2019 World Conference on Natural Resource Modelling

HEC Montréal, Canada, 22 — 24 mai 2019

2019 World Conference on Natural Resource Modelling

HEC Montréal, Canada, 22 — 24 mai 2019

Horaire Auteurs Mon horaire

Case Studies 3

23 mai 2019 08h30 – 10h30

Salle: Banque CIBC

Présidée par Sabrina Streipert

4 présentations

  • 08h30 - 09h00

    Do heterogeneous tourists and residents value differently coastal erosion management? Evidence from Hoian (Vietnam), a UNESCO World Heritage Site

    • Thi Lan Anh Nguyen, prés., SupAgro Montpellier
    • Michel Simioni, Professor
    • Arnaud Reynaud, Toulouse School of Economics
    • Manh-Hung Nguyen, Toulouse School of Economics
    • Cecile Aubert, Gretha, University of Bordeaux

    The paper provides an in-depth comparison between tourists’ and residents’ preferences towards coastal erosion management programs. The paper applies Generalized Multinomial Model with all correlated terms between random parameters to account for both taste heterogeneity and scale heterogeneity of respondents . The paper finds similar preference for a wider and more public beach but different inclination to facilities and protection structures between two groups. The results show a strong taste and scale heterogeneity across respondents. Households’ choices are more difficult to predict than tourists due to complexity of choice set, poor definition of choice card and unfamiliarity of survey towards household. High scale heterogeneity also reflects random and lexicographic respondents in group of households.

  • 09h00 - 09h30

    Coastal dynamics and adaptation to uncertain sea level rise: optimal portfolios for salt marsh migration

    • Orencio Duran, Texas A&M University
    • Robert Johnston, Clark University
    • Matthew Kirwan, Virginia Institute of Marine Science
    • Anke Leroux, prés., Monash University
    • Vance Martin, University of Melbourne

    The sustainability of dynamic natural systems often depends on their capacity to adapt to uncertain climate-related changes, where different management options may be combined to facilitate this adaptation. Salt marshes exemplify such a system. Marsh sustainability under rapid sea level rise requires the preservation of transgression zones - undeveloped uplands onto which marshes migrate. Whether these uplands eventually become marsh depends on uncertain sea level rise and natural dynamics that determine migration onto different land types. Under conditions such as these, systematically diversified management actions likely outperform ad hoc or non-diversified alternatives. This paper develops the first adaptation portfolio model designed to optimize the benefits of a migrating coastal resource. Results are illustrated using a case study of marsh conservation in Virginia, USA. Results suggest that models of this type can enhance adaptation benefits beyond those available via current approaches.

  • 09h30 - 10h00

    Snowfall pattern and its impact on snow resources in Kunes Valley of Tianshan Mountains,China

    • Lanhai Li, prés., Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences
    • Jiansheng Hao, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences

    Snow resource from snowfall is a key source contributing to water resources in arid region. Better understanding snowfall pattern and its impact on snow resource can improve water resources management. Based on the monitoring data of snowfall and snowpack, this study integrated the weather, snowfall and snowpack to analyze snowfall pattern and snow resource in the study area. The results showed that snowfall mainly takes place from October to April in next year. Since the study area has the continental snow climate, the snow resource is characterized by low density, low shear strength and high proportion of raw frost.

  • 10h00 - 10h30

    Intermittent electric generation technologies and smart meters: substitutes or complements?

    • Fadoua Chiba, prés., GREThA
    • Sébastien Rouillon, GREThA

    We model a simplified electric market with producers using either conventional or intermittent electric generators and consumers equipped with either smart or traditional meters. We calculate the investment in intermittent technologies and smart meters in a social optimum. We find that the optimal penetration of smart meters is increasing in the volatility of the electric spot price. As a consequence, intermittent capacities and smart-meters are complement, only if the correlation existing between intermittent energy and demand is negative or if the capacity of intermittent generators is large enough. Otherwise, larger intermittent capacities actually help to decrease the volatility of the electric spot price, making smart-meters less useful. We also give a numeral application, calibrated to represent the French electric market in 2016 and policy objective for 2030. We show in particular that a general adoption of smart meters would be optimal only if the cost of installing and operating smart meters was unrealistically low.

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