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

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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.
Date Created
2020-05
Agent

Impacts of new crop portfolios on water consumption in Maricopa County

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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%.
Date Created
2020-05
Agent

Optimization Models for Iraq’s Water Allocation System

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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.
Date Created
2019
Agent

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

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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.
Date Created
2018
Agent

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.

Date Created
2017
Agent

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

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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.

Date Created
2017
Agent
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