VTechWorks staff will be away for the Memorial Day holiday on Monday, May 27, and will not be replying to requests at that time. Thank you for your patience.

Show simple item record

dc.contributor.authorRoberson, Travis Leonen_US
dc.description.abstractThe need for water conservation continues to increase as global freshwater resources dwindle. In response, many golf course superintendents are implementing new methods and tools to become more frugal with their water applications. For example, scheduling irrigation using time-domain reflectometer (TDR) soil moisture sensors can decrease water usage. Still, TDR measurements are time-consuming and only cover small scales, leading to many locations being unsampled. Remotely sensed data such as the normalized difference vegetation index (NDVI) offer the potential of estimating moisture stress across larger scales; however, NDVI measurements are influenced by numerous stressors beyond moisture availability, thus limiting its reliability for irrigation decisions. An alternative vegetation index, the water band index (WBI), is primarily influenced by water absorption within a narrow spectral range of near-infrared light. Previous research has established strong relationships between moisture stress of creeping bentgrass (CBG) grown on sand-based root zones, a typical scenario for golf course putting greens. However, this relationship characterizes only a small portion of total acreage across golf courses, which limits widespread adoption. In our research, �007� CBG and �Latitude 36� hybrid bermudagrass (HBG) were grown on three soil textures, USGA 90:10 sand (S), sand loam (SL) and clay (C), arranged in a 2 x 3 factorial design, randomized within six individual dry-down cycles serving as replications. Canopy reflectance and volumetric water content (VWC) data were collected hourly between 0700 and 1900 hr using a hyperspectral radiometer and an embedded soil moisture sensor, until complete turf necrosis. The WBI had the strongest relationship to VWC (r = 0.62) and visual estimations of wilt (r = -0.91) compared to the green-to-red ratio index (GRI) or NDVI. Parameters associated with non-linear regression were analyzed to compare grasses, soils, indices, and their interactions. The WBI and GRI compared favorably with each other and indicated significant moisture stress approximately 28 hr earlier than NDVI (P = 0.0010). WBI and GRI respectively predicted moisture stress 12 to 9 hr before visual estimation of 50% wilt, whereas NDVI provided 2 hr of prediction time (P = 0.0317). When considering the time to significant moisture stress, the HBG lasted 28 hr longer than CBG, while S lasted 42 hr longer than either SL and C (P �� 0.0011). Nonlinear regression analysis showed that WBI and GRI can be useful for predicting moisture stress of CBG and HBG grown on three diverse soils in a highly controlled environment. Our results provide substantial evidence and direction for future research investigating how WBI and GRI can expedite moisture stress assessment and prediction on a large-acreage basis.en_US
dc.publisherVirginia Techen_US
dc.rightsThis item is protected by copyright and/or related rights. Some uses of this item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en_US
dc.subjectWater Band Index (WBI)en_US
dc.subjectNormalized Difference Vegetation Index (NDVI)en_US
dc.subjectGreen-to-Red-Ratio (GRI)en_US
dc.subjectHyper-Spectral Radiometer (HSR)en_US
dc.subjectTime-Domain Reflectometer (TDR)en_US
dc.subjectVolumetric Water Content (VWC)en_US
dc.titleImproving Soil Moisture Assessment of Turfgrass Systems Utilizing Field Radiometryen_US
dc.contributor.departmentPlant Pathology, Physiology, and Weed Scienceen_US
dc.description.degreeMaster of Science in Life Sciencesen_US
thesis.degree.nameMaster of Science in Life Sciencesen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplinePlant Pathology, Physiology, and Weed Scienceen_US
dc.contributor.committeechairMcCall, David Scotten_US
dc.contributor.committeememberStewart, Ryan Danielen_US
dc.contributor.committeememberErvin, Erik H.en_US
dc.contributor.committeememberAskew, Shawn D.en_US

Files in this item


This item appears in the following Collection(s)

Show simple item record