Water resource development plans (such as dams) has the numerous environmental effects, which altering the natural regime of River and River flow reduction is the most important. One of the most important environmental challenges in water resources planning is River water rights estimation affected by natural variables, understanding the importance of protecting water resources, variety biological and ecosystems related to River flow. Environmental flows is meaning time, quality and amount of required current to protect freshwater, estuarine ecosystems, human welfare and livelihoods related to water. The main aim of this study is estimation of environmental water right Gorganrood River (Aq Qala station) based on 33-year period, using hydrological methods: Tennant, Tessman, aquatic base flow, flow duration curve and duration curve change in different months of years. The results show that at least the Gorganrood River flow (Aq Qala station) to provide environmental flows using the above methods, respectively should equal to 27/2, 8/1, 51/5, 47/4 and 33/3 (class C) cubic meters per second. This study has shown that in the absence of information on the ecological, hydrological indices can be used for preliminary estimation of environmental flows.

Hydrological drought usually have a considerable impact on the quantity and quality of water resources, causing water shortages in consumption sector and its study is important in terms of intensity, frequency and spatial extent. The aim of this study is to determine the periods of hydrological droughts, drought characteristics and amount of flow deficit in a 38-year recorded data over hydrometric stations of the Golestan Province. The weighting factor of drought importance for each month was calculated based on the flow distribution in different months. The subtracted mean discharge of particular month from the long-term average was multiplied by the weighting factor to determine the effective discharge. The difference of mean monthly discharge and effective discharge considered as monthly flow deficit. The onset and end of hydrological drought periods were defined and the cumulated flow deficits were calculated. The results showed that the highest flow deficit amounts were recognized for in Taghiabad, Basirabad, and Hajighoshan stations with 1. 28, 1. 27, and 1. 07 respectively. In general, the flow deficit were observed in June, July and August in almost all River gauge stations of the study area. Moreover, the deficit volume was lower at stations located in upland areas.

Accurate estimation of suspended sediment in Rivers is very important from different aspects including agriculture, soil conservation, shipping, dam construction and aquatic research. There are different methods for suspended sediment estimation. In the present study to evaluate the ability of time-series models including Markov and ARIMA in predicting suspended sediment and to compare their results to sediment rating curve (SRC), it was tried to use daily suspended data from Ghazaghly station of Gorganroud River, as an average monthly values in Minitab 16 software and finally suspended sediment was predicted for 111 months. In the next step, different combinations of all types of SRC and bias correction factors were used in Excel software to evaluate ability of SRC in suspended sediment estimation. Based on the results of this study, monthly SRC without bias correction factor was the most appropriate SRC models. To compare efficiency of different models in estimating suspended sediment, Root Mean Square Errors (RMSE) and Normalized Mean Square Errors (NMSE) were used. Time series model performance measured by RMSE and NMSE was about 71.34 and 2.48, respectively compared to SRC model with RMSE 220.75 and NMSE 28.62.Results showed a good ability of time series models in estimating average monthly suspended sediment.

The amount of sediment load significantly changes along a River due to environmental effects. This variability should be considered to estimate the amount of sediment load. In this research, spatial and seasonal variation of sediment load along of Gorganroud River were evaluated based on the information of 7 hydrometry stations sited in main branch of the River namely, Tamar, Hajighoshn, Gonbad, Voshmgir, Aghghala and Basirabad. Since the amount of sediment load is directly correlated with water discharge, for assuming the effect of water discharge, linear form of sediment rating curve is used where the linear form is produced by the logarithm transformation. Based on this linear relationship with possibly different slopes, the generalized analysis of covariance with logarithm of discharge as its covariate was used to compare the logarithm of sediment load as its response. In order to precisely estimate the amount of sediment load and adequately modify the sediment rating curve, the spatial comparison was drawn separately at low, middle and high rate of water discharge. Spatial evaluation demonstrated an increase in sediment load from Tamer station to Basirabad but there are some distinctive areas between mentioned stations with noticeably decreasing (80% in average) in their sediment load mainly due to reservoir building. For seasonal evaluation of sediment load, the percentage of sediment yield at different seasons was compared. This evaluation revealed that spring with at least 50% and at most 70% of total suspended sediment discharge has the highest amount of suspended sediment yield in this River.

Introduction: The coastal zone is one of the greatest environmental and economic assets of each nation. In coastal regions the natural forces that cause shoreline changes are embodied in waves, currents, wind and other factors. Gorganroud River Delta is located in 53o 57 to 54 o I E and 36 o 56 to 37 o N in Southeast part of Caspian Sea. In this study, gibbosity of Gorgan River delta has been studied at the River mouth. The Gorganroud River basin from the Caspian Sea catchment basin is covering a large part of it in Golestan Province. The total flow rate of Gorgan Bay River Catchment is about 500 cubic meters and total of their discharge is 3.5 million tons per year. With average slope less than 0.1 percent, the study area is very low slope.

The distribution and abundance of high aquatic plants in the Gorganroud River was examined at five stations in four seasons (20 samples) over one year period during 2009-2010. We identified 21 species of aquatic plants from 21 genera, belonging to 9 families. These species were determined as 3 halophytic species (14.2%) and 18 high aquatic plants (85.7%).The highest species diversity was observed at Khajenafas, Aq qala and Chargoli stations (17, 13 and 11 species) respectively, The highest biomass of high aquatic plants were recorded in summer (for Inspection and Chargoli stations 11.5 and 10.1 g.m-2, respectively) and autumn (for the station of Inspection was 8.5 g.m-2 dry weight). The most dominant species were different in the investigated stations. At station 1 species Tamarix kotschyi, at station 2 species Juncus acutiflorus, at station 3 species Hordeum murinum hudson, at station 4 species Salicornia europaea L and at station 5 Juncus acutiflorus species were dominated.

This study surveyed Intrabasin variation in the growth models of C. capoeta in 5 streams of Gorganroud River basin during the reproduction season between April and May, 2010 and 2011. A total number of 1500 specimens were caught through electro-shocking. Total length, total weight, sex and b-value were determined. Total length ranged between 4.1 and 20 cm and total weight ranged between 0.81 and 108.34 g in Pishkamer and Tilabad streams, respectively. The growth models were estimated separately for each sex. The b-value ranged from 2.90 for the males of Pishkamer and Tilabad to 3.13 for the females of Chelchai. Growth model was positive allometric (b>3) for most of the females, while the males had different growth models. A comparison between the b-value of the streams can aid the identification of the factors contributing to the growth model of the populations. In fact, different types of habitats differ in their general environmental conditions which can cause reactions. This reflects a change in the body form with population. This variation in the allometry coefficient of C. capoeta suggests different growth strategies for the populations.

This study was conducted to investigate abundance and species distributn of macrobenthos in 3 stations in Gorganroad River (S1: 36 58 42E, 54 00 28; S2: 36 58 41, 54 01 27; S3: 36 59 14, 54 02 54) from March to February 2013. Samples collected using Van ven grab in 3 replicates in each station. In the study area, 6 orders belonging to 9 families were indentified including Naididae, Gammaridae, Cardidae, Nereidae, Neritidae, Ampharetidae, Pyrgulidae, Ostracoda, Foraminifera, Balanidae and Cumaceae. The most abundant taxa were Ampharetidae (28. 62%), Lumbriculidae (24. 24%), Naididae (11. 3%), Chironomidae (10. 44%), Balanidae (10. 39%), Gammaridae (6. 14%), Nereididae (31. 91%), Cardiidae (2. 73%) and Tubificidae (2. 19%). Generally, in all 3 stations the highest and lowest biomass belonged to the Ampharetidae family (25410) and Tubificidae (1946), respectively.

In this research it is attempted to optimize relations between flow discharge and suspended sediment discharge in selected hydrometric stations located on the main branch of Gorganroud River. Homogeneity of data was initially tested using Smirnov-Kolmogrov technique. Then, using daily discharge data and employing "Technical Hydrology" software, monthly hydrographs of the discharge were drawn for all selected stations. Considering hydro-climatic factors that affect the suspended sediment discharge, such as hydrograph condition, classified discharge, and time, some models were tested on the basis of the sediment transport equation. Some regression models were obtained between flow and suspended sediment discharge, and values of “a” and “b” parameters were then resulted for each parts of the model. To select the optimum model, mean squares of errors were used as an index according to which models with low values of mean squares of errors were selected as optimum ones for each station. Results indicated that general regression model which uses only one equation as sediment rating curve equation bears the highest error among all tested models for estimating suspended sediment. So, it is recommended to employ the models with low errors for estimating sediment discharge in the study area.

Accurate estimation of suspended sediment in Rivers is very important from different aspects including agriculture, soil conservation, shipping, dam construction and aquatic research. There are different methods for suspended sediment estimation. In the present study to evaluate the ability of time-series models including Markov and ARIMA in predicting suspended sediment and to compare their results to Artificial Neural Networks it was tried to use daily suspended data from Ghazaghly station of Gorganroud River, as average monthly values in Minitab 16 software and Neurosolutions 5, and finally suspended sediment was predicted for 111 months. Calculation of the error measurement indices including RMSE and NMSE based on the results of this study showed a good ability of Artificial Neural Network models in estimating average monthly suspended sediment. On the other hand between time series models, Markov model has better ability in estimating monthly suspended sediment in comparison to the ARIMA model.