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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
31

Water Risk Assessment of Agricultural Raw Materials in a Global Supply Chain : A Case Study of IKEA / Bedömning av vattenrisker för jordbruksråmaterial i en global värdekedja : En fallstudie på IKEA

Berggren, Victoria January 2022 (has links)
Current mass consumption and production patterns have led to an unsustainable use of natural resources, including freshwater, which is one the most crucial natural resources for people and the planet. Agricultural production systems are alone responsible for 72 percent of all global water withdrawals. Therefore, companies with an agricultural supply chain, such as IKEA, play an important role in minimising the negative impacts on water due to agricultural production. In order to do so, companies need to conduct assessments to become aware of their contribution and thereafter develop water targets and strategies on how to mitigate and minimise the company’s water impacts. Several different guidances, methodologies, and tools aiding companies in how to do this have recently been developed, however there is not yet one common established methodology. Therefore, this research project aimed to test and evaluate a new assessment methodology and tool for IKEA, by conducting a water risk assessment on water availability of the sourcing locations of two of IKEA’s key agricultural raw materials: soy and palm oil, and identifying mitigation possibilities, in order to aid in the company’s further work with achieving a sustainable water management and material sourcing, and developing water targets and strategies. Soy is a prioritised raw material to work with in terms of environmental and social risk, and through the conducted water risk assessment, a high risk for water depletion was identified in many of the company’s most likely sourcing locations. The water risk assessment results for palm oil indicated no significant risk for water depletion in any of the sourcing locations. The high water depletion risk scores of the hotspots were found to most likely be due to several different causes, both climatic conditions and anthropogenic activities, including agriculture. Therefore, it was identified that there are possibilities for a company, such as IKEA, to aid in mitigating the water availability challenge of the hotspots through the company’s agricultural supply chain. For example, a few agricultural management practices for increasing the water use efficiency suitable for the different hotspots could be recommended and incentivised by the company to the local farmers of the hotspot sourcing locations. The WRA methodology used in this research project, following the guidance for setting enterprise water targets by Reig et al. (2021), was assumed suitable for IKEA to use and incorporate into a more comprehensive environmental assessment methodology for agricultural raw materials in order to develop water targets and strategies. The Aqueduct Food tool was assumed to be a robust tool for water risk assessment, and can be a suitable tool for IKEA to use to quickly gain a high-level picture of a material, location or water risk of specific interest. The water risk assessment results will mainly be useful in the future, when more comprehensive environmental assessments of agricultural raw materials have been conducted, and the water use has been assessed to a greater extent. Future research is needed to be conducted in order to confirm the results and recommendations of this research project, as well as to further complement the results for the needs of IKEA. This future research includes conducting field studies of the identified hotspots and the operations of the local farms, and conducting an equivalent water risk assessment of the two materials and sourcing locations on the water quality. / Nuvarande masskonsumtion och produktionsmönster har lett till en ohållbar användning av naturresurser, inklusive sötvatten, som är en av de mest avgörande naturresurserna för människor och planeten. Jordbruk står ensam för 72 procent av alla globala vattenuttag. Därför har företag med en jordbruksförsörjningskedja, som IKEA, en viktig roll i att hjälpa till att minska de negativa effekterna på vatten från jordbruk. För att kunna göra det behöver företag utföra bedömningar för att bli medvetna om sin vattenpåverkan och därefter utveckla vattenmål och strategier för hur de kan minimera den påverkan. Det har nyligen utvecklats flera olika vägledningar, metodiker och verktyg som hjälper företag att göra detta, men det finns ännu inte en gemensam etablerad metodik. Därför hade detta forskningsprojekt som syfte att testa och utvärdera en ny bedömningsmetodik och ett nytt verktyg för IKEA, genom att genomföra en riskbedömning av vattentillgången för produktionsplatserna för två av IKEAs viktigaste jordbruksråmaterial: soja och palmolja, och genom en litteraturstudie identifiera möjligheter att minska vattenpåverkan, för att bidra till företagets fortsatta arbete med att uppnå en hållbar vattenanvändning och materialförsörjning i jordbruksförsörjningskedjan och att utveckla vattenmål och strategier. Soja är ett prioriterat råmaterial att arbeta med gällande miljömässiga och sociala risker, och genom den genomförda bedömningen av vattenrisker identifierades en hög risk för vattenbrist på många av de produktionsplatser som företaget mest troligen köper in ifrån. Riskbedömningsresultaten för palmolja indikerade ingen signifikant risk för vattenbrist på någon av de produktionsplatser som företaget troligen köper in ifrån. Den höga risken för vattenbrist i de identifierade hotspotsen visade sig troligen bero på flera olika orsaker, både klimatförhållanden och antropogena aktiviteter, inklusive jordbruk. Därför identifierades det att det finns möjligheter för ett företag, som IKEA, att kunna hjälpa till att mildra vattentillgänglighetsutmaningen i hotspotsen genom företagets jordbruksförsörjningskedja. Till exempel kan ett par olika jordbruksförvaltningsmetoder för att öka vattenanvändningseffektiviteten som är lämpliga för de olika hotspotsen rekommenderas och uppmuntras av företaget till de lokala bönderna. Den WRA-metodik som används i detta forskningsprojekt, som följde vägledningen för att sätta upp vattenmål för företag av Reig et al. (2021), antogs lämplig för IKEA att använda och integrera i en mer omfattande miljöbedömningsmetodik för jordbruksråmaterial för att utveckla vattenmål och strategier. Aqueduct Food-verktyget antogs vara ett robust verktyg för riskbedömning för vatten och kan vara ett lämpligt verktyg för IKEA att använda för att snabbt få en översikt av ett material, en plats eller en vattenrisk av specifikt intresse. Riskbedömningsresultaten kommer främst att vara användbara i framtiden, när mer omfattande miljöbedömningar av jordbruksråvaror har gjorts och vattenanvändningen har bedömts i större utsträckning. Framtida forskning behövs för att bekräfta resultaten och rekommendationerna i detta forskningsprojekt, samt för att ytterligare komplettera resultaten för IKEAs behov. Denna framtida forskning inkluderar att genomföra fältstudier av de identifierade hotspotsen och de lokala sojafarmernas verksamhet, och att genomföra en likvärdig riskbedömning för vatten av de två materialen och produktionsplatserna som utförts i detta forskningsprojekt för vattenkvaliteten.
32

Nonpoint Source Pollutant Modeling in Small Agricultural Watersheds with the Water Erosion Prediction Project

Ryan McGehee (14054223) 04 November 2022 (has links)
<p>Current watershed-scale, nonpoint source (NPS) pollution models do not represent the processes and impacts of agricultural best management practices (BMP) on water quality with sufficient detail. To begin addressing this gap, a novel process-based, watershed-scale, water quality model (WEPP-WQ) was developed based on the Water Erosion Prediction Project (WEPP) and the Soil and Water Assessment Tool (SWAT) models. The proposed model was validated at both hillslope and watershed scales for runoff, sediment, and both soluble and particulate forms of nitrogen and phosphorus. WEPP-WQ is now one of only two models which simulates BMP impacts on water quality in ‘high’ detail, and it is the only one not based on USLE sediment predictions. Model validations indicated that particulate nutrient predictions were better than soluble nutrient predictions for both nitrogen and phosphorus. Predictions of uniform conditions outperformed nonuniform conditions, and calibrated model simulations performed better than uncalibrated model simulations. Applications of these kinds of models in real-world, historical simulations are often limited by a lack of field-scale agricultural management inputs. Therefore, a prototype tool was developed to derive management inputs for hydrologic models from remotely sensed imagery at field-scale resolution. At present, only predictions of crop, cover crop, and tillage practice inference are supported and were validated at annual and average annual time intervals based on data availability for the various management endpoints. Extraction model training and validation were substantially limited by relatively small field areas in the observed management dataset. Both of these efforts contribute to computational modeling research and applications pertaining to agricultural systems and their impacts on the environment.</p>
33

<strong>Agbufferbuilder for decision support in the collaborative design of variable-width conservation buffers in the Saginaw Bay watershed</strong>

Patrick T Oelschlager (16636047) 03 August 2023 (has links)
<p>Field-edge buffers are a promising way to address nonpoint source pollution from agricultural runoff, but concentrated runoff flow often renders standard fixed-width linear buffers ineffective. AgBufferBuilder (ABB) is a tool within ESRI ArcMap Geographic Information Systems software that designs and evaluates targeted, nonlinear buffers based on hydrologic modeling and other field-specific parameters. We tested ABB on n=45 Areas of Interest (AOIs) stratified based on estimated sediment loading across three sub-watersheds within Michigan’s Saginaw Bay watershed to evaluate the effectiveness of ABB relative to existing practices across a wide range of landscape conditions. We modeled tractor movement around ABB buffer designs to assess more realistic versions of the likely final designs. ABB regularly failed to deliver the desired 75% sediment capture rate using default 9 m x 9 m output raster resolution, with Proposed buffers capturing from 0% to 68.49% of sediment within a given AOI (mean=37.56%). Differences in sediment capture between Proposed and Existing buffers (measured as Proposed – Existing) ranged from -48% to 66.81% of sediment (mean=24.70%). Proposed buffers were estimated to capture more sediment than Existing buffers in 37 of 45 AOIs, representing potential for real improvements over Existing buffers across the wider landscape. In 13 of 45 AOIs, ABB buffers modified for tractor movement captured more sediment than Existing buffers using less total buffer area. We conducted a collaborative design process with three Saginaw Bay watershed farmers to assess their willingness to implement ABB designs. Feedback indicated farmers may prefer in-field erosion control practices like cover cropping and grassed waterways over field-edge ABB designs. More farmer input is needed to better assess farmer perspectives on ABB buffers and to identify preferred data-based design alternatives. Engineered drainage systems with raised ditch berms and upslope catch basins piped underground directly into ditches were encountered several times during site visits. ABB only models surface flow and does not recognize drain output flow entering waterways. Modified ABB functionality that models buffers around drain inlets would greatly improve its functionality on drained sites. This may be accomplishable through modification of user-entered AOI margins but requires further investigation. Unfortunately, the existing tool is built for outdated software and is not widely accessible to non-expert users. We suggest that an update of this tool with additional functionality and user accessibility would be a useful addition in the toolbox of conservation professionals in agricultural landscapes.</p>

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