15 Aug 2022
15 Aug 2022

GEB v0.1: A large-scale agent-based socio-hydrological model – simulating 10 million individual farming households in a fully distributed hydrological model

Jens A. de Bruijn1,2, Mikhail Smilovic1, Peter Burek1, Luca Guillaumot1, Yoshihide Wada1,3, and Jeroen C. J. H. Aerts2 Jens A. de Bruijn et al.
  • 1International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
  • 2Institute for Environmental Studies, VU University, De Boelelaan 1087, 1081 HV Amsterdam, the Netherlands
  • 3Department of Physical Geography, Utrecht University, Utrecht, the Netherlands

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.

Jens A. de Bruijn et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on egusphere-2022-664', Dedi Liu, 20 Aug 2022
  • RC1: 'Comment on egusphere-2022-664', Anonymous Referee #1, 07 Sep 2022
    • AC1: 'Reply on RC1', Jens de Bruijn, 08 Nov 2022
  • RC2: 'Comment on egusphere-2022-664', Anonymous Referee #2, 12 Sep 2022
    • AC2: 'Reply on RC2', Jens de Bruijn, 08 Nov 2022
  • RC3: 'Comment on egusphere-2022-664', Anonymous Referee #3, 13 Sep 2022
    • AC3: 'Reply on RC3', Jens de Bruijn, 08 Nov 2022
  • RC4: 'Comment on egusphere-2022-664', Anonymous Referee #4, 21 Sep 2022
    • AC4: 'Reply on RC4', Jens de Bruijn, 08 Nov 2022

Jens A. de Bruijn et al.

Jens A. de Bruijn et al.


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Short summary
Here, we present a computer simulation model of the hydrological system and human system. Using this model we can simulate the behaviour of farmers and their interactions with the water system, and assess how the systems will evolve in the future. For example, we can simulate the effect of subsidies provided for the adoption of efficient irrigation techniques. This could lead to farmers switching to more water intensive crops, and thus an intensification of droughts rather than drought relieve.