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11	Evaluating drainage water recycling in tile-drained systems Benjamin D Reinhart (8071469) 03 December 2019 (has links) <p>Drainage water recycling (DWR) is the practice of capturing, storing, and reusing subsurface drained agricultural water to support supplemental irrigation and has recently been proposed as a practice for improving the crop production and water quality performance in the tile-drained landscape of the U.S. Midwest. This study describes the development of a modeling framework to quantify the potential irrigation and water quality benefits of DWR systems in tile-drained landscapes and the application of the model using ten years of measured weather, tile drain flow and nutrient concentrations, water table, and soil data from two sites in the U.S. Midwest. From this modeling framework, the development and testing of an open-source online tool is also presented.</p><p></p><p>A spreadsheet model was developed to track water flows between a reservoir and drained and irrigated field area at each site. The amount of tile drain flow and associated nutrient loads that could be captured from the field and stored in the reservoir was estimated to calculate the potential water quality benefits of the system. Irrigation benefits were quantified based on the amount of applied irrigation annually. A reservoir size representing 6% to 8% of the field area with an average depth of 3.05 m was sufficient in meeting the annual irrigation requirements during the 10-year period at each site. At this reservoir size, average annual nitrate-N loads were reduced by 20% to 40% and soluble reactive phosphorus loads by 17% to 41%. Variability in precipitation within and across years, and differences in soil water characteristics, resulted in a wide range of potential benefits at the two sites.</p><p>An online tool was developed from the model, and a variance-based global sensitivity analysis was conducted to determine influential and low-sensitivity input parameters. The input parameter, depth of root zone, was the most influential input parameter suggesting that the estimation of total available water for the field water balance is a critical component of the model. Input settings describing the irrigation management and crop coefficients for the initial establishment and mid-season crop growth periods were also influential in impacting the field water balance. Reservoir seepage rate was influential in regard to the reservoir water balance, particularly at larger reservoir sizes. Sensitivity analysis results were used to develop a user-interface for the tool, Evaluating Drainage Water Recycling Decisions (EDWRD).</p><p>This study shows that DWR is capable of providing both irrigation and water quality benefits in the tile-drained landscape of the U.S. Midwest. The developed modeling framework supports future research on the development of strategies to implement and manage DWR systems, and the online tool serves as a resource for users to increase their awareness and understanding of the potential benefits of this novel practice.</p><p></p> Supplemental Irrigation Water Reuse Nutrient Load Reduction Reservoir Water Storage Tile Drainage Sensitivity Analysis Online Tool Water Balance Model Crop Coefficient
12	<b>The impact of agricultural conservation practices on water quality in tile-drained watersheds</b> Noah R Rudko (19200181) 25 July 2024 (has links) <p dir="ltr">In the Midwest, tile drainage is used to lower water tables and remove excess water from the soil to improve crop production. This network of underground pipes (i.e., tiles) and expansive agriculture also increases nutrient export, contributing to ecological harm in local lakes and rivers and further downstream in the Gulf of Mexico. Conservation practices that avoid, control, or trap nutrients can mitigate these losses, but studies quantifying their impact at the watershed scale are challenging. This work uses water quality monitoring data collected throughout the Midwest to identify potential nutrient sources and pathways, the hydroclimatic variables influencing them, and the effects of conservation practices. In a study in northeast Indiana, nutrient travel times for total phosphorus, soluble reactive phosphorus, nitrate, and dissolved organic carbon were observed to be faster during winter storm events, likely due to a lack of vegetative processes. Tile drains were the primary contributor to in-stream nitrogen and phosphorus during spring storms but were not a primary contributor for phosphorus in the winter. Data from nitrate sensors across the Midwest were used to quantify the effect of sampling frequency on hysteresis and flushing indices, showing that sampling intervals greater than 8 hours estimates could lead to inaccurate values, and that caution should be used when interpreting outcomes when using longer sampling intervals. Wet antecedent conditions were associated with a dilution pattern of nitrate during storm events, and tile drainage exacerbates this by causing greater leaching during wet periods. A systematic review of water quality monitoring studies at the watershed scale showed the limits using current data, and suggested how providing better statistics could be used to facilitate a more robust meta-analysis to determine effect sizes and sources of heterogeneity among studies. In a monitoring study located in the central Indiana, agricultural conservation practices reduced nitrate concentrations by 27% in an artificially drained watershed. While tile drainage is a critical pathway for nutrients in the Midwest, the combined effect of various conservation practices can improve water quality at the watershed scale.</p> Agricultural hydrology Agricultural management of nutrients Environmental assessment and monitoring Watershed Biogeochemistry nutrients water quality hydrology agriculture tile drainage watershed management. Conservation practices
13	Water management effects on potato production and the environment Satchithanantham, Sanjayan January 2012 (has links) Potatoes (Solanum tuberosum) were grown in a fine sandy loam soil in southern Manitoba in a three-year field study comparing four water management treatments: No Drainage with No Irrigation (NDNI), No Drainage with Overhead Irrigation (NDIR), Free Drainage with Overhead Irrigation (FDIR), and Controlled Drainage with Subirrigation (CDSI). The objectives of the study were (i) to evaluate the effect of the four treatments on yield and quality of potatoes, (ii) to evaluate the effect of water management on the environment, (iii) to estimate the shallow groundwater contribution to potato water requirement, and (iv) to simulate the shallow groundwater hydrology using the DRAINMOD and HYDRUS 1-D model. Subsurface drains were installed at 0.9 m depth and at spacings of 15 m (FDIR) and 8 m (CDSI). Subirrigation was done by pumping water back into the tiles through the drainage control structures. Overhead irrigation was carried out using a travelling gun. Water table depth, soil water content, drainage outflow, nutrient concentration in drainage water, irrigation rate, weather variables, potato yield and quality parameters, and biomass were measured. Compared to the NDNI treatment, the potato yield increase in the other treatments ranged between 15-32% in 2011 and 2-14% in 2012. In 2011, potato yield from FDIR was higher than CDSI (p = 0.011) and NDNI (p = 0.001), and yield from NDIR was higher than NDNI (p = 0.034). In 2012, potato yield was higher in FDIR in comparison to NDNI (p = 0.021). In 2012, the NDIR gave higher dark ends (p = 0.008) compared to other treatments. Under dry conditions, up to 92% of the potato crop water demand could be met by shallow groundwater contribution. Compared to free drainage, controlled drainage was able to lower the nitrate export by 98% (p = 0.033) in 2010 and by 67% (p = 0.076) in 2011, and the phosphate export decreased by 94% (p = 0.0117) in 2010. A major part of the drainage flow and nutrient export took place between April and June in southern Manitoba. DRAINMOD was able to accurately predict the shallow groundwater hydrology for this particular research site. Irrigation Drainage Subirrigation Potato Nutrient export Best management practices Shallow groundwater contribution Potato quality Potato yield Irrigated potato Tile drainage in Manitoba Water table management Moisture stress Groundwater Soil moisture redistribution Excess moisture Modeling DRAINMOD
14	Harmful Algal Blooms in Small Lakes: Causes, Health Risks, and Novel Exposure Prevention Strategies Mrdjen, Igor 28 September 2018 (has links) No description available. Aquatic Sciences Biology Environmental Health Environmental Science Ecology Geology Land Use Planning Public Health Remote Sensing Water Resource Management harmful algal bloom microcystin carcinogenesis cancer algae cyanobacteria community tile drainage drone UAV remote sensing NDVI toxicity
15	Digital Soil Mapping of the Purdue Agronomy Center for Research and Education Shams R Rahmani (8300103) 07 May 2020 (has links) This research work concentrate on developing digital soil maps to support field based plant phenotyping research. We have developed soil organic matter content (OM), cation exchange capacity (CEC), natural soil drainage class, and tile drainage line maps using topographic indices and aerial imagery. Various prediction models (universal kriging, cubist, random forest, C5.0, artificial neural network, and multinomial logistic regression) were used to estimate the soil properties of interest. Agricultural Land Management Agricultural Land Planning Sustainable Agricultural Development Agronomy Digital soil mapping (DSM) Organic matter content Cation exchange capacity Natural soil drainage classes geostatistical methods Cubist modeling Random Forest models Universal Kriging C5.0 or see5 modeling Artificial neural network Tile drainage lines Soil spatial variation Plant Phenotyping Aerial Imagery digital elevation model (DEM) terrain attributes Soil and Landscape Very poorly drained poorly drained somewhat poorly drained moderately well drained User's accuracy producer's accuracy kappa coefficient Multinomial logit regression Tile Probe topographic wetness index Topographic Position Index slope height cross sectional curvature Relative slope position channel network distance SSURGO soils data internal validation external validation

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