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Theses and Dissertations

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Browsing Theses and Dissertations by Author "Arabi, Mazdak, committee member"

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    Impacts of conservation tillage on water quality and soil health characteristics under furrow irrigation
    (Colorado State University. Libraries, 2017) Deleon, Emmanuel, author; Bauder, Troy, advisor; Fonte, Steven, committee member; Arabi, Mazdak, committee member
    Furrow irrigation-induced sediment and nutrient loss continues to be a serious problem in the Western States of the US. Sediment and nutrients in runoff can eventually be discharged into streams and rivers impairing water quality, causing adverse effects on the environment and reducing soil productivity over time. Continuous intensive tillage along with excessive sediment and nutrient loss ultimately lead to the degradation of soil quality. We hypothesize that conservation tillage under furrow irrigation can reduce the sediment and nutrient losses in surface runoff as well as improve soil quality parameters. The objectives of this research are to compare two conservation tillage treatments, minimum tillage (MT) and strip tillage (ST), to a traditional conventional tillage (CT) system under furrow irrigation and understand the impacts of these practices on annual sediment and nutrient concentrations and loads from irrigation and storm events. We quantified total suspended solids (TSS), total Kejdahl nitrogen (TKN), nitrate (NO3), ammonium (NH4), total nitrogen in aqueous solution (TNa), total phosphorus (TP), dissolved reactive phosphorus (DRP), and total soluble phosphorus (TSP) loads from irrigation runoff over two growing seasons for the three treatments. Relative to CT, conservation tillage reduced TSS loads by 84% and 88% in 2015 and by 98% and 87% in 2016 for MT and ST, respectively. In 2015, TKN was reduced by 80% and 86% in MT and ST respectively when compared to CT. Total P was significantly higher in CT, with an 87% load reduction under MT and ST in 2015 and an 85% load reduction under MT in 2016. Total P concentration (mg L-1) correlated well with TSS concentrations (g L-1) (R2 = 0.72, P < 0.001). Total soluble P loads were significantly higher in the CT treatment when compared to the conservation treatments in the 2015 season. Reduced tillage and residue management in the conservation treatments improved irrigation flow parameters such as reduced runoff. The conservation treatments had a greater impact on sediment-bound than soluble nutrients largely due to surface residue reducing erosion in the furrows. Results show that reduced tillage and residue management are an effective best management practices (BMPs) in sediment and nutrient abatement in irrigation and storm runoff. Furrow irrigation is still practiced in 40% of all irrigated lands in Colorado and it is expected to continue across much of the State. Under furrow-irrigated systems, CT practices are common, but such practices can degrade soil quality. The project sought to examine the effects of conservation tillage on soil health at a production scale, understand relationships between soil parameters, and to evaluate the economic feasibility of conservation practices. Soil biological, physical, and chemical parameters were evaluated during the fifth and sixth years of a study (2015 and 2016) comparing two different management systems, MT and ST, verses CT (the control). Measurements included Active C (POXC), macrofauna diversity and abundance, aggregate stability, infiltration, and residue cover. POXC was significantly higher for MT when compared to CT and ST. Results from both years suggest that conservation treatments increased macrofauna abundance, especially earthworms, and diversity (richness) relative to the control. Aggregate stability was significantly higher in the conservation treatments for 2015, but not in 2016. Infiltration rates in the ST treatment was 18% higher when compared to CT. Residue cover was positively correlated with earthworm abundance while earthworm abundance was positively correlated with aggregated stability and infiltration. When comparing economic cost, and returns among systems, ST and MT treatments had a 39% and 32% greater net return when compared to CT plots. These preliminary results show potential for conservation tillage under furrow-irrigation to improve soil quality parameters as well as increasing net income.
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    Improving accuracy for sugar beet and developing an iOS app to increase functionality of a Colorado irrigation scheduler
    (Colorado State University. Libraries, 2014) Bartlett, Andrew Charles, author; Andales, Allan A., advisor; Bauder, Troy, committee member; Arabi, Mazdak, committee member
    Modeling actual crop water usage allows for improved information-based decision making and ultimately more effective use of water allocations within irrigated agriculture. Evapotranspiration (ET), a dynamic process of water loss through the soil surface (evaporation) and plant stomata (transpiration), is the main component of consumptive water use. Scheduling agricultural irrigation events is an effective tactic to minimize crop stress while avoiding unnecessary irrigation. A cloud based irrigation scheduling tool (WISE - Water Irrigation Scheduling for Efficient Application) which applies the soil water balance (SWB) approach, has been developed on the eRAMS (Environmental Risk Assessment Management System) platform. Actual crop water usage (ETc) is the main cause of the depletion of soil moisture, thus ETc is one of the most important variables within the SWB. Multiple ET equations have been developed as a function of a handful of meteorological measurements including the equation used in this thesis, the 2005 American Society of Civil Engineers (ASCE-EWRI) Standardized Reference equation. The alfalfa based reference evapotranspiration (ETr) models the water loss via ET for a 0.5 m tall, well watered alfalfa stand. In order to model sugar beet water use, an empirically derived crop coefficient (Kcr) curve is applied to the alfalfa reference (ETc = ETr x Kcr). Region specific sugar beet crop coefficient values are available; however, these values have not yet been adjusted for the semi-arid climate of Northeastern Colorado. The first objective of this thesis was to modify the sugar beet Kcr curve for the semi-arid climate of Northeastern Colorado to increase the accuracy of sugar beet scheduling within WISE. By using the soil water balance and observing plant growth and water uptake rates, it was discovered that the original coefficient was drastically overestimating ETc. Shortening the full canopy stage by delaying the initial point (cutoff 2) from 33% to 43% maturity and reducing the length until senescence from 83% to 69% maturity reduced predicted water use to an acceptable value. After comparing actual soil water deficits (D) with modeled values for both the original and adjusted Kcr over two growing seasons, it was found that the relative error (RE) of daily D over all fields was decreased from RE values ranging from 11% - 300% down to RE values ranging from 0% - 265%. Large errors were caused by uncertainties in soil properties, effects of hail damage on actual leaf area and ETc, spatial variability in precipitation or irrigation, and differences in field micro-climate and measured weather station data. The second objective of this thesis was to describe the development and purpose of an iPhone and iPad application that was created to add mobile functionality to the WISE tool. This app allows users to view their field's current soil moisture profile, previous day's weather, upload irrigation and precipitation amounts, and calculate gross irrigation amounts as a function of flow rate, length of application, and acreage. The new sugar beet Kcr curve and the iOS app can lead to more effective irrigation scheduling in agriculture within Colorado.
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    Simulating canopy dynamics, productivity and water balance of annual crops from field to regional scales
    (Colorado State University. Libraries, 2016) Zhang, Yao, author; Paustian, Keith, advisor; Arabi, Mazdak, committee member; Parton, William, committee member; Schipanski, Meagan, committee member
    To provide better understanding of natural processes and predictions for decision support, dynamic models have been used to assess impact of climate, soils and management on crop production, water use, and other responses from field to regional scales. It is important to continue to improve the prediction accuracy and increase the reliability. In this work, we first improved the DayCent ecosystem model by developing a new empirical method for simulating green leaf area index (GLAI) of annual crops. Its performance has been validated using experimental observations from different experimental field locations as well as more aggregate NASS yield data spanning the country. Additionally, sensitivity and uncertainty of important parts of the crop growth model have been quantified. Our results showed the new model provided reliable predictions on crop GLAI, biomass, grain yield, evapotranspiration (ET), and soil water content (SWC) at field scale at various locations. At national scale, the predictions of grain yields were generally accurate with the model capable of representing the geographically-distributed differences in crop yields due to climate, soil, and management. The results indicated that the model is capable of providing insightful predictions for use in management and policy decision making. Although there are challenges to be addressed, our results indicate that the DayCent model can be a valuable tool to assess crop yield changes and other agroecosystem processes under scenarios of climate change in the future.