M.Sc. Tezi Görüntüleme | |||||||||||||||||||||
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| Summary: Master Thesis SUMMARY SURFACE FUELS MOISTURE DYNAMICS IN CALABRIAN PINE STANDS Yetkin USTAKaradeniz Technical University The Graduate School of Natural and Applied Sciences Forest Engineering Graduate Program2018, 48 Pages This study presents a model that predicts diurnal changes of dead fuels in normally stocked Calabrian pine (Pinus brutia Ten.) stands for dry and rainy periods in relation to varying weather conditions. The model is a state-dependent, dynamic, semi-physical model and was developed based on the functional relationships between moisture contents of dead surface fuels and weather variables using empirical and semi-physical relationships. The model describes functional quantitative relationships between weather variables and surface fuel moisture for a wide range of situations rather than moisture changes from a small set of measured weather variables. The developed model was structured such that it included all the necessary variables, and model parameters were determined by using a combination approach including both statistical methods and graphical inspection using field data. Predictions of the model yielded a MAE of 0.79 for litter and 0.70% for duff at Mugla and 3.38 % for litter and 11.57% for duff at Antalya. When the rainy period was excluded from the validation data at Antalya site, the MAE decreased from 11.57 to 3.78% for duff fuels. The model was tested and validated with independent dataset from field observations. The graphical inspection and statistical validation of the model indicated that the performance of the model under varying weather conditions and different stand characteristics at different locations was reasonably accurate, and the model performed well for dry periods and was relatively satisfactory for the rainy periods. The model is a generic model, and it can be easily applicable to other similar fuel types in the Mediterranean region for which specific model parameters are provided.
Key Words: Fuel moisture content, process based modeling, equilibrium moisture content, timelag, vapor pressure deficit. | |||||||||||||||||||||