A Hetero-functional Graph State Estimator for Watershed Systems: Application to the Chesapeake Bay

TL;DR

This paper presents a novel hetero-functional graph state estimator framework for watershed systems, enabling integrated analysis of natural and institutional interdependencies, demonstrated through Chesapeake Bay case study.

Contribution

It introduces a region-independent architecture and extends Hetero-functional Graph Theory for nutrient flow estimation in watershed management.

Findings

Effective nutrient flow estimation from uncertain data

Framework supports integration of ecological, economic, and governance systems

Demonstrated applicability to Chesapeake Bay Watershed

Abstract

Regional watersheds are complex systems of systems encompassing hydrology, land-use decision-making, estuarine ecological feedbacks, and overlapping governance jurisdictions. Their effective management underlies many modern societal challenges and therefore requires models that capture interdependencies between natural and institutional systems. Regional-specific models such as the Chesapeake Assessment Scenario Tool, used in this paper's case study, provide valuable nutrient estimates but rely on structurally opaque watershed routing that limits integration into broader systems-level analyses. This paper introduces a modeling framework for watershed systems. First, a region-independent reference architecture is developed. Second, the Weighted Least Squares Error Hetero-functional Graph State Estimator, an extension of Hetero-functional Graph Theory (HFGT), is adapted to estimate nutrient flows from uncertain data. The framework is demonstrated through instantiation in the Chesapeake Bay Watershed. By establishing a shared ontology grounded in Systems Modeling Language and HFGT, the approach enables integration of economic and governance systems to support sustainable watershed management.