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PR-SMART - Puerto Rico Soil Moisture Advance Radiometric Test-Bed

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Mapping field-scale soil moisture using ground-based L-band passive microwave observations in Western Puerto Rico


 

About

 

The Project

 
 
 

Ground-based L-band passive microwave observations are needed to validate the accuracy in the measurements made by satellite-based radiometers such as the NASA’s Soil Moisture Active Passive (SMAP) mission. Field observations were made at three Agricultural Experimental Stations (Isabela, Lajas, and Mayagüez) in Western Puerto Rico using an L-band (1.48GHz) microwave radiometer observation unit. Measurements of brightness temperature, temperature, humidity, and volumetric water content of the soil were performed in multiple parts of each field to cover a wide variety of soil conditions, crop types and crop densities. This work presents early results and preliminary soil moisture simulation using the Tau-Omega Radiation transfer model. Future work, includes validation of SMAP and GCOM-W soil moisture products.

 
 

Scope and Objectives

 
 

This project will provide new information related to soil and vegetation parameters by performing ground measurements of soil moisture content from L-band passive microwave observations. These parameters influence the readings of the L-Band Microwave Radiometers Satellite and will be useful for the calibration and validation of the data provided by the NASA Soil Moisture Active Passive (SMAP) mission. Also, more accurate readings of soil moisture content in the western area of Puerto Rico are to be provided. These results will help the characterization and modeling of spatial characteristics of soil moisture over Puerto Rico soils, which are highly representative of the soils in the tropics.

 
 

The Sites

 
 

Isabela Agricultural Experiment Station is located in the north-western region of Puerto Rico (18°27'46"N 67°02'05"W)

The total area is about 296 acre (1.12 sqr km)

The annual average precipitation is around 65.0 inches (165.1 cm)

The average temperature ranges from 88°F to 66°F (31.1°C to 18.9°C)

Predominant soils: Coto (Cu) and Cotito (Ct)



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Lajas Agricultural Experiment Station is located in the south-western region of Puerto Rico (18°01'55"N 67°04'23"W)

The total area is about 361 acres (1.46 sqr km)

The annual average precipitation is around 39.1 inches (99.3 cm)

The average temperature ranges from 87°F to 64°F (30.6°C to 17.8°C)

Predominant soils: Fraternidad (Fr) and Cartagena (Ce)


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Mayagüez Agricultural Experiment Station is located in the south-western region of Puerto Rico (18°12'32"N 67°08'17"W)

The total area is about 52 acres (0.21 sqr km)

The annual average precipitation is around 54.0 inches (137.16 cm)

The average temperature ranges from 80°F to 55°F (26°C to 13°C)

Predominant soils: Daguey (Da), Consumo (Co)


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Expected Results

 

 

Significance of the Research

 
 

The availability of accurate and representative soil moisture content data can have a significant impact on environmental aspects such as:

 
 
  • Droughts - Having a continuous monitoring system for soil moisture will enhance the models which are used to determine potential water shortage and drought events, which is strongly useful for agricultural development.
  • Floods - The surface soil moisture state is highly related to the partitioning of precipitation into infiltration and runoff, which are key variables for flood prediction modeling.
  • Once calibrated and validated, soil moisture measurements will provide reliable information on availability of water and environmental stress for estimating productivity and potential yield of plants.
  • Accurate soil moisture data enhances the results provided by numerical weather prediction and seasonal climate models. These improvements are of great benefit to climate-sensitive socioeconomic activities.
  • Droughts - Having a continuous monitoring system for soil moisture will enhance the models which are used to determine potential water shortage and drought events, which is strongly useful for agricultural development.
  • Floods - The surface soil moisture state is highly related to the partitioning of precipitation into infiltration and runoff, which are key variables for flood prediction modeling.