Streefkerk, Ileen N., de Bruijn, Jens, Haer, Toon, Van Loon, Anne F., Quichimbo, Edisson A., Wens, Marthe, Hassaballah, Khalid and Aerts, Jeroen C. J. H.
2023.
A coupled agent-based model to analyse human-drought feedbacks for agropastoralists in dryland regions.
Frontiers in Water
4
, 1037971.
10.3389/frwa.2022.1037971
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Abstract
Drought is a persistent hazard that impacts the environment, people's livelihoods, access to education and food security. Adaptation choices made by people can influence the propagation of this drought hazard. However, few drought models incorporate adaptive behavior and feedbacks between adaptations and drought. In this research, we present a dynamic drought adaptation modeling framework, ADOPT-AP, which combines socio-hydrological and agent-based modeling approaches. This approach is applied to agropastoral communities in dryland regions in Kenya. We couple the spatially explicit hydrological Dryland Water Partitioning (DRYP) model with a behavioral model capable of simulating different bounded rational behavioral theories (ADOPT). The results demonstrate that agropastoralists respond differently to drought due to differences in (perceptions of) their hydrological environment. Downstream communities are impacted more heavily and implement more short-term adaptation measures than upstream communities in the same catchment. Additional drivers of drought adaptation concern socio-economic factors such as wealth and distance to wells. We show that the uptake of drought adaptation influences soil moisture (positively through irrigation) and groundwater (negatively through abstraction) and, thus, the drought propagation through the hydrological cycle.
Item Type: | Article |
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Date Type: | Published Online |
Status: | Published |
Schools: | Earth and Environmental Sciences |
Additional Information: | License information from Publisher: LICENSE 1: URL: http://creativecommons.org/licenses/by/4.0/ |
Publisher: | Frontiers Media |
Date of First Compliant Deposit: | 30 January 2023 |
Date of Acceptance: | 8 December 2022 |
Last Modified: | 03 May 2023 08:18 |
URI: | https://orca.cardiff.ac.uk/id/eprint/156353 |
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