ملیحه مزین

Sustainable management of renewable natural resources has special importance and sensitivity in Iran. Identify elements of the forest including forest types, is the most consistent way to manage natural resources and especially forests. River forests are important areas for preserving biodiversity and ensuring the sustainability of the forest ecosystem. On this principle, it is necessary to know and understand the state of the structure of these forests and the types of trees in them and to know the evolutionary process of forest ecosystems before any planning. The aim of this study is forests typing of Maroon riverbank.
Material and

116 plots were chosen with an area of 100 using a systematic random sampling method with dimensions of grid for the study area. In each plot, tree and shrub species, canopy cover in the area of plot were estimated and recorded according to Braun-Blanquet scale corrected. Various parameters such as frequency, abundance and density were calculated. Through the sum of the above three relative parameters, the IVI index was obtained for each species. In order to compare the degree of similarity between types, Sorenson's similarity index was used. Relative abundance values for each species in pure and mixed types were set on a 10-unit scale and divided into four specific groups. After determining the tree types of the area, their map was drawn through IDW interpolation method in GIS10.1 software.

In pure type, Tamarix ramosissima and Populus euphratica, with the highest and lowest frequency (6.7 and 3.3) are indicated as high and low respectively. In general, three types were found
including pure, mixed with two and three species. The most amount of Sorenson similarity index was determined between two types of Tamarix-Populus and Tamarix-Lycium (93%) and also Populus-Tamarix and Populus-Lycium (92%). The lowest similarity index value of 12% to 15% was observed between the Populus-Lysium-Tamarix type with pure Tamarix, Tamarix-Lysium, Tamarix-Populus and Populus-Tamarix types. Minimum and maximum maturity index was obtained for pure types (50%) and mixed types (79%), respectively. Pure types have low maturity and mixed types have high maturity. The maturity index for the entire region was 72%, which indicates high maturity.
Discussion and

The tree cover of the river forests of Maroon Behbahan were classified into pure and mixed types on a general scale. The number of two pure types of Tamarix and Populus and seven mixed types including four cases of two types and three cases of three types were obtained. Three species (Tamarix arceuthoides, Populus euphratica and Lycium Shawii) are generally important in the creation of regional types. Among the pure and mixed types, Tamarix was recognized as the most abundant species. The great similarity between pure Tamarix, Tamarix-Lycium and Tamarix-Populus types is due to the common and dominant presence of Tamarix in these types. A variety of different types in a limited area represents complex river ecosystems.

The present research aims to determine areas with flood susceptibility using CART, RF and BRT models. Twelve factors affecting flood susceptibility including altitude )DEM), slope, aspect, distance from stream, lithology, rainfall, land use, SPI, TPI, TWI, curvature and RSP were selected. Out of 82 flood points, 70 percent to 30 percent were randomly classified as training and validation data. Also, random forest method was used to determine the most important parameters. The ROC curve was also used to validation the model. According to the random forest model, DEM, distance from stream, rainfall, land use and RSP were the most important factors affecting the susceptibility and probability of floods, respectively. According to the ROC chart, the accuracy of the RF model as a superior model has been very good in both training )0.884) and validation )0.856). According to the final flood susceptibility map, 32.7 percent of the study area has a medium to high flood susceptibility. The results showed due to the high accuracy of the spatial distribution map of flood susceptibility can be promising for decision makers, local managers and policymakers to reduce flood damages.

Accurate in situ measurement of DBH is easy and cost-effective but, height measurement is labor-intensive, time-consuming and expensive. Understanding its height–diameter relationship is essential for developing growth, biomass production and carbon storage prediction models to be applied in the current forest management projects. The existence of a strong relationship between the diameter and the height of trees is considered as a useful index in forest management and it can be described with mathematical models. Considering that non-linear models are flexible, interpretable and strong, therefore some of the most important models were used in this study.

In this research, 21 widely used candidate nonlinear and one simple linear models were fitted to tree height and diameter at breast height (DBH) data for Populus euphratica Oliv. within a 100 square meter plots at Shoosh area of Khuzestan province. Data from 1163 trees were used and split randomly into two sets: 80 % of the data were used to estimate model parameters (model fitting), and the remaining data (20 %) were reserved for model validation. All model performances were evaluated and compared by means of model performance criteria such as t-statistics of model parameters, root mean square error percentage (RMSE%), mean absolute error percentage (MAE%), mean bias error percentage (ME%), Akaike’s information criterion (AIC) and Bayesian information criterion (BIC).

The parameters of 8 models were not significant at a level of 5%. RMSE, MAE, Bias, AIC and BIC values for M12 model were obtained: 8.98%, 6.78%, -0.0010%, 1451.82 and 1469.73, respectively. The same values were obtained for M21 model: 9.15%, 6.94%, 0.0005%, 1476.95 and 1494.86 respectively. The predicted and actual height values in these two models were not significantly different at a level of 5%. The results of the paired sample t test showed that the nonlinear models M21 and M12 have predicted the height of Populus euophratica trees with appropriate accuracy. Two models (Prodan1 with the name of M12) and (Prodan2 with the name of M21) were selected as the best models based on the ranking of all model performance evaluation criteria in fit and validity data.

The majority of two-parameter models and some three-parameter models showed a significant fit with the data. However, in terms of all performance evaluation criteria, two three-parameter models were chosen as the best models. According to the results of this study and the wide range of non-linear two and three parameter models, mixed models that include one or two covariates in the modeling in addition to the main variables, more research is needed in larger geographical areas, wider sites and stands with different structures are done.

Biodiversity of rangeland ecosystems is directly affected by the biotic traits and environmental factors of the ecosystem. These ensures the sustainability of the ecosystem against environmental and biological changes. The aim of this study was to investigate the response of Performance diversity and species diversity indices to topographic-climatic factors in Angmar region, Mazandaran province. For the task plots were placed in the study area Plant feature including leaf area, dry matter percentage and plant height in each plot were measured and recorded. Environmental factors included topography (slope, aspect and altitude) and climatic factors included average annual temperature, humidity and rainfall were mostly the target features. Performance diversity indices including FAD1, FAD2 and MFAD, FDvar performance divergence indices and FRao performance uniformity indices as well as species diversity indices (Simpson, Shannon, richness and uniformity indices) were calculated in Fdiversity package and to evaluate the significance of the relationship between environmental factors and these indicators, the generalized linear regression (GLM) model was used in R software. The results showed that relationship between species richness and rainfall, altitude and Shannon index was significant only with slope. Simpson index was significantly associated with direction and altitude variables, but uniformity was not significantly associated with any of the environmental factors. The results of Spearman correlation between species diversity indices and performance characteristic diversity indices show that among the species diversity index, Shannon index has the highest correlation with FAD1 yield diversity index. In general, the results showed that topographic-climatic factors have an important relationship with yield. There is a positive relationship between species characteristics in the ecosystem and ecosystem processes.

Monitoring and evaluation of hydrological drought has become a necessity due to its frequent occurrence in various basins of Iran, and in order to prevent and manage the resulting crisis. In most studies, drought indices have been used to investigate it. Drought indices like Streamflow Drought Index, using statistical calculations on river flow data, ultimately leads to a number that does not have the ability to completely investigate and analyze drought in the studied area. Low flow or minimum river flow is one of the most important drought indices that using different criteria can get a comprehensive understanding of the hydrological drought situation in the region. In most studies, deficit characteristics or low flow frequency analysis have been used. Using different low flow indices is necessary to recognize different aspects of drought and its management. Therefore, the aim of this research was to study hydrological drought of Armand river using all of the low flow indices including flow duration curve, deficit characteristics, low flow frequency analysis and base flow index, which can be used to determine characteristics such as dry and wet periods, amount of flow during drought, drought threshold, duration of drought, volume and intensity deficit and frequency of low flows. Also, in this study, the environmental flow of river was calculated and analyzed.

The Armand River basin with 9961 Km2 area located in Chaharmahal and Bakhtiari province was selected as the study area and the daily flow statistics of the Armand hydrometric station were used from 1957 to 2013. First, by plotting the flow duration curve, three low flow indices Q70, Q90 and Q95 also, the river status including wet, normal and drought periods was determined. Then, the minimum environmental flow was calculated based on the two indices Q75 and Q90, and the deficit characteristics using the threshold level Q70. In order to estimate the return period of low flow series (AM7), a suitable two-parameter gamma distribution function was considered appropriate. Finally, the base flow index was calculated using recursive digital filter method in different time scales.

Based on the results, the Armand River in 28, 22 and 14 years (from 57 years of statistical period) has a flow of less than Q70, Q90 and Q95, respectively (45, 32 and 27 m3/s). Due to the gentle slope of the flow duration curve of basin, also the high value of the BFI index (0.95), it was concluded that groundwater had a high participation in the river flow. The dry period in this river begins when the flow reaches less than 45 m3/s (the threshold level Q70). The results showed that the deficit volume and intensity increased over the past 50 years. Based on the frequency analysis of low flow, in the return periods of 2, 5, 10, 20, 50 and 100 years, the low flow was 34.26, 26.8, 23.1, 21.1, 19.1 and 17 m3/s. Comparison of these values with the minimum environmental flow showed that the river flow becomes less than its minimum environmental flow on average every two years.

Despite the sustained flow in the Armand River (due to the snow-rainy regime of the region, the ability of the basin to save water and drain it during the dry season), the dry periods with different intensities occurred over the past 57 years. Also, the severity of drought has increased due to the increase in the volume deficit of the river in recent years, and if this continues in the future, the severity and frequency of the drought occurrence will increase and the overall flow of the river will decrease.

Modeling of the rainfall-runoff process is important. The Results of the rainfall-runoff models have been used directly on issues such as water resource management, flood control and design of hydraulic structures. According to variety of accessible rainfall runoff models, selecting an appropriate model for a basin is important in terms of productivity and water resources management. In this study the performance of two rainfall–runoff models, IHACRES and GR2M in simulation of monthly flow were evaluated in Darhe Tkaht basin between 2000 and 2013 time. The models in the study region were calibrated and validated. The error between observed and simulated flow values was estimated based on the criteria Nash, root mean square error and the total flow volume error. Simulations is indicative satisfactory performance of two models in monthly flow simulation. In addition, the results show that the HACRES model simulate monthly flow with The Nash coefficient 0.7 and RMSE 0.56, better than the GR2M model.

Run off simulation is one of the most important topics in hydrology And its study is based on rainfall- run off models. Several rain fall and run off models have been developed and the most appropriate model should be selected for each catchment. By applying the appropriate model the water consumption will be optimized. The model should be selected for each catchment based on the model abilities and limits. In this study, the performance of two rain fall and runoff models, GR2M and GR4J were compared in Darehtakht Basin in Lorestan Province during 1379 to 1392. The Nash coefficient was used as a decision criteria for comparing two model performances. Nash coefficient for GR4J and GR2M were 42.7 and 65.5, respectively. Results showed that both models can predict the performance of the catchment accurately, but, based on Nash coefficient the GR2M is more accurate than the GR4M.

Due to the effects of climate change on water resources and hydrology, Changes in low flow as an important part of the water cycle, is of interest to researchers, water managers and users in various fields. Changes in characteristics of low flows affected by climate change may have important effects on various aspects of socioeconomic , environmental, water resources and governmental planning. There are several indices to assess the low flows. The used low flow indices in this research for assessing climate change impacts, is include the extracted indices from flow duration curve (Q70, Q90 and Q95), due to the importance of these indices in understanding and assessing the status of river flow in dry seasons that was investigated in Tang Panj Sezar basin in the west of Iran.
In this paper, the Tang Panj Sezar basin with an area of 9410 km2 was divided into 6 smaller sub catchments and the changes of low flow indices were studied in each of the sub catchments. In order to consider the effects of climate change on low flow, scenarios of temperature and precipitation using 10 atmospheric general circulation models (to investigate the uncertainty of GCMs) for both the baseline (1971-2000) and future (2011-2040) under A2 emission scenario was prepared. These scenarios, due to large spatial scale need to downscaling. Therefore, LARS-WG stochastic weather generator model was used. In order to consider the effects of climate change on low flows in the future, a hydrologic model is required to simulate daily flow for 2011-2040. The IHACRES rainfall-runoff model was used for this purpose . After simulation of daily flow using IHACRES, with two time series of daily flow for the observation and future period in each of the sub catchment, the low flow indices were compared.
Results According to results, across the whole year, the monthly temperature in the future period has increased while rainfall scenarios show different variations for different months, also within a month for different GCMs. Based on the results of low flow indices, in most cases, the three indices of Q70, Q90, and Q95 will show incremental changes in the future compared to the past. Also, the domain simulation by 10 GCMs for all three indices is maximum in Tang Panj Sezar and less for other sub catchments, which is related to better performance of IHACRES model in smaller sub catchments. In order to investigate the uncertainty of type changes in different indices in every sub catchment, changes in any of the indices were considered based on the median of GCMs. To achieve the correct type of changes in low flow indices, the amount of error in a simulation of the indices of IHACRES rainfall-runoff model should also be taken into consideration. Therefore, considering the error, the three indices Q70, Q90 and Q95 in all sub catchments (except for Tang Panj Sezar) will have the relative increase in the future period. The improvement of low flow state in the future period is related to the changes occurred in the state of climate scenarios. As the results indicated, most often, there is an increase in rainfall in dry seasons. Also, in different months of the wet season wet season, if the result of changes in quantity of rainfall is incremental, it can lead to an increase in river flow through groundwater recharge. On the other hand due to the limestone and karst forms in most of the basin area, water storage ability and increase the amount of river flow during low water season in this area is expected. The study on rainfall quantity in Tang Panj Sezar sub catchment also indicated that, there will be no significant increase or decrease in the quantity of rainfall in the dry season. Thus, it is expected that there will not be significant changes in low flow indices. In this sub catchment, changes in various low flow indices do not match perfectly, so more difficult to obtain reliable results. With regard to incremental changes of Q95, low flow index with less uncertainty, as well as improving indices of low flow in other sub-basins, it is possible to predict a relatively better state for low flow indices of Tang Panj Sezar in the future period.
Using temperature and rainfall scenarios to simulate river flow in the future, a relative increase of all three low flow indices Q70, Q90 and Q95 was predicted compared with the past period. Although all three of mentioned indices show the amount of low flow in the dry season, it is recommended that only two indices of Q90 and Q95 to assess the effects of climate change be considered. Q90 and Q95 indices are more suitable indices than Q70 for studying the effects of climate change on low flow state. These two indices indicate less quantity of flow in dry seasons; therefore, the changes of the two indices are more important in identifying the low flow state. However, there is less uncertainty in the estimation of the two Q90 and Q95 indices than Q70.

Low flow is one of the very effectual hydrologic parameters on the state of aquatic ecosystems as well as power production, reservoir management and industry. Therefore, it is necessary to investigate the changes in this parameter in the future periods under affecting factors such as climate change. In this regard, the impacts of climate change on low flows of Sepid dasht sezar catchment were evaluated, in this research. First, the ability of IHACRES rainfall-runoff model for simulation of low flows of this catchment was evaluated. After calibration and verification of model, in this study observed that the model has a good ability for simulating of mean daily flow (R2-log>0.7), also low flow (R2-inv>0.6). In addition, the ability of model to low flow indices (including Q95, AM7Q with different return period and QdefS)was evaluated. Then, The outputs of the temperature and precipitation of 10 general circulation models of the atmosphere under A2 emission scenario was used in order to assess the effects of climate change over the period 2015-2044. LARS-WG model was applied for downscaling of the output of these 10 models. Finally, downscaled values ​​of temperature and precipitation were introduced to the IHACRES rainfall - runoff model and the low flow in the future was assessed based on the low flow indices. Changes of two indices Q95 and AM7Q in the future period to the past, based on the median of 10 AOGCM model results is decreasing (-40% for Q95 and from -52% to -79% for AM7Q with different return period). Also, the QdefS index show the increasing change (30% based on the median of AOGCM model results). All three indices have confirmed each other's results and show that the expected climate change in the future, greatly affect the low flows.