Optimisation of harvest scheduling with respect to water yield and quality

Forests are generally range in high mountainous areas. Watersheds forming forests, main source of water used in many areas for human needs, especially drinking water. The interventions in the forests also affect the amount of water yield, water quality, carbon stocks and income from forests. For this reason, it is necessary to overcome the lack of knowledge for other functions provided by forests for long-term estimation of the cutting plans to be regulated. Then we need to produce relations with forest dynamics. Interdisciplinary studies are also required to obtain these basic data. Therefore, it is aimed to reveal the relationship between watershed characteristics and forest structure in the first stage. By choosing a sample planning unit after the obtained data and relations, it was aimed to develop a planning model for that planning unit and to make a long-term comparison of the solutions obtained from the model for different objective functions. The model integration of all forestry functions is very difficult due to lack of information. For this reason, it was attempted to understand how the function of wood production, hydrological function and carbon accumulation function of forests changes according to different objective functions and different constraints during a planning process and how a harvest scheduling scheme is formed. Mixed Integer Programming is used as the planning technique. GAMS software has been utilized in the execution of the optimization model and in obtaining the solutions. Seven different planning strategies have been developed for the planning unit and it is aimed to maximize profits according to these different strategies. The highest objective function value of the developed strategies was obtained in the absence of the optimal periodic area constraint. The strategy in which the highest amount of water is obtained is also the strategy in which there is limit to the amount of area to be regenerated. Carbon accumulation values were decrease in most strategies because of the high amount of regenerated areas in the planning strategies, while only the periodical regeneration constraint had positive results in all periods. The amount of standing volume at the end of the planning horizon has also increased only ST7 planning strategy. Other strategies, the amount of standing volume has decreased.