Matching Items (12)

Pay-for-Performance Conservation Using SWAT Highlights Need for Field-Level Agricultural Conservation

Description

Pay-for-performance (PFP) is a relatively new approach to agricultural conservation that attaches an incentive payment to quantified reductions in nutrient runoff from a participating farm. Similar to a payment for ecosystem services approach, PFP lends itself to providing incentives for

Pay-for-performance (PFP) is a relatively new approach to agricultural conservation that attaches an incentive payment to quantified reductions in nutrient runoff from a participating farm. Similar to a payment for ecosystem services approach, PFP lends itself to providing incentives for the most beneficial practices at the field level. To date, PFP conservation in the U.S. has only been applied in small pilot programs. Because monitoring conservation performance for each field enrolled in a program would be cost-prohibitive, field-level modeling can provide cost-effective estimates of anticipated improvements in nutrient runoff. We developed a PFP system that uses a unique application of one of the leading agricultural models, the USDA’s Soil and Water Assessment Tool, to evaluate the nutrient load reductions of potential farm practice changes based on field-level agronomic and management data. The initial phase of the project focused on simulating individual fields in the River Raisin watershed in southeastern Michigan. Here we present development of the modeling approach and results from the pilot year, 2015-2016. These results stress that (1) there is variability in practice effectiveness both within and between farms, and thus there is not one “best practice” for all farms, (2) conservation decisions are made most effectively at the scale of the farm field rather than the sub-watershed or watershed level, and (3) detailed, field-level management information is needed to accurately model and manage on-farm nutrient loadings.

Supplemental information mentioned in the article is attached as a separate document.

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2017

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Impacts of new crop portfolios on water consumption in Maricopa County

Description

Agriculture is the second largest water consumer in the Phoenix Metropolitan region, after the municipal sector. A significant portion of the cultivated land and agricultural water demand is from the production of animal feed, including alfalfa (~69% of total cropland

Agriculture is the second largest water consumer in the Phoenix Metropolitan region, after the municipal sector. A significant portion of the cultivated land and agricultural water demand is from the production of animal feed, including alfalfa (~69% of total cropland area), corn (~8), and sorghum (-3%), which are both exported and needed to support local dairy industry. The goal of this thesis is to evaluate the impacts on water demand and crop production of four different crop portfolios using alfalfa, corn, sorghum, and feed barley. For this aim, the Water Evaluation And Planning (WEAP) platform and the embedded MABIA agronomic module are applied to the Phoenix Active Management Area (AMA), a political/hydrological region including most of Phoenix Metro. The simulations indicate that the most efficient solution is a portfolio where all study crop production is made up by sorghum, with an increase of 153% in crop yield and a reduction of 60% of water consumption compared to current conditions. In contrast, a portfolio where all study crop production is made up by alfalfa, which is primary crop grown in current conditions, decreased crop yield by 77% and increases water demand by 105%. Solutions where all study crop production is achieved with corn or feed barley lead to a reduction of 77% and 65% of each respective water demand, with a portfolio of all corn for study crop production increasing crop yield by 245% and a portfolio of all feed barley for study crop production reducing crop yield by 29%.

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2020-05

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MODELING OF LONG-TERM RECLAMATION PROCESSES ON MARTIAN REGOLITH FOR SUSTAINABLE MARTIAN AGRICULTURE

Description

To successfully launch and maintain a long-term colony on Mars, Martian agricultural systems need to be capable of sustaining human life without requiring expensive deliveries from Earth. There is a need for more studies on this topic to make this

To successfully launch and maintain a long-term colony on Mars, Martian agricultural systems need to be capable of sustaining human life without requiring expensive deliveries from Earth. There is a need for more studies on this topic to make this a feasible mission. This thesis aims to study from a high level one such agricultural system, specifically examining the requirements and flow of Nitrogen, Phosphorus and Potassium required to sustain a given human colony size. We developed a Microsoft Excel based model that relates human nutritional needs to the amount available in food crops and in turn the amount of Martian soil required for agriculture. The model works by inputting the number of humans, and then utilizing the built-in calculations and datasets to determine how much of each nutrient is needed to meet all nutritional needs of the colony. Using that information, it calculates the amount of plants needed to supply the nutrition and then calculates the amount of nutrients that would be taken from the soil. It compares the Martian regolith to the nutrient uptake, accounting for inedible biomass from the plants and human waste that can be added to the regolith. Any deficiencies are used to determine if and how much fertilizer should be added to the system initially and over time. Using the total amount of plants and the number of harvests, the amount of Martian land required for sustaining the colony is computed. These results can be used as a building block to enable the successful design of an agricultural system on Mars.

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2020-05

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Assessing Urban Agricultural Practices in Desert Cities

Description

Is there a mismatch between urban farmers’ perceptions of their farm’s environmental sustainability and its actual environmental impact? Focusing on the use of water and nutrients on each farm as described by the farmers through interviews, it is evident that

Is there a mismatch between urban farmers’ perceptions of their farm’s environmental sustainability and its actual environmental impact? Focusing on the use of water and nutrients on each farm as described by the farmers through interviews, it is evident that there is some level of disconnect between ideals and practices. This project may aid in bridging the gap between the two in regard to the farmers’ sustainability goals. This project will move forward by continuing interviews with farmers as well as collecting soil and water from the farms in order to more accurately quantify the sustainability of the farms’ practices. This project demonstrates that there is some degree of misalignment between perception and reality. Two farms claimed they were sustainable when their practices did not reflect that, while 2 farms said they were not sure if they were sustainable when their practices indicated otherwise. Samples from two farms showed high concentrations of nutrients and salts, supporting the idea that there may be a mismatch between perceived and actual sustainability.

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2021-05

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On the Statistical and Scaling Properties of Observed and Simulated Soil Moisture

Description

Soil moisture (θ) is a fundamental variable controlling the exchange of water and energy at the land surface. As a result, the characterization of the statistical properties of θ across multiple scales is essential for many applications including flood prediction,

Soil moisture (θ) is a fundamental variable controlling the exchange of water and energy at the land surface. As a result, the characterization of the statistical properties of θ across multiple scales is essential for many applications including flood prediction, drought monitoring, and weather forecasting. Empirical evidences have demonstrated the existence of emergent relationships and scale invariance properties in θ fields collected from the ground and airborne sensors during intensive field campaigns, mostly in natural landscapes. This dissertation advances the characterization of these relations and statistical properties of θ by (1) analyzing the role of irrigation, and (2) investigating how these properties change in time and across different landscape conditions through θ outputs of a distributed hydrologic model. First, θ observations from two field campaigns in Australia are used to explore how the presence of irrigated fields modifies the spatial distribution of θ and the associated scale invariance properties. Results reveal that the impact of irrigation is larger in drier regions or conditions, where irrigation creates a drastic contrast with the surrounding areas. Second, a physically-based distributed hydrologic model is applied in a regional basin in northern Mexico to generate hyperresolution θ fields, which are useful to conduct analyses in regions and times where θ has not been monitored. For this aim, strategies are proposed to address data, model validation, and computational challenges associated with hyperresolution hydrologic simulations. Third, analyses are carried out to investigate whether the hyperresolution simulated θ fields reproduce the statistical and scaling properties observed from the ground or remote sensors. Results confirm that (i) the relations between spatial mean and standard deviation of θ derived from the model outputs are very similar to those observed in other areas, and (ii) simulated θ fields exhibit the scale invariance properties that are consistent with those analyzed from aircraft-derived estimates. The simulated θ fields are then used to explore the influence of physical controls on the statistical properties, finding that soil properties significantly affect spatial variability and multifractality. The knowledge acquired through this dissertation provides insights on θ statistical properties in regions and landscape conditions that were never investigated before; supports the refinement of the calibration of multifractal downscaling models; and contributes to the improvement of hyperresolution hydrologic modeling.

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2018

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Optimization Models for Iraq’s Water Allocation System

Description

In the recent past, Iraq was considered relatively rich considering its water resources compared to its surroundings. Currently, the magnitude of water resource shortages in Iraq represents an important factor in the stability of the country and in protecting sustained

In the recent past, Iraq was considered relatively rich considering its water resources compared to its surroundings. Currently, the magnitude of water resource shortages in Iraq represents an important factor in the stability of the country and in protecting sustained economic development. The need for a practical, applicable, and sustainable river basin management for the Tigris and Euphrates Rivers in Iraq is essential. Applicable water resources allocation scenarios are important to minimize the potential future water crises in connection with water quality and quantity. The allocation of the available fresh water resources in addition to reclaimed water to different users in a sustainable manner is of the urgent necessities to maintain good water quantity and quality.

In this dissertation, predictive water allocation optimization models were developed which can be used to easily identify good alternatives for water management that can then be discussed, debated, adjusted, and simulated in greater detail. This study provides guidance for decision makers in Iraq for potential future conditions, where water supplies are reduced, and demonstrates how it is feasible to adopt an efficient water allocation strategy with flexibility in providing equitable water resource allocation considering alternative resource. Using reclaimed water will help in reducing the potential negative environmental impacts of treated or/and partially treated wastewater discharges while increasing the potential uses of reclaimed water for agriculture and other applications. Using reclaimed water for irrigation is logical and efficient to enhance the economy of farmers and the environment while providing a diversity of crops, especially since most of Iraq’s built or under construction wastewater treatment plants are located in or adjacent to agricultural lands. Adopting an optimization modelling approach can assist decision makers, ensuring their decisions will benefit the economy by incorporating global experiences to control water allocations in Iraq especially considering diminished water supplies.

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2019

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Review of the Quantitative Tradeoffs of Using Organic Residuals in Arid Agriculture

Description

Water reuse and nutrient recovery are long-standing strategies employed in agricultural systems. This is especially true in dry climates where water is scarce, and soils do not commonly contain the nutrients or organic matter to sustain natural crop growth. Agriculture

Water reuse and nutrient recovery are long-standing strategies employed in agricultural systems. This is especially true in dry climates where water is scarce, and soils do not commonly contain the nutrients or organic matter to sustain natural crop growth. Agriculture accounts for approximately 70% of all freshwater withdrawals globally. This essential sector of society therefore plays an important role in ensuring water sources are maintained and that the food system can remain resilient to dwindling water resources. The purpose of this research is to quantify the benefits of organic residuals and reclaimed water use in agriculture in arid environments through the development of a systematic review and case study. Data from the systematic review was extracted to be applied to a case study identifying the viability and benefits of organic residuals on arid agriculture. Results show that the organic residuals investigated do have quantitative benefits to agriculture such as improving soil health, reducing the need for conventional fertilizers, and reducing irrigation needs from freshwater sources. Some studies found reclaimed water sources to be of better quality than local freshwater sources due to environmental factors. Biosolids and manure are the most concentrated of the organic residuals, providing nutrient inputs and enhancing long-term soil health. A conceptual model is presented to demonstrate the quantitative benefits of using a reclaimed water source in Pinal County, Arizona on a hypothetical crop of cotton. A goal of the model is to take implied nutrient inputs from reclaimed water sources and quantify them against standard practice of using irrigated groundwater and conventional fertilizers on agricultural operations. Pinal County is an important case study area where farmers are facing cuts to their water resources amid a prolonged drought in the Colorado River Basin. The model shows that a reclaimed water source would be able to offset all freshwater and conventional fertilizer use, but salinity in reclaimed water sources would force a need for additional irrigation in the form of a large leaching fraction. This review combined with the case study demonstrate the potential for nutrient and water reuse, while highlighting potential barriers to address.

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2020

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Predicting De Facto Reuse Impacts on Drinking Water Sources at Small Public Water Systems

Description

De facto potable reuse (DFR) occurs when surface water sources at drinking water treatment plants (DWTPs) contain treated effluents from upstream wastewater treatment plants (WWTPs). Contaminants of emerging concerns (CECs) originate from treated effluents (e.g., unregulated disinfection by-products, pathogenic microorganisms

De facto potable reuse (DFR) occurs when surface water sources at drinking water treatment plants (DWTPs) contain treated effluents from upstream wastewater treatment plants (WWTPs). Contaminants of emerging concerns (CECs) originate from treated effluents (e.g., unregulated disinfection by-products, pathogenic microorganisms as Cryptosporidium oocyst, Giardia cyst, and Norovirus) can be present in surface water and pose human health risks linked to CECs. Previously developed De facto Reuse Incidence in our Nations Consumable Supply (DRINCS) model predicted DFR for the national largest DWTPs that serve >10,000 people (N = 2,056 SW intakes at 1,210 DWTPs). The dissertation aims to quantify DFR at all surface water intakes for smaller DWTPs serving ≤10,000 people across the United States and develop a programmed ArcGIS tool for proximity analysis between upstream WWTPs and DWTPs. The tested hypothesis is whether DWTPs serving ≤10,000 people are more likely to be impacted by DFR than larger systems serving > 10,000 people.The original DRINCS model was expanded to include all smaller DWTPs (N = 6,045 SW intakes at 3,984 DWTPs) in the U.S. First, results for Texas predicted that two-thirds of all SW intakes were impacted by at least one WWTP upstream. The level of DFR at SW intakes in Texas ranged between 1% to 20% under average flow and exceeded 90% during mild droughts. Smaller DWTPs in Texas had a higher frequency of DFR than larger systems while < 10% of these DWTPs employed advanced technology (AT) capable of removing CECs. Second, nationally over 40% of surface water intakes at all DWTPs were impacted by DFR under average flow (2,917 of 6,826). Smaller DWTPs had a higher frequency (1,504 and 1,413, respectively) of being impacted by upstream WWTP discharges than larger DWTPs. Third, the difference in DFR levels at smaller versus larger DWTPs was statistically unclear (t-test, p = 0.274). Smaller communities could have high risks to CECs as they rely on surface water from lower-order streams impacted by DFR. Furthermore, smaller DWTPs lack more than twice as advanced unit processes as larger DWTPs with 52.1% and 23%, respectively. DFR levels for DWTPs serving > 10,000 people were statistically higher on mid-size order streams (3, 5, and 8) than those for smaller DWTPs. Finally, DWTPs serving > 10,000 people could pose risks to a population impacted by DFR > 1% as 40 times as those served by smaller DWTPs with 71 million and 1.7 million people, respectively. The total exposed population to risks of CECs served by DWTPs impacted by upstream WWTP discharges (DFR >10%) was estimated at 12.3 million people in the United States. Future studies can use DRINCS results to conduct an epidemiological risk assessment for impacted communities and identify communities that would benefit from advanced technology to remove CECs.

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2020

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Hydrologic and Water Quality Modeling of a CAFO Dairy Lagoon

Description

In recent decades animal agriculture in the U.S. has moved from small, distributed operations to large, Concentrated Animal Feeding Operations (CAFOs). CAFOs are defined by federal regulations based on animal numbers and confinement criteria. Because of the size of these

In recent decades animal agriculture in the U.S. has moved from small, distributed operations to large, Concentrated Animal Feeding Operations (CAFOs). CAFOs are defined by federal regulations based on animal numbers and confinement criteria. Because of the size of these operations, the excessive amount of manure generated is typically stored in lagoons, pits, or barns prior to field application or transport to other farms. Water quality near CAFOs can be impaired through the overflow of lagoons, storm runoff, or lagoon seepage. Assessing water quality impacts of CAFOs in a modeling framework has been difficult because of data paucity. A CAFO lagoon module was developed to assess lagoon overflow risk, groundwater quality, and ammonia emissions of a dairy lagoon. A groundwater quality assessment of a Dairy Lagoon in Lynden Washington was used to calibrate and validate the groundwater quality model. Groundwater down stream of the lagoon was negatively impaired. The long-term effects of this lagoon on water quality were explored as well as the effectiveness of improving the lagoon lining to reduce seepage. This model can be used to improve understanding of the impacts of CAFO lagoon seepage and develop sustainable management practices at the watershed scale for these key components of the agricultural landscape.

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2021

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Comparative Exposure Assessment of Antibiotic Resistance Determinants in Biosolids in Fertilizer Application to Lettuce Crops

Description

Water is a scarce resource that is recycled through wastewater treatment plants (WWTPs) to help fulfill the demand for water. Agriculture is a large consumer of water, indicating that WWTP-treated water is proportionally applied to crops at a high rate.

Water is a scarce resource that is recycled through wastewater treatment plants (WWTPs) to help fulfill the demand for water. Agriculture is a large consumer of water, indicating that WWTP-treated water is proportionally applied to crops at a high rate. Recycled water is highly regulated but is capable of containing high-risk pathogens and contaminants despite the efforts of physical and microbial treatments throughout the WWTP process. WWTPs are also producers of biosolids, treated sewage sludge regulated by the EPA that can be applied in agricultural settings to act as a fertilizer. Biosolids are a useful fertilizer as they are rich in nitrogen and contain many beneficial nutrients for soil and crops. Due to biosolids being a by-product of recycled water, they are susceptible to containing the same pathogens and contaminants that can be transferred in the WWTP systems. Antibiotic resistance (AR) is an ever-growing threat on a global scale and is one of the areas of concern for consideration of pathogen spread from WWTPs. Antibiotic resistance bacteria, created through mutation of bacterial plasmids producing antibiotic resistance genes (ARGs), have been quantified and studied to help mitigate the risk posed by continued AR spread in the environment. This study aims to produce a comprehensive collection of quantified ARG concentration data in biosolids, as well as producing a QMRA model integrating Monte Carlo distributions to provide groundwork for understanding of the direct dosage and consumption of ARGs to the standard U.S. citizen. The study determined that sul1, sul2, tetM, and tetO are ARGs of high concern in biosolid samples based on current concentration data of biosolid samples. The resulting dose models and gene concentration distributions provide data to support the need to mitigate AR risk presented by agricultural biosolid application.

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2022-05