2008 Annual Report
1a.Objectives (from AD-416)
Develop new remote sensing, modeling and data assimilation techniques to improve the monitoring of hydrologic fluxes and agricultural pollutant pathways at the field, watershed and regional scale.
1b.Approach (from AD-416)
Effective management of these watersheds requires detailed process-level understanding concerning the complex hydrologic and constitutive flux pathways that govern: the availability of root-zone soil moisture, the delivery of agricultural pollutants to surface water bodies and feedbacks operating along the soil-plant-atmosphere continuum. The inability to measure the relative magnitude of these pathways hampers the development of effective water management strategies at watershed- and regional-scales. This project attempts to develop novel remote sensing and modeling tools to better characterize key hydrologic and constitutive flux pathways operating within agricultural watersheds. An overarching theme of the project is that the integration of remote sensing products into models can enhance the utility of models for critical agricultural applications.
This project attempts to develop novel remote sensing and modeling tools to better characterize key hydrologic and constitutive flux pathways operating within agricultural watersheds. An overarching theme of the project is that the integration of remote sensing products into models can enhance the utility of models for critical agricultural applications. Early portions (2007 to 2009) of the project plan focus on the development and implementation of modeling and/or remote sensing techniques in isolation. A number of (successfully completed) 2008 milestones involved the early implementation and/or calibration of key modeling approaches including the Soil Water Assessment Tool (SWAT), the Annualized AGricultural Non-Point Source (AnnAGNPS), the Atmosphere-Land Exchange (ALEXI) model and a large-eddy simulation (LES) models. In parallel, remote sensing activities focused on the refinement of techniques for detecting soil and canopy moisture contents, the collection of spectral dataset information in arid ecosystems, the development of a nitrogen sequestration algorithm for winter cover crops and a novel resolution sharpening technique to improve the spatial resolution of surface energy flux retrievals. These accomplishments address NP211 Problem Areas I Effectiveness of Conservation Practices, II Irrigation and Water Management, and IV Watershed Management, Water Availability, and Ecosystem Restoration. The ongoing delivery of remotely-sensed corn and soybean yield information to the National Agriculture Statistics Service (NASS) was also continued. In anticipation of > 2010 project milestones focused on the multi-scale merging of modeling and remote sensing activities, 2008 research also focused on describing spatial scaling patterns found in ground-based soil moisture observations and the development of novel data assimilation techniques to ingest remote sensing observations into land surface models. All 2008 research milestones have been either “fully met” of “substantially met.” The project research team is on track to reach future project milestones without substantial modification to the approved research plan.
Measuring the effectiveness of winter cover crops on the Maryland's Eastern Shore with Remote Sensing:
We have continued to develop and evaluate an innovative methodology that combines farm program records, satellite remote sensing, and on-farm sampling to calculate the amount of nitrogen sequestered in cover crop biomass on farms enrolled in state cover crop cost share programs within the Choptank and Chester River watershed, increasing our sample size to over 1400 fields per year. Results were transferred to the Chesapeake Bay Program, assisting in the development of efficiency estimates for various cover crop scenarios. Additionally, on-farm field experiments have been planned and funded (Targeted Watersheds Grant) for implementation in the fall of 2008. These experiments will evaluate the effect of reduced fall fertilization on wheat yield and soil nitrate leaching, with implications for setting appropriate incentive rates for commodity cover crops (non-fertilized fall grains). This work addresses the Effectiveness of Conservation Practices problem area of NP 211 (Water Availability and Watershed Management).
Completion of cloud and land surface interaction Campaign 2007:
As a part of the Department of Energy, Atmospheric and Radiation Measurement program, the Cloud and Land Surface Interaction Campaign was conducted in June of 2007 to collect soil moisture and land cover information to complement the extensive energy flux and meteorological information collected by other researchers. Land cover and vegetation water content information was collected and used to generate critical parameters for modeling and interpreting the numerous remote sensing datasets. This work will lead ultimately to a better understanding of cloud development within the Southern Great Plains, which is a critical area for agriculture. This work addresses the Watershed Management, Water Availability, and Ecosystem Restoration problem area of NP 211 (Water Availability and Watershed Management).
Evaluation of a remote sensing approach to estimate county and state yields for corn and soybean crops:
A 5-year database (2002-07) of MODIS TERRA imagery was compiled and validated. The surface reflectance data was reprocessed using data filters to remove errors due to cloud cover and data acquisition issues. The algorithm for the disaggregation of NASS state yields using only MODIS imagery was tested for the Iowa, Illinois and Indiana. County level corn and soybean yield were produced at the end of the 2007 crop season based on a regression analyses of the past six years of NASS reported yields. These results were provided to the NASS for potential use in their operational applications. This work addresses the Watershed Management, Water Availability, and Ecosystem Restoration problem area of NP 211 (Water Availability and Watershed Management).
Field observations of soil moisture variability across scales:
Numerous studies have suggested that the realistic representation of spatial variability of surface soil moisture content can improve the predictive skill of hydrologic, weather prediction, and general circulation models, including processes such as evapotranspiration and runoff, precipitation, and atmospheric variability. In this study, soil moisture variability with respect to both spatial scale and field-mean moisture content was characterized. More than 36,000 ground-based measurements of soil moisture collected during field experiments spanning seven years were combined and analyzed to infer the statistical behavior of soil moisture variations at six distinct spatial scales and across a range of wetness conditions. Empirical relationships between soil moisture variations and mean moisture content were derived across scales. Such relationships can be used to estimate the uncertainty in field observations of mean moisture content. Moreover, the work described here can provide insight into improving the parameterization of surface soil moisture variations in land surface models. The results will contribute not only to efficient and reliable satellite validation, but also to better utilization of remotely sensed soil moisture products for enhanced modeling and prediction. This work addresses the Watershed Management, Water Availability, and Ecosystem Restoration problem area of NP 211 (Water Availability and Watershed Management).
Developing a remote sensing-based thermal sharpening technique for monitoring evapotranspiration for rain fed and irrigated agriculture landscapes: There has been a major effort to develop surface energy balance models for deriving distributed evapotranspiration (ET) maps over landscapes by using remote sensing imagery in the visible–near-infrared (VIS/NIR) providing fractional canopy cover, and thermal infrared (TIR) bands for estimating land surface temperature (LST). For water management applications and other agricultural purposes, ET maps would be optimally produce daily at high spatial resolution (<100 m). For daily coverage, the Moderate Resolution Imaging Spectrometer (MODIS) is available. A strategy that utilizes the functional relationship between the spaceborne-derived land surface temperature and vegetation indices to sharpen 1-km MODIS TIR imagery to the resolution of the MODIS VIS/NIR bands (250m), deriving near daily ET is proposed. A Two-Source Model (TSM) of surface energy balance was used to derive field-scale resolution ET maps using TIR data at different spatial resolutions. The utility of TsHARP for TSM flux evaluations was examined over two agricultural regions: a rain fed area in Iowa, and an irrigated agricultural area in the Texas High Plains. It is concluded that TsHARP provides an important tool for routine monitoring ET over rain fed agricultural areas. In contrast, over irrigated regions, TsHARP applied to kilometer-resolution TIR imagery is unable to provide accurate fine resolution LST due to sub-pixel moisture variations. Reliable estimation of ET and crop stress requires thermal imagery acquired at high spatial resolution or a more sophisticated technique in order to resolve the dominant length-scales of moisture variability. This research addresses the Irrigation Water Management and Watershed Management, Water Availability, and Ecosystem Restoration problem areas of the NP 211 (Water Availability and Watershed Management).
Application of the AnnAGNPS Model at the Choptank Watershed:
A primary goal of CEAP program during the initial five-year period is to assess and quantify the environmental benefits of Agricultural Conservation Practices (ACPs) at both the CEAP Benchmark and Special Emphasis watersheds using water quality models. Studies are being underway at the Choptank River Watershed in Maryland to assess the effectiveness of ACPs such as cover crops & control drainage structures in protecting water quality using the Annualized AGricultural Non-Point Source (AnnAGNPS) model. Fifteen sub-basins within the non-tidal zone of the Choptank watershed were selected for this model comparison. Five years of published Maryland Department of Environment (MDE) database has been used to both models testing and validations. Preliminary model simulations revealed significant nitrogen load reductions as a result of increased in cover crop acreage. With the increased in cover crops implementations from 40 to 70 percent, the AnnAGNPS simulations showed nearly 58% N reduction. Whether or not this large amount of N load reductions is realistic is a question for our future modeling efforts. The ultimate goal, however, is to use the well-tested and validated AnnAGNPS model, as a management tool, for both scenario evaluations as well as the assessment of the effectiveness of ACPs in reducing nutrient loads into the Choptank River and ultimately the Chesapeake Bay watershed. This work addresses the Effectiveness of Conservation Practices problem area of NP 211 (Water Availability and Watershed Management).
Successful completion of the Soil Moisture Experiments in 2003 (SMEX03) Data Archive:
Begun in 2003, the Soil Moisture experiments in 2003 (SMEX03) was conducted in Oklahoma, Georgia, Alabama, and Brazil during June, July, and November. Satellite, aircraft, and ground based sampling was coordinated among numerous federal and international agencies, and universities to produce a large in scope soil moisture data set for various regimes to validate the Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture data products. This dataset will be used to compare to soil moisture retrieval algorithms from existing satellites and ground measurements. This work addresses the Watershed Management, Water Availability, and Ecosystem Restoration problem area of NP 211 (Water Availability and Watershed Management).
Assessment of controls on nitrogen export from a first-order watershed:
Some pollutants, particularly nitrate, are predominantly transmitted through ground water and riparian buffer zones have the potential to remove contaminants from ground water and reduce the amount of nitrate that enters surface water providing justification for setting aside vegetated buffer strips along waterways. To assess effectiveness of the riparian buffer for removing nitrate, we assessed temporal and spatial variability of stream nitrate in a well gauged first-order stream over a five year period which varied considerably in hydrologic condition. Over this 5-year study, most of the nitrate exported during base flow originated from a critical area comprising less than 10% of the total riparian zone land area and base-flow generation was highly variable (spatially and temporally) with average base-flow nitrate loads greater in winter than summer, and higher during a wetter year than in dryer years. This research indicates that site specific management of riparian buffers would be the most cost effective mitigation strategy to reduce nitrogen export. This work addresses the Effectiveness of Conservation Practices problem area of NP 211 (Water Availability and Watershed Management).
Development of an adaptive data assimilation system for remotely-sensed land variables:
Data assimilation systems provide a powerful tool for merging land surface information gleaned from a variety of sources (e.g. modeling and remote sensing) into a single enhanced estimate of a given land surface variable (e.g. root-zone soil moisture, stream flow or evapotranspiration). Such systems typically require detailed information concerning the uncertainty of both model and remote sensing-based land variable estimates in order to function in an optimal manner. In practice such detailed error information is almost never available for agricultural landscapes. As a result, most operational applications of land data assimilation techniques are run in a sub-optimal manner. To address this issue, a novel adaptive data assimilation approach has been developed and tested which provides accurate estimates of modeling and remote sensing uncertainty during the on-line assimilation of remotely-sensed soil moisture information into a land surface model. Such an approach has great potential benefit for enhancing the value of remote sensing retrievals for key agricultural applications including the monitoring of root-zone water availability for irrigation scheduling and the enhanced initialization of numerical weather prediction models for improved precipitation forecasting. This work addresses the Watershed Management, Water Availability, and Ecosystem Restoration problem area of NP 211 (Water Availability and Watershed Management).
Remote sensing of canopy vegetation water content:
Water in vegetation reduces the sensitivity of microwave sensors for measurement of soil moisture content, so if remote sensing methods could be developed for vegetation water content, soil moisture will be determined more accurately. ARS scientists in Beltsville, MD in collaboration with George Mason University, University of California – Davis, and NASA Ames Research Center developed algorithms for the estimation of vegetation water content based on allometric equations and multispectral remote sensing. This algorithm could be implemented with polar-orbiting meteorological satellites for the new NASA mission, Soil Moisture Active Passive. This work addresses the Watershed Management, Water Availability, and Ecosystem Restoration problem area of NP 211 (Water Availability and Watershed Management).
Soil Moisture Influences on the North American Monsoon System:
Land surface antecedent boundary conditions may control the onset and intensity of the summer monsoon rainfall (North American Monsoon System) in the southwestern U.S. and northern Mexico. Increased soil moisture after precipitation promotes evapotranspiration between storm events, which may contribute to enhanced convection and further precipitation, all of which influence agriculture throughout the western U.S. Soil Moisture Experiments 2004 (SMEX04) addressed the goal of studying these processes using ground based and remotely sensed observations. Accomplishments included soil moisture network validation, the spatial scaling and temporal variability of surface soil moisture for large footprint validation in mountainous terrain, the scaling of tower fluxes and the effect of remote sensing spatial resolution on land surface models, using remote sensing to determine the spatial and temporal patterns of vegetation water content, aircraft-based microwave remote sensing of soil moisture, broader issues of modeling root-zone soil moisture using data assimilation and characterizing the land surface water cycle within the region with a multi-sensor approach. It is anticipated, that the results of the investigation will provide valuable input parameters for coupled land-atmosphere models used to investigate the importance of surface parameterization. The improved parameterization may lead to more accurate predictions of annual water supplies in the western U.S., which will impact agricultural management and productivity. This work addresses the Watershed Management, Water Availability, and Ecosystem Restoration problem area of NP 211 (Water Availability and Watershed Management).
Quantification of subsurface flow processes at the field scale:
In theory preferential and matrix flow processes govern transit times of pollutants to groundwater as well as their travel time off-site to ecosystems neighboring agricultural land. Unfortunately, the relative impact of these processes, especially at the field scale is poorly understood and still in its infancy. To more accurately quantify subsurface travel times of agrochemicals, ground-penetrating radar was collected and analyzed and subsequently used to locate nested monitoring wells. Each well samples up to three different depths and are equipped with specific ion electrodes and ports for small water sample collections. Pressure transducers were also installed for monitoring the spatial aspect of water table heights. Preliminary experiments support the thought that although matrix and preferential flow processes occur simultaneously they each dominate transport over different spatial locations. As a result, if water quality models are to eventually predict chemicals transit times they must have the capacity for accurately describing both matrix and preferential flow processes as well as how these processes interact spatially and temporally. This work addresses the Watershed Management, Water Availability, and Ecosystem Restoration problem area of NP 211 (Water Availability and Watershed Management).
Using a Large Eddy Simulation model with remote sensing to accounting for variability in air properties and the impact on spatially distributed fluxes:
Land surface fluxes are affected by variability in land surface properties (soil texture and land cover) and states (soil moisture and surface temperature) as well as overlying atmospheric conditions. The Large Eddy Simulation (LES) model simulates the turbulent exchange of heat, water vapor and momentum (wind energy) between the land surface and lower atmosphere and considers the two-way interaction between land surface variability and the lower atmosphere. The LES has been fully coupled with remote sensing-based land surface model and validated applied to agricultural study regions in the Texas High Plains, Southern Great Plains, and the Desert Southwest. Analyses over several different agricultural landscapes indicate the strength of surface contrasts in surface temperature, canopy cover and moisture has a significant affect on surface-air coupling and resulting spatial distribution of near-surface air properties (wind speed, air temperature and humidity). This in turn has a significant impact on flux computations since typically land surface models assume uniform atmospheric properties over the landscape. For agriculture, this relates directly to techniques estimating water use and monitoring crop yield from field to regional scales. This work addresses the Watershed Management, Water Availability, and Ecosystem Restoration problem area of NP 211 (Water Availability and Watershed Management).
Detection of noxious invasive weeds by remote sensing:
Worldwide, invasive plants cause billions of dollars worth of damage annually. Saltcedar is an invasive shrub taking over streams and riparian areas in the western United States, and is starting to invade the San Pedro River Valley in Arizona. ARS scientists in Beltsville, MD in collaboration with the University of Arizona and University of California – Davis showed that salt cedar did not have sufficient spectral differences from native vegetation in the summertime for detection by hyperspectral remote sensing. This negative result is significant because it indicates that a methodology developed by ARS scientists can be used to determine a priority which species can be detected by remote sensing. This work addresses the Watershed Management, Water Availability, and Ecosystem Restoration problem area of NP 211 (Water Availability and Watershed Management).
In situ reflectance measurements of semiarid rangelands:
Changing patterns of vegetation on semiarid rangelands leads to different energy and water balances. Ten years of in situ reflectance measurement with an ASD Spectroradiometer have been compiled and showed differences in reflectance between grass and shrub vegetation. Understanding reflectance patterns as vegetation patterns change will allow improved understanding of heat and moisture balances in semiarid rangelands. This work relates to Watershed Management, Water Availability, and Ecosystem Restoration problem area of NP 211 (Water Availability and Watershed Management).
Wetland hydrologic assessment using radar remote sensing:
Wetlands have the potential to remove agrochemicals before they enter streams and contribute to the poor health of estuaries, like the Chesapeake Bay. However, the majority of wetlands in the Chesapeake Bay Watershed are forested, and this type of wetland is difficult to map and monitor using existing methodologies. We have developed a new methodology to map forested wetland hydrology at a watershed scale using satellite-borne radar data. Forested wetland hydrology maps produced using radar data were found to be well correlated with in situ measurements of soil moisture and inundation. Next generation wetland maps, produced using radar, will improve water quality management by helping to better understand the fate of select agrochemicals and sediment, thus improving the health of the Chesapeake Bay. This work addresses the Effectiveness of Conservation Practices problem area of NP 211 (Water Availability and Watershed Management).
Using thermal remote sensing to monitor evaporation and soil moisture stress in vegetation:
The ability to map evapotranspiration (ET) and moisture availability via satellite has broad applications: in monitoring drought and consumptive water use, administering irrigation projects, predicting local and regional water demand, and in providing important boundary conditions to hydrological and weather forecast models. Land-surface temperature (LST) derived from remote-sensing data in the thermal-infrared waveband is a valuable diagnostic of biospheric stress resulting from soil moisture deficiencies. A thermal remote sensing model of Atmosphere-Land Exchange (ALEXI) and associated flux disaggregation technique (DisALEXI) has been applied to areas surrounding flux towers from the AmeriFlux network, sampling a range in climatic and vegetation cover conditions in agricultural landscapes, grasslands, forests, and semi-arid deserts. The model was executed using local observations at targeted sites and output was compared to micrometeorological flux data. The model reproduced observed ET rates to within 10% at an hourly time step. These local-scale assessments facilitated identification of important improvements required in the regional-scale modeling framework. The ultimate goal is a real-time, satellite-based daily ET and drought product covering the contiguous U.S. This research addresses the Irrigation Water Management and Watershed Management, Water Availability, and Ecosystem Restoration problem areas of the NP 211 (Water Availability and Watershed Management).
5.Significant Activities that Support Special Target Populations
One project team member sits on the Technical Advisory Committee for the Center for Hydrologic Remote Sensing at Alabama A&M University.
|Number of Non-Peer Reviewed Presentations and Proceedings||6|
Crow, W.T., Zhan, X. 2007. Continental-scale evaluation of remotely sensed soil moisture products. Geoscience and Remote Sensing Letters. 4(3):451-455.
Jackson, T.J., Moran, M.S., O'Neill, P.E. 2008. Introduction to Soil Moisture Experiments 2007 (SMEX04). Remote Sensing of Environment. 112:301-303.
Li, F., Kustas, W.P., Anderson, M.C., Prueger, J.H., Scott, R.L. 2008. Effect of remote sensing spatial resolution on interpreting tower based flux observations. Remote Sensing of Environment. 112:337-349.
Doraiswamy, P.C., Akhmedov, B., Beard, L., Stern, A.J., Mueller, R. 2007. Operational prediction of crop yields using MODIS data and products. In: Chen, J., Saunders, S.C., Brosofske, K.D. and Crow, T.R. editors. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences Special Publications, Commission Working Group VIII WG VIII/10, European Commision DG JRC-Institute for the Protection and Security of the Citizen, Ispra, Italy. p. 1-5.
Yilmaz, M.T., Hunt, E.R., Goins, L.D., Ustin, S.L., Vanderbilt, V.C., Jackson, T.J. 2008. Vegetation water content during SMEX04 from ground data and Landsat 5 Thermatic Mapper Imagery. Remote Sensing of Environment. 112:350-362.
Ryu, D., Jackson, T., Bindlish, R., LeVine, D. 2007. L-Band microwave observations over land surface using a two-dimensional synthetic aperture radiometer. Geophysical Research Letters. 34, L14401, http://dx.doi.org/10.1029/2007GL030098.
Sanchez, J., Kustas, W.P., Caselles, V., Anderson, M.C. 2008. Modelling surface energy fluxes over maize using a two-source patch model and radiometric soil canopy temperature observations. Remote Sensing of Environment. 112:1130-1143.
Sharif, H., Crow, W.T., Miller, N., Wood, E. 2007. Multi-decadal high-resolution hydrologic modeling of the Arkansas/Red River Basin. Journal of Hydrometeorology. 8(5):1111-1127.
Yilmaz, M.T., Hunt, E.R., Jackson, T.J. 2008. Remote sensing of vegetation ater content from equivalent water thickness using satellite imagery. Remote Sensing of Environment. 112:2514-2522.
Kung, K., Kladivko, E., Helling, C.S., Gish, T.J., Steenhuis, T.S., Jaynes, D.B. 2006. Quantifying pore size spectrum of macropore-type preferential pathways under transient flow. Vadose Zone Journal. 5:978-989.
Narayan, U., Lakshmi, V., Jackson, T.J. 2006. A simple algorithm for high resolution change detection of soil moisture using L-band radiometer and radar. IEEE Transactions on Geoscience and Remote Sensing. 44:1545-1554.
Narvekar, P.S., Jackson, T.J., Bindlish, R., Li, L., Heygster, G., Gaiser, P. 2007. Observations of land surface passive polarimetry with the WindSat instrument. IEEE Transactions on Geoscience and Remote Sensing. 45:2019-2028.
LeVine, D., Jackson, T.J., Haken, M. 2007. Initial images of the synthetic aperture radiometer 2D-STAR. IEEE Transactions on Geoscience and Remote Sensing. 45:3623-3632.
Crow, W.T., Kustas, W.P., 2008. Monitoring root-zone soil moisture through the assimilation of a thermal remote sensing-based soil moisture proxy into a water balance model. Remote Sensing of Environment. 112(4):1268-1281.
Agam, N., Kustas, W.P., Anderson, M.C., Li, F., Colaizzi, P.D. 2008. Utility of thermal image sharpening for monitoring field-scale evapotranspiration over rainfed and irrigated agricultural regions. Geophysical Research Letters. 35, L02402, http://dx.doi.org/10.1029/2007GL032195.
Bindlish, R., Jackson, T.J., Gasiewski, A., Stankov, B., Klein, M., Cosh, M.H., Mladenova, I., Watts, c., Vivoni, e., Lakshmi, v., Bolten, J., Keefer, T. 2008. Aircraft based soil moisture retrievals under mixed vegetation and topographic conditions. Remote Sensing of Environment. 112:375-390.
Vivoni, E.R., Gebremichael, M., Watts, C.J., Bindlish, R., Jackson, T.J. 2008. Comparison of ground-based and remotely-sensed surface soil moisture estimates over complex terrain during SMEX04. Remote Sensing of Environment. 112:314-325.
Zhan, X., Crow, W.T., Jackson, T.J., O'Neill, P. 2008. Improving space-borne radiometer soil moisture retrievals with alternative aggregation rules for ancillary parameters in highly heterogeneous vegetated areas. Institute of Electrical and Electronic Engineering, Transaction on Geoscience and Remote Sensing. 2:261-265.
Reichle, R.H., Crow, W.T., Koster, R.D., Sharif, H.O., Mahanama, S.P. 2008. The contribution of soil moisture retrievals to land data assimilation products. Geophysical Research Letters. 35, L01404, http://dx.doi.org/10.1029/2007GL031986.