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Accueil du site → Projets de développement → Projets de recherche pour le Développement → 2020 → MULTI-SENSOR ESTIMATION OF DAILY ROOTZONE SOIL MOISTURE AT A FINE RESOLUTION FOR AGRICULTURAL REGIONS

United States Department of Agriculture (USDA) 2020


Estimation Sensor Moisture

United States Department of Agriculture (USDA) National Institute of Food and Agriculture


Identification : 1022589

Pays : Etats Unis

Durée : START : 01 JUL 2020 TERM : 30 JUN 2023

Efficient and sustainable agricultural production requires accurate knowledge of rootzone soil moisture (volumetric water content).Soil moisture provides the source of water for crop transpiration, so maintaining soil moisture within a controlled range is essential to ensure crop health and productivity. Soil moisture also influences soil evaporation, which represents a non-beneficial consumptive use of water and contributes to the salinization of farmlands. Soil moisture also affects groundwater recharge, which can mobilize metals and salts in a shallow unconfined aquifer (e.g., an irrigated alluvial valley) and ultimately degrade water quality in nearby streams.To be useful for such agricultural applications, soil moisture estimates must meet several key requirements. First, they must span large regions (e.g., 150 km by 150 km or larger) to benefit many stakeholders. Second, they must have a fine resolution (e.g., 30 m grid cells or finer) to differentiate the soil moisture conditions between and within individual fields. Third, the estimates must characterize the soil moisture throughout the rootzone to relate directly to crop health and productivity. Fourth, the estimates must be accurate enough to distinguish between water-stressed and unstressed crops and facilitate irrigation decisions. Fifth, the estimates must be available nearly daily to facilitate prompt decisions.Unfortunately, no existing technology estimates soil moisture in a way that meets all the practical requirements for agricultural applications. Various in-situ probes (such as neutron probes, time-domain reflectometers (TDRs), and Hydra Probes) are available to measure soil moisture, but they only sense the moisture within centimeters of the probe, so they remain impractical for characterizing soil moisture over large agricultural regions. Cosmic ray sensors can characterize the soil moisture over larger footprints ( 600 m diameter), but they are too expensive to provide complete spatial and temporal coverage throughout large agricultural regions. Several active/passive microwave satellites, such as Soil Moisture Active Passive (SMAP), provide reliable soil moisture estimates for nearly the entire globe at a daily time step. However, these satellites only sense the moisture in the top 10 cm of the soil, while crop productivity depends on the moisture throughout the entire rootzone (top 40 cm or more).In addition, the spatial resolution of active/passive microwave estimates (9 km grid cells or larger) is much too coarse to identify moisture differences within or between fields. Alternatively, several remote-sensing methods have been proposed to estimate soil moisture based on optical/thermal satellite data. These methods estimate the soil moisture over the entire rootzone and can be produced nearly globally at a fine enough resolution for agricultural purposes (30 m grid cells if using the Landsat satellites). However, they are only available every 16 days (for Landsat), which reduces their value for decision making. Optical/thermal data from MODIS can be used to produce more frequent images, but those images have a much coarser resolution. Furthermore, optical/thermal sensors only provide reliable data for cloud-free conditions.The objective of this project is to develop and test a method that estimates daily rootzone soil moisture at a fine resolution by fusing active/passive microwave and optical/thermal estimates. If successful, the soil moisture estimates would span large regions, have a fine resolution, characterize the entire rootzone, have sufficient accuracy, and be available daily. Thus, they would meet all the key requirements for agricultural applications

Performing Institution : COLORADO STATE UNIVERSITY
Investigator : Niemann, J.

Présentation : USDA (NIFA)

Page publiée le 27 novembre 2021