مجله مهندسی و مدیریت آبخیز
سال سیزدهم شماره 3 (پاییز 1400)

Preservation of river ecosystem depends on the quantity and quality of the river flow regime, and the construction of large dams causes quantitative and qualitative changes in downstream rivers, so it is necessary to pay attention to the quality of rivers in addition to the quantity of water needs. Therefore, in this study, a 22 km long section of the river at the bottom of Taleghan Dam located in Alborz Province (103 km of Karaj City) was selected with the aim of determining the minimum flow quantitatively in accordance with aquatic biological standards. Based on this, the average annual and monthly flow of the river in four stations in the study period with an approximate distance of six km from each other was estimated. Since there is a relationship between river hydraulic parameters such as depth and flow velocity with the habitat of the target species (such as the index fish), the measured field value was calculated to determine the optimal habitat conditions. Also, in this study period, to compare the possible change in the concentration of pollutants, each of the water quality parameters with its standard concentration for salmon survival was used as an ecological indicator and it was found that among 17 physicochemical parameters of water quality, Sulfate parameter (SO4) and its concentration can be considered as the most appropriate indicator for determining the minimum environmental flow for red-spotted trout in the Taleghan River. SPSS-24 software and One Sample T Test method were used to determine the mean concentration comparison test with standard concentrations of water quality parameters for Salmon biology.

The dynamics of rainfal erosivity (R), crop management (C) and soil erodibility (K) factors compared to the others (topography-LS and land management-P) is the most important note for the correct estimate of soil erosion at different time bases. Spatio-temporal estimates of soil erosion in the representative paired watersheds are of particular importance due to their educational functions as well as the possibility of generalizing the results to larger areas of the country. Therefore, in the present study, while examining the dynamics of R, C and K factors in the Khamsan representative paired watershed, the distribution map of soil erosion in seasonal and annual time scales were prepared using RUSLE model for two water years of 2015-2016 and 2017-2018. The results showed that soil erosion in winter with values ​​of 3.94 and 4.95 t ha-1 y-1 accounted for about 49 and 74% of the total erosion of the year, respectively. Considering the melting conditions in calculating the K factor for the winter along with the lack of vegetation in this season led to a higher estimate of soil erosion than other seasons. These results are in consistent with plots soil loss data recorded in different seasons and the higher concentration of suspended sediments in the rivers especially in March. In the water year of 2015-2016, the distribution of rainfalls in the autumn was much higher than in the spring, so that soil erosion in the autumn accounted for about 33% of the total erosion of the year. In the water year of 2017-2018, although the average annual soil erosion was less, but due to more distribution of erosive rainfalls in winter at the same time with the lack of vegetation on the soil surface and the soil melting, the rate of winter erosion was very high.

In hydrological models, in order to better model the runoff process, it is necessary to calibrate the model using observational data. In the process of calibration of hydrological models, in addition to the quality of observation data and the optimization algorithm, the objective function also affects the efficiency of the model. In most studies, statistical criteria such as NSE and RMSE are used as objective functions in the calibration process of hydrological models. Given the structure of the model and the relationships used in each of the evaluation criteria, each of them has good performance in simulating a part of the hydrograph. One of the important parameters of each basin, which is a kind of basin reaction indicator for different discharge values, is the Flow Continuity Curve (FDC). In this study, the efficiency of objective functions based on flow continuity curve and statistical objective functions in optimizing the parameters of the HBV hydrological model in Ziyarat Watershed of Golestan Province was investigated and compared. After introducing input data to model using DDS algorithm, model was calibrated 100 times for each objective function. When model was calibrated, using optimized parameter sets model output for calibration and validation period was obtained. Results showed that criteria such as NSE and KGE have better performance in predicting high flows, criteria such as RMSE and AME predicted moderate flow discharge better and criteria based on FDC had better performance in predicting low flows. In prediction different parts of hydrograph FDC objective function has the best performance, RMSE and MAE were in sound order and NSE and KGE did not have suitable performance.

Any change in the concentration of greenhouse gases will upset the balance between the components of the climate system. But, the change in the concentration of these gases and how they will affect in the future is unknown. To study the effects of climate change on different systems in the future, climate variables must first be simulated under changes in greenhouse gases (climate scenarios). There are several ways to do this, the most reliable of which is the use of climatic models. AOGCMs can simulate climate parameters globally in large scale, while these may not be suitable for small scales. One of the most important downscaling methods is dynamic methods that are based on increasing the resolution and analysis of planetary climate models. Here, in this research, climate change status in Karkheh River Basin where a major basin for water and agricultural yields is studied. For this purpose, the PRECIS model was used. PRECIS is an exponential dynamics downscaling model used to estimate the temperature and precipitation rates for the period of 2070 to 2100 under A2 and B2 scenarios. According to the results of climate change assessment under scenario A2, precipitation would increase up to 11% and up to five degree centigrade would rise in average maximum and minimum temperature while concerning B2 scenario, an increase in precipitation up to 7% and a rise in temperature rise up to three degree centigrade are estimated. However, under both the scenarios, despite, the fall’s precipitation is higher than the winter’s precipitation.

Estimation of sediment bed load is one of the most important issues in river engineering. Accordingly, several methods and relations have been proposed to estimate the bed load in streams for the past decades. The present research aimed to select the most accurate method to estimate bed load through the testing of various relations to estimate the bed load of the Hablehroud River. The hydraulic and geometric specifications of the Hablehroud River at Bankouh hydrometry station were measured on specific dates by the expert team. The bed load rate was calculated by four different relations in Bankouh hydrometry station from 2011 to 2017. Resultant data showed that the Toffaletti method with RMSE, MAE, and R2 of 20.07, 10.86, and 83 estimates more accurate in comparison with other methods. The sensitivity analysis of the Toffaletti equation revealed that the bed load depends greatly on the velocity of the river flow. Such a method is firmly recommended to use in the mountainous region.

Every year, floods destroy the economic and social structure of communities and cause a lot of financial and human losses. One of the effective factors in the occurrence of floods is the development of urbanization around rivers. Due to climate change, in recent decades, Sistan and Baluchestan Province with hot and dry climate, is prone to floods. The aim of the present study is to zoning the flood of Sarbaz Watershed using HEC-RAS hydraulic model. To conduct the research, the SCS model of the area was first determined according to satellite images, land use map and runoff curve number. Then, the flood discharge of the basin with 10, 25, 50 and 100 years return periods was simulated using the HEC-HMS hydrological model. The simulation results resulted in the occurrence of peak flood discharges of 3363.8, 4563.7, 54462 and 6359.3 m3s-1 for return periods of 10, 25, 50 and 100 years in the study basin, respectively. In order to evaluate the efficiency of the model in calibration and validation stage, Nash-Sutcliffe evaluation indices and the mean square error were used, the results of which indicate the optimal performance of the model. Then, the flood zoning map of Sarbaz Watershed in Rusk City was prepared in desired return period with the help of HEC-RAS hydraulic model. The results showed that with the return periods of 10, 25, 50 and 100 years, 366.86, 397.12, 449.95 and 580.78 hectares of flood zone of Sarbaz Watershed in Rask City area will increase, respectively.

Increased concentration of atmospheric carbon dioxide due to human activities has resulted in accelerated global warming process. Forestation is the most effective way to absorb atmospheric carbon dioxide and store it in terrestrial ecosystems in order to reduce and mitigate global warming. This study aimed to investigate the comparison of soil carbon sequestration in various stands in ​​Kuhdasht Aquifer and to present the best regression model for carbon sequestration based on all soil characteristics. In each stand (20-year old) of Ficus carica, Punica granatum, Pistacia vera, Amygdalus lycioides and Cupressus arizonica species as well as control rangeland, a number of 10 sample plots (5×5 m) were randomly selected and soil samples were taken in each plot at 0-10, 10-30 and 30-50 cm depths. All soil samples were transferred to the laboratory in order to measure soil characteristics including soil texture, organic carbon, bulk density, electrical conductivity, lime percentage and soil acidity. The results showed that the highest value of carbon sequestration in soil of Pistacia vera stand (54.94 tha-1) significantly (P <%1) higher compared to other stands, followed by Ficus carica (50.23 tha-1), Amygdalus lycioides (31.53 tha-1), Punica granatum (27.09 tha-1), Cupressus arizonica (24.17 tha-1) and control rangeland (9.01 tha-1) stands. Results also showed significant differences (P <%1) between the studied stands in terms of soil texture, acidity, organic carbon, electrical conductivity and soil bulk density. Also, the result of stepwise regression indicated that soil texture and acidity were the most important components affecting soil carbon sequestration, respectively.

The correct and accurate estimation of river flow can play an important role in reducing the effects of flood damage. In this research, Gene Expression Programming (GEP) model and Bayesian Network (BN) were used to predict daily flow of Mahabad River in Urmia Lake Basin. Accordingly, four input models with a delay of one to four days used to estimate daily flow at time t+1 over a 23-years period and 75% of data was used to train the models and 25% of the remaining data was used for the test stage. Results showed that the best model in both methods was the input pattern with three-time lags. Also, based on the correlation coefficient (R), Root Mean Square Error (RMSE) and Nash-Sutcliffe (E) coefficient in the test stage of the GEP method with R=0.902, RMSE=2.71(m3s-1) and E=0.812 compared to the BN method with R=0.905, RMSE=2.679(m3s-1( and E=0.817 is more accurate. In general, both methods have acceptable accuracy and are they relatively similar, but because of the simpler modeling, Bayesian Network method can be used as an efficient method for predicting river flow.

The increasing exploitation of groundwater reserves and consequently the drop in the water level and reduction of the reserves have seriously caught the attention of officials and planners to the integrated management of groundwater and surface water resources. The evaluation and management of water resources are considered as one of the key factors in comprehensive development. Boein Aquifer in Isfahan Province located in the Gavkhooni Basin is studied in this study. The Standard Precipitation Index (SPI), Reclamation Drought Index (RDI) and Groundwater Standard Index (GRI) in the time scales of three, six, 12, 24 and 48 months and Cultivated Land Index (CLI) in annual time scale are calculated. Results showed that the highest correlation between the SPI and GRI is in 18 and 24 months' time scale, and there is a delay of 1.5 to 2 years between these two droughts. Contrary to the results of some references, the correlation between meteorological drought index and GRI does not always increase with increasing the time scale. A synchronic study of the SPI, GRI and CLI shows a large difference between the SRI and the other two indicators in 2004-2008 periods that may be related to the poor management of the region. However, more close values obtained for these three indices in the recent years mainly due to the better management of water consumption by relevant organizations. To determine homogeneous drought regions, different combinations of temporal and spatial scales were used by creating 39 different scenarios and running 390,000 simulations. None of the heterogeneity measures were met in 90% of cases. This indicated that the linear moment technique is not a suitable method for determining homogeneous arid regions of groundwater probably due to the non-random data. Therefore, the linear moment technique will be more useful if the data is random.

In recent years, flooding of rivers has resulted in destructive implications, especially in the coastal areas. Dashtyari coastal plain is located in the southeastern of Iran. The occurrence of destructive floods has led to extensive damage to agricultural facilities, buildings, and residents of the region in recent years. Morphometric factors of the river and its surroundings land-uses and their changes in the future are effective and necessary factors in the planning of coastal plains. Remote sensing is an applicable tool to investigate the past, present, and postcondition of rivers. The GIS-Ready layers included satellite images (Landsat 5, 1987; 7, 2001; 8, 2019; Sentinel-2, 2020), and specific software (Envi 5.3, ArcGIS 10.4.1, and Idrisi TerrSet), as well as the existence and fieldwork documents, have been used to achieve the research aims. Probability values of land-use changes in 2019 were obtained based on Markov chains. Accordingly, the highest probability of changes 24.87% and 23.5% were obtained between the river and plain units, and between farms and river, respectively. Then, an automatic cell prediction map of 2019 is accomplished with the overall kappa coefficient of 95%. According to the accuracy of the output of the cellular Automata Markov model, forecasted Land use and river morphology maps for 2030 were developed. Further, possible changes in the river environment were obtained by fitting the two maps of 2019 and forecasting 2030. Moreover, bank erosion was identified in the 6 critical points along the Kajo, Dashtyari, and Bahu rivers. Finally, the destructive flood event in January 2020 in the Dashtyari region was investigated to match the results with natural events.