Andrew G. Ristvey

Estimating Nitrogen and Phosphorus Total Maximum Daily Loads for Container Nursery and Greenhouse Production Systems

In 1998, the state of Maryland adopted one of the toughest nutrient management planning laws in nthe United States, requiring that virtually all agricultural operations to write and implement nitrogen- n(N) and phosphorus- (P) based management plans by December 31, 2002. Writing nutrient nmanagement plans for most ornamental nursery and greenhouse operations is a complicated task, nsince these operations grow a large number of plant species, and utilize a range of fertilization and nirrigation strategies. A nutrient management planning process has been developed which combines nwater management (i.e. leaching fraction, interception efficiency and potential runoff) data with nnutrient management (source and application rate) data into an estimate of total daily maximum nloading (TMDL) rates. A risk assessment process based on operational management units identifies nthose site-specific factors that contribute most to nutrient leaching and runoff, and enables targeted nbest management practices to be developed to reduce the risk of N and P run-off into surface waters nand the Chesapeake Bay. nIn association with this process, our research is examining interactions between irrigation and nnutrient strategies with two model ornamental plant species that are widely grown in the nursery nindustry. Nitrogen and P applications, plant uptake and nutrient leaching are being continuously nquantified to provide nutrient budgets over a three-year production cycle, to assess the effects of ndifferent management strategies on leaching and nutrient runoff potential. The development and use nof new moisture-sensing technology, which can sense real-time water availability in soilless nsubstrates will be necessary to provide more accurate irrigation scheduling and applications to nnursery systems.

Utilizing sensor networks to assess evapotranspiration by greenroofs

Greenroofs are roof designs that incorporate plants and growing media above a water-proofing membrane. They are implemented to achieve a number of ecosystem services, especially stormwater management whereby the goal is to achieve the maximum amount of overall stormwater used or stored. The purpose of this study is to demonstrate how wireless sensor networks can gather the real-time data needed to assess the impact of storm events and efficiency of green roofs, to eventually maximize stormwater retention by greenroofs. In this paper, we present data from three intensively-sensored experimental greenroof platforms planted in either Sedum album, Sedum spurium, or left unplanted. Substrate moisture is monitored continuously at 5-minute intervals with 25 Echo-TM sensors, with ECRN-50 rain gauges measuring stormwater runoff in each platform. Environmental variables such as air and soil temperature, relative humidity, wind speed, photosynthetic and total solar radiation, and precipitation are also collected at the study site in real time. We show how this data can be used to validate model predictions about evapotranspiration and runoff from greenroofs. We compare the Hargreaves Samani and FAO Penman Monteith equations for estimating evapotranspiration with data collected from the platforms. Information from this comparison will be used in the future to create a mechanistic model of the greenroof water cycle. Only with a clear understanding of how much water greenroofs might retain for different climatic scenarios will managers be able to consider or refine policies regarding permitting and incentives for this type of roof construction.