Generalized Approach to Integrated Modeling of Watershed, Waterbody, and BMP Optimization

GAIM stands for the Generalized Approach to Integrated Modeling of Watershed, Waterbody, and BMP Optimization.

Researchers who are interested in mitigating harmful algal blooms through modeling simulations and optimization process for selecting and placing nutrient management strategies.

For HydroModelMatch, there is no requirement to upload any files, instead, you can select the specific model features that best fit your interests on the HydroModelMatch webpage.

For AquaNutriOpt, two files are required to upload:

1. A hydrologic network CSV file (including nutrient transport network, nutrient loads at each reach, land use types, etc.)
2. A BMP database CSV file (including cost and nutrient removal efficiency).

Users can download or view the User Guide, which provides detailed guidance on applying the GAIM approach to any case.

Users can browse the comprehensive Model Library, which contains useful information on a wide range of watershed and waterbody simulation models.

The AquaNutriOpt App can be used to find a spatially optimized configuration of nutrient management practices implementation.

We provide a default database of nutrient management practices in the APPS tab. Users can also add their own strategies to this database. These practices include storm retention Best Management Practices (BMPs), fertility BMPs, water control structures, and so on. More information can be found in AquaNutriOpt's User Guide.

AquaNutriOpt formulates the nutrient management problem as a mixed-integer combinatorial optimization linear program (MILP), where the goal is to minimize phosphorus and/or nitrogen loads at the outlet target (lake or basin) under budget constraints. Depending on user’s selection, the tool can perform either a single-objective optimization (phosphorus removal or nitrogen removal) or a multi-objective optimization (simultaneous phosphorus and nitrogen removal, generating trade-offs). The solver then identifies the optimal set and spatial placement of BMPs across the watershed. It can incorporate varying nutrient load inputs as parameters and provide robust, forward-looking BMP implementation strategies.

Yes. Users can define multiple budget scenarios, time periods, and optimization objectives, and the tool can compare results across these scenarios. The visualization module and text-based outputs enable direct comparison of nutrient reduction outcomes, BMP distributions, and cost trade-offs between single-objective and multi-objective runs.

Watershed boundaries are extracted from the watershed model where the specific watershed model delineates the study area and identifies the watershed boundary. These boundaries are defined using inputs from hydrological models (WAM, SWAT or any other simulation software).

Users are encouraged to create an account, but the app can also be accessed without registering for one.

For HydroModelMatch, there is no specific requirement for software and hardware. However, if you want to use the Python version of HydroModelMatch, any version of Python will be required.

For AquaNutriOpt, the core codes and binary files (excluding dependency packages such as pandas, numpy, PuLP, CBC solver etc., and visualization packages like GDAL and GeoPandas) are approximately 4 MB. However, after installing all other necessary dependencies, the complete software will be large.

The tutorials provide step-by-step instructions for using the main website, the model library, and the two main applications of the GAIM approach (e.g., HydroModelMatch and AquaNutriOpt) through a case study.

 The app was specifically designed to help users select a watershed and/or waterbody model that best suits user’s needs.

Information is available in the Sections 1.2  Model Catalog and 4.2 Input File Needed of the HydroModelMatch's User Guide.