Improving Soil Moisture Assessment of Turfgrass Systems Utilizing Field Radiometry
datasetposted on 2021-02-23, 23:24 authored by Travis Roberson, David McCall
Managed turfgrasses provide several benefits including filtering pollutants, cooling their surroundings, generating oxygen, preventing erosion, serving as recreational surfaces, and increasing landscape aesthetics. Intensively managed turfgrass systems, such as on golf courses and sports fields, require more inputs to maintain acceptable conditions. Freshwater use is often excessive on intensively managed turfgrasses to maintain proper plant growth. Drought conditions often limit water availability, especially in regions with limited rainfall. Turf managers tend to over-apply water across large acreage when few localized areas begin to show symptoms of drought. Additionally, turf managers sometimes wrongly identify stressed areas from other factors as ones being moisture deprived. Advancements such as the use of soil moisture meters have simplified irrigation decisions as an aid to visual inspections for drought stress. While this method enhances detection accuracy, it still provides no solution to increase efficiency. Expanding our current knowledge of turfgrass canopy light reflectance for rapid moisture stress identification can potentially save both time and water resources. The objective of this research was to enhance our ability to identify and predict moisture stress of creeping bentgrass (CBG) and hybrid bermudagrass (HBG) canopies integrated into varying soil textures (USGA 90:10 sand (‘S’), sand loam (‘SL’) and Clay (‘C’)) using light reflectance measurements. Dry-down cycles were conducted under greenhouses conditions collecting soil moisture and light reflectance data every hour from 7 am to 7 pm after saturating and withholding water from established plugs. Moisture stress was most accurately estimated over time using two vegetation indices, the water band index (WBI = R900/R970) and green-to-red ratio index (GRI = R550/R670), with approximately ninety percent accuracy to visible wilt stress. The WBI and GRI predicted moisture stress of CBG in all soil types and HBG in ‘SL’ and ‘C’ approximately fourteen hours before the grasses reached fifty percent wilt. While light reflectance varies on exposed soils, our research shows that underlying soils do not interfere with measurements across typical turfgrass stands. This research provides a foundation for future research implementing rapid, aerial measurements of moisture-stressed turfgrasses on a broad application of CBG and HBG on constructed or native soils.
PublisherUniversity Libraries, Virginia Tech
creeping bentgrassHBGsUAVinflection pointsmall unmanned aerial vehiclesIPNDVIETvegetation index4PLVIvolumetric water contentevapotranspirationVWCTQturf qualityGRIHSRnormalized difference vegetation indexhybrid bermudagrassCBGhyper-spectral radiometerWBIfour-parameter logisticwater band indextime-domain reflectometerTDRgreen-to-red ratio indexRemote sensing