2008 Annual Report
1a.Objectives (from AD-416)
1. Use remote sensing tools to develop rapid assessment procedures for soil and water resources in Coastal Plain agricultural systems.
a. Evaluate tillage and residue management effects on soil carbon accretion, soil water content and associated changes in crop response.
b. Remotely quantify variability in crop residue cover to better develop indices that may be used to rapidly assess conservation tillage adoption at the watershed scale.
2. Modify, test, and apply the Riparian Ecosystem Management Model (REMM) to evaluate and guide restoration and management of riparian buffers and wetlands.
3. Develop an improved GIS modeling framework for accurately quantifying soil moisture, evapotranspiration (ET), and infiltration in Coastal Plain watersheds.
a. Evaluate techniques for assimilating estimates of soil-moisture at the soil surface into field and watershed scale hydrologic models.
b. Improve methods for estimating evapotranspiration and infiltration within Coastal Plain watersheds.
4. Evaluate the effects of land use and surface water features on nutrient and dissolved oxygen levels in Coastal Plain watersheds.
1b.Approach (from AD-416)
OBJ.1: Direct measurements of soil and plant attributes will be related to crop yield and measurable changes in soil organic carbon accretion, soil water content, plant available water content, microbial community size, soil nitrogen, and nitrate leaching. Remotely sensed data will allow us to.
1)integrate the combined effects of soil organic carbon accretion and nitrogen management via real-time, non-destructive assessments of crop response,.
2)monitor crop response as a function of plant available water and nitrogen contents, and.
3)refine crop coefficients for improved irrigation management and water use efficiency. OBJ.2: The Riparian Ecosystem Management Model will be modified to facilitate use for specific applications such as pesticide transport, P retention estimates, and watershed scale buffer scenario testing. Procedures will be tested for integrating modifications of REMM with watershed scale models. REMM integrations with watershed and channel process models will be tested using watershed data collected at ARS and cooperator watersheds in Georgia, Delaware, Mississippi, Maryland, and elsewhere. OBJ.3: A GIS based modeling system will be developed to simulate soil moisture conditions across the region. Based upon existing soil, climate, and vegetation data, the system will allow point, field, and watershed scale estimates of evapotranspiration, runoff, and soil moisture. It is anticipated that the system will be capable of estimating soil moisture across spatially variable fields for purposes of irrigation scheduling, as well as watersheds equivalent in size to the Little River Experimental Watershed for purposes of long term water resource planning. OBJ.4: Levels of dissolved oxygen will be correlated with other measured water quality parameters for 18 sites in the Suwannee River Basin to determine if relationships exist between dissolved oxygen and stream chemistry.
Research focused on Problem Area 6, Water Quality Protection Systems of Nation Program 211, Water Availability and Watershed Management. Measurement of processes affecting dissolved oxygen in coastal plain streams were continued, focusing on biological oxygen demand from sediment and litter in third order and fifth order streams of the Little River Watershed. Measurements of water quality in the Suwannee River Basin continued including activation of new sampling stations on streams draining an urban area. These sampling stations will allow comparison of water quality and hydrology in agricultural and urban watersheds of the Suwannee River Basin. Changes to computer code of Riparian Ecosystem Management Model to add pesticide components were completed and verified. Changes to computer code to provide alternatives for phosphorus adsorption were completed and verified. Satellite, small unmanned aircraft systems (SUAS) and ground-based sensors measuring spectral response are being developed as tools to assess regional conservation tillage practice placement (satellite) and in-field affects of soil and water management (SUAS and ground-based sensors). Research collected to date indicates rapidly acquired SUAS data is more sensitive to changes in crop response than traditional point-based sampling regimes and has been successfully used to quantify differences in crop response to crop residue management and irrigation. Satellite derived mapping algorithms have been developed to:.
1)delineate conservation tillage adoption, and.
2)predict winter biomass yields on a regional basis. These tools show promise as a means to relate changing land use/land management to changes in water quality/quantity. Soil moisture measurements interpreted from satellite collected data as well as estimates from a large-scale computer simulation model were compared to data collected from a ground-based network in South-central Georgia.
Quantifying crop residue cover at spring planting using remotely sensed data.
Conservation tillage can reduce erosion, increase infiltration and help build soil organic carbon. However, monitoring adoption of conservation tillage within a watershed using a line-transect or windshield survey approach is time-consuming, subject to bias, and can misrepresent within field variability in crop residue coverage. A ground-based remotely sensed index using blue (445 nm) and middle infrared (1650 nm) regions of the light spectrum has been used to differentiate between conventional and conservation tillage treatments. Indices were tested over a period of weeks, and exhibit a strong linear relationship with increasing amounts of crop residue coverage in Coastal Plain systems. These data provided the foundation of a satellite-based mapping algorithm developed in CRIS 6602-13000-020-00D, depicting conservation tillage adoption in the Little River Experimental Watershed. The research falls under National Program 201, Water Resource Management, Problem Area 1, 'Effectiveness of Conservation Practices'. Low dissolved oxygen (DO) levels in coastal plain streams are a major reason that these streams do not meet water quality standards set by state and federal regulatory agencies. The low DO may be due to excess nutrients from agricultural non point source pollution that stimulates algae growth in streams. The research also falls under National Program 211 Water Availability and Watershed Management, Water Resource Management Component, Problem Area 5, Water Availability, Watershed Management and Ecosystem Restoration.
Remote sensing as a method for estimating soil moisture.
Soil moisture content is a critical soil property which can affect many geophysical processes in the environment including flooding, drought, climate, and plant/soil interactions. Knowledge of the amount of water existing in the soil is critical to understanding many fundamental environmental processes. Soil moisture measurements interpreted from satellite collected data as well as estimates from a large-scale computer simulation model were compared to data collected from a ground-based network in South-central Georgia. The comparison indicated the simulation model provided estimates of ground-based soil moisture within reasonable error ranges and accurately predicted the extremes of the observed soil moisture. This study indicates that the satellite estimates and the computer simulation model may be useful tools for estimating soil moisture in regions where ground-based data are not available. The research falls under National Program 211 Water Availability and Watershed Management, Water Resource Management Component, Problem Area 5, Watershed Management, Water Availability, and Ecosystem Restoration.
A small unmanned aerial vehicle, equipped with a thermal infrared camera can be used to evaluate crop response to irrigation and winter cover crop management.
Thermal infrared (TIR) emittance has been well-correlated with canopy temperature and oftentimes used as a measure of a plant’s ability to dissipate excess energy. However, until recently field-scale estimates of TIR emittance have been compromised by expense, lack of temporal resolution and feasibility. Recent advancements in TIR cameras mounted in small unmanned aerial systems have allowed researchers to assess crop response to irrigation and winter cover crop management at the field scale. Findings from recent studies indicate that TIR data acquired in this way are more sensitive to crop response to micro-climate conditions compared to traditional, and more time intensive, methods of assessment. Practical implications of this tool include in-season mitigation of crop stress, improved irrigation strategies, and an assessment of landscape level effects on crop productivity. The research falls under National Program 211 Water Availability and Watershed Management, Water Resource Management Component, Problem Area 2, Irrigation Water Management and Security.
5.Significant Activities that Support Special Target Populations
Carey, R.O., Vellidis, G., Lowrance, R.R., Pringle, C.M. 2007. Nutrient and light limitation of algal periphyton in blackwater coastal plain streams characterized by low dissolved oxygen, Georgia, USA. Journal of the American Water Resources Association.
Crompton, B., Vellidis, G., Lowrance, R.R., Smith, M.C. 2008. Factors affecting sediment oxygen demand dynamics in blackwater streams of Georgia's coastal plain. Journal of the American Water Resources Association. 44:724-741.
Sullivan, D.G., Fulton, J.P., Shaw, J.N., Bland, G. 2008. Evaluating the Sensitivity of an Unmanned Thermal Infrared Aerial System to Detect Water Stress in a Cotton Canopy. Transactions of the ASABE. 50:1963-1969.
Sullivan, D.G., Shaw, J.N., Price, A.J., Van Santen, E. 2007. Spectral Reflectance Properties of Winter Cover Crops in the Southeastern Coastal Plain. Agronomy Journal. 99:1589-1596.
Yuan, Y., Bingner, R.L., Williams, R.G., Lowrance, R.R., Bosch, D.D., Sheridan, J.M. 2007. Integration of AnnAGNPS and REMM for watershed riparian buffer system assessment. International Journal of Sediment Research, 22(1): 60-69.