نشریه فناوری های پیشرفته در بهره وری آب
سال یکم شماره 1 (زمستان 1400)

In this research, monthly temperature, precipitation and discharge values of Jamishan Dam in 1988-2017 have been considered as the base period. Simulation of resources and uses of Dam-d-Gomishan basin in WEAP model with existing cropping patterns in the region was investigated. To evaluate the effect of climate change on precipitation and temperature parameters in this region, the outputs of the RCP8.5 scenario of the HADGEM2_ES models were used from the cmip5 fifth report series and the output of these models was downscaled for the desired area. In this study, using the method of change factor downscaling the climatic model and monthly temperature and precipitation parameters of Jamishan Dam for the period 2021-2050 were generated. In order to investigate the runoff of the area due to climate change, SVM, GEP and IHACRES models were investigated and compared. The results of the climatic model show an average temperature increase of 1.5 °C and an increase in precipitation of 5%. In general, results of discharge forecasting in all three models indicate a decrease in runoff that the highest runoff reduction was related to SVM with 21.6% and the lowest runoff reduction was related to IHACRES with 4%. In this study, IHACRES and GEP models have more favorable accuracy than SVR method. Simulation of different cropping patterns in WEAP shows that the highest supply is equal to 74.9% in GEP model and the lowest supply is equal to 70% in SVR model which is related to cropping pattern 1 and cropping pattern 3, respectively.

Accurate and correct prediction of surface water flow plays an important role in the principled planning and proper management of water resources. To achieve this, various prediction models using mathematical relationships based on hydrological information can be used. In this study, monthly discharge of Polechehr hydrometric station for a 48-year has been used (Sep. 2018-October 1971). Two main scenarios with and without pre-processing (standardization), two time series or non-time series approaches were considered. Also, two cases with and without feature selection have been considered by a random forest algorithm. In all cases, 80% and 20% of the data are intended for model training and testing, respectively. The entire coding process is done in the Python programming platform. Genetic algorithm was used to optimize the parameters of the support vector regression method. The results showed that standardization, non-time series approach, reducing the dimensionality of the model input to select and also using genetic algorithm to optimize the parameters of the support vector regression model have the greatest effect on prediction accuracy, respectively. So that the highest coefficient of explanation for training data is 0.85 and for testing is equal to 0.6.If standardization is not applying on the data, adopting a time series approach and feature selection will lead to better results in predicting the SVR model, and also the use of genetic algorithm optimizer compared to the simple model will have a significant effect on improving results.

Common water resources have caused tensions as well as partnerships across the regional to international levels. Undoubtedly, identifying the factors influencing the management of such resources will be a prerequisite for bilateral or multilateral negotiations to resolve existing tensions and establish cooperation between stakeholders. Therefore, in this article, an attempt has been made to identify the effective parameters from a hydropolitical point of view with a comprehensive look at the issues of transboundary water resources management and to categorize them in an innovative framework. The approach used to achieve this goal is the deep review of existing literature as well as the use of remote sensing to study different criteria. Harirud basin as one of the obvious examples of transboundary water issues is involved in specific challenges between the three countries and may be a suitable choice for covering different factors in this field. The innovative framework based on four areas of political, economic, social and environmental has been presented as the main dimensions of hydropolitics and prioritized based on the opinion of experts. The results show that in order to reach a comprehensive and lasting agreement, the greatest focus should be on the political and economic areas. In this regard, paying attention to the sub-criteria of geographical location, management of available water resources, stability of political sovereignty, water management, food security, hydrology of the basin, water and energy exchanges, water trade and conflict of strategic interests will have the greatest impact on the negotiation process.

The impact of flow on the bridge piers creates turbulent flows that cause scour around it, and as result collapse of the bridges. Despite to most research which done in this area, but due to the complexity of the phenomena and the many parameters involved in the phenomenon, there is still no exact relationship or fundamental solution to predict scour depth. In the present study, using the measured data, the scour depth was estimated with data mining methods such as artificial neural network, linear and nonlinear regression models and also empirical relationships. The data were used in two ways, with dimensions and non-dimension, which were obtained using dimensional analysis. The results showed that the artificial neural network model able to predict scour depth with determination coefficient (R2) equal to 0.97 and 0.81, as well as RMSE error equal to 0.06 m and 0.32, respectively, when data was used with dimension and non-dimension forms. Also, the empirical equations of the Colorado State University between the empirical relationships predicted scour depth with R2 and RMSE error equal to 0.84 and 0.52. Comparison of the results of different models shows that the best results are related to the artificial neural network model and it decreased error of prediction 70, 85.5 and 87.7% compared to linear regression model, nonlinear regression model and the empirical equation of the Colorado State University, respectively.

IntroductionSezar River of the main branches of Dez River and long term streamflow predicting of the river is important, in order to optimal operation of Dez Dam Reservoir. MethodsIn this research initially, streamflow trend of Sezar River evaluated with TFPW-MK method at statistical period 1970-1971 to 2008-2009 that is a period without trend of the basin precipitation. The results showed, streamflow of Sezar River has a significant negative trend. Then in order to evalution streamflow reduction causes of the river, were evaluated, three basic factors affecting on river streamflow, that is precipitation, inter and intra basin withdrawals from surface water resources of basin and withdrawals from groundwater resources of basin. ConclusionThe results showed, main cause of streamflow reduction of the river is excessive harvesting of groundwater. Finally, predicted long term streamflow of Sezar River. The results showed, average of prediction streamflow time series of Sezar River, about 22.42 m3/s is lower than average of streamflow time series of the river in the case of excessive withdrawals from groundwater resourses are not that cause the interaction of surface water and groundwater is not. The data used is include, data of 3 hydrometric stations and 15 pluviometry stations of Sezar basin, information of development projects inside and outside basin surface water resources, and data of digging year and coordinates of waterwells in the basin.

Structural methods that can be used to control the flood are dams without a core. The flow of these dams is disturbed and the Darcy law is not valid. the turbulent flow equations, including the relations between the Reynolds number and the friction coefficient, are used. relations governing these hydraulic dams are non-linear, extraction of a simple and precise discharge-stage relationship can double management and operation of these dams. Experiments were performed in a laboratory floam in correct the one-dimensional discharge-stage theory equation in rockfill dams and Through dimensional analysis, dimensionless quantities, were extracted in the flow problem from a rockfill dam. 21 series of experiments were carried out on rectangular and trapezoidal sections with rocks in diameters of 3, 5 and 7 cm and lengths of 0.5, 1 and 1.5 meters. And by applying multivariate nonlinear regression on a large of laboratory results (70%), two correctional equations were presented. Based on the statistical indices obtained from 30% of the data, the validation of the equations was considered and the acceptable results were obtained for the correction equations. The results and statistical indices show that the resulting equation of dimensional analysis is more consistent with the one-dimensional theory and one-dimensional modified equations and its error rate for 30% of the data, equal to 0.107%, therefore, Can be used as an appropriate equation. The one-dimensional theory and one-dimensional modified equations were compared with the two-dimensional theory and two-dimensional modified equations and the results showed that the two-dimensional equations have high accuracy.