Location: Agroecosystems Management Research
Project Number: 5030-13000-011-64-N
Project Type: Non-Funded Cooperative Agreement
Start Date: Jul 1, 2018
End Date: Jun 30, 2020
1. Feature the Big Creek watershed as a case study to create and demonstrate an economic optimization tool and protocol for use with the USDA Agricultural Conservation Planning Framework (ACPF) that will allow users to: 1) determine the least-cost combination of conservation practices for achieving different nutrient reduction goals, or 2) given a budget constraint, find the combination of conservation practices that offer the maximum estimated nutrient reductions (initially focusing on nitrate reduction); 2. Make a financial optimization add-on module to complement the existing ACPF toolset; and 3. Develop online programming to train users on the ACPF-compatible optimization module.
1. Watershed conditioning: First, the Big Creek watershed will be hydro-conditioned for use with the ACPF toolset to identify spatial locations for various watershed scale scenarios utilizing differing sets of conservation practices offered within the toolbox. This stage will also utilize newly available Iowa Best Management Practice (BMP) Mapping Project data (state-wide digitization of existing BMPs) so that land use scenarios can be scaled by existing conservation efforts. 2. Assigning cost to nitrate reductions: Develop a Geographic Information System that combines the ACPF conservation mapping with the direct costs of any given conservation practice along with a weighted soil rent estimate of opportunity costs for practices that require cropland retirement. This will then be used in combination with the multiplicative spreadsheet method developed by Tomer et al.  to track and aggregate expected field-level nutrient reductions as per ACPF land use scenarios. This step will allow an assessment of the total costs of each scenario and the cost-effectiveness of different arrangements of conservation practices. 3. Optimization: Develop a linear programming (optimization) approach compatible with ACPF output that utilizes our cost-effectiveness data layer (step 2) so as to either: 1) find least cost combinations of land use to achieve a given level of nitrate reduction, or 2) achieve the maximum amount of nitrate reductions given a limited budget. We will use linear programming optimization tools within the "CPLEX" Python Application Programming Interface (API), and develop a module that can be used in concert with the ACPF toolbox. Linear programming is a mathematical approach to optimizing minimization/maximization situations subject to various contextualizing constraints used extensively in engineering, economics, and resource management situations when allocation of scarce resources is key to solution-oriented management.