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Browsing by Author "Badzmierowski, Mike J."

Now showing 1 - 4 of 4
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    Biosolids as a source of soil conditioning and fertility for turfgrass
    Badzmierowski, Mike J. (Virginia Tech, 2019-11-04)
    Wastewater treatment plants are shifting towards producing exceptional quality (EQ) biosolids to increase recycling rates to land, especially urban areas. Other methods of improving the environmental impact of wastewater treatment includes additions of iron (Fe) to reduce phosphorus (P) concentrations in outgoing treated water and precipitate the P into the biosolids. Proper management of biosolids to rehabilitate anthropogenically disturbed urban soils for improved plant growth and effects on the cycling of nutrients requires further study. Our objectives were: 1) to determine whether various EQ biosolids could be managed to improve degraded soil properties and turfgrass quality while minimizing risk of P loss in a field study; and 2) to use spectral reflectance data to compare relationships of vegetation indices to soil and turfgrass parameters. We found that after an initial lag-time of one year, biosolids amendments increased turfgrass clipping biomass and aesthetic quality greater than did synthetic fertilizer. Repeated topdressing applications of biosolids reduced soil bulk density and increased soil organic carbon (OC) and nitrogen (N) stocks. Biosolids applied at the agronomic N rate did not increase water-soluble P (15 and 18 mg P kg-1 of soil) compared to biosolids applied at the agronomic P rate (9.6 mg P kg-1 of soil) and synthetic fertilizer (13 mg P kg-1 of soil) after five years. We further demonstrated at this field site that collecting continuous data improves spectral reflectance vegetation indices relationships to turfgrass quality, clipping biomass, and tissue N accumulation. Soil volumetric water content was best correlated to the water band index (r = 0.60) and the green-to-red ratio index (r = 0.54) vegetation indices. Differences in soil and turfgrass measured parameters were best detected when there was drought-stressed versus irrigated turfgrass.
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    Improving Soil Moisture Assessment of Turfgrass Systems Utilizing Field Radiometry
    Roberson, Travis L.; Badzmierowski, Mike J.; Stewart, Ryan D.; Ervin, Erik H.; Askew, Shawn D.; McCall, David S. (MDPI, 2021-09-29)
    The need for water conservation continues to increase as global freshwater resources dwindle. Turfgrass mangers are adapting to these concerns by implementing new tools to reduce water consumption. Time-domain reflectometer (TDR) soil moisture sensors can decrease water usage when scheduling irrigation, but nonuniformity across unsampled locations creates irrigation inefficiencies. Remote sensing data have been used to estimate soil moisture stress in turfgrass systems through the normalized difference vegetation index (NDVI). However, numerous stressors other than moisture constraints impact NDVI values. The water band index (WBI) is an alternative index that uses narrowband, near-infrared light reflectance to estimate moisture limitations within the plant canopy. The green-to-red ratio index (GRI) is a vegetation index that has been proposed as a cheaper alternative to WBI as it can be measured using digital values of visible light instead of relying on more costly hyperspectral reflectance measurements. A replicated 2 × 3 factorial experimental design was used to repeatedly measure turf canopy reflectance and soil moisture over time as soils dried. Pots of ‘007’ creeping bentgrass (CBG) and ‘Latitude 36’ hybrid bermudagrass (HBG) were grown on three soil textures: United States Golf Association (USGA) 90:10 sand, loam, and clay. Reflectance data were collected hourly between 07:00 and 19:00 using a hyperspectral radiometer and volumetric water content (VWC) data were collected continuously using an embedded soil moisture sensor from soil saturation until complete turf necrosis by drought stress. The WBI had the strongest relationship to VWC (r = 0.62) compared to GRI (r = 0.56) and NDVI (r = 0.47). The WBI and GRI identified significant moisture stress approximately 28 h earlier than NDVI (p = 0.0010). Those metrics also predicted moisture stress prior to fifty percent visual estimation of wilt (p = 0.0317), with lead times of 12 h (WBI) and 9 h (GRI). By contrast, NDVI provided 2 h of prediction time. Nonlinear regression analysis showed that WBI and GRI can be useful for predicting moisture stress of CBG and HBG grown on three different soil textures in a controlled environment.
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    Using Hyperspectral and Multispectral Indices to Detect Water Stress for an Urban Turfgrass System
    Badzmierowski, Mike J.; McCall, David S.; Evanylo, Gregory K. (MDPI, 2019-08-08)
    Spectral reflectance measurements collected from hyperspectral and multispectral radiometers have the potential to be a management tool for detecting water and nutrient stress in turfgrass. Hyperspectral radiometers collect hundreds of narrowband reflectance data compared to multispectral radiometers that collect three to ten broadband reflectance data for a cheaper cost. Spectral reflectance data have been used to create vegetation indices such as the normalized difference vegetation index (NDVI) and the simple ratio vegetation index (RVI) to assess crop growth, density, and fertility. Other indices such as the water band index (WBI) (narrowband index) and green-to-red ratio index (GRI) (both broadband and narrowband index) have been proposed to predict soil moisture status in turfgrass systems. The objective of this study was to compare the value of multispectral and hyperspectral radiometers to assess soil volumetric water content (VWC) and tall fescue (Festuca arundinacea Schreb.) responses. The multispectral radiometer VI had the strongest relationships to turfgrass quality, biomass, and tissue N accumulation during the trial period (April 2017–August 2018). Soil VWC had the strongest relationship to WBI (r = 0.60), followed by GRI and NDVI (both r = 0.54) for the 0% evapotranspiration (ET). Nonlinear regression showed strong relationships at high water stress periods in each year for WBI (r = 0.69–0.79), GRI (r = 0.64–0.75), and NDVI (r = 0.58–0.79). Broadband index data collected using a mobile multispectral sensor is a cheaper alternative to hyperspectral radiometry and can provide better spatial coverage.
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    What is the impact of human wastewater biosolids (sewage sludge) application on long-term soil carbon sequestration rates? A systematic review protocol
    Badzmierowski, Mike J.; Evanylo, Gregory K.; Daniels, W. Lee; Haering, Kathryn C. (2021-03-19)
    Background Human wastewater biosolids, hereafter referred to as biosolids, are produced in significant quantities around the world and often applied to an extensive land mass including agricultural fields, forests, mine lands, and urban areas. Land-application of biosolids has been reported in peer-reviewed and non-peer-reviewed work to change soil organic carbon stocks in varying amounts. Determining the potential of soil organic carbon (SOC) stock change and sequestration from biosolids land application is critical for biosolids producers and users to gain access to carbon credit markets. Our review question is, "what is the impact of biosolids application on long-term soil carbon sequestration rates?” We look to explore this main question with the follow-up, "does biosolids processing methods and characteristics, application method, soil properties, land management and other modifiers affect rates of carbon accumulation from land-applied biosolids?" Methods Searches will be conducted using online databases (i.e., Web of Science Core Collection, CAB Abstracts, Scopus, ProQuest Dissertations & Theses Global), search engines (Google Scholar and Microsoft Academic), and specialist websites to find primary field studies and grey literature of biosolids land-application effects on soil organic carbon stocks. We will use English search terms and predefined inclusion criteria of: (1) a field study of at least 24 months that reports soil organic carbon/matter (SOC/SOM) concentrations/stocks; (2) has two types of treatments: (i) a control (non-intervention AND/OR synthetic fertilizer) AND (ii) a biosolids-based amendment; and (3) information of amendment properties and application dates and rates to estimate the relative contribution of the applied materials to SOC changes. We will screen results in two stages: (1) title and abstract and (2) full text. A 10% subset will be screened by two reviewers for inclusion at the title and abstract level and use a kappa analysis to ensure agreement of at least 0.61. All results in the full text stage will be dual screened. Data will be extracted by one person and reviewed by a second person. Critical appraisal will be used to assess studies’ potential bias and done by two reviewers. A meta-analysis using random effects models will be conducted if sufficient data of high enough quality are extracted.