r.naghdi

Forest fires is one of the most important environmental problems and often as an important driver in runoff generation and soil erosion in the forest. This study was conducted with the aim of investigating the mutual effect of slope and rainfall intensity on the runoff generation and soil loss in a burned forest using a rainfall simulator.

This study was conducted in series 4 of Babakoh of the 25 Forestry Zone of Shenroud, Siahkal County, Guilan Province, where about 8(ha) of the forest area of this zone suffered from a relatively severe fire in 2019. The climate of the region is semi-humid and moderate, the minimum and maximum relative humidity varies between 70 and 90 percent, respectively. The height above the sea level is 350 meters, the slope direction is southwest, the annual rainfall is 1465 mm, the initial soil moisture is 16.46%, the texture of the soil is loamy sand. Changes in parameters of runoff volume, runoff coefficient, soil loss and sediment concentration due to changes with two treatments, slopes at two levels of 15 and 30% and rainfall intensity at three levels of 8.16, 7.16, and 4.13 mm min-1 in the time of 6.26 min was investigated using a rainfall simulator. Analysis of variance of the parameters measured in the experiments was performed with three replications within 18 plots (25×25 cm) by using Komforest type rain simulator. Factorial analysis of variance was performed in the form of complete randomized design and comparison of the average interaction effects of treatments was performed with Duncan's method at the 95% confidence level.

The results of analysis of variance showed that the interaction effect of slope treatments and rainfall intensity on the studied components is significant (p≤0.05). The highest amount of runoff volume was recorded in the treatment of rainfall intensity of 16.8 mm/min and slope of 30% with a value of 2418.33 ml and a runoff coefficient of 81.53%  and the lowest one related to the treatment of rainfall intensity of 13.4 mm/min and slope of 15% was recorded with a value of 846 ml. The results of soil loss showed that the highest value was related to the rainfall intensity of 16.8 mm/min with a slope of 15% to the value of 11.06 gr and the lowest soil loss was 13.4 mm/min related to the intensity of rainfall and a slope of 30% to the value of 1.79 gr. The highest concentration of sediment was recorded at a slope of 15% and intensity of 13.4 mm/min.

This research showed that the total average volume of runoff increased by 17.61% in the period of one year after the fire in this area with the increase of slope from 15% to 30%. Also, in the rainfall intensity of 8.16 mm/min, as the maximum intensity in this research, the volume of runoff increased by 33.6% from the slope of 15 to 30%. The results of the study of soil loss showed that it had an average increase of 61.9% in the slope of 15% compared to 30%. Also, there was a 76% increase in the rainfall intensity treatment of 8.16 mm/min. These results indicate that the slope and intensity of rainfall are effective factors in the hydrological cycle and erosion in the forest area of this study after the fire.

The purpose of this research is to investigate the attitude of forest-dwelling villagers towards forest management, their satisfaction with the way forests are managed, and the level of people's participation in forest administration and natural resources management.

The statistical population of the research including 50 individuals was selected randomly from among the villagers of the villages on the edge of the forests using the Delphi survey method. The questionnaire included nine main topics of natural resource management and 59 executative indicators. The validity of the items was confirmed through the Lavache relationship and the reliability of the research options was confirmed by Cronbach's alpha test. For each index, the product of the average importance was calculated based on the 5-point Likert scale in the normalized weight of the index.

The result of the Kruskal Wallis statistical test showed that there is no significant difference between the experts of 4 selected cities in terms of executive indicators of natural resources and forest management. According to the results of this research, the level of satisfaction of local experts with the functioning of the core activities of the Natural Resources Custodian in Gilan province was declared to be weak. The topics of protection and conservation, education, people's participation for forest administration and protection have the most impact and value. In exploitation, the most value was given to wood farming activities, local exploitation and tourism capacity. The indicators of forest protection and preservation in line with management, the most important factors of forest destruction were valued. Satisfaction with all indicators of restoration and reconstruction of damaged forests (5 indicators) was at a low level. In terms of the effectiveness of the index of people's participation in fire fighting, the activities of NGOs (non-governmental organizations) for the protection and maintenance of natural resources and the reporting of cases of destruction of natural resources by people (people's participation in forest protection) and handling all public reports, were ranked first to third, respectively.

The attitude of the local forest-dwelling leaders towards the performance of the forest administration and natural resources management shows moderate to low satisfaction, which is necessary to be improved by increasing the participation of local communities, the positive impact of the projects on the livelihood of the forest-dwellers and strengthening the implementation measures toward protection, restoration and reconstruction and principled exploitation.

Forest roads are essential infrastructures for accessing and managing forest units. Sustainable road management requires accurate spatial information from the road network. Various methods, differing in accuracy, precision, efficiency, and cost, are available for providing the location of roads. Given the remote location of forest roads, the lack of reference stations, potential inaccessibility to online networks, and conditions affecting positioning error, it is necessary to investigate the efficiency of existing positioning methods.

In this research, we studied the accuracy of PPK, RTK, online platforms such as Shamim, GPS, and mobile apps in positioning 34 points on 5 km of forest roads in watershed No. 30 in the Hyrcanian forest. The coordinates were first extended to the study area using the rapid static method. After post-processing and determining reference points, the exact coordinates of all ground control points on the road were obtained through the direct method. Then, the coordinates of all points were measured three times using various methods.

The health survey's statistical results showed that the highest mean differences were 2.53 m and 2.38 m for GPS and mobile apps, respectively. The least mean difference was 0.048 m, 0.049 m, and 0.092 m for PPK, RTK, and Shamim, respectively. The RMSE amount showed that the results from GPS and mobile apps had the least accuracy, and the methods PPK, RTK, and Shamim had the highest. Based on the one-sample T-test and Wilcoxon’s analysis, the amount of differences was not the same within each method through the 34 investigated points. Accuracy analysis indicated that GPS, with a distance mean of 1.14 m, had the least precision, and Shamim and RTK, with 0.0621 m and 0.063 m, were the most precise methods. The analysis of variance showed that the mobile app, Shamim, and PPK had the highest convergence.

The results of this research indicate that the PPK method was the most accurate, and the Shamim method was the most precise. Therefore, these methods can be used for purposes such as optimizing the forest road plan and longitudinal profile that require accurate location information.

Forest roads are recognized as one of the primary sources of sediment production in mountainous watersheds. Predicting the amount of sediment they produce is crucial for effective management. The WARSEM model, developed in the forests of the United States and used globally, is one of the most efficient models for estimating sediment from forest roads. However, a significant limitation of this model is the lack of fillslope data. Given the unique characteristics of the northern forests of Iran, such as steep slopes, this study investigated the potential impact of this factor on the model's results. The study was conducted in the third district of the Chelavand forestry project, located in the natural resources area of Astara city in Northwestern Iran. The total length of the roads studied was 5.5 km, divided into 48 samples with homogeneous characteristics. Essential information was collected for the implementation of the model. The model estimated the amount of road and cutslope sediment to be 94.786 tons per kilometer per year. After incorporating information about the fillslope area, the model was run again. The predicted amount of sediment from the fillslope area was 3.4 tons/km per year. A t-test analysis revealed that the observed difference between the results was not significant. Therefore, it can be concluded that adding features related to the fillslope area does not significantly affect the final results of the model in the study area.

In this study, we investigated the effects of forest operation on runoff and sediment using small-scale plots. The runoff and sediment samples were collected from 36 sample plots with dimensions of one by two meters in different areas of the operation. We used the Multi-Layer Perceptron (MLP) for modeling, with 65% of the data for training, 10% for validation, and 25% for testing. We evaluated the accuracy of the model using the coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE), and compared our results with optimized models obtained through trial and error. We collected information and produced runoff and sediment maps using GIS. Our results showed that the most important factors affecting runoff production were soil bulk density, rainfall intensity, slope, rainfall values, percentage of grass cover, and canopy cover percentage. For sediment, the most important factors were rainfall intensity, soil bulk density, slope percentage, and surface cover percentage. The MSE and R values for runoff modeling were 0.009 and 0.9 in the training stage and 0.01 and 0.82 in the test stage, respectively. For sediment modeling, the MSE and R values were 0.01 and 0.86 in the training stage and 4.3 and 0.8 in the test stage, respectively. Our results showed that neural networks have high capability in modeling runoff and sediment in forest lands. We also conducted an overlap analysis to measure the accuracy, precision, and efficiency of the results and methods presented in our study. Therefore, the proposed model can be used to combine ANN and GIS in the simulation and modeling of runoff and sediment in forest areas."

This study aimed at investigating the effect of landslides causing by executive activities on some physical and chemical of soil properties in Tonekabon and Ramsar forests. For this purpose, the geographical location of the landslides was collected. Landslides in altitude (<750 and > 750 m), aspect (north, south, east and west), age (< 15 and > 15 years) and slope (< 50 and > 50%) were classified. In the each class, three sample plot (100 m2) were established to measure of soil properties. Soil properties includingpH, organic carbon, bulk density and particle density. Totally, 88 sample of soil were collected. The results showed that the mean of BD, PD, OC and pH in the landslide area were 1.69, 2.38, 2.33 and 6.80, respectively, and in the control area they were 1.64, 2.32, 3.49 and 6.56, respectively.  The study of soil properties under the effect of slope showed that the mean of pH and OC in the control area was higher than landslide areas, but the BD in the control area was less than the landslide area. Soil properties recovery showed that except soil OC, other soil properties were fully recovered. The statistical results of soil properties showed that there was a significant difference between the mean OC in landslide and control areas in all studied classes.

Trees are one of the most important carbon reservoirs on the earth and carbon sequestration into plant biomass is an easiest and economically most practical way for mitigating the CO2 from atmosphere. This study aims at determining the biomass and carbon storage in stump and roots of Populus deltoides in Tanian poplar plantations of Guilan province. For this purpose, 15 poplar trees were selected based on selection sampling method 15. After the cutting and moving the logs from the stump to somewhere outside the plantation, excavator machinery (KOMATSU PC 200) was used to remove the stumps and roots from the soil. After separating the stumps and roots, mentioned parts were weighed using a digital scale. In order to estimate the amount of biomass and carbon storage, some samples of various components of poplar trees were then fallen down and weighed. After drying the samples in oven (80 ̊C), the dry weight of the samples was determined. After burning an enough amount of dried samples in the electric kiln, the weight of organic matter and carbon of the stump and root samples were obtained. Results showed that the mean of stump biomass, root biomass, stump and root carbon sequestration for each tree were 2.15, 22.18, 1.05 and 10.94 kg per tree, respectively. Results indicated there was a positive and significant correlation between the biomass and carbon sequestration of stump and root with collar diameter. The amount of carbon storage in the root and stump parts was 3.836 tons per hectare and the economic value of carbon storage was calculated as 46723015.68 Rials per hectare.

The present study compares the performance of three statistical models including logistic regression, frequency ratio and maximum entropy in preparing the zoning map of landslide sensitivity on the watersheds of 24 and 25 (Malak-roud and Shen-roud) regions of Guilan province. For this purpose, all the roads of the two areas were survyed and the number of 844 landslides were detected. Then effective data layers on landslide formation were prepared and then zoning maps of the landslide sensitivity were extracted to the three methods. The results showed that the logistic regression model has an accuracy of 74.6 percent of the Area under ROC Curve in prediction of sensitive areas compared to the accuracy of 68.2 and 65.2 percent by the probabilistic frequency ratio model and Entropy model, respectively. Moreover, based on the logistic regression model, the distance and slope factors have the highest effect on the landslide of forest road trenches. According to this study, a total of 4.32 square kilometers (43.25%) of the landslide areas is categorized in very high and high susceptible groups which have occurred along 51.38 percent of the area. Despite the lack of consideration to superstructure conditions in the present study, a notable percentage of existing roads are exposed to the collapse of trenches and require adequate funding for repair operations. According to the logging ban as a new approach in forest utilization and lack of revenue regeneration of alternative conservation projects great dangers threaten the forest engineering installations and road structures.