries within the humid tropics and the other warm humid regions contain almost one- third of the total world population. It is common knowledge that small tropical islands are subject to an ever-increasing risk as a result of water management. Although the general characteristics of the hydrological cycle are well understood, little information is available on the flux rates and therefore, relative importance of the various components of the hydrologic cycle especially under different scenarios in the tropical regions. No quantitative investigation of the hydrological cycle for any Caribbean island has been reported. Only the work by Capiel and Calversbert (1976) attempted to identify these sources on a qualitative basis. Among their findings, the lower atmosphere inversion was identified as a major source of cloud formation and eventual precipitation, and hurricane activity was identified to be a lesser contributor to the water balance.

To investigate the hydrological cycle of PR we propose to combine the Regional Atmospheric Model (RAMS) with models dealing with other aspects of the climate system. Our unique modeling approach is to couple the RAMS/LEAF-2/TOPMODEL system (Walko et al., 2000) to MODFLOW (McDonald and Harbaugh, 1984), a fully three-dimensional, multi-layer groundwater flow model. In our approach, we will explicitly simulate the interchange of water between multiple aquifer systems where significant aquifer systems exist. Where significant deep aquifer systems do not exist, we will utilize TOPMODEL to simulate shallow hillslope groundwater flow. Another innovative aspect of this research is that we will simulate the complete hydrologic cycle for the entire island of PR, which has never been attempted.

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Although this effort will focus on PR, the methodology may be generally applicable to tropical island environments. Many of the islands of the West Indies archipelago share similar characteristics with respect to climate. This is due in part to the influence of the trade winds and the islands’ mountainous topography (Kent, 2002). Generally, for these islands, rainfall is greatest in the northeast and interior mountain areas. Due to orthographic effects, the leeward side may be quite dry and even semi-arid, as in the case of southwest PR. The rainy season tends to be from June to November and the dry season from December to May. For a given location, air temperature variations throughout the year are small; however, air temperatures are highly correlated with elevation. An exception to this occurs within interior mountain valleys where warm air can become trapped. In some cases average temperatures within interior mountain valleys may be higher than coastal areas at lower elevations (Capiel and Calvesbert, 1976).

Atmosphere/Land Modeling Weaver and Pacala (2001) used RAMS coupled with the Princeton University Ecosystem Dynamics (ED) model to simulate the change in climate due to changes in land use in the U.S. between 1700 and 1990. The model showed that changing conditions at the land surface could have significant impacts on temperature and precipitation. These results are supported by the work of Chase et al. (1998), Baron et al. (1998), Stohlgren et al. (1998), and Pielke et al. (1999). Lu et al. (2000) coupled RAMS with the CENTURY model to simulate the two-way interactive biosphere and atmosphere feedbacks for 1988, 1989 and 1993, focusing on the central U.S. CENTURY simulates the dynamic biospheric response (i.e., change in land cover characteristics) to atmospheric and hydrologic conditions. The analysis showed that vegetation phenological variation strongly influences regional climate patterns through its control over land-surface water and energy exchange.

Several models have been developed to simulate subsurface hydrogeologic conditions. A few of these studies are mentioned here. Bouraou et al. (1998) coupled the hydrologic model ANSWERS (Bouraou et al., 1997) with a large-scale general circulation model (GCM) to simulate the effect of global warming on aquifer recharge in the Bièvre-Valloire watershed in France. ANSWERS assumes that the groundwater system is limited to a homogenous, single- layer water table aquifer. Pan et al. (2001) coupled the National Center for Atmospheric Research (NCAR) mesoscale model (MM5), the U.S. Department of Agriculture (USDA) Soil Water Assessment Tools (SWAT), and California Environmental Resources Evaluation System (CERES) together to form a two-way coupled soil-plant-atmosphere agroecosystem model. The purpose of the model was to predict seasonal crop-available water, thereby allowing evaluation of an alternative cropping system.

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Walko et al. (2000) described coupled atmosphere-biophysics-hydrology models: RAMS, the Land Ecosystem-Atmosphere Feedback model LEAF-2, and TOPMODEL, a land hydrology model that represents surface and subsurface downslope lateral transport of groundwater. They describe the subdivision of a RAMS surface grid cell into multiple areas or patches of distinct land-use type, each containing its own LEAF-2 model. The TOPMODEL code was modified to account for transient redistribution of soil moisture. A sensitivity study showed that TOPMODEL had a significant effect not only in producing subgrid inhomogeneities of soil moisture but also on the surface fluxes of sensible and latent heat. Figure 1 shows the coupling of RAMS, LEAF-2 and TOPMODEL. TOPMODEL has previously been coupled with soi- vegetation-atmosphere transfer models by, for example, Famiglietti and Wood (1991), Band (1993), Band et al. (1993), and Stieglitz et al. (1997).

RAMS Water that discharges to surface water bodies Water and Water and energy fluxes energy fluxes

LEAF-2

Lateral surface and subsurfce moisture transport TOPMODEL

Figure 1. Coupling of RAMS, LEAF-2 and TOPMODEL.

None of the atmospheric/hydrologic models referred to above simulate multi-aquifer groundwater flow, and therefore are not capable of predicting the true water table position. Conceptually, TOPMODEL assumes that all groundwater recharge is diverted to lateral

4/29/2018 Revision subsurface flow near the surface, and subsequently becomes river base flow. It is true that virtually all aquifer recharge may become base flow in large-scale continental environments, however, in the case of small islands, a significant portion of the aquifer recharge may discharge directly to the ocean. Furthermore, in semi-confined aquifer systems, there is significant inter- flow between shallow and deep aquifers, which partially controls the position of the water table and piezometric surface, respectively. Although the ANSWERS model can estimate the position of the water table in a water table aquifer, it cannot handle the case of a water table aquifer over a partially confined aquifer. To effectively evaluate the response of groundwater resources to climate change, future research efforts should be directed towards coupling atmospheric/near- surface hydrologic models with fully three-dimensional groundwater models.

Comarazamy (2001) (also Comarazamy et al., 2001) presented results from a simulation study of precipitation for PR in April 1998 using RAMS. The model was configured with two grids, the coarser one having a resolution of 20 km in the horizontal for the Caribbean, nudged to a finer grid of 5 km covering the Island. The vertical levels were spaced into 13 levels starting at 100 meters above the sea with a stretching factor of 1.1. Transient lateral conditions were obtained from the NCEP reanalysis. Numerical results for the total monthly precipitation were compared with upper air data as well as with measurements from a network of cooperative surface stations. Figures 2 shows results from the model and Figure 3 compares results of the model with fifteen cooperative stations for the entire month demonstrating good agreement between both data sets.

Figure 2. RAMS-estimated accumulated total precipitation (mm) for Puerto Rico during April 1998 (contour inc. 10 mm).

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Figure 3. RAMS-estimated monthly-accumulated precipitation for 15 stations in Puerto Rico during April 1998.

Project Outcomes

In 1995 municipalities across PR pumped on average 95 million gallons of water per day (MGPD). In that same year, freshwater withdrawals from surface water sources was 335 MGPD. Combined surface and groundwater supplies provided water for 3.5 million people (USGS, 1998). Roughly one-third of the water supply is derived from groundwater sources. Changing climatic conditions and changes in land use will affect the islands water balance, and possibly threaten these water supplies. In the case of groundwater, if water tables in an area drop due to reduced recharge rates, current withdrawal rates may not be sustainable. In addition, saltwater intrusion may become a greater threat in areas along the coasts. In 1995 there were 6,890 acres of reservoir area in PR with a corresponding annual evaporation of 7.8 x 109 gallons (USGS, 1998). If rainfall is reduced and evaporation rates increase, surface water levels in these reservoirs may drop, thus reducing the surface water supply. The principal water supply for the San Juan metropolitan area is Carraízo Reservoir, which because of sedimentation, has lost 58 percent of its initial capacity since it was constructed almost 40 years ago. In addition to the loss of potable water storage capacity of the reservoir (particularly during droughts), the Carraízo Reservoir becomes less efficient each year at reducing flood peaks (Sepúlveda, 1996). As population continues to increase in PR, reductions in water supplies below current levels must be avoided through developing a better understanding of the controlling factors in the hydrologic cycle in PR. Using the proposed methodology, this study will address the following questions: 1. What are the synoptic conditions required that lead to droughts and floods? 2. Under climate change scenarios

o How will river flows be affected?

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o How might reservoir levels drop or rise due to changing surface water evaporation rates? o How might groundwater levels drop or rise due to changing aquifer recharge rates? o If groundwater levels drop, owing to a reduction in aquifer recharge rates, how might saltwater intrusion increase in the coastal areas? o What will be the water requirements by agriculture, and how might competition between water users (agriculture, urban and industrial) increase? 3 . How would changes in land-use and industrial growth affect the local hydrologic budgets?

Objectives The objectives of this study are 1. Develop a meso-scale atmospheric/land/groundwater model that could simulate the hydrological balance of the island. 2. Calibrate the models for PR conditions. 3. Validate the models. 4. Conduct simulation studies of the hydrological cycle on PR.

Figure 4 shows how flow of the major project activities.

Start Non-Changing Model Configuration Remotely Sensed Data e.g., Land Cover

Non-remotely sensed data e.g.., weather station data Model Calibration and stream discharge.

Validation

Time-varying Remotely Sensed Data e.g., ET and soil moisture

Island-wide Compare Island-wide Water Balance Water Balance (Simulated)

Perform Predictive Simulations

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Figure 4. Flow of project activities and sources of data for the model configuration, calibration and validation.

Work Plan

The approach proposed here is to investigate the hydrological cycle for tropical islands using PR as the control scenario. The approach will consist in integrating all possible positive and negative contributors including synoptic and orthographic cloud formations, soil storage, surface runoff, local anthropogenic and vegetative consumption, evapotranspiration, and groundwater flow into a common system at a regional level. The investigation will include a statistical analysis of the monthly and annual water balance in the island based on reported observations by the USGS, the National Weather Service, and local water distribution companies. A second major task will be to develop a meso-scale atmosphere/land/groundwater model that simulates the hydrological balance of the island. This model effort will be validated with results from the analysis and will be used to predict future events in which local and large- scale events will be present. The effort of investigating in detail the hydrological cycle in tropical islands could be used for other islands different from PR. An interdisciplinary team that includes climatologists, hydrologists, remote sensing, and computational fluid dynamics experts has been assembled to address this challenging but yet interesting problem. Specific models that will be coupled include:

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o RAMS – Atmospheric processes o LEAF-2/TOPMODEL – Near surface processes (i.e., soil moisture, runoff, evapotranspiration, subsurface hillslope moisture transport ) o MODFLOW – Groundwater flow Figure 5 shows how the various models will work together.

RAMS Water that discharges to surface water bodies Water and Water and energy fluxes energy fluxes Water that discharges to surface water LEAF-2 bodies

Grid cell is located within Interior Mountain area

TOPMODEL Grid cell is located withing coastal or karstic limestone area Aquifer Recharge MODFLOW Calculation

Figure 5. Flowchart of numerical models used to simulate Puerto Rico water balance.

RAMS will be the simulation tool for the atmospheric component. It is a highly versatile numerical code developed for simulating and forecasting meteorological phenomena. It consists of three major components, 1) a data analysis component, 2) an atmospheric model, and 3) a post-processing component. The data analysis component prepares the data for model initialization and nudging from observed meteorological data. The atmospheric model is built around the full set of non-hydrostatic, dynamical equations that governs atmospheric dynamics and thermodynamics, plus conservation equations for scalar quantities like mass, water vapor, liquid and ice hydrometeor mixing ratios. These equations are complemented by a large selection of parameterizations available in the model. Pielke et al. (1992) describes the data analysis technique available in RAMS. The data analysis for the initial and boundary conditions is as follows. An isentropic analysis interpolates the pressure data in the vertical direction to specified isentropic levels, and horizontally interpolates this data to the higher resolution grid to be used in

4/29/2018 Revision the simulation. Then the vertical isentropic data set is interpolated to the model, to obtain a full set of prognostic fields for model integration. The transient data introduced in the model is the pressure level data provided by the National Center of Environment Prediction (NCEP) at 2.5 degree of resolution. In this study the model will include three nodes of 20, 5 and 1 km to avoid possibly instabilities. We plan to make full use of remotely sensed (RS) data, which will be obtained from NOAA and NASA via the Internet, and from the Direct Broadcast (DB) station at UPRM. RS products will be used for both model calibration and validation in situations where there are either sparse or no appropriate in-situ data. The local DB station is called the Space Information Laboratory (SIL) and is a component of the NASA-funded Tropical Center for Earth and Space Studies (TCESS). One of SIL’s main functions is to support projects at UPRM that require RS data over the Caribbean region. The SIL collects AVHRR, SeaWiFS, MODIS, Radarsat, and Landsat 7 data. SIL is able to process AVHRR data to level 3, and SeaWiFS and MODIS to level 2. At present SIL cannot process Landsat and Radarsat data beyond level 0. This situation could change by 2003 if licensing negotiations are successful.

The major tasks associated with configuring LEAF-2 and TOPMODEL model include:

o Delineation of Land Cover. This work will utilize a variety of sources of data including remotely-sensed data for PR. Remotely-sensed data may be obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Landsat Multispectral Scanner (MSS), the Landsat Thematic Mapper (TM), and/or the Calibrated Airborne Multispectral Scanner (CAMS). Although air photos are generally too detailed for the scale of this modeling project, they will be used in some cases where remote sensing techniques are inadequate. o Delineation of Soil Type. A soil GIS has been previously developed for PR and will be used in this project. The GIS database will provide soil hydraulic properties (e.g., layer texture, permeability, bulk densities, water holding capacity, layer thicknesses, etc.) o Delineation of Watershed Boundaries and Stream Network. Watershed boundaries and the stream network will be delineated using USGS Digital Line Graph (DLG) files. o Topography. Development of slope directions will be obtained from DEM (Digital Elevation Model). The DEM for PR will be used for elevation data needed in the TOPMODEL subsurface flow model. Slope directions will be determined within ARC/INFO/ArcView.

Data from hydrologic models previously developed in PR (e.g., Cruise and Miller, 1993 and 1994; Miller and Cruise, 1995; Mashriqui and Cruise, 1997; Boyington, 1998; PRWRERI, 2002; Vélez-Rodrigüez, 2002; Pérez-Alegría, 2002) will be used to assist in configuring LEAF-2 and TOPMODEL.

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Modifications will be made to the version of TOPMODEL currently being used in the RAMS/LEAF-2/TOPMODEL modeling system. In those areas of the island where deep vertical seepage occurs (e.g., coastal alluvial and karstic limestone aquifers), aquifer recharge will be estimated and passed to the MODFLOW groundwater flow model. MODFLOW will only simulate groundwater flow in selected areas of the island. In those areas of the island where significant aquifer systems are not present (e.g., the interior mountain area/volcanic rock), TOPMODEL will be used as is to simulate lateral downslope transport of water within saturated regions of the soil. Modifications to the computer codes will be made using the Lahey FORTRAN 95 and/or Digital Visual Fortran compilers, depending upon which compiler was used for developing the original code.

The groundwater flow model will be configured using data from numerous USGS groundwater resources studies conducted in PR (e.g., Puig and Rodríguez-Martínez, 1993; Rodríguez-Martínez, 1996; Pérez-Blair and Carrasquillo-Nieves, 1994; Pérez-Blair, 1997; Graves, 1991; Rodríguez-Martínez and Richards, 2000; Rodríguez-Martínez, 2001; Ramos- Ginés, 1994). Data will also be obtained from previously developed groundwater flow models in PR (e.g., Torres-González, 1985; Quiñones-Aponte, 1986; Graves, 1989; Tucci and Martínez, 1995; Quiñones-Aponte et al., 1996; Sepúlveda, 1999; and Kipp, 1987). The locations of these studies are summaries in Figure 6. The GIS-based user interface GMS (Groundwater Modeling System; Brigham Young University, 1997) will be used to manipulate input and output databases for the groundwater flow model. GMS was developed under the direction of the U.S. Army Corps of Engineers and involved support from the Department of Defense, the Department of Energy, and the Environmental Protection Agency. Tools are provided for site characterization, model conceptualization, finite-difference grid generation, geostatistics, telescopic model refinement, and output post-processing.

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Figure 6. Locations of Groundwater Resource and Modeling Studies in Puerto Rico

CALIBRATE THE MODELS FOR REGIONAL/LOCAL CONDITIONS.

RAMS/ LEAF-2/TOPMODEL RAMS/LEAF-2/TOPMODEL will be calibrated by adjusting model parameters until simulated calibration variables correspond reasonably close to actual measured data. Calibration variables will include rainfall, near surface temperature and relative humidity, reference evapotranspiration, stream base flow and storm discharge. The calibration will be conducted during a one-month period during the dry season (e.g., February) and a one-month during period during the wet season (e.g., November). Surface water data is collected at forty stream flow stations throughout the island. Weather data (rainfall and air temperature) is collected at over seventy stations. Daily information will be used to perform a transient calibration. We will perform the RAMS/LEAF-2/TOPMODEL calibration with the assistance of a commercially available nonlinear optimization program such as PEST (Doherty, 1994). PEST is able to "take control" of a complex, multi-dimensional, transient model, running it as many times as it needs to while adjusting its parameters until the discrepancies between selected model outputs and a complementary set of field measurements is reduced to a minimum in the weighted least squares sense. PEST implements a particularly robust variant of the Gauss-Marquardt-Levenberg method of nonlinear parameter estimation. The program can run within a Windows or UNIX operating environment.

MODFLOW Where sufficient data exist, steady-state and transient model calibrations will be performed. Many of the areas being modeled will be based on data from previously calibrated groundwater flow models. However, for various reasons, it may be necessary to configure the larger regional- scale model differently from the smaller local-scale models (e.g., because different grid spacing may be used), and these differences may have an effect on the simulated groundwater levels. The groundwater flow model will initially be calibrated for long-term average steady-state conditions. Calibration will be achieved by adjusting aquifer properties within reasonable limits in order to match observed average groundwater levels and discharge rates. Discharges will include base flow to rivers and discharges to the ocean. These data will be obtained from published reports. We will perform the MODFLOW calibration with the assistance of a commercially available nonlinear optimization program such as PEST (Doherty, 1994). In addition, a one-year transient model calibration will be performed in aquifers where synoptic groundwater level and discharge data exist.

MODEL VALIDATION We propose validating the model in two ways.

1. Compare model estimates with ground-based historical data; and 2. Compare the model-estimated island-wide water balance with a water balance obtained from ground-based and remotely-sensed data.

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Validation Step 1 The data used for Validation Step 1 will be of the same form as was used in the model calibrations (i.e., from data collection stations), except that the data will be selected from different years.

For example, if the transient calibration data for the groundwater flow model were from 1994, the validation data set would be from some other year, preferably a year with significantly different conditions (e.g., more wet or more dry).

Validation Step 2

The monthly water balance for the island, over a period of one year, will be calculated using the following simple equation:

DP = P + ET + RO + BF - S (1)

where DP is deep percolation or aquifer recharge, P is precipitation, ET is evapotranspiration, RO is surface runoff, BF is river base flow, and S is change in moisture storage. Each component of equation 1 is a function of space and time. On average S is negligible for long periods (e.g., one year), however, it will be important for shorter periods (e.g., one month). The components on the right-hand-side of equation 1 will be estimated using ground-based and remotely-sensed data. Soil moisture will be estimated using the coupled hydrologic/radiobrightness model (Laymon et al., 2002) with data from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E). Daily soil moisture content will also be estimated using a simplified water budget approach. The GIS-based water budget procedure is as follows:

1. Infiltration will be estimated by subtracting surface runoff from rainfall. Runoff will be estimated using the curve number (CN) approach. Soils data (e.g., CN and soil moisture holding capacity) currently exist in GIS form for PR. 2. If water initially within the soil profile plus the infiltrating water does not exceed the soil water holding capacity, then soil moisture content is equal to the initial volume plus infiltration. 3. If water initially within the soil profile plus the infiltrating water exceeds the soil water holding capacity, then the excess water will be considered percolation and the soil moisture content will be adjusted to the value of the soil moisture holding capacity.

Remotely-sensed evapotranspiration will be obtained from the Aqua/MODIS system. Evapotranspiration will also be determined (within a GIS) using simplified procedures for estimating average monthly climate data for PR described by Harmsen et al., 2002.

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Microwave, Surface and Precipitation Products (MSPPS) suite of products, which includes rain rate, land surface temperature, and land-surface emissivity will be obtained from NOAA/NESDIS. These are proven hydrological data products produced from the NOAA polar orbiters and are updated globally every four hours. These products have coarse spatial resolution (16-48 km) and will be downscaled. The most useful NASA products will be those generated from MODIS data. MODIS data can now be obtained from both the Terra (AM) and Aqua (PM) satellites. They have good temporal (1-2 days) and spatial (1-km) resolution. Products include land-surface temperature, land-cover type, vegetation indices, and leaf area index.

CONDUCT SIMULATION STUDIES OF THE HYDROLOGICAL CYCLE ON PUERTO RICO. A series of short-term simulations on the order of days and months will be conducted to determine the sources and sinks of the precipitation across the island and parameters that could influence the hydrological balance. The hydrological sources and sinks will be stratified into evapotranspiration, runoff, soil storage, aquifer recharge, precipitation from convective clouds, frontal systems, and easterly waves, etc. These simulations will be configured for the following scenarios: o Doubling CO2. o Doubling the atmospheric carbon dioxide concentration represents a realistic condition that may exist in the future if concentrations continue to increase at present rates. This scenario was considered, for example, by Bouraoui et al. (1999) in a study that evaluated the impact of climate change on water storage and groundwater recharge at the watershed scale. Doubling the CO2 is expected to increase the mean air temperatures by 1 to 5 oC. o Land-Use. PR is currently undergoing dramatic changes in land-use patterns, which can be expected to affect the components of the hydrologic cycle. We will run simulations that consider probable changes that are expected in land-use in PR in next 25 to 50 years. Land-use changes will include conversion of agricultural land to residential and urban land, as well as increase industrialization. o o o Hurricanes. Capiel and Calvesbert (1976) have suggested (qualitatively) that hurricanes are not important to PR’s water balance. We would like to investigate this assertion on a quantitative basis. o ENSO Index. Someone else needs to write this!!

Questions that we will attempt to answer, relative to the above scenarios include: o How will river flows be affected?

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o How might reservoir levels drop or rise due to changing surface water evaporation rates? o How might groundwater levels drop or rise due to changing aquifer recharge rates? o If groundwater levels drop, owing to a reduction in aquifer recharge rates, how might saltwater intrusion increase in the coastal areas? o What will be the water requirements by agriculture, and how might competition between water users (agriculture, urban and industrial) increase?

EXPECTED RESEARCH PRODUCTS

A number of significant research products can be expected from this research, including:  The RAMS/LEAF-2/TOPMODEL/MODFLOW coupled numerical models.  Increased understanding of the hydrology of PR and other tropical islands.  Possible recommendations for water managers within PR.  The research team will gain additional experience in simulating the atmosphere/land system.  Training of five graduate students  Training of four undergraduate students  Strengthen collaborative ties between the modeling group and

Time Frame The proposed time frame for the work under the NSF-WEAVE program is three calendar years. Figure 7 shows the detailed schedule by task.

1st 2nd Summer 1st 2nd Summer 1st 2nd Summer Semester Semester Semester Semester Semester Semester Semester Semester Semester 2003 2003 2003 2004 2005 2005 2005 2006 2006 Literature Review and Data Compilation Coupling of MODFLOW and LEAF-2/TOPMODEL Model Configuration RAMS LEAF-2 TOPMODEL MODFLOW Model Calibration RAMS/LEAF- 2/TOPMODEL MODFLOW Model Validation Ground-based data

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validation Island-wide water balance validation Model Simulations

Doubling CO2 Land-Use Hurricanes ENSO-Index Presentation/Publication of Results Figure 7. Project Schedule

Personnel This proposal is being submitted by the Joint Institute for Caribbean Climate Studies (JICCS) with over four years of experience based at the University of Puerto Rico-Mayagüez. The interdisciplinary research team has over four years of joint experience in atmospheric dynamic modeling, remote sensing, computer science, meteorological data acquisition, and statistical analysis. Included in the team are graduate and undergraduate students interested in solving pertinent climate and hydrological problems. A list of the personnel to be involved in this project is given below.

Name Institution Title Dr. Jorge González UPRM-Mech. Eng. PI Dr. Amos Winter UPRM-Marine Sciences Co-PI

Dr. Nazario Ramírez UPRM-Industrial Eng. Co-PI Dr. Ramon Vásquez UPRM-Electr.& Co-PI Comp.Eng Dr. Eric Harmsen UPRM Agr. and Co-PI Biosystems Engineering Dr. Robin Williams URRM- Mech. Eng. Co-PI Graduate Students (5) UPRM Undergraduate UPRM Students (4) GIS Specialist UPRM Computer UPRM Administrator Dr. Joseph Eastman Maryland Baltimore Collaborator Faculty County/NASA Goddard Dr. Robert Waide University of New Collaborator Faculty Mexico Teppley Collaborative Researchers Friedman Collaborative

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Researchers Cooper Collaborative Researchers

PI – Dr. Gorge Gonzalez will be responsible for assuring the success and time lines of the proposal. He will assure that all products are delivered in a timely manner. He will be in charge of the data gathering and analysis part of the proposal. Dr. J.E. González and Williams will be responsible for the successful implementation and interpretation of the model. Dr. Ramirez will provide the atmospheric high-resolution data needed to configure RAMS and will develop a multivariate time series models to express the relationships among the regional upper-air, mid-layer, SLP, and SST observations with PR rainfall observations. Dr. Vásquez will provide data from remote sensing platforms. He will provide estimates of soil moisture content and evaporation for the island-wide water balance analysis. Dr. Harmsen will be responsible for the coupling of MODFLOW to the TOPMODEL, and overall development of the groundwater flow model. He will also be involved in various aspects of the near-surface hydrologic model.

Project Assessment and Management The project will be extensively assessed to ensure success in academic and research activities and in expansion and continuation. A set of robust metrics with associated criteria will be established along with an assessment schedule. Among performance indicators to be included are: number of undergraduate and graduate students participating; number of graduate thesis completed; number of peer-reviewed and conference publications per researcher per year; number of semester courses offered and developed; number of industrial and governmental collaborations established per researcher; and amount of new external funds obtained by the research team. A three-member Technical Advisory Board (TAC) will be used as a direct evaluator of the program. The mission of the TAC is to oversee the overall progress of the project and to suggest modifications in strategy that will add effectiveness to the project as well as ensure focus towards meeting objectives. It is expected that the project will undergo two overall assessment processes per year, one internal and one external. The TAC will consist of an expert in regional modeling (Dr. Roger Pielke, from Colorado Sate University), an expert in atmospheric data collection with optical instruments mostly interferometry, (Dr. Robert Kerr of Scientific Solutions, Inc.), and a regional climate change expert from NASA (Dr. William Lau, team leader of the RELACS projects is a potential candidate). This project will consist of six faculty members (González, Nazario, Vásquez, Winter, Williams, Harmsen); one collaborative faculty (Waide); three collaborative researchers (Teppley, Friedman, and Cooper); two post doctoral associates; five graduate students; five undergraduate students; one remote sensing analyst; and one project coordinator. The project has also been divided into three interdependent technical tasks, one educational component and one product dissemination component. The Principal Investigator (PI) for the entire project will be Dr. J.E. González. The PI will be responsible for insuring that all individual tasks are accomplished in a timely manner and that progress is made according to plan and to facilitate communication

4/29/2018 Revision avenues among individual projects. The complete research team will meet in a monthly basis to report progress. Team members not residing in UPRM Campus will join the meetings through teleconferences.

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REFERENCES Allen, R. G., L. S. Pereira, Dirk Raes and M. Smith, 1998. Crop Evapotranspiration Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage Paper 56, Food and Agriculture Organization of the United Nations, Rome. Band, L. E., 1993. Effect of land surface representation on forest water and carbon budgets. J. Hydrol., 150, 749-772. Band, L. E., P. Patterson, R. Nemani, and S. W. Running, 1993. Forest ecosystem processes at the watershed scale: Incorporating hillslope hydrology. Agric. For Meteor., 63, 93-126. Baron , J. S., M. D. Harman, T. G. G. Kittel, L. E. Band, D. S. Ojima, and R. B. Lammers, 1998. Effects of land cover, water redistribution, and temperature on ecosystem processes in the South Platte Basin. Ecol. Appl., 8, 1037-1051. Bennet, G. D., 1976. Electric analog simulation of the aquifer along the south coast of Puerto Rico. U.S. Geological Survey Open File Report 74-4, 101 p. Bouraou F., G. Vachaud, L. Z. X. Li, H. Le Treut and T. Chen. 1999. Evaluation of the impact of climate changes on water storage and groundwater recharge at the watershed scale. Climate Dynamics 15:153-161. Boyington, T. M. 1998. A Runooff-Erosion Model for the Añasco Watershed, Puerto Rico, Utilizing a Remotely Sensed Database, Geographic information System and Soil-Lumped Computational Zones. Master’s Thesis. Tulane University. Brigham Young University, 1997. Groundwater Modeling System (GMS), User's Manual, Version 2.1. Engineering Computer Graphics Laboratory. Capiel, M. and R. J. Calvesbert, 1976. On the Climate of Puerto Rico and its Agricultural Water Balance. Journal of Agriculture of the University of Puerto Rico. Vol. LX, No. 2, pgs. 139-153. Chase, T. N., R. A. Pielke Sr., T. G. G. Kitel, J. S. Baron, and T. J. Stohlgren, 1998. Potential impacts on Colorado Rocky Mountain weather and climate due to land use changes on the adjacent Great Plains. J. Geophys. Res., 104, 16 673 – 16 690. Chen, A. A. and M. A. Taylor (2002). Investigating the link between early season Caribbean rainfall and the El Nino plus 1 year.International Journal of Climatology 22(1): 87-106. Comarazamy D., 2001. Atmospheric modeling of the Caribbean Region: Precipitation and Wind Analysis in Puerto Rico for April 1998. Comarazamy D., González J., Stalker, J.R., and Ramírez, N., 2001, Atmospheric modeling of the Caribbean region: precipitation simulations, Proceeding of Sixth Caribbean Islands Water Resources Congress, February 22-23, Mayagüez, Puerto Rico. Collatz, J.G., Bounoua, L., Los, S.O., Randall, D.A., Fung, L.Y., and Sellers, P.J., 2000, A mechanism for the influence of vegetation on the response of the diurnal temperature range to changing climate, Geophysical Research Letters, Vol. 27, pp. 3381-3384. Cruise, J. G. and R. L. Miller, 1993. Hydrologic Modeling with Remotely Sensed Databases. Water Resources Bulletin 29(6):997-1001. Cruise, J. F. and R. L. Miller, 1994. Hydrologic Modeling of Land Processes in Puerto Rico Using Remotely Sensed Data. Water Resources Bulletin 30(3):419-428. DeLong, L. L., 1986. Extension of the unsteady one-dimensional open-channel flow equations for flow simulation in meandering channels with flood plains, in Selected Papers in the Hydrologic Sciences, S. Subitzky (ed): U.S. Geological Survey Water-Supply Paper 2290, p. 101-105.

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Deser C. and Blackmon M. L. (1993) Surface climate variations over the North Atlantic Ocean during winter. J. Climate 6, 1743-1754. Doherty, J. 1994. PEST Model Independent Parameter Estimation. Watermark Company. Donigian A. S. J., B. R. Bicknell, and J. C. Imhoff,, 1995. Hydrological Simulation Program – FORTRAN (HSPF). In: V. P. Sigh (Editor), Computer Model s of Watershed Hydrology. Chapter 12. Water Resources Publicaitons, Littleton, CO, pp. 345-442. Enfield, D.B., and D.A. Mayer, Tropical Atlantic sea surface temperature variability and its relation to El Nino Southern Oscillation, Journal of Geophysical Research-Oceans, 102 (C1), 929-945, 1997. Etter, P. C., P. J. Lamb, D. H. Potis. 1987. Heat and freshwater budgets of the Caribbean with revised estimates of the Central American seas. Journal of Physical Oceanography, 17:1232-1248. Famiglietti, J. and E. G. Wood, 1991. Evapotranspiration and runoff for large land areas: Land surface hydrology for atmospheric general circulation models. Surv. Geophys., 12, 179- 204. Famiglietti, J. and E. G. Wood, 1994. Multiscale modeling of spatially variable water and energy balance processes. Water Resourc. Res., 30, 3061-3078. Freeze R. A. and J. A. Cherry. 1979. Groundwater. Prentice Hall Publishers. Garriott, E. B., 1906: The West Indian hurricanes of September, 1906. Mon. Wea. Rev .,34, 416--423. Giannini, A., Y. Kushnir, and M.A. Cane, Interannual variability of Caribbean rainfall, ENSO, and the Atlantic Ocean, Journal of Climate, 13 (2), 297-311, 2000. Graves. R. P. 1989. Water Resources of the Humacao-Naguabo Area, Eastern Puerto Rico. U.S. Geological Survey Water-Resources Investigation Report 87-4088. San Juan, Puerto Rico. pp 69. Graves, R. P., 1991. Ground-water resources in Lajas Valley, Puerto Rico. U.S. Geological Survey. Water-Resources Investigations Report 89-4182. Gray, W. M., 1968: Global view of the origins of tropical disturbances and storms. Mon. Wea. Rev .,96 , 669--700. Gray, W. M., 1984: Atlantic seasonal hurricane frequency. Part I: El Nino and 30mb Quasi- Biennial Oscillation influences. Mon. Wea. Rev ., 112 , 1649--1668. Gray, W.M., C.W. Landsea, P.W. Mielke, and K.J. Berry, Predicting Atlantic Basin Seasonal Tropical Cyclone Activity by 1 June, Weather and Forecasting, 9 (1), 103-115, 1994. Gray, W.M., C.W. Landsea, P.W. Mielke, and K.J. Berry, Predicting Atlantic Basin Seasonal Tropical Cyclone Activity by 1-August, Weather and Forecasting, 8 (1), 73-86, 1993. Harmsen, E. W., M. R. Goyal, and S. Torres Justiniano, 2002. Estimating Evapotranspiration in Puerto Rico. Puerto Rico Journal of Agriculture. In Press Hastenrath, S., 1978: On modes of tropical circulation and climate anomalies. Journal of theAtmospheric Sciences, 35, 2222–2231. Heisel, J. E. and J. R. González, 1979. Water budget and hydraulic aspects of artificial recharge, south coast of Puerto Rico. U.S. Geological Survey Water-Resources Investigations Report 78-58. 102 p. Kent, R. B. 2002. West Indies. Microsoft® Encarta® Online Encyclopedia 2002. Kipp, K. L., 1987. HST3D: A computer code for simulation of heat and solute transport in three- dimensional ground-water flow systems: U.S. Geological Survey Water-Resources Investigations Report 86-4095, 512 p.

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Lu, L. R. A. Pielke Sr., G. E. Liston, W. J. Parton, D. Ojima, and M. Hartman. 2000. Coupling Atmospheric, Ecologic, And Hydrologic Processes in a Regional Climate Model. 15th Conference on Hydrology, January 9-14. Long Beach, CA. Laymon, C. A. F. Archer, W. L. Crosson, and A. Limaye, 2002. Soil Moisture Measurements and Modeling for Validating AMSR-E Soil Moisture Products. USRA, Huntsville. http://ams.confex.com/ams/annual2003/VARIH2O/abstracts/56501.htm . Malmgren B. J., Winter A., and Chen D. (1998) El Nino–Southern Oscillation and North Atlantic oscillation Control of Climate in Puerto Rico. J. Climate 11(10), 2713-2718. Malgrem, B.A. and Winter A., 1999, climate zonation in Puerto Rico based on principal components analysis and an artificial neural network, American Meteorological Society, Vol. 12, pp. 977-985. Mashriqui, H. S. and J. F. Cruise, 1997. Sediment Yield Modeling by Grouped Response Units. Journal of Water Resources Planning and Management. ASCE 123(2): 95-104. McDonald, M. G. and A. W. Harbaugh. 1984. A Modular Three-Dimensional Finite Difference Ground-Water Flow Model. U.S. Geological Survey. Miller , R. L. and J. F. Cruise, 1995. Effects of Suspended Sediments on Coral Growth: Evidence from Remote Sensing and Hydrologic Modeling. Journal of Environmental Remote Sensing. 53:177-187. Mestas-Nuñez, M. Alberto, and D.B. Enfield, Rotated Global Modes of Non-ENSO Sea Surface Temperature Variability. Journal of Climate, Journal of Climate, 12 (9), 2734–2746., 1999 Neitsch, S. L., J. G. Arnold, J. R. Kiniry, S. Srinivasan, and J. R. Williams, 2002. Soil and Water Assessment Tool User’s Manual Version 2000. Grassland Soil and Water Research Laboratory, Agricultural Research Service, Temple Texas. GSWRL Report 02-02. Olcott, P. G., 1997. Ground Water Atlas of the United States – Segment 13 Alaska, Hawaii, Puerto Rico and the U.S. Virgin Islands. Hydrologic Investigations Atlas 730-N, U.S. Geological Survey, Reston, Virginia. Pan, A., E. Takle, R. Horton, and M. Segal. 2002. Warm-Seasonal Soil Moisture Prediction Using A Coupled Regional Climate Model. 16th Conference on Hydrology, January 13-18. Orlando, Florida. Penland, C., and L. Matrosova, 1998: "Prediction of tropical Atlantic sea surface temperatures using Linear Inverse Modeling," J. Climate, 11, 483-496. Pérez-Alegría, L. R. 2002. Total Maximum Daily Load (TMDL) Environmental Regulations: Proceedings of the March 11-13, 2002 Conference, Fort. Worth, TX, USA, Pp. 163. Pérez-Blair, F., 1997. Ground-water resources of alluvial valleys in northeastern Puerto Rico : Río Espíritu Santo to Río Demajagua area. U.S. Geological Survey. Water-Resources Investigations Report 96-4201. Perez-Blair, F. and Carrasquillo-Nieves, R. A., 1994. Potentiometric surface of the principal alluvial aquifers in the Rio Espiritu Santo to Rio Demajagua area, Puerto Rico, U.S. Geological Survey. Water-Resources Investigations Report 94-4152. Pielke, R. A., W. R. Cotton, R. L. Walko, C.J. Tremback, W. A. Lyons, L.D. Grasso, M.E. Nicholls, M. D. Moran, D. A. Wesley, T. J. Lee, and J. H. Copeland, 1992: A comprehensive meteorological modeling system – RAMS. Meteor.Atmos.Phys., 49, 69- 91. Pielke, R. A., Walko, L. Steyaert, P. L. Vidale, G. E. Liston, and W. A. Lyons, 1999. The influence of anthropogenic landscape changes on weather in south Florida. Mon. Wea. Rev., 127, 1663-1673.

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Puerto Rico Water Resources and Environmental Research Institute, 2002. Assessing Cumulative and Secondary Point and Non-Point Pollution Sources at Jobos Bay Watershed. Website: http://www.ece.uprm.edu/rumhp/prwrri/ Puig, J. C. and Rodríguez-Martínez, J. 1993. Ground-water resources of the Caguas-Juncos Valley, Puerto Rico. U.S. Geological Survey. Water-Resources Investigations Report 91- 4079. Quiñones-Aponte, V., 1986. Simulation of ground-water flow in the Río Yauco alluvial valley, Puerto Rico. U.S. Geological Survey Water-Resources Investigations Report 85-4179. San Juan, Puerto Rico. 32 p. Quiñones-Aponte, V., F. Gómez-Gómez, and R. A. Renken, 1996. Geohydrology and simulation of ground-water flow in the Salinas to Patillas Area, Puerto Rico. U.S. Geological Survey Water-Resources Investigations Report 95-4063. San Juan, Puerto Rico. 37 p. Ramos-Ginés, O. 1994. Effects of changing irrigation practices on ground-water hydrology of the Santa Isabel-Juana Díaz area, South Central Puerto Rico. U.S. Geological Survey Water-Resources Investigations Report 91-4183. San Juan, Puerto Rico. 22 p. Ray, C. L., 1935: Relation of tropical cyclone frequency to summer pressures and ocean surface- water temperatures. Mon. Wea. Rev ., 63 , 10--12. Robertson A. W., Mechoso C. R., and Kim Y.-J. (2000) The Influence of Atlantic Sea Surface Temperature Anomalies on the North Atlantic Oscillation. Journal of Climate 13, 122-138. Robison, T. M. and R. B. Anders, 1973. Electrical analog model study of the alluvial aquifer in the Yabucoa Valley, Puerto Rico. Pase 2 – The Planning, construction, and use of the model. U.S. Geological Survey Open File Report 73-1. 22 p. Rodríguez-Martínez, J., 1996. Hydrogeology and ground-water/surface-water relations in the Bajura area of the Municipio of Cabo Rojo, southwestern Puerto Rico. U.S. Geological Survey. Water-Resources Investigations Report 95-4159. Rodríguez-Martínez and Richards, R. T., 2000. Detection of conduit-controlled ground-water flow in northwestern Puerto Rico using aerial photographs interpretation and geophysical methods. U.S. Geological Survey. Water-Resources Investigations Report 00-4147. Sepúlveda, N., F. Pézez-Blair, L. L. DeLong, and D. López-Trujillo. 1996. Real-time rainfall- runoff model of the Carraízo-Reservoir Basin in Puerto Rico. U.S. Geological Survey Water-Resources Investigations Report 95-4235. San Juan, Puerto Rico. 112 p. Sepúlveda, N., 1999. Groundwater flow, solute transport, and simulation of remedial alternatives for the water-table aquifer in Vega Alta, Puerto Rico. U.S. Geological Survey Water- Resources Investigations Report 97-4170. San Juan, Puerto Rico. 96 p. Shapiro, L. J., 1982: Hurricane climatic fluctuations. Part I: Patterns and cycles. Mon. Wea. Rev., 110 , 1007--1013. Stalker, J.R., et al., 2000: Use of cumulus parameterization and explicit microphysics fro climate studies over the Rio Grande basin. Proceedings of 15 th Conference on Hydrology, Annual Meeting, American Meteorological Society, Long Beach, CA, pp. 74-79 Stieglitz, M., D., Rind, J. S., Famiglietti, and C. Rosenzwieg, 1997. An efficient approach to modeling the topographic control of surface hydrology for regional and global climate modeling. J. Climate, 10, 118-137. Strohlgen, T. J., T. N. Chase, R. A. Pielke, T. G. G. Kittel, and J. S. Baron, 1998. Evidence that local land use practices influence regional climate, vegetation, and stream flow patterns in adjacent natural areas. Global Change Biol., 4, 495-504.

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Torres-González, A. 1985. Simulation of ground-water flow in the water table aquifer near Barceloneta, Puerto Rico. U.S. Geological Survey Water-Resources Investigations Report 84-4113. San Juan, Puerto Rico. 39 p. Tucci, P. and M. I. Martínez, 1995. Hydrology and simulation of groundwater flow in the Aguadilla to Río Camuy area, Puerto Rico. U.S. Geological Survey Water-Resources Investigations Report 95-4028. San Juan, Puerto Rico. 39 p. USGS, 1998. Estimated Water Use in Puerto Rico, 1995. Open-File Report 98-276. pp 28. Veve, T. D. And B. E. Taggart (Editors), 1996. Atlas of Ground-Water Resources in Puerto Rico and the U.S. Virgin Islands. U.S. Geological Survey. Water-Resources Investigations Report 94-4198. Vélez-Rodrigüez, L. L. 2002. Monitoring Land Use and Land Cover in the Jobos Bay National Estuary Watershed. Puerto Rico Water Resources and Environmental Research Institute. Website: http://www.ece.uprm.edu/rumhp/prwrri/ Weaver, C. P. and S. W. Pacala. 2001. Impact Of Land Use/Land Cover Change On U. S. Climate. 16th Conference on Hydrology, January 13-18. Orlando, Florida. Walko, R. L, L. E. Band, J. Baron, T. G. F. Kittel, R. Lammers, T. J. Lee, D. Ojima, R. A. Pielke Dr., C. Taylor, C. Tague, C. J. Tremback, and P. L. Vidale. 2000. Coupled Atmosphere- Biophysics-Hydrology Models for Environmental Modeling. Journal of Applied Meteorology. June 2000: 931-944.

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BIOGRAPHICAL SCHETCHES

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PROPOSED BUDGET

The total estimated budget for the three year study is $534,178.

Miscellaneous Callaborators Travel 5@$1500 x 3 years $22,500 Board Travel 3@$1500 x 3 years $13,500 Computer Administrator Salary (assistantship) x 3 years $29,400 GIS Specialist Salary (assistantship) x 3 years $29,400

Total $94,800

Climate Analysis

Amos Winter: 1/9 annual salary (approximate) x 3 years $18,000 Undergraduate Students (1 @ 15 hours/week for 48 weeks at $6.80/hr x 3 years $14,688 RAMS/LEAF-2/TOPMODEL Training $2,500 Attendance at Professional Meeting x 3 years $5,250 Publishing costs (page charges) $2,500 Total $42,938

RAMS Robin Williams: 1/9 annual salary x 3 years $18,000 Graduate Students (1 @ $9,400 x 3 years) $28,200 Undergraduate Students (1 @ 15 hours/week for 48 weeks at $6.80/hr x 3 years) $14,688 RAMS Training $2,500 Remotely Sensed Products $5,000 ArcINFO-related maps/tools $1,000

Local Travel – Trips within PR for obtaining data required for model construction $2,000 Attendance at Professional Meeting x 3 years $5,250 Publishing costs (page charges) per year $2,500 Books $1,000

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Total $80,138

LEAF-2/TOPMODEL Gonzalez/Harmsen: 1/9 annual salary x 3 years $18,000 Graduate Students (1 @ $9,400 x 3 years) $28,200 Undergraduate Students (1 @ 15 hours/week for 48 weeks at $6.80/hr x 3 years) $14,688 LEAF-2/TOPMODEL Training $2,500 Remotely Sensed Products $5,000 ArcINFO-related maps/tools $1,000 Local Travel – Trips within PR for obtaining data required for model construction $2,000 Attendance at Professional Meeting x 3 years $5,250 during last year $2,500 Books $1,000 Total $80,138

MODFLOW Eric Harmsen: 1/9 annual salary (approximate) x 3 years $18,000 Graduate Students (1 @ $9,400 x 3 years) $28,200 Undergraduate Students (1 @ 15 hours/week for 48 weeks at $6.80/hr x 3 years) $14,688

GMS pre/post-processor for MODFLOW (includes all modules and interfaces) $2,250 GMS Refresher Training for Eric Harmsen (estimate) $2,500 RAMS/LEAF-2/TOPMODEL Training $2,500 Visual PEST (Parameter Estimation Software) $1,000 ArcINFO-related maps/tools $1,000 Local Travel – Trips within PR for obtaining data required for model construction $2,000 Attendance at Professional Meeting x 3 years $5,250 Publishing costs (page charges) $2,500 USGS Publications and Books $1,000 Total $80,888

Validation with Ground-based Data Nazario: 1/9 annual salary x 3 years $18,000

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Graduate Students (1 @ $9,400 x 3 years) $28,200 Undergraduate Students (1 @ 15 hours/week for 48 weeks at $6.80/hr x 3 years) $14,688 RAMS/LEAF-2/TOPMODEL Training $2,500 ArcINFO-related maps/tools $1,000 Local Travel – Trips within PR for obtaining data required for model construction $2,000 Attendance at Professional Meeting x 3 years $5,250 Publishing costs (page charges) per year $2,500 Books $1,000 Total $75,138

Validation - Island-wide analysis Vasquez: 1/9 annual salary x 3 years $18,000 Graduate Students (1 @ $9,400 x 3 years) $28,200 Undergraduate Students (1 @ 15 hours/week for 48 weeks at $6.80/hr x 3 years) $14,688 RAMS/LEAF-2/TOPMODEL Training $2,500 Remotely Sensed Products $5,000 ArcINFO-related maps/tools $1,000 Local Travel – Trips within PR for obtaining data required for model construction $2,000 Attendance at Professional Meeting x 3 years $5,250 Publishing costs (page charges) $2,500 Books $1,000 Total $80,138

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FACILITIES, EQUIPMENT AND OTHER RESOURCES

The proposers already have an established research program to investigate climate change processes in the Caribbean. As part of this program a data collection and analysis center has been established for the Caribbean region having accesses more than 200 voluntary surface stations. They have also the required infrastructure to conduct remote sensing studies through the Space Information Laboratory (SIL: http://tcess.uprm.edu). The group has current licenses for RAMS, up-to-date workstations and access to a parallel machine located at the University of Puerto Rico-Rio Piedras Campus that host 32 processors on a SGI Origin 2000. The group has active collaboration with Los Alamos National Laboratory and with the Arecibo Observatory. Robin, please include something in this section on  UMBC/NASA  Workstations (INME)  Pascor/GIS