An interactive land use transition agent-based model (ILUTABM): Endogenizing human-environment interactions in the Western Missisquoi Watershed

Tsai, Yushiou; Zia, Asim; Koliba, Christopher; Bucini, Gabriela; Guilbert, Justin; Beckage, Brian

doi:10.1016/j.landusepol.2015.07.008

Cited by 43 publications

(18 citation statements)

References 74 publications

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“…Also, as we are interested in the potential mechanisms behind observed behavior, we adopt a stylized approach. Several sociohydrological studies have already incorporated insights from sociology and psychology into quantitative, dynamic models leading to an increased understanding of system functioning (Di Baldassarre et al, 2013Baldassarre et al, , 2017Elshafei et al, 2014;Garcia et al, 2016;Kuil et al, 2016;Le et al, 2012;Tsai et al, 2015;Viglione et al, 2014;Yu et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Exploring the Influence of Smallholders' Perceptions Regarding Water Availability on Crop Choice and Water Allocation Through Socio‐Hydrological Modeling

Kuil

McCord

Salinas

et al. 2018

Water Resources Research

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While it is known that farmers adopt different decision‐making behaviors to cope with stresses, it remains challenging to capture this diversity in formal model frameworks that are used to advance theory and inform policy. Guided by cognitive theory and the theory of bounded rationality, this research develops a novel, socio‐hydrological model framework that can explore how a farmer's perception of water availability impacts crop choice and water allocation. The model is informed by a rich empirical data set at the household level collected during 2013 in Kenya's Upper Ewaso Ng'iro basin that shows that the crop type cultivated is correlated with water availability. The model is able to simulate this pattern and shows that near‐optimal or “satisficing” crop patterns can emerge also when farmers were to make use of simple decision rules and have diverse perceptions on water availability. By focusing on farmer decision making it also captures the rebound effect, i.e., as additional water becomes available through the improvement of crop efficiencies it will be reallocated on the farm instead of flowing downstream, as a farmer will adjust his (her) water allocation and crop pattern to the new water conditions. This study is valuable as it is consistent with the theory of bounded rationality, and thus offers an alternative, descriptive model in addition to normative models. The framework can be used to understand the potential impact of climate change on the socio‐hydrological system, to simulate and test various assumptions regarding farmer behavior and to evaluate policy interventions.

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Section: Introductionmentioning

confidence: 99%

Exploring the Influence of Smallholders' Perceptions Regarding Water Availability on Crop Choice and Water Allocation Through Socio‐Hydrological Modeling

Kuil

McCord

Salinas

et al. 2018

Water Resources Research

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“…The framework of the LULCC ABM, shown in figure S1 of supplementary materials and explained in detail by Tsai et al [36] and Zia et al [37,38] consisted of four procedures. First, the ABM initialized agents and parameters based on 2001 National Land Cover Database, zoning and economic development data.…”

Section: Lulcc Abmmentioning

confidence: 99%

Coupled impacts of climate and land use change across a river–lake continuum: insights from an integrated assessment model of Lake Champlain’s Missisquoi Basin, 2000–2040

Zia

Bomblies

Schroth

et al. 2016

Environ. Res. Lett.

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Global climate change (GCC) is projected to bring higher-intensity precipitation and highervariability temperature regimes to the Northeastern United States. The interactive effects of GCC with anthropogenic land use and land cover changes (LULCCs) are unknown for watershed level hydrological dynamics and nutrient fluxes to freshwater lakes. Increased nutrient fluxes can promote harmful algal blooms, also exacerbated by warmer water temperatures due to GCC. To address the complex interactions of climate, land and humans, we developed a cascading integrated assessment model to test the impacts of GCC and LULCC on the hydrological regime, water temperature, water quality, bloom duration and severity through 2040 in transnational Lake Champlain's Missisquoi Bay. Temperature and precipitation inputs were statistically downscaled from four global circulation models (GCMs) for three Representative Concentration Pathways. An agent-based model was used to generate four LULCC scenarios. Combined climate and LULCC scenarios drove a distributed hydrological model to estimate river discharge and nutrient input to the lake. Lake nutrient dynamics were simulated with a 3D hydrodynamic-biogeochemical model. We find accelerated GCC could drastically limit land management options to maintain water quality, but the nature and severity of this impact varies dramatically by GCM and GCC scenario.

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“…Figure 3 graphically summarises the findings, which are discussed in the following subsections. Tsai et al, 2015 [76] agents' financial conditions-expected utilities from food production and other ecosystem services-land use decisions-ecosystem services for food production and other services * …”

Section: Indicators Usedmentioning

confidence: 99%

“…The fifth category of models was those representing feedbacks between land use and social institutions. These demonstrated how land use changes can give rise to policy change (via formal institutions such as government or nongovernmental institutions, e.g., [67]) and behavioural change (via informal institutions such as social networks [12], altered financial conditions [76], or perceived quality of life [69]), which could result in land use changes in turn. In the reviewed articles, no models were found to represent feedbacks between land use and technological systems.…”

Section: Feedback Processes Between Land Use Systems and Related Systemsmentioning

confidence: 99%

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How Are Feedbacks Represented in Land Models?

Chen

Bakker

Ligtenberg

et al. 2016

Land

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Land systems are characterised by many feedbacks that can result in complex system behaviour. We defined feedbacks as the two-way influences between the land use system and a related system (e.g., climate, soils and markets), both of which are encompassed by the land system. Land models that include feedbacks thus probably more accurately mimic how land systems respond to, e.g., policy or climate change. However, representing feedbacks in land models is a challenge. We reviewed articles incorporating feedbacks into land models and analysed each with predefined indicators. We found that (1) most modelled feedbacks couple land use systems with transport, soil and market systems, while only a few include feedbacks between land use and social systems or climate systems; (2) equation-based land use models that follow a top-down approach prevail; and (3) feedbacks' effects on system behaviour remain relatively unexplored. We recommend that land system modellers (1) consider feedbacks between land use systems and social systems; (2) adopt (bottom-up) approaches suited to incorporating spatial heterogeneity and better representing land use decision-making; and (3) pay more attention to nonlinear system behaviour and its implications for land system management and policy.

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An interactive land use transition agent-based model (ILUTABM): Endogenizing human-environment interactions in the Western Missisquoi Watershed

Cited by 43 publications

References 74 publications

Exploring the Influence of Smallholders' Perceptions Regarding Water Availability on Crop Choice and Water Allocation Through Socio‐Hydrological Modeling

Exploring the Influence of Smallholders' Perceptions Regarding Water Availability on Crop Choice and Water Allocation Through Socio‐Hydrological Modeling

Coupled impacts of climate and land use change across a river–lake continuum: insights from an integrated assessment model of Lake Champlain’s Missisquoi Basin, 2000–2040

How Are Feedbacks Represented in Land Models?

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