Assessing Impacts of Decision-Making Theories on Agrohydrological
Networks Using Agent-Based Modelling.
Abstract
Water scarcity, population growth and climate change dilemmas
imperatively require adaption strategies for a more efficient and
sustainable use of water resources. Agricultural systems are part of a
wider network, where all social, economic and, ecologic parameters must
be taken into consideration to assess the performance and resilience of
said network. The importance of accounting the complexity of human
decisions and their impact on the water cycle has been increasingly
studied, nevertheless the integration and analysis of different decision
making theories into hydrological models still remains a major challenge
and uncertainty source. Therefore, the ongoing project is aimed to
improve the understanding of social dynamics in agrohydrological
networks by assessing different irrigation practices including rainfed
agriculture and deficit irrigation within a hydro-economic network. We
developed an agent-based model (ABM) of farmer decision making on crop
water productivity and groundwater levels using two existing
optimization models: (i) the Assessment, Prognosis, Planning and
Management Tool (APPM) (Schmitz, et al. 2010) that integrates the
complex interactions of the strongly nonlinear meteorological,
hydrological and agricultural phenomena, considering the socio-economic
aspects and (ii) the Deficit Irrigation Toolbox (DIT) (Schütze and
Mialyk 2019) to maximize crop-water productivity by analyzing the crop
yield response to climate change, soil variability, water management
practices. The developed ABM was assessed with the different theories on
human decision-making based on the Modelling Human Behavior (MoHuB)
framework (Schlüter, et al. 2017). As a result of this study, a
sensitivity analysis of how different behavioral theories affect the
dynamics of social-ecological systems which enables the evaluation of
the robustness of policy implementation to different assumptions of
human behavior where cooperation is a mechanism to improve resilience.
This research was funded by the Technische Universität Dresden, by means
of the Excellence Initiative by the German Federal and State
Governments.