Location: Hydrology and Remote Sensing Laboratory2017 Annual Report
Objective 1: Develop and verify new observational tools (both remote sensing- and ground observation-based) and scaling techniques for characterizing water balance components, from plot (~10 m) to regional scales (~100 km). Objective 2: Develop remote sensing and modeling approaches for monitoring the magnitude of agricultural drought and its subsequent impact on agricultural crop condition and yield. Objective 3: Develop remote sensing and modeling approaches for characterizing the multi-scale impacts of conservation practices on water quality variables.
Ground measurements, remote sensing observations, and modeling each provide a partial description of hydrologic variables required at different spatial scales for agricultural applications. This project seeks to integrate these various sources of information into true multi-scale assessments and leverage their mutual strengths.
This is the final report for 8042-13610-028-00D. A number of significant milestones were reached in this project. For example, a rigorous validation was completed for the primary soil moisture product obtained from the NASA Soil Moisture Active/Passive (SMAP) mission. Likewise, a new suite of enhanced resolution SMAP soil moisture products were developed and validated. These products provide improved temporal and spatial resolution and enhance the value of SMAP soil moisture data products for agricultural applications requiring high-resolution soil moisture data. SMAP soil moisture data products were also successfully integrated into the USDA Foreign Agricultural Services (FAS) global drought monitoring system and demonstrated to improve the ability of FAS to anticipate region-scale variability in commodity crop production. Finally, the project demonstrated that SMAP soil moisture products provide a better description of pre-storm soil saturation conditions than other existing soil moisture products within the United States. As a result, its incorporation into operational stream flow forecasting systems is expected to significantly enhance the monitoring of flash flood risk in agricultural regions. These advances in soil moisture remote sensing were complemented by analogous advances in multi-scale surface evapotranspiration (ET) products. The first microwave-based global ET product was developed, validated, and compared to a thermal infrared (TIR) ET product. This new product provides improves all-weather coverage and supports the key project goal of integrating microwave and TIR remote sensing for agricultural drought monitoring. Advances in TIR-based products focused primarily on the development of a multi-scale tool which fuses remote sensing observations acquired from multiple satellite platforms to produce ET estimates at a daily time scale and a 30-m resolution. Obtaining ET estimates at such a fine time/space resolution represents an important breakthrough in the routine remote sensing of ET for field-scale agricultural applications. These methods were used to develop multi-scale modeling system for generating ET estimates to improve water use efficiency in operational vineyard irrigation systems. For example, the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) project, collected micrometeorogical, biophysical and remote sensing data in adjacent vineyards at different levels of maturity near Lodi, CA from 2013 to 2016. The aim of GRAPEX is to combine in-situ and remotely-sensed data to investigate the effects of canopy structure and row orientation on energy and water exchange processes both within and above the vine canopy. Using these ground observations, the remote sensing model was evaluated and refined to improve ET estimates for highly-structured canopies such as vineyards, as well as the ability to separate vine water use from evaporation from the inter-row cover crop. In addition to the characterization of water quantity variables, significant progress was also made in terms of our ability to characterize basin-scale water quality impacts of field- and farm-scale conservation practices. In particular, a key project goal is the evaluation of winter cover crop (WCC) performance as a best management practice for maximizing water quality. Using the Soil and Water Assessment Tool (or SWAT) model, land use and soil characteristics were identified as having the strongest impact on water and nutrient transport mechanisms and pathways which determine the effectiveness of WCCs within the Chesapeake Bay Watershed. This work was paired with the development of remote sensing maps for the regional-scale mapping of WCCs and the successful demonstration of these maps for the detection of wintertime vegetative cover crops. This capacity to monitor wide-scale conservation practice implementation enhances the ability of watershed managers to achieve environmental outcomes required for restoration of the Chesapeake Bay ecosystem.
1. A multi-scale data fusion remote sensing toolkit for daily evapotranspiration (ET). A fundamental requirement for effective agricultural water management is acquiring the means to accurately measure crop water use at appropriate temporal and spatial scales. To address this need, ARS scientists in Beltsville, Maryland, have developed and distributed a novel evapotranspiration (ET) mapping toolkit based on the fusion of remote sensing observations obtained from multiple satellite platforms. The fusion allows for the production of daily crop water use estimates at an unprecedented 30-m spatial resolution. Due to its significant resolution advantages, the toolkit has already been used to address many water resource issues in agriculture, including: groundwater depletion via irrigation in Central Wisconsin (Wisconsin-Department of Natural Resources, University of Wisconsin), the impact of expanding agricultural drainage on regional hydrology in the Corn Belt (U.S. Geological Survey; USGS), water use in managed forest plantations (U.S. Forest Service, Virginia Polytechnic Institute and State University), calibration of hydrologic/water quality models for the Chesapeake Bay Watershed (ARS, University of Maryland), irrigation management decision making in vineyards (in collaboration with E&J Gallo), consumptive use assessments for the U.S. Water Census and California’s new Sustainable Groundwater Management Act (USGS, University of California-Davis), and drought and water information delivery for the Near-East North African region (Daugherty Water for Food Institute and U.S. Agency for International Development). The toolkit will also be used to generate ET and water stress products for NASA’s ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission. Through these projects, this ET mapping tool has greatly expanded our ability to monitor, and therefore optimize, water use and availability across a broad range of agricultural systems.
2. Dating and tracking agricultural nitrogen. Determining the age of nitrate in groundwater and stream networks is critical for assessing the effectiveness of conservation practices designed to reduce off-site nitrogen pollution from farms. ARS scientists in Beltsville, Maryland, have demonstrated how Metolachlor ethane sulfonic acid (MESA), a commonly used crop herbicide, can be used to measure the mean residence time of groundwater and surface water and provide an age estimate for dissolved agricultural nitrogen. This age estimate gives scientists important new information about watershed residence times and how nutrients are being transported off fields and into streams and rivers. In particular, the approach can be applied to assess the effectiveness of field and farm-scale conservation practices for reducing agricultural nitrogen pollution. This approach has substantial advantages over other water dating methods because it can be applied to both surface and groundwater samples while previous techniques did not allow the water sample to be exposed to the open atmosphere.
3. The Soil Moisture Active/Passive Validation Experiment in 2016 (SMAPVEX16). ARS scientists in Beltsville, Maryland, contributed to an international validation experiment for the NASA Soil Moisture Active/Passive (SMAP) satellite mission in the Red River Basin of the Northern Plains that was completed in 2016. The satellite mission is the first mission to use both active and passive L-band sensors to monitor surface soil moisture at a high resolution. A ground and aircraft validation campaign was conducted in and around the South Fork Experimental Watershed near Iowa City, Iowa and the Carman Study region near Winnipeg, Ontario to provide a valuable ground truth dataset to verify the accuracy of the mission product. This was conducted from May 2016 to August of 2016, providing a range of conditions for a critical agricultural region and the results of this experiment are providing datasets for the revision of algorithms for monitoring soil moisture in row crop domains, such as the central and northern plains of the United States. This will ultimately improve the understanding of climate and weather dynamics in a drought-prone region of significant interest to the USDA.
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Wigneron, J., Jackson, T.J., O'Neill, P., De Jeu, R., De Rosnay, P., Walker, J., Ferrazoli, P., Mirnov, V., Bircher, S., Grant, J., Kurum, M., Schwank, M., Levine, D., Das, N., Royer, A., Al-Yarri, A., Bitar, A., Fernandez-Moran, R., Lawrence, H., Mialon, A. 2017. Modelling the passive microwave signature from land surfaces: a review of recent results and application to the SMOS & SMAP soil moisture retrieval algorithms. Remote Sensing of Environment. 192:238-262.