استان گیلان

Throughout history, humans have harnessed the healing power of plants and animals, accumulating invaluable knowledge about their therapeutic benefits. Today, the rise in side effects of modern medicine, the urgent need for new drug discovery, and the potential loss of indigenous wisdom necessitate documenting this knowledge. This research aimed to record the traditional treatment practices of stockbreeders in eastern Gilan, Iran, relying on ethnographic methods like direct observation, participatory observation, and semi-structured interviews conducted in rural and nomadic communities. The results were classified into four sections: medicinal and edible plants, animal products, minerals, and other measures. Stockbreeders utilize 52 medicinal plants from 28 families, primarily for treating digestive, respiratory, infectious, kidney, heart, wound, and fracture ailments. Milk and its products are important for digestive, skin, and hair health. Minerals like mountain soil are used to treat kidney diseases and wounds. Quantitative analysis is crucial in studying traditional therapies and can lead to the discovery of new bioactive compounds for clinical trials. Documenting indigenous treatment methods and passing them on to future generations strengthens scientific knowledge, preserves our rich medical heritage, and provides a valuable source of treatment options.

The Eurasian otter (Lutra lutra) as one of the mammals of the inland waters of Iran is at the top of the food pyramid and encounter to endanger of extinction. The diet studies are critical to understanding the ecology of wildlife and preserving their populations. The objectives of this study were the presence and diet of otter in estuary region of Acharod, Khoshkrod and Polrood rivers, in the east of Guilan province, and also the study of the level of dependency of this species on fish species of the Caspian Sea. The length of the last five kilometers of each river, as three sections with an approximate length of 1700 meters, was examined in terms of distance or proximity to the sea. The results showed that of the five km length studied of the rivers, the Eurasian Otter was present up to 4/3 km of the estuary. In total, 511 presence indices with specific seasonal changes were observed in each of the river sections. The highest index was observed in the autumn season and the lowest in the summer season. Based on the analysis and investigation of spraints, 955 prey items including fishes, crustaceans, snakes, frogs, birds and insects were observed. The highest feeding index (FI) in three studied rivers was for fish and the lowest FI was for insects. Also, the seasonal changes in food items between sections were observed. So that in the two seasons of autumn and winter in all three sections of the rivers, the highest FI was for fish. In the spring and autumn, the feeding index of the fed fish was mainly related to river fish and common river-sea fish. In summer and winter, the percentage of sea fish was higher than in spring and autumn. The feeding index of non-fish items has also increased in the summer compared to other seasons.

Tea is not only known as one of the most common beverages in the world but also as a quite favorable and frequently consumed drink in Iran. Accordingly, studying the fresh tea leaves’ heavy metal content is an area of attention considering the environment quality assessment in addition to the public health issues. The research aimed at determining the concentration of heavy metals including lead, cadmium, zinc, nickel, cobalt, and chromium in the fresh leaves of tea and topsoils of the tea fields in Fouman County, Guilan, Iran. To do so, tea fresh leaves and respective topsoils were sampled at 5 sampling sites. After initial preparation, digestion of the taken samples was performed using HCl, HNO3, and H2O2 reagents. The concentration of heavy elements in the samples was determined by inductively coupled plasma (ICP). There have also been statistical tests such as one-way analysis of variance, T-test, principal component analysis (PCA) and cluster analysis (CA) performed using the SPSS software. Based on the results, the average concentrations of lead, cadmium, zinc, nickel, cobalt, and chromium in soil samples were obtained 3.94, 1.06, 60.29, 22.79, 9.49, and 2.77, mg/kg, respectively. According to the metal pollution load index (0<1), the soil quality of the study area was identified at an acceptable level. The levels of lead, cadmium, zinc, nickel, cobalt, and chromium in fresh leaves were obtained 0.44, 0.08, 22.58, 9.93, 0.23, and 0.36 mg/kg, respectively. Compared to the international standards (WHO / FAO), the amount of lead in fresh leaves was higher than permissible levels. By contrast, the amounts of cadmium, zinc, nickel, cobalt, and chromium were at acceptable values. As for soil samples, only the concentration of cadmium was higher than admissible levels based on the given standards. As such, the leaching process and biological uptake (happened by the rest of the flora) should have a part to play justifying the former results.

Nowadays, the importance of water is known more than before as a life factor and the axis of sustainable development that to protect and manage it, it needs to be controlled using laboratory tests and regular monitoring program. The purpose of this study was to investigate the treatment plant effluent of three large industrial towns in Gilan province and comparing the index parameters with Environmental Protection Organization standards; the measured parameter included pH, TDS, DO, COD and BOD5. The results showed that, some index parameters in the treatment plant effluent in some industrial towns were more than the approved discharge standards to the receiving environments which indicates the necessity of paying attention to regular monitoring and investigation of wastewater treatment systems in industrial towns more than before.

Industrial development and rapid population growth due to the increase in consumed materials and the consequent increase in industrial waste is one of the challenges in the world. The purpose of this study is to investigate the quantity of industrial waste production in the industrial group of plastics and synthetic rubber in Guilan province and the conditions of resulting pollution. The results of this study show that the major industrial wastes identified in this group include plastic waste, paint cans, cardboard waste, paint powder, packaging strap, polymer waste, polymer sludge, wood waste, glass and carbon fiber waste. Plastic waste with 136.08 tons is the highest and paint powder with 0.04 tons is the lowest industrial waste produced in this group. The used oil with a total amount of 14092 liters per year is the only hazardous waste identified in this group. From the present study, it is concluded that the main management methods used in this industrial group are recycling and sales, but hazardous waste is not disposed of properly. The proposed method for used oil is refining.

Sustainable land management requires the identification of key land use planning actors. Social network analysis is one of the best ways to identify important factors in Management change. In this study, to analyze the stakeholders related to participatory Management in the watershed of Anzali Wetland, the criteria and policy indicators at the level of the network of organizational stakeholders were done using the method of social network analysis . In this regard, 36 organizational stakeholders related to participatory land use management in Gilan province were studied and analyzed. In this research indices of density, size, Reciprocity, Transitivity, Centralization and Geodesic Distance in the network of relationships at the macro level and Core-peripheral index in the middle scale and centrality indicators at the micro (actors) scale of the network were examined. Based on the results ofmacro-level indicators, the density is moderate and according to the results of the Reciprocity and the moderate amount of Mutual relations among organizational stakeholders, the cohesion and organizational capital are also assessed as moderate. The resilience and balance of the information exchange network are also low due to the low transitivity index. The results of the core-periphery index analysis show a higher density of links and greater organizational cohesion among central organizations compared to the peripheral subgroup. Also, the amount of information exchange between central and peripheral subgroups was evaluated as moderate. Based on the results of centrality indices, the geometric position of each actor was determined according to the desired criteria in the network

Due to the lack of information in most of the watersheds, many researchers attempt to use spatial analysis within Geographic Information System (GIS) in hydrological and Flood Prone (FP) area studies. The present study was designed to compare the efficiency of three models i.e. Support Vector Machine (SVM), Generalized Linear Model (GLM) and Generalized Additive Model (GAM) for preparing the flood susceptibility mapping in Guilan province, Iran. For this purpose, slope, aspect, plan curvature, elevation, distance from the river, drainage density, geology, land use, Topographic Wetness Index (TWI) and Stream Power Index (SPI) layers were derived in GIS (ArcGIS and SAGA-GIS). Using 220 flood locations, 70% and 30% out of total flood locations were then used to calibrate and to validate the performance of the models, respectively. The evaluation results of the models accuracy using the area under the curve (AUC) and Kappa indices showed that in terms of AUC, the SVM with 0.835 and the GAM with 0.827, and the GLM with of 0.79 performed very good and good classes, respectively. In terms of Kappa index, the SVM with 0.58, GAM with 0.53 and GLM with 0.48 are performed good and acceptable classes, respectively. Therefore, based on the mentioned indices, the SVM superior to other two models for identifying the flood susceptibility areas.

The western region of Anzali wetland (Abkenar) is located in Guilan province in Iran. This area is between the 37o 49'-37o 51' north latitude and 49o 25'-49o 27' east longitude. Abkenar wetland is importance in the region due to its special position, such as the fishing of native marginalists. Survey of regional ecological characteristics and aquatic plants distribution contributes to the water ecosystems, conservation and sustainable use of their potential. Flora of this region includes 14 plant species which belong to 11 families. The largest families are Potamogenaceae (2 species), Thyphaceae (2 species). Phragmites auastralis is the most abundant species in the western region of the Anzali Wetland. The result showed that according to the classification Raunkiaer system (Raunkiaer, 1934) there were 21/42% Therophytes, 35/71% and 42/8% Holophytes. Also, Investigation on chorology of plant species showed that 57/14 Cosmopolitan, 21/42 Plurinational, 7/14 European-Siberian-Mediterranean and 7/14% Irano_Touranian in The western region of Anzali wetland.

Industrial and agricultural developments and the population of rural and communities led to excessive consumption of chemical detergents and fertilizers and increasing industrial wastwater which threaten water resources in last decades. Vulnerability of the water resources is a continuation of such trends. The first step in management of the groundwater resources is a determination of the vulnerable areas. The objective of this research was determin the vulnerability assessment of the central plain of Guilan using DRASTIC model. Principles of the model are based on overlaying of seven thematic maps of depth to water table, net recharges, aquifer media, soil media, topography, vados zone and hydraulic conductivity by considering appropriate weights and rates. The database was constructed by introducing the mentionec maps. Index of DRASTIC model for aquifer vulnerability of the central plain Guilan was ranged in 82-182. In this plain, there was not very much and very low vulnerability classes. The final map of DRASTIC model showed that % 48.64 of the area has high vulnerability and % 50.55 has medium vulnerability and only a small area of plain (% 0.81) has low vulnerability. Th estatistical summary of the DRASTIC model elements shows that the element of depth to groundwater table has the greatest impact on DRASTIC model. Also based on the map remove and single element sensitivity, depth to groundwater table is identified as the effective element in the central plain of Guilan. The results of the correlation between the elements of DRASTIC model and nitrate concenteration showed that there is the highest correlation between nitrate and depth to groundwater table. The average concentration of nitrates is 8.92 mg/lit in the wells studied at the Central Plains Guilan. In all wells studied, nitrate concentration was lower than the recommended level by US Environmental Protection Agency (45 mg/lit).

Evaluation of soil contamination by heavy metals such as cadmium in soils is essential for human health and also for environment management. As direct measurement of soil cadmium is time-consuming and costly, in this study, the two methods of artificial intelligence, artificial neural network (ANN) and adaptive fuzzy neural network (ANFIS) used to estimate the amount of cadmium in soil as one of the dangerous heavy metals. For estimating of cadmium, soil readily available properties such as clay and sand percentage, organic carbon, EC, T.N and P used as input parameters and the relationship between these parameters and the concentration of cadmium established by ANN and ANFIS models. For training and testing the models, 250 soil samples collected from soils of Guilan province. For assessment of artificial intelligence models the statistical criteria such as the coefficient of determination (R2), mean absolute error (MAE), root mean square error (RMSE) used. The results showed that ANN model with R2 = 0.83 and RMSE= 1.01, and MAE= 0.54 is superior to ANFIS model. Also the results of the sensitivity analysis on the input variables to the model showed that organic carbon and EC have the most and the least effect on the amount of Cd. The proposed model could be used to estimate the amount of cadmium in other parts of the studied area which the concentration of cadmium has not been measured, as well as for other areas with similar conditions.

Atmospheric precipitation management and efficient use of these resources are extremely helpful to the management of water resources and it has the basic role in the management of the water resources of hydrological parameter estimate as well. In this research, rainfall estimate of three synoptic station situated in Astara, Lahijan and Jirandeh in Gilan province has been done using artificial neural network (ANN) and support vector machines (SVM). The principal component analysis method (PCA) was applied to determine the data pre-processing and input data. According to the results, the main component analysis method for synoptic stations as well as for the five main components of Astara and jirandeh, and for the four main components of Lahijan station is selected. The results of model-making indicate that the artificial neural network model based on principal component analysis (PCA-ANN) in Astara and Jirandeh stations in order with average 2.74 mm squares of 2.62and mm backup-based support vector machine model analysis of the main components (PCA-SVM) mean squares of squares in Lahijan station with error 2.53 mm can be selected as selected models for the aforementioned stations. Finally, with respect to the results can be fitted such that the methods used for data pre-processing in this research to predicate the rainfall as well as the SVM in Lahijan station and model Ann model in Astara and Jirandeh stations have been acceptable.

Two factors of cost and time are related directly to the accurate estimate of runoff in the watersheds. More detailed information on the status of rainfall runoff also facilitate decisions on future programs for watershed managers, a step towards the preservation of natural resources for sustainable development. In this study, in order to achieve optimal amount of runoff in the Shafaroud watershed, first significant rainfall data of four stations during 1998 to 2011 were collected and combined with other maps of the study area, such as DEM, land use and soil as input data in the form of SWAT model was software. After running the model, the SUFI-2 and GLUE algorithms in SWAT-CUP program used to evaluate the data uncertainty and the most accurate simulation. The first three years (1998-2000) of rainfall data for warm-up and the next 7 years (2001-2007) for the calibration and final 4 years (2008-2011) were used for the validation. Finally, with multiple simulations, the uncertainty of the parameters assessed with P-factor, R-factor, and NS coefficients. The results indicated in runoff simulation, the SUFI2 algorithm ( =0.85, NS=0.74) is more accurate than GLUE algorithm ( =0.82, NS=0.71).

To assess the sources, entry routes and degree of contamination of PAH compounds in surface sediments of the southwestern Caspian Sea coasts (Gillan province) total of 129 surface sediment samples from 28 rivers and 5 transect across the Gillan province coasts (from Astara to Lahijan; 10, 20 and 50 m depth) were collected in the spring and summer of 2012. After extraction using Soxhlet method, the samples were analysed using Gas chromatography-Mass spectrometry (GC-MS) and concentrations of 30 PAH compounds were determined. The mean of total 30 PAH compounds (TPAH30) in the coastal sediments (565.1±266.1 ng g-1) have shown significant difference (p

The objective of this study is to find empirical equation for the determination of the estuaries displacements of Gilan Province’s Rivers، Iran. For this purpose، first، the displacement of estuary of each river was determined using the Geographical Information Systems (GIS). Remote sensing data and topographical maps of four different years were used in this study and the displacement of estuary of the rivers were determined by providing the estuaries map in those periods. On the other hand، the sediment transport rate of the rivers was calculated in different periods using observed sediment data. Correlation between the sediment concentration indices and displacement of the estuaries indices in Gilan Province’s Rivers were studied. Results show that the ratio of maximum sediment concentration to average sediment concentration of each river has high correlation with the transversal average displacement of the estuaries in each period. Examination of results show that variation of transversal displacement of rivers’ estuaries with sediment index can be investigated in three intervals. In the first interval، sediment index was 0-50، in the second interval 50-100 and in the third interval 100-150. The average transversal displacement of rivers estuaries in three intervals are about 15 m، 87 m، 286 m per year، respectively. This research shows that erosion and sedimentation management of watersheds، debris flood control and limiting the up-stream dams’ flushing play crucial role in estabilization of the morphology of Gilan’s estuaries.

Human activities induced changes in land cover/use have extensive impacts on the landscape. In recent years, these changes had an increasingly growth due to irrational use of the natural resources in Iran. Hence, considering the negative effects of the inappropriate use of land and land-use change, understanding of the landscape changes over time is necessary to planning and implementation of sustainable management. This study has been carried out aiming to investigate trends in the landscape changes in Korganrud watershed during 1975-2007. In order to generate the land use/cover map and analysis of the changes, satellite images, including Landsat (MSS), IRS/P6 (LISS III) were applied and landscape metrics, including Class Area (CA), Patch Number (PN), Mean Patch Size (MPS) and Average Weighted of Mean Shape Index (AWMSI) were used to quantify the landscape patterns. Results of the present study revealed an extensive change in the landscape metrics in distribution and ratio of the land uses due to the increase in the area of disturbing patches (agriculture, urban and barren lands) in expense of decrease in the natural resources (forests and rangeland) during the study period. Degradation and reduction of integrity of the landscape have also been observed due to the increase in patch number of the land uses that were in association with the increase in shape complexity and decrease in the patch size in the study area. If such a trend continues, without any appropriate management plan and or land use planning, it could result in adverse impacts on the structure of the ecosystems. Therefore, the results suggest the necessity of implementation of land use planning in order to determination of the suitability between land supply and demand, and decreasing degradation of the natural resources.