Forest ecosystems provide a lot of service functions which are not only sustainable conditions for life, but also the material foundation and guarantee for human survival and socio-economic development. Therefore, these years more and more attention has been paid to forest health and health assessment has become extraordinarily important. This study is primarily based on the evaluation criteria prescribed by Continuous Forest Inventory Technique, combining with site, geography, climate conditions and so on in Liangshui nature reserve to define the evaluating indicators. In this thesis, windthrow hazarel is divided into four grades: zero, mild, moderate and severe. The data of forest resource inventory in Liangshui nature reserve in 2009 is used to calculate the accumulation of different forest compartment and species of wind fallen trees. And based on ARCGIS, windthrow hazarel geodatabase, disaster distribution, volume distribution of wind fallen trees of Liangshui nature reserve are built and mapped. Then with the combination of aspect, slope and stand density distribution, this thesis is to analyze the factors which influence the disaster grade and distribution, to propose target-oriented prevention measures and treatment strategies. The results demonstrate that in Liangshui nature reserve, forest compartments in mild disaster are the most with the total number of 21, those in moderate disaster are 4, in zero degree disaster are 4 and in severe are 2. And the area of forest compartments whose main variety of wind fallen tree is pinus koraiensis takes up over 45% of the total forest zone, the area of forest compartments whose main varieties are fir and spruce takes up approximately 40%, and the areas of forest compartments whose main varieties respectively are poplar and basswood takes up about 10% and 5%.

An accurate and reasonable finite element model is essential for bridge structural health monitoring and safety assessment. To improve the accuracy and efficiency of the finite element model updating, this paper proposes a finite element model updating method for bridge structures based on an improved response surface method. By introducing the radial basis function as the augmentation term of the polynomial function, a response surface model based on the augmentation polynomial is established, and the fitting accuracy of the global response surface model is improved. The convergence speed and accuracy of the response surface model optimization solution are improved by improving the regression step and annealing strategy in the simulated annealing algorithm. The method is validated using the numerical case of a simply supported beam and the finite element model of the main bridge of the Tonghe Songhua River Highway Bridge (Tonghe Bridge), and the safety condition of the main bridge of the Tonghe Bridge is evaluated using the updated finite element model. The results show that the maximum relative error of the updated parameters of the simply supported beam decreased from 13.011% before improvement to 0.719% after improvement, and the maximum relative error of the natural frequencies decreased from 0.728% before improvement to 0.225% after improvement; the maximum relative error of the natural frequencies of the finite element model of the Tonghe Bridge main bridge decreased from 21.68% before improvement to 4.23% after improvement. In April, May, and June of 2021, the main bridge of the Tonghe Bridge operated well and had a good security reserve.

2638 branch samples are gained from the 14 sample spots and the data of 50 parse trees in the spots investigated by Muling Forestry Bureau in 2008. The type of the curve are determined by the observation of the radius(r) of various kinds of trees and the scatter diagram graph of crown depth (lx) . This paper is to use power function, single formula, parabola and hyperbolic function models to fit. Through the comparison of the results of fitting, it is found that the fitting effect of the average crow of Korean pine is the best whose correlation coefficient achieves 0.58, and for parabola, spruce and fir are the best respectively with correlation coefficient 0.69 and 0.72; The same model is applied to fit the outside shape of the three species and the result is similar with that of average crown: hyperbolic function of Korean pine is the best and parabola of spruce and fir are the best. After test, it is found that forecast accuracy of model is higher. Average crown of Korean pine is 95.7% and outside crown is 92.1%; Average crown of fir is 94.9% and outside crown is ：95.9%; Average crown of Spruce is 96.0% and outside crown is 95.4%. From the point of comprehensive results, the fitting of crown shape model is better and the model chosen can better describe the crown shape of the main conifer species in Muling area, achieving the desired objectives.