An Agent based Simulation of the Forest Water People Nexus; Simulating the complex system of hydrological processes, human decision making, and land use changes in the context of coffee farming in the tropical agroforest ed region of Sumberjaya, Lamp

Abstract
Global warming poses significant challenges to the global climate system, leading to disruptions in precipitation patterns and hydrological systems , and intensifying the frequency and severity of extreme water related events such as floods and droughts. The consequences extend beyond hydrological imbalances, as they can trigger conflicts over wat er allocation, limit economic growth in developing nations, and impact food availability. As future projections indicate a grim outlook, there is an urgency for effective water management strategies, particularly in vulnerable regions. This requires a science based understanding of the complex interactions between water cycles, forests, and humans. While models that simulate hydrological systems and human decision making already exist, they do not bridge the gap between biophysical and socio economic processes. Th e aim of this thesis is to explore the potential of spatial simulation in bridging this gap by building and evaluating a n agent based simulation of the complex system of forest , water, and people, that allows for the exploration of system dynamics and inter actions. Coffee farming in the catchment area of the Way Besai River in Sumberjaya, Lampung, Indonesia is used as context for building the simulation. A structured literature study guided by the ARDI method is used to establish the conceptual framework for the simulation , and functionality of existing models such as GenRiver and Consumat are used to guide the implementation of system dynamics. This thesis resulted in a functional Netlogo simulation that maintains a complex system , in which many microscale dynamics and interactions form larger scale patterns. Testing results show no major system escalations, realistic water distribution patterns, and stable peer networks Emergent patterns are overall explainable, and the simulation shows logical responses to triggers and manipulation of variables. Th e results, however, also show challenges : they suggest a large effect of conceptual assumptions and model ling decisions on the output, processes being overshadowed by modelling limitations, and unrealistically high odds of prosperity for farmers due to large land holdings. Furthermore, slow simulation speed and memory intensive processes significantly limit simulation options and use cases. Overall, this thesis shows a promising outlook for spatial, agent based simulation of complex human environment systems, but future development is needed to fine tune system interactions and to address modelling limitations.

Keywords: Complex systems, A gent based simulation, Human environment interactions, Hydrology Land use decisions, Pe er networks, GenRiver, Consumat