Coupled Human and Natural Systems Projects

Project Title: Modeling Reservoir Operators as Autonomous Agents

Project Overview: This project aims to model reservoir operations as per water control manuals to gain understanding about multi-level institutional decision-making. This project fits into the Coupled Human and Natural Systems and Crosscuts research themes.

Funding: Funding for this project is provided by CAREER award.

Key Collaborators: U.S. Bureau of Reclamation

Lab Participants:

• Kendra Kaiser
• Lejo Flores

Needs:

1. Reservoir operations are often calibrated out of physically based hydrologic models, or optimized in systems models, this does not reflect the reality of day-to-day reservoir operations.
2. Understanding the institutional and social norms that influence reservoir operations will be important for assessing how operations might react to changing environmental conditions

Objectives and Hypothesis:

• Objective: characterize how reservoir operators are using discretion to operate the system of reservoirs in the Upper Boise Basin
• Hypothesis: The water control manual is not sufficiently detailed to re-create actual operations, rather, additional complex institutional norms and standards influence storage and discharge

Tools, models, datasets: This research has built a model of the Upper Boise Basin reservoir system in R using USBR data.

Expected outcomes and deliverables:  Potential outcomes from this research/project include a published paper and open source model.

Key words: water management, human decision-making, reservoir operations

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Project Title: Policy and Management Impacts on Forest Ecohydrologic Processes

Project Overview: The overall goal of this project is to link macro scale policy changes to forest management implementation and the resultant changes to land surface energy budget, forest structure, and ecohydrological processes. This project aims to incorporate more realistic representations of land policy and land management into land surface models.

Funding: NSF CAREER: Citizens, Conservation, and Climate: Research & Education for Climate Legacy in Managed Landscapes grant.

Key collaborators

• Dr. Jackie Shuman (National Center for Atmospheric Research)
• Dr. Trevor Caughlin (Boise State University, Department of Biology)
• Dr. Vicken Hillis (Boise State University, Department of Human Environment Systems)

Lab Participants

• Dr. Lejo Flores (PI/Advisor)
• Katie Murenbeeld (PhD dissertation)
• Dr. Kendra Kaiser

Needs:

1. As land surface models have become more computationally efficient there is a need to better incorporate realistic and theory grounded policy and management practices
2. Understanding of the impact of time lags between policy and management implementation on forest characteristics
3. The Intermountain West is a region undergoing rapid population growth is also a region with changing fire return intervals. Therefore one needs to:
   1. Understand the regional climate and hydrologic implications of changes to forest structure in order to,
   2. Make informed decisions about how to adaptively manage for forests that are resilient to disturbances (fire, insects, disease)

Research Questions:

• How have forest management policies changed through time and how have those changes impacted forest management practices?
• What are the cumulative effects of multiple forest management practices, through vegetation removal, addition, or changing plant types, on ecohydrologic processes (water yield)?
• How do forest management practices impact forest resilience in the face of natural or man-made disturbances and a changing climate and how will a changing climate subsequently impact management activities?

Tools, models and datasets:

This research uses:

• The Functionally Assembled Terrestrial Ecosystem Simulator (FATES) module of the Community Land Model (CLM)
• Forest Service activity and treatment data

Expected Outcomes and Deliverables:

Potential outcomes for this research includes:

• An example model framework for incorporating policy dynamics into land surface models

Key words: forest management, land surface models, policy theory

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Project Title: Land Use and Land Cover change in the Snake River Basin, Idaho

Project Overview: This project aims to create an agent-based model of land cover and land use change in the Snake River Basin in such a way that modeling components will be module, scalable and extensible. This project fits into the Coupled Human and Natural Systems research theme.

Funding: Funding for this project is provided by the Pacific Northwest National Lab, Department of Energy

Key Collaborators: Pacific Northwest National Lab

Lab Participants:

• Kendra Kaiser
• Lejo Flores

Needs:

1. Land use change (LUC) is a combination of global influences and local manifestations and constraints of those influences. While top-down approaches offer a key advantage of capturing how global economic and political factors influence LULC, they are associated with key limitations. Specifically, it is computationally infeasible to simultaneously capture regional, or even individual-level, constraints on LULC change which results in a lack of detail regarding the spatial extent, organization, and other geospatial features (i.e., patch size distribution, etc.) of land cover categories.
2. Allowing for stochasticity and variation in the decision making process will allow for the creation of multiple plausible realizations of LULC change and the analysis of variability across all realizations. 

Research Questions: 

• How many agents are needed to represent regional-scale heterogeneity in LULCC decision-making?
• What scaling methodologies would best represent sub-grid heterogeneity?

Tools, models, datasets: This research will develop an Agent- Based model of land use and land cover change in python and use various global forcings from the Global Change Assessment Model (GCAM). This work relies heavily on the Crop Data Layer and the National Agricultural Statistics Service from the USDA. 

Expected Outcomes and Deliverables: Outcomes from this research include publications, open source agent-based modelling code.

Key words: land use land cover change, decision-making, global change

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