WATER AND ENERGY BALANCE ESTIMATION IN PUERTO RICO USING SATELLITE REMOTE SENSING

Similar documents
Eric. W. Harmsen 1, John Mecikalski 2, Pedro Tosado Cruz 1 Ariel Mercado Vargas 1

Eric. W. Harmsen Agricultural and Biosystems Engineering Department, University of Puerto Rico Mayaguez Campus

Eric. W. Harmsen 1, John Mecikalski 2, Vanessa Acaron 3 and Jayson Maldonado 3

Research Note COMPUTER PROGRAM FOR ESTIMATING CROP EVAPOTRANSPIRATION IN PUERTO RICO 1,2. J. Agric. Univ. P.R. 89(1-2): (2005)

ATMET Technical Note. Modifications for the Transition From LEAF-2 to LEAF-3

Treatment of Land-Use and Urbanization

Estimating Daily Evapotranspiration in Puerto Rico using Satellite Remote Sensing

METRIC tm. Mapping Evapotranspiration at high Resolution with Internalized Calibration. Shifa Dinesh

METR 130: Lecture 2 - Surface Energy Balance - Surface Moisture Balance. Spring Semester 2011 February 8, 10 & 14, 2011

Hydrologic Modelling of the Upper Malaprabha Catchment using ArcView SWAT

Land Data Assimilation at NCEP NLDAS Project Overview, ECMWF HEPEX 2004

P1.34 MULTISEASONALVALIDATION OF GOES-BASED INSOLATION ESTIMATES. Jason A. Otkin*, Martha C. Anderson*, and John R. Mecikalski #

VIC Hydrology Model Training Workshop Part II: Building a model

The role of soil moisture in influencing climate and terrestrial ecosystem processes

Estimation of Wavelet Based Spatially Enhanced Evapotranspiration Using Energy Balance Approach

12 SWAT USER S MANUAL, VERSION 98.1

Soil Moisture Prediction and Assimilation

2. Irrigation. Key words: right amount at right time What if it s too little too late? Too much too often?

Land Surface Processes and Their Impact in Weather Forecasting

Name period date assigned date due date returned. Texas Ecoregions

A GROUND-BASED PROCEDURE FOR ESTIMATING LATENT HEAT ENERGY FLUXES 1 Eric Harmsen 2, Richard Díaz 3 and Javier Chaparro 3

Assimilation of satellite derived soil moisture for weather forecasting

CIMIS. California Irrigation Management Information System

ONE DIMENSIONAL CLIMATE MODEL

Evaluation of SEBAL Model for Evapotranspiration Mapping in Iraq Using Remote Sensing and GIS

Analyzing spatial and temporal variation of water balance components in La Vi catchment, Binh Dinh province, Vietnam

John R. Mecikalski #1, Martha C. Anderson*, Ryan D. Torn #, John M. Norman*, George R. Diak #

Atmospheric Sciences 321. Science of Climate. Lecture 14: Surface Energy Balance Chapter 4

Validation of NOAA Interactive Snow Maps in the North American region with National Climatic Data Center Ground-based Data

Implementation of the NCEP operational GLDAS for the CFS land initialization

Evapotranspiration. Rabi H. Mohtar ABE 325

Existing NWS Flash Flood Guidance

KEY WORDS: Palmer Meteorological Drought Index, SWAP, Kriging spatial analysis and Digital Map.

IMPACT OF CLIMATE CHANGE OVER THE ARABIAN PENINSULA

Joint International Surface Working Group and Satellite Applications Facility on Land Surface Analysis Workshop, IPMA, Lisboa, June 2018

Soil Water Atmosphere Plant (SWAP) Model: I. INTRODUCTION AND THEORETICAL BACKGROUND

Physical Aspects of Surface Energy Balance and Earth Observation Systems in Agricultural Practice

NIDIS Intermountain West Drought Early Warning System October 17, 2017

MET 3102-U01 PHYSICAL CLIMATOLOGY (ID 17901) Lecture 14

EVALUATION OF UPSCALING PARAMETERS AND THEIR INFLUENCE ON HYDROLOGIC PREDICTABILITY IN UPLAND TROPICAL AREAS

A Time Lag Model to Estimate Rainfall Rate Based on GOES Data

Climate Impacts of Agriculture Related Land Use Change in the US

5. General Circulation Models

Climate Dynamics (PCC 587): Hydrologic Cycle and Global Warming

Improvement of vegetation parameters for the estimation of evapotranspiration in the Midwest United States

Evaporative Fraction and Bulk Transfer Coefficients Estimate through Radiometric Surface Temperature Assimilation

4.5 Comparison of weather data from the Remote Automated Weather Station network and the North American Regional Reanalysis

AWRA 2010 SUMMER SPECIALTY CONFERENCE San Juan, Puerto Rico CALIBRATION AND VALIDATION OF CASA RADAR RAINFALL ESTIMATION

GRID RAINFALL DISAGGREGATION TOWARD A PATCH-BASED ENSEMBLE KALMAN FILTER FOR SOIL MOISTURE DATA ASSIMILATION

Lecture 3A: Interception

Promoting Rainwater Harvesting in Caribbean Small Island Developing States Water Availability Mapping for Grenada Preliminary findings

5B.1 DEVELOPING A REFERENCE CROP EVAPOTRANSPIRATION CLIMATOLOGY FOR THE SOUTHEASTERN UNITED STATES USING THE FAO PENMAN-MONTEITH ESTIMATION TECHNIQUE

Name period date assigned date due date returned. Texas Ecoregions

NIDIS Intermountain West Drought Early Warning System July 18, 2017

MARIAN MARTIN, ROBERT E. DICKINSON, AND ZONG-LIANG YANG

MODULE 8 LECTURE NOTES 2 REMOTE SENSING APPLICATIONS IN RAINFALL-RUNOFF MODELLING

Light Up Your World Adapted from Reflecting on Reflectivity,

NIDIS Intermountain West Drought Early Warning System May 23, 2017

CARFFG System Development and Theoretical Background

Modelling changes in the runoff regime in Slovakia using high resolution climate scenarios

NIDIS Intermountain West Drought Early Warning System April 16, 2019

Evaluation of a MODIS Triangle-based Algorithm for Improving ET Estimates in the Northern Sierra Nevada Mountain Range

Global Water Cycle. Surface (ocean and land): source of water vapor to the atmosphere. Net Water Vapour Flux Transport 40.

Google Earth Engine METRIC (GEM) Application for Remote Sensing of Evapotranspiration

Changes in Seasonal Albedo with Land Cover Class

Zachary Holden - US Forest Service Region 1, Missoula MT Alan Swanson University of Montana Dept. of Geography David Affleck University of Montana

Name period date assigned date due date returned. Texas Ecoregions

Mapping of Taiga Ecosystems Evapotranspiration by Using Results of EOS and Flux Tower observations

Environment Canada Modelling Systems and the 2013 Alberta Floods

Evaluation of a New Land Surface Model for JMA-GSM

Remote sensing estimation of land surface evapotranspiration of typical river basins in China

Status report on the La Plata Basin (LPB) - A CLIVAR/GEWEX Continental Scale Experiment

The Colorado Climate Center at CSU. residents of the state through its threefold

What is a Biome? An Overview of Biomes. The Holdridge Life Zones. Tundra 9/14/2010. In the following slides, you ll

Hydrologic Overview & Quantities

NIDIS Intermountain West Drought Early Warning System December 30, 2018

Incorporation of SMOS Soil Moisture Data on Gridded Flash Flood Guidance for Arkansas Red River Basin

NIDIS Intermountain West Drought Early Warning System April 18, 2017

CHAPTER VII FULLY DISTRIBUTED RAINFALL-RUNOFF MODEL USING GIS

NIDIS Intermountain West Regional Drought Early Warning System February 7, 2017

Application and impacts of the GlobeLand30 land cover dataset on the Beijing Climate Center Climate Model

Cloud Analysis Image: Product Guide

Precipitation. Standardized Precipitation Index. NIDIS Intermountain West Regional Drought Early Warning System January 3, 2017

forest tropical jungle swamp marsh prairie savanna pampas Different Ecosystems (rainforest)

Observation: predictable patterns of ecosystem distribution across Earth. Observation: predictable patterns of ecosystem distribution across Earth 1.

USGS Water Census Guidelines and Specifications for ET Remote Sensing

The Atmosphere. Topic 3: Global Cycles and Physical Systems. Topic 3: Global Cycles and Physical Systems. Topic 3: Global Cycles and Physical Systems

Global Biogeography. Natural Vegetation. Structure and Life-Forms of Plants. Terrestrial Ecosystems-The Biomes

NIDIS Intermountain West Drought Early Warning System March 26, 2019

Remote Sensing Applications for Land/Atmosphere: Earth Radiation Balance

The Importance of Snowmelt Runoff Modeling for Sustainable Development and Disaster Prevention

Regional Precipitation and ET Patterns: Impacts on Agricultural Water Management

May 3, :41 AOGS - AS 9in x 6in b951-v16-ch13 LAND SURFACE ENERGY BUDGET OVER THE TIBETAN PLATEAU BASED ON SATELLITE REMOTE SENSING DATA

Lei Zhao. F&ES Yale University

Ecosystem-Climate Interactions

WMS 9.0 Tutorial GSSHA Modeling Basics Infiltration Learn how to add infiltration to your GSSHA model

Terrestrial Snow Cover: Properties, Trends, and Feedbacks. Chris Derksen Climate Research Division, ECCC

Regional Drought and Crop Yield Information System to enhance drought monitoring and forecasting in Lower Mekong region

An Internet-based Agricultural Land Use Trends Visualization System (AgLuT)

Hands On Applications of the Latin American and Caribbean Flood and Drought Monitor (LACFDM)

Transcription:

WATER AND ENERGY BALANCE ESTIMATION IN PUERTO RICO USING SATELLITE REMOTE SENSING Eric. W. Harmsen, Ariel Mercado Vargas, Pedro Tosado Cruz, Jonellys M Maldonado Morales and Angel O. Ortiz Lozada OCTAVA REUNIÓN NACIONAL DE PERCEPCIÓN REMOTA Y SIG DE PUERTO RICO 30 DE NOVIEMBRE DE 2010 USDA Hatch http://academic.uprm.edu/abe/pragwater/

LAST YEAR S OBJECTIVE To develop an algorithm for estimating daily, high resolution (1-km), crop reference evapotranspiration (ET o ) over Puerto Rico. ET a = K c ET o

THIS YEAR S OBJECTIVES To introduce several new water resourcerelated remote sensing products for Puerto Rico, Haiti and the Dominican Republic. The development of the methodology has advanced more quickly in Puerto Rico, therefore, the information presented here can be considered a prototype of what is being developed for the other two countries (i.e., Haiti and the Dominican Republic).

Technical Approach

Algorithm Flow Chart SM 2 = Precip ET a RO DP SM 1 Obtain Solar Radiation, wind speed, rainfall, etc,. for yesterday Estimate Components of the Surface Water Budget Expand the components of the Surface Energy Budget Estimate Actual Evapotranspiration (ET a ) Solve Surface Energy Budget implicitly in terms of the Effective Surface Temperature Estimate the components of the surface energy budget R net + λe + H + G = 0

Remotely Sensed Solar Radiation Solar radiation was obtained using the Modified Gautier and Diak method (Gautier et al., 1980; Diak and Gautier, 1983). Data were obtained from the GOES-East satellite. Geostationary platform 1 km resolution for Puerto Rico 2 km Haiti and the Dominican Republic High time resolution (30 minutes)

Comparison of daily integrated solar radiation obtained from pyranometers at six locations in Puerto Rico and satellite remote sensing. Data collected between March 2009 and June 2010

Estimated Variables Reference evapotranspiration Net Radiation Latent heat flux Sensible heat flux Actual evapotranspiration Evapotranspiration Crop coefficient Surface runoff (Curve Number method) Deep percolation (based on field capacity concept) Soil moisture content (based on field capacity concept)

Transient Input Parameters and Variables Solar Radiation Rainfall Wind speed Vapor pressure Air temperature Effective surface temperature Bulk surface resistance Aerodynamic resistance

Non-Transient Input Parameters Surface elevation Soil texture Soil field capacity Soil wilting point Rooting depth Roughness length Zero plane displacement

RESULTS Reference Evapotranspiration for PR, Dominican Republic and Haiti Radiation-based Hargreaves formula is used

Estimated reference evapotranspiration (ET o ) for Puerto Rico on June 29 th, 2010. ET a = K c ET o

Estimated reference evapotranspiration (ET o ) for Haiti and the Dominican Republic on June 29 th, 2010. Haiti ET a = K c ET o Dominican Republic

RESULTS Actual ET and the Water and Energy Budgets for PR An analysis was performed for a10 day period between June 20 and June 29, 2010. The soil moisture was adjusted daily based on the surface water balance Images are shown for June 29, 2010

Land Cover Land Use Map (Obtained from RAMS Surface Characteristics Dataset, http://bridge.atmet.org/users/data.php)

Land Cover Land Use Map (Obtained from RAMS Surface Characteristics Dataset, http://bridge.atmet.org/users/data.php) albedo emiss LAI vfrac zo zdisp rootdep LAND CLASS # 0.14 0.99 0 0 0 0.1 0 0 Ocean 0.14 0.99 0 0 0 0.1 0 1 Lakes rivers stre 0.4 0.82 0 0 0.01 0.1 0 2 Ice cap/glacier 0.1 0.97 6 0.8 1 15 1.5 3 Evergreen needlelea 0.1 0.95 6 0.8 1 20 1.5 4 Deciduous needlelea 0.2 0.95 6 0.8 0.8 15 2 5 Deciduous broadleaf 0.15 0.95 6 0.9 2 20 1.5 6 Evergreen broadleaf 0.26 0.96 2 0.8 0.02 0.2 1 7 Short grass 0.16 0.96 6 0.8 0.1 1 1 8 Tall grass 0.3 0.86 0 0 0.05 0.1 1 9 Desert 0.25 0.96 6 0.1 0.1 0.5 1 10 Semi-desert 0.2 0.95 6 0.6 0.04 0.1 1 11 Tundra 0.1 0.97 6 0.8 0.1 1 1 12 Evergreen shrub 0.2 0.97 6 0.8 0.1 1 1 13 Deciduous shrub 0.15 0.96 6 0.8 0.8 20 2 14 Mixed woodland 0.2 0.95 6 0.85 0.06 0.7 1 15 Crop/mixed farming 0.18 0.95 6 0.8 0.06 0.7 1 16 Irrigated crop 0.12 0.98 6 0.8 0.03 1 1 17 Bog or marsh 0.06 0.97 6 0.8 0.98 10.2 1 18 Evergreen needlelea 0.08 0.95 6 0.9 2.21 20.7 1.2 19 Evergreen broadleaf 0.06 0.95 6 0.8 0.92 9.2 1 20 Deciduous needlelea 0.09 0.95 6 0.8 0.91 7.2 1.2 21 Deciduous broadleaf 0.07 0.96 6 0.8 0.87 6.5 1.1 22 Mixed cover 0.08 0.96 5.7 0.8 0.83 7.4 1 23 Woodland 0.18 0.96 5 0.8 0.51 3.6 1 24 Wooded grassland 0.1 0.97 5.1 0.63 0.14 1.4 0.7 25 Closed shrubland 0.12 0.97 6 0.22 0.08 0.2 0.6 26 Open shrubland 0.11 0.96 2.6 0.73 0.04 0.2 0.7 27 Grassland 0.1 0.95 6 0.84 0.11 0.2 0.7 28 Cropland 0.16 0.86 0.7 0.07 0.05 0.2 0.5 29 Bare ground 0.15 0.9 4.8 0.74 0.8 1.1 0.8 30 Urban and built up

Average Surface Albedo for Puerto Rico

Percentages of sand, silt and clay for Puerto Rico were obtained from the Soil Survey Geographic (SSURGO) Database of the USDA Natural Resource Conservation Service (http://soils.usda.gov/survey/geography/ss urgo/). Sand Silt Clay

Values of field capacity and wilting point were obtained from regression equations based on percent sand, silt and clay presented by Cemek et al. (2004). Field Capacity Wilting Point

(Obtained from RAMS Surface Characteristics Dataset, http://bridge.atmet.org/users/data.php) Land Cover Zero Plane Displacement Surface Roughness

(Root depth obtained from RAMS Surface Characteristics Dataset, http://bridge.atmet.org/users/data.php) Root depth CN number

Puerto Rico Surface Elevation (m)

GOES-13 Integrated Daily Solar Radiation (MJ/m 2 /day) for Puerto Rico on June 29 th, 2010.

Estimated Average Air Temperature for PR on June 29 th, 2010 (Obtained using lapse rate approach of Goyal et al. (1988), adjusted with measured air temperatures)

Effective Surface Temperature for PR on June 29 th, 2010.

Wind Speed (m/s) for Puerto Rico on June 29 th, 2010 (National Weather Service s National Digital Forecast Database ).

NET Radiation (MJ/m 2 /day) for Puerto Rico on June 29th, 2010 (Eestimated from solar radiation using method presented by Allen et al., 1998)

Latent Heat Flux (MJ/m 2 /day) for Puerto Rico on June 29 th, 2010

Sensible Heat Flux (MJ/m 2 /day) for Puerto Rico on June 29 th, 2010

Bulk Surface Resistance (s/m) for Puerto Rico on June 29 th, 2010

Aerodynamic Resistance (s/m) for Puerto Rico on June 29 th, 2010

Bulk Surface Resistance + Aerodynamic Resistance (s/m) for Puerto Rico on June 29, 2010

Estimated Actual Evapotranspiration (ET a ) for Puerto Rico on June 29 th, 2010.

Estimate crop coefficient (K c ) over Puerto Rico on June 29, 2010.

Rainfall over Puerto Rico on June 29, 2010 (NOAA s Advance Hydrologic Prediction Services).

Estimated surface runoff in Puerto Rico on June 29, 2010.

Estimated deep percolation on June 29, 2010.

Estimated soil moisture in Puerto Rico on June 29, 2010.

Summary and Conclusions We describe a method for estimating reference evapotranspiration in Puerto Rico, Haiti and the Dominican Republic. Methods for estimating the actual evapotranspiration and the water and energy budgets over Puerto Rico were described. Estimates of reference evapotranspiration for June 29, 2010, were provided for Puerto Rico, Haiti and the Dominican Republic, Estimated actual evapotranspiration, surface runoff, deep percolation and soil moisture content for Puerto Rico for the same day were presented. Components of the energy balance were also presented.

Future Work Complete the actual ET and water balance algorithm for DR and Haiti Automate the calculation process, which will publish the daily results on a website each day. Provide archived tabular and graphical results, and statistics of these data (e.g., wet season aquifer recharge)

Acknowledgements Financial Support: USDA-Hatch (H-402) NOAA-CREST (NA17AE1625) NSF-CASA (NSF 0313747)