Wayne P. Dulaney

Effectiveness of vegetated filter strips in retention of Escherichia coli and Salmonella from swine manure slurry

Vegetated filter strips (VFS) are commonly recommended as a best management practice to prevent manure-borne microorganisms from reaching surface water resources. However, relatively little is known about the efficacy of VFS in mitigating bacterial runoff from land-applied swine manure. A field lysimeter study was designed to evaluate the effect of surface soil hydrologic conditions and vegetation on the retention of swine manure-borne Escherichia coli and Salmonella under simulated rainfall conditions. Experimental plots (6.5 m × 3.9 m) were set on a 5% slope lysimeter with loamy topsoil, clay loam or loam subsoil and a controllable groundwater level. Three small flow-intercepting miniflumes were installed 4.5 m from the plots top, while all remaining runoff was collected in a gutter at the bottom. Plots were divided into bare soil and grass vegetation and upper surface soil moisture before rainfall events was controlled by the subsurface groundwater level. Swine manure slurry inoculated with E. coli and Salmonella, and with added bromide tracer, was applied on the top of the plots and simultaneously initiated the simulated rainfall. Runoff was collected and analyzed every 5 min. No substantial differences between retention of E. coli and Salmonella were found. In initially wet soil surface conditions, there was limited infiltration both in bare and in vegetated plots; almost all bromide and about 30% of bacteria were recovered in runoff water. In initially dry soil surface conditions, there were substantial discrepancies between bare and vegetated plots. In bare plots, recoveries of runoff water, bromide and bacteria under dry conditions were comparable to wet conditions. However, in dry vegetated plots, from 50% to 75% of water was lost to infiltration, while bromide recoveries ranged from 14 to 36% and bacteria recovery was only 5%. Substantial intraplot heterogeneity was revealed by the data from miniflumes. GIS analysis of the plot microtopography showed that miniflumes located in the zones of flow convergence collected the majority of bacteria. Overall, the efficiency of VFS, with respect to the retention of swine manure bacteria, varied dramatically depending upon the hydrologic soil surface condition. Consequently, VFS recommendations should account for expected amounts of surface soil water saturation as well as the relative soil water storage capacity of the VFS.

Daily Mapping of 30 m LAI and NDVI for Grape Yield Prediction in California Vineyards

Wine grape quality and quantity are affected by vine growing conditions during critical phenological stages. Field observations of vine growth stages are too sparse to fully capture the spatial variability of vine conditions. In addition, traditional grape yield prediction methods are time consuming and require large amount grape samples. Remote sensing data provide detailed spatial and temporal information regarding vine development that is useful for vineyard management. In this study, Landsat surface reflectance products from 2013 and 2014 were used to map satellite-based Normalized Difference Vegetation Index (NDVI) and leaf area index (LAI) over two Vitis vinifera L. cv. Pinot Noir vineyards in California, USA. The spatial correlation between grape yield maps and the interpolated daily time series (LAI and NDVI) was quantified. NDVI and LAI were found to have similar performance as a predictor of spatial yield variability, providing peak correlations of 0.8 at specific times during the growing season, and the timing of this peak correlation differed for the two years of study. In addition, correlations with maximum and seasonal-cumulative vegetation indices were also evaluated, and showed slightly lower correlations with the observed yield maps. Finally, the within-season grape yield predictability was examined using a simple strategy in which the relationship between grape yield and vegetation indices were calibrated with limited ground measurements. This strategy has a strong potential to improve the accuracy and efficiency of yield estimation in comparison with traditional approaches used in the wine grape growing industry.

Alternative approaches for estimating leaf area index (LAI) from remotely sensed satellite and aircraft imagery

Plant foliage density expressed as leaf area index (LAI) is an important parameter that is widely used in many ecological, meteorological and agronomic models. LAI retrieval using optical remote sensing usually requires the collection of surface calibration values or the use of image information to invert radiative transfer models. A comparison of LAI retrieval methods was conducted that included both empirical methods requiring ground based LAI calibration measurements and image based methods using remotely sensed data and literature reported parameter values. The empirical approaches included ordinary least squares regression with the Normalized Difference Vegetation Index (NDVI) and the Gitelson green index (GI) spectral vegetation indices (SVI) and a geostatistical approach that uses ground based LAI measurements and image derived kriging parameters to predict LAI. The image based procedures included the scaled SVI approach, which uses NDVI to estimate fraction of vegetation cover, and a hybrid approach that uses a neural network and a radiative transfer model to retrieve LAI. Comparable results were obtained with the empirical SVI methods and the scaled SVI method. The geostatistical approach produced LAI patterns similar to interpolated ground-based LAI measurements. The results demonstrated that although reasonable LAI estimates are possible using optical remote sensing data without in situ calibration measurements, refinements to the analytical steps of the various approaches are warranted.

Field-Scale Assessment of Land and Water Use Change over the California Delta Using Remote Sensing

The ability to accurately monitor and anticipate changes in consumptive water use associated with changing land use and land management is critical to developing sustainable water management strategies in water-limited climatic regions. In this paper, we present an application of a remote sensing data fusion technique for developing high spatiotemporal resolution maps of evapotranspiration (ET) at scales that can be associated with changes in land use. The fusion approach combines ET map timeseries developed using an multi-scale energy balance algorithm applied to thermal data from Earth observation platforms with high spatial but low temporal resolution (e.g., Landsat) and with moderate resolution but frequent temporal coverage (e.g., MODIS (Moderate Resolution Imaging Spectroradiometer)). The approach is applied over the Sacramento-San Joaquin Delta region in California—an area critical to both agricultural production and drinking water supply within the state that has recently experienced stresses on water resources due to a multi-year (2012–2017) extreme drought. ET “datacubes” with 30-m resolution and daily timesteps were constructed for the 2015–2016 water years and related to detailed maps of land use developed at the same spatial scale. The ET retrievals are evaluated at flux sites over multiple land covers to establish a metric of accuracy in the annual water use estimates, yielding root-mean-square errors of 1.0, 0.8, and 0.3 mm day−1 at daily, monthly, and yearly timesteps, respectively, for all sites combined. Annual ET averaged over the Delta changed only 3 mm year−1 between water years, from 822 to 819 mm year−1, translating to an area-integrated total change in consumptive water use of seven thousand acre-feet (TAF). Changes were largest in areas with recorded land-use change between water years—most significantly, fallowing of crop land presumably in response to reductions in water availability and allocations due to the drought. Moreover, the time evolution in water use associated with wetland restoration—an effort aimed at reducing subsidence and carbon emissions within the inner Delta—is assessed using a sample wetland chronosequence. Region-specific matrices of consumptive water use associated with land use changes may be an effective tool for policymakers and farmers to understand how land use conversion could impact consumptive use and demand.

Mapping evapotranspiration at multiple scales using multi-sensor data fusion

Thermal-infrared remote sensing of land surface temperature (LST) provides valuable information for quantifying root-zone water availability, evapotranspiration (ET) and crop condition. This paper describes a multi-scale LST-based energy balance model built using a Two-Source Energy Balance (TSEB) algorithm, which solves for the soil/substrate and canopy temperatures and flux partitioning. A regional modeling system applies the TSEB to time-differential LST measurements from geostationary satellites, providing coarse ET estimates which can be downscaled to finer spatial resolutions using data from polar orbiting satellites. This modeling system, along with strategies for fusing information from multiple satellite platforms and wavebands, has been used to generate ET maps from field to global scales. We describe applications for high spatiotemporal resolution ET retrievals in assessing impacts of human activities and climate change on water resources and agricultural production.

Daily mapping of Landsat-like LAI and correlation to grape yield

Wine grape quality and quantity are affected by vine growing conditions during some critical growing stages. In this paper, MODIS and Landsat were used to map daily LAI in two Grape Remote sensing Atmospheric Profiling and Evapotranspiration eXperiment (GRAPEX) experimental fields near Lodi, California in 2013. A data fusion approach was applied to map daily LAI at 30 m spatial resolution. The LAI data from two fields were validated using insitu measurements. Cumulative LAI from two fields were compared to the 2013 grape yields. High correlations were found between yield and cumulative LAI. The within-season yield predictability was examined using daily LAI maps. Results show that the grape yields were highly correlated with the cumulative LAI after the month of June. This suggests that grape yields are predictable using remotely sensed data 2-3 months prior to harvest under normal conditions.

Analysis of surrogate indicators for evidence of subsurface preferential flow pathways: impact of subsurface preferential flow on variability of NDVI

Watershed-scale processes governing chemical fluxes to adjacent ecosystems are so poorly understood that effective strategies for mitigating chemical contamination cannot be formulated. Characterization of hydrologic processes and chemical behavior at the watershed scale is critical to the development of sustainable agricultural practices. Identifying locations for monitoring hydrologic processes like subsurface preferential flow is difficult because conventional sampling methods are inadequate for measuring this highly variable, yet critical process. A method for detecting and mapping subsurface preferential flow pathways based primarily on ground-penetrating radar (GPR) data and digital elevation maps (DEM) was developed. This procedure was confirmed for a Maryland cornfield using real-time soil moisture data, maps of within-field grain yield, and remotely sensed imagery. Unfortunately, it is economically unfeasible and logistically impractical for producers to use the GPR-DEM procedures to map subsurface preferential flow pathways for all crop fields. It may, however, be possible to use remotely sensed imagery, grain yield maps, and a DEM as surrogate indicators of subsurface preferential flow pathways occurring at or near crop rooting depth. The normalized difference vegetation index (NDVI) shows an increase with distance from primary, secondary and tertiary preferential flow pathways during above-normal rainfall growing seasons. There appears to be a decrease of NDVI with distance from preferential flow pathways for a dry/drought year. Imagery collected during drought conditions appears especially useful as only within-field locations with subsurface irrigation from preferential flow pathways maintain vigor. Maps of vegetative productivity derived from remotely sensed imagery may be more useful than within-field grain yield maps for detecting and delineating locations of subsurface preferential flow pathways. The ability to delineate field locations with a high probability of subsurface preferential flow pathways will allow producers to better manage crop production, and mitigate losses of agricultural chemical inputs to neighboring ecosystems and waterways.

Variability and covariance of factors affecting canopy reflectance within a 6 ha corn field

The variability of factors affecting landscape reflectance are of interest for remote sensing validation experiments, remote sensing parameter retrieval efforts, and plant canopy simulation studies among others. Leaf optical properties and foliage density, expressed as leaf area index (LAI) are significant factors affecting canopy reflectance. Canopy height can be important when using a 3-dimensional simulation model. Variations in these elements cause variations in field-scale canopy reflectance although detailed measurements on scales larger than individual plots are rare. These factors are also usually treated as independent. However each is a function of plant vigor and thus should exhibit some covariance. Measurements of these factors at 64 locations within a 6 ha corn field were made at the Beltsville Agricultural Research Center, Beltsville, MD during July and August, 1997. The August data were collected after onset of a drought. The ranges of values for the factors are examined and covariance among the factors are examined. Results show a slight positive trend between LAI and height. A positive relationship between leaf reflectance and transmittance is noticeable for 501 nm, 550 nm, 601 nm and 702 nm, although not 1:1. There are also trends between leaf reflectance and transmittance, and LAI.

Multispectral, Multialtitude Observations of The Kurex-91 Experiment Site from a Helicopter Platform

An eight-channel modular multiband radiometer, a 252-channel SE-590 spectroradiometer, and a single-channel infrared thermometer were mounted in a nadir-looking attitude on a Soviet MI-8 helicopter to collect visible, infrared, and thermal measurements of the KUREX-91 study area. These measurements were coincident with surface, other airborne, and spaceborne measurements collected during the July 1991 field campaign. The helicopter missions included both hovers and slow-flight transects over specific sites. Multiple altitude flights over several of the study sites were also made. Study sites included grasslands, forest stands, and agricultural fields. Data collection was executed so that observations from the multispectral devices could be compared with multispectral and biophysical observations made on the surface as well as with multispectral observations from other airborne and spaceborne systems. A preliminary analysis of multispectral and multialtitude data of several study sites is presented.