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1. Applying a Coupled Hydrologic-Economic Modeling Framework: Evaluating Alternative Options for Reducing Impacts for Downstream Locations in Response to Upstream Development

   https://doi.org/10.3390/su14116630  

   Amaya, Maria; Duchin, Faye; Hester, Erich; Little, John C. (June 2022, Sustainability)

   Economic input-output and watershed models provide useful results, but these kinds of models do not use the same spatial units, which typically limits their integration. A modular hydrologic-economic modeling framework is designed to couple the Rectangular Choice-of-Technology (RCOT) model, a physically constrained, input-output (I-O) model, with the Hydrological Simulation Program-Fortran (HSPF). Integrating these two models can address questions relevant to both economists and hydrologists, beyond addressing only administrative or watershed concerns. This framework is utilized to evaluate alternative future development prospects within Fauquier County, northern Virginia, specifically residential build-up, and agricultural intensification in the upstream location of the local watershed. Scenarios are designed to evaluate the downstream impacts on watershed health caused by upstream development and changes made within the economic sectors in response to these impacts. In the first case, an alternative residential water technology is more efficient than the standard for ensuring adequate water supply downstream. For scenarios involving upstream agricultural intensification, a crop shift from grains to fruits and vegetables is the most efficient of the alternatives considered. This framework captures two-way feedback between watershed and economic systems that expands the types of questions one can address beyond those that can be analyzed using these models individually. 

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2. A Coupled Hydrologic-Economic Modeling Framework for Scenario Analysis

   https://doi.org/10.3389/frwa.2021.681553  

   Amaya, Maria; Baran, Ayden; Lopez-Morales, Carlos; Little, John C. (June 2021, Frontiers in Water)

   null (Ed.)

   To capture the interactions between hydrologic and economic systems necessary for modeling water quality at a sufficient level of spatial detail, we have designed a modular framework that couples an economic model with a watershed model. To represent the economic system, the Rectangular Choice-of-Technology (RCOT) model was used because it represents both the physical and monetary aspects of economic activities and, unlike traditional input-output or general equilibrium models, it can optimize choices among operational technologies in addition to the amount and location of production. For the first implementation of this modeling framework, RCOT is coupled with a watershed model, Hydrological Simulation Program-Fortran (HSPF), which was calibrated to represent Cedar Run Watershed in northern Virginia. This framework was used to analyze eight scenarios related to the expansion of agricultural activity in Fauquier County. The database for RCOT used county-level input-output data representative of the region in 2012. Thus, when crop farming was expanded to fully utilize the farmland available in the watershed, the nitrogen concentration at the outflow of the watershed increased from 0.6 to 4.3 mg/L. However, when RCOT could select between a standard and a more nitrogen-efficient management practice, the outflow nitrogen concentration only increased to 2.6 mg/L because RCOT selected the more resource-efficient practice. Building on this modular framework, future work will involve designing more realistic scenarios that can test policy options and regional planning decisions in a wide range of watersheds. 

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3. River flow decline across the entire Arkansas River Basin in the 21st century

   https://doi.org/10.1016/j.jhydrol.2023.129253  

   Yang, Jia; Zou, Chris; Will, Rodney; Wagner, Kevin; Ouyang, Ying; King, Chad; Winrich, Abigail; Tian, Hanqin (March 2023, Journal of Hydrology)

   The Arkansas River and its tributaries provide critical water resources for agricultural irrigation, hydropower generation, and public water supply in the Arkansas River Basin (ARB). However, climate change and other environmental factors have imposed significant impacts on regional hydrological processes, resulting in widespread ecological and economic consequences. In this study, we projected future river flow patterns in the 21st century across the entire ARB under two climate and socio-economic change scenarios (i.e., SSP2-RCP45 and SSP5-RCP85) using the process-based Dynamic Land Ecosystem Model (DLEM). We designed “baseline simulations” (all driving factors were kept constant at the level circa 2000) and “environmental change simulations” (at least one driving factor changed over time during 2001–2099) to simulate the inter-annual variations of river flow and quantify the contributions of four driving factors (i.e., climate change, CO2 concentration, atmospheric nitrogen deposition, and land use change). Results showed that the Arkansas River flow in 2080–2099 would decrease by 12.1% in the SSP2-RCP45 and 27.9% in the SSP5-RCP85 compared to that during 2000–2019. River flow decline would occur from the beginning to the middle of this century in the SSP2-RCP45 and happen throughout the entire century in the SSP5-RCP85. All major rivers in the ARB would experience river flow decline with the largest percentage reduction in the western and southwestern ARB. Warming and drying climates would account for 77%–95% of the reduction. The rising CO2 concentration would exacerbate the decline through increasing foliage area and ecosystem evapotranspiration. This study provides insight into the spatial patterns of future changes in water availability in the ARB and the underlying mechanisms controlling these changes. This information is critical for designing watershed-specific management strategies to maintain regional water resource sustainability and mitigate the adverse impacts of climate changes on water availability. 

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4. Cross-watershed leakage of agricultural nutrient runoff

   https://doi.org/10.1088/1748-9326/ad4e4a  

   Akinyemi, Taiwo; Elbakidze, Levan; Xu, Yuelu; Gassman, Philip_W; Yen, Haw; Arnold, Jeffrey_G (June 2024, Environmental Research Letters)

   Abstract Agricultural nutrient runoff has been a major contributor to hypoxia in many downstream coastal ecosystems. Although programs have been designed to reduce nutrient loading in individual coastal waters, cross watershed interdependencies of nutrient runoff have not been quantified due to a lack of suitable modeling tools. Cross-watershed pollution leakage can occur when nutrient runoff moves from more to less regulated regions. We illustrate the use of an integrated assessment model IAM that combines economic and process-based biophysical tools to quantify Nitrogen loading leakage across three major US watersheds. We also assess losses in consumer and producer surplus from decreased commodity supply and higher prices when nutrient delivery to select coastal ecosystems is restricted. Reducing agricultural N loading in the Gulf of Mexico by 45% (a) increases loading in the Chesapeake Bay and Western Lake Erie by 4.2% and 5.5%, respectively, and (b) results in annual surplus losses of $7.1 and $6.95 billion with and without restrictions on leakage to the Chesapeake Bay and Lake Erie, respectively. 

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5. Assessing Multi‐Dimensional Impacts of Achieving Sustainability Goals by Projecting the Sustainable Agriculture Matrix Into the Future

   https://doi.org/10.1029/2022EF003323  

   Kyle, Page; Ollenburger, Mary; Zhang, Xin; Niazi, Hassan; Durga, Siddarth; Ou, Yang (October 2023, Earth's Future)

   Abstract The concept of sustainability inherently spans multiple spatial scales, sectors, variables, and time horizons. This study links a recently developed method of assessing present‐day agricultural sustainability across environmental, economic, and social dimensions with a process‐based integrated assessment model, in order to allow forward‐looking analysis of sustainability by region and scenario. The sustainable agriculture matrix estimates present‐day agricultural sustainability at the national level using 18 indicator variables, of which this study estimates nine to the year 2100, using an enhanced version of the Global Change Analysis Model. Scenarios include a reference scenario, and scenarios that apply the following measures, both individually and in combination, that are thought to improve sustainability: yield intensification, transition toward more plant‐based (“flexitarian”) diets, and economy‐wide greenhouse gas emissions mitigation. The scenarios illustrate considerable complexity and tradeoffs inherent to efforts to improve agricultural sustainability in all regions globally. For example, yield intensification typically increases nitrogen pollution, flexitarian diets can reduce agricultural output, and greenhouse gas mitigation efforts may either increase deforestation or crowd out crop and livestock production due to consequent bioenergy demands. However, there is considerable inter‐regional heterogeneity in the responses, and the importance of such secondary responses also differs by region. The analysis and post‐processing methods developed in this study allow quantification and visualization of the absolute and relative magnitude of the tradeoffs between agricultural sustainability indicator variables across regions, time periods, and scenarios. 

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