JpGU-AGU Joint Meeting 2017

講演情報

[EE] 口頭発表

セッション記号 H (地球人間圏科学) » H-CG 地球人間圏科学複合領域・一般

[H-CG27] [EE] 水―人間系の動態:観測、理解、モデル化とマネジメント

2017年5月23日(火) 13:45 〜 15:15 A05 (東京ベイ幕張ホール)

コンビーナ:沖 大幹(東京大学生産技術研究所)、Murugesu Sivapalan(University of Illinois at Urbana Champaign)、Giuliano Di Baldassarre(Uppsala University)、座長:Baldassarre Giuliano(Uppsala University, Sweden)、座長:花崎 直太(国立環境研究所)

14:30 〜 14:45

[HCG27-04] Size and stochasticity in irrigated socio-hydrological systems

*Rachata Muneepeerakul1Arnald Puy2,3Andrea L. Balbo4 (1.University of Florida, USA、2.University of Haifa, Israel、3.Universität zu Köln, Germany、4.University of Hamburg, Germany)

キーワード:Coupled natural-human systems, Stochasticity, Agriculture, Regime shift

Here we present a systematic study of the relation between the size of socio-hydrological systems and stochastic forcing. In particular, through a stylized theoretical model, we focus on how stochasticity in water availability and taxation interacts with the stochastic behavior of the population within irrigated socio-hydrological systems. Our results indicate the existence of two key population levels for the sustainability of such systems: (i) the critical population size required to keep the system operative--with a smaller population size, the system may self-organize toward a collapse; and (ii) the population threshold at which the incentive to work inside the system equals the incentive to work elsewhere—the system will self-organize toward this level, despite sub-optimal per capita payoff to its population. When subjected to strong stochasticity in water availability or taxation, the system may suffer sharp population drops and irreversibly disintegrate into a system collapse, via a mechanism we dub ‘collapse trap.’ Our theoretical study establishes the basis for further work aiming at understanding the dynamics between size and stochasticity in irrigated systems, which is key for devising mitigation and adaptation measures to ensure their sustainability in the face of increasing and inevitable uncertainty.