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Accueil du site → Doctorat → Royaume-Uni → 1996 → Modelling hydrology and vegetation change in a degraded semi-arid environment (BL)

University of London, King’s College (1996)

Modelling hydrology and vegetation change in a degraded semi-arid environment (BL)

Mulligan, M

Titre : Modelling hydrology and vegetation change in a degraded semi-arid environment (BL)

Auteur : Mulligan, M

Université de soutenance : University of London, King’s College

Grade : Doctor of Philosophy (PhD) 1996

Résumé
This thesis examines the issues of land degradation in Mediterranean environments. The emphasis of the research is vegetation as the link between atmospheric climate change and the kinds of land surface change associated with land degradation or desertification. A complex and tightly coupled hydrology and vegetation growth model, is developed from first principles. The model, PATTERN, is a cellular model which is designed to recognise peculiarly Mediterranean characteristics, particularly sparse vegetation canopies, stony soils, high spatial variability and erratic and sometimes very high intensity rainfall. The model simulates all the component hydrological fluxes in a finite difference grid and allows vegetation growth of different functional types of vegetation. The processes of seed dispersal, germination, growth, maintenance, dynamic (environmentally conditioned) allocation, structural development, dormancy and death are simulated. The growth model is a production efficiency type model limited by temperature and water stress. The hydrology and growth sub-models are coupled through the stomatal aperture which is determined by soil moisture through soil and leaf matric potential and which determines evapotranspiration and the radiation use efficiency as well as the leaf and root area. PATTERN requires high resolution meteorological data since it runs on a variable time step to accurately simulate rapid rate fluxes. This data is not commonly available and so a storm and weather generator have been developed to produce high resolution data from low resolution measurements. The generators are employed to produce long term weather series from historical rainfall records for Castilla La Mancha (CLM) and for GCM derived predicted rainfall series for the Cobres Basin.

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