Conceptual modeling for improved understanding of the Rio Grande/Río Bravo socio-environmental system - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement
Article Dans Une Revue Socio-Environmental Systems Modelling Année : 2019

Conceptual modeling for improved understanding of the Rio Grande/Río Bravo socio-environmental system

Résumé

Social processes are essential components of human-environment systems and their dynamics. However, modeling a tightly coupled socio-environmental system over a large area and across wide social and environmental diversity presents several challenges, given the complexity of the interactions and their spatial heterogeneity. The transboundary Rio Grande/Río Bravo (RGB) Basin is an excellent case study to address these challenges. Water scarcity and over-allocation of water are present in a highly engineered system with extensive damming and a complex structure of agreements and compacts that govern the distribution of hydrological resources among users. Since no basin-wide approaches to modeling the RGB as a socio-environmental system exist, we attempt to close this gap. Building on data collected through extensive ethnographic fieldwork, we used a structured, collaborative, and integrative approach for documenting existing knowledge on and modeling of the RGB socio-environmental system. We assess different models for conceptualizing human behavior applied in the RGB, identify a need to redefine the (spatial) boundaries of the system and produce inductively generated knowledge about the interlinkages of social processes with environmental system components in the form of a semi-quantitative conceptual model. Our research demonstrates an alternative to ad-hoc approaches to defining “the social” in socio-environmental models and is a first step towards the development of a basin-wide computer simulation model of the RGB socio-environmental system.

Mots clés

Fichier principal
Vignette du fichier
2019-serenahamilton,+Koch16127-FinalAcceptedProof2.pdf (1.41 Mo) Télécharger le fichier
Origine Fichiers éditeurs autorisés sur une archive ouverte
Licence

Dates et versions

hal-03325402 , version 1 (16-08-2023)

Licence

Identifiants

Citer

Jennifer Koch, Jack Friedman, Stephanie Paladino, Sophie Plassin, Kyndra Spencer. Conceptual modeling for improved understanding of the Rio Grande/Río Bravo socio-environmental system. Socio-Environmental Systems Modelling, 2019, 1, pp. 16127. ⟨10.18174/sesmo.2019a16127⟩. ⟨hal-03325402⟩

Collections

INRAE
30 Consultations
28 Téléchargements

Altmetric

Partager

More