Water and Energy Balance Model GOES-PRWEB: Development and Validation

Abstract

In 2009, the University of Alabama-Huntsville configured their GOES satellited-based solar radiation product to include Puerto Rico, the US Virgin Islands (USVI), Dominican Republic, Haiti, Jamaica, and Cuba. The half-hourly and daily integrated data are available at 1 km resolution for Puerto Rico and the USVI and 2 km for Hispaniola, Jamaica, and Cuba. These data made it possible to implement estimates of satellite radiation-based evapotranspiration methods on all of the islands. The use of the solar radiation data in combination with estimates of other climate parameters facilitated the development of a water and energy balance algorithm for Puerto Rico. The purpose of this paper is to describe the theoretical background and technical approach for estimating the components of the daily water and energy balance. The operational water and energy bal-ance model is the first of its kind in Puerto Rico. Model validation results are presented for reference and actual evapotranspiration, soil moisture, and streamflow. Mean errors for all analyses were less than 7%. The water and energy balance model results can benefit such diverse fields as agriculture, ecology, coastal water management, human health, renewable energy development, water resources, drought monitoring, and disaster and emergency management. This research represents a preliminary step in developing a suite of gridded hydro-climate products for the Caribbean Region.

Hydrology in the Caribbean Basin

“…The article Water and Energy Balance Model GOES-PRWEB: Development and Validation [10], by Eric Harmsen, John Mecikalski, Victor Raventos, Estefania Perez, Sopuruchi Uwakweh, and Christie Garcia, introduces the creation of a data service that uses the GOES solar radiation and other parameters to compute radiation-based evapotranspiration methods. The authors describe the theoretical background and technical approach to estimating the daily water and energy balance components.…”

Resilience of an Urban Coastal Ecosystem in the Caribbean: A Remote Sensing Approach in Western Puerto Rico

“…The integration of remote sensing techniques, climate models, and land surface models into ET numerical simulations has led to the development of diverse global and regional ET products [11,12]. These products can be categorized into three primary groups based on their method of estimation: (a) interpolation using field measurements and machine learning techniques [13]; (b) simulation through remotely sensed ET models, such as MODIS [14], and (c) reanalysis data and products assimilated using various land surface models [15]. This integration of advanced technologies and modeling approaches enhances our ability to understand and quantify ET dynamics across different spatial and temporal scales.…”

“…A study regarding ET estimation was conducted in Puerto Rico. Geostationary Operational Environmental Satellite-Puerto Rico Water and Energy Balance (GOES-PRWEB) is a product with a 1 km image resolution that provides us with additional data on actual ET estimation [15]. GOES-PRWEB is also based on the Penman-Monteith (PM) equation.…”

“…Furthermore, additional calculations are necessary to be able to compare data sets. GOES-PRWEB's previous study suggested that ET values were underestimated [15]. Another study in Northeastern Brazil-a tropical region as well-used remote sensing technology to assess land degradation and drought impacts over terrestrial ecosystems based on water and carbon fluxes, i.e., MOD16A2 and MOD17A2 to estimate ET and gross primary production (GPP), respectively [16].…”

Uniplanar multirod TDR probe for soil water content measurement over a larger spatial scale

“…Soil water data are essential for understanding many land surface processes, such as the water, energy and carbon cycles of the earth system (Bai et al, 2019; Fisher & Koven, 2020; Harmsen et al, 2021; Rasheed et al, 2022; Tavakol et al, 2021). It is an important ecohydrological parameter for many modelling applications related to energy balance, such as numerical weather forecasting, climate prediction, radiative transfer modelling, global change modelling and satellite data validation (Njoku et al, 2003; Owe et al, 2008; Zhang et al, 2022).…”