GEB v0.1: A large-scale agent-based socio-hydrological model – simulating 10 million individual farming households in a fully distributed hydrological model
TLDR
The Geographical, Environmental and Behavioural model (GEB) as discussed by the authors is a coupled agent-based hydrological model that simulates the behaviour and daily bi-directional interaction of up to ~10 million individual farm households with the hydrologogical system on a personal laptop.Abstract:
Abstract. Humans play a large role in the hydrological system; for example, by extracting large amounts of water for irrigation, often resulting in water stress and ecosystem degradation. By implementing large-scale adaptation measures, such as the construction of irrigation reservoirs, water stress and ecosystem degradation can be reduced. Yet we know that many decisions, such as the adoption of more effective irrigation techniques or changing crop types, are made at the farm level by a heterogeneous farmer population. While these decisions are often advantageous for an individual farmer or their community, detrimental effects are frequently experienced downstream. Therefore, to fully comprehend how the human-natural water system evolves over time and space, and to explore which interventions are suitable to reduce water stress, it is important to consider human behaviour and feedbacks to the hydrological system simultaneously at the local household and large basin scales. Therefore, we present the Geographical, Environmental and Behavioural model (GEB), a coupled agent-based hydrological model that simulates the behaviour and daily bi-directional interaction of up to ~10 million individual farm households with the hydrological system on a personal laptop. GEB is dynamically linked with the spatially distributed grid-based hydrological model CWatM at 30’’ resolution (< 1 km at the equator). Because many small-holder farmer fields are much smaller than 1×1 km, CWatM was specifically adapted to implement dynamically sized hydrological response units (HRUs) at the farm level, providing each agent with an independently operated hydrological environment. While the model could be applied globally, we explore its implementation in the heavily managed Krishna basin in India, which encompasses ~8 % of India’s land area and ~11.1 million farmers. Here, we show how six combinations of storylines with endogenous and exogenous drivers of adaptation affect both the hydrological system and the farmer population. read more
Citations
More filters
Journal ArticleDOI
A coupled agent-based model to analyse human-drought feedbacks for agropastoralists in dryland regions
Ileen Streefkerk,Jens de Bruijn,Toon Haer,Anne Van Loon,E. A. Quichimbo,Marthe L. K. Wens,Khalid Hassaballah,Jeroen C. J. H. Aerts +7 more
TL;DR: In this article , the authors present a dynamic adaptation model for agropastoral communities in dryland regions in Kenya, which combines socio-hydrological and agent-based modeling approaches.
Journal ArticleDOI
A coupled agent-based model for France for simulating adaptation and migration decisions under future coastal flood risk
Lars Tierolf,Toon Haer,W. J. Wouter Botzen,Jens de Bruijn,Marijn J. Ton,Lena Reimann,Jeroen C. J. H. Aerts +6 more
TL;DR: In this article , an integrated flood damage and agent-based model (ABM) with a gravity model of internal migration and a flood risk module (DYNAMO-M) was used to project household adaptation and migration decisions under increasing coastal flood risk in France.
Related Papers (5)
Evaluation of Supplying Instream Flow by Operation Rule Curve for Heightening Irrigation Reservoir
Jae-Nam Lee,Jae-Kyoung Noh +1 more
Variation of water supply for instream flow from reservoirs with various magnifications of paddy irrigation area to watershed area
Jae-Kyoung Noh,Jae-Nam Lee +1 more