Management and Simulation of the Latian Multi-purpose Reservoir Dam and Its Performance Evaluation Based on the Operation Policy on Daily Time Scale

IntroductionDevelopment of reservoirs helps to meet food and energy needs by supplying water for agriculture and hydropower plants. Efficient management of water resources is important and vital to overcome the problems of water leakage and meet agricultural, industrial and drinking needs. Each of these requirements creates limitations in the way the reservoir is operated, which requires accurate information on the changes in the reservoir storage and other influential components during the operation period. In order to manage and plan water resources at country scale, using reservoir simulation models as a suitable tool in simulating processes related to dams, such as the operation of water reservoirs, will be very effective. Reservoir simulation models such as the HEC-ResSim model provide the opportunity to simulate the natural and hydrological processes related to the water resources system and the relationships between the supply and demand sectors by implementing a schematic structure of a real reservoir. Two scenarios of water savings of 20 and 30 percent were used in the current investigation.  Additionally, using this method, the objectives of water resource management can be assessed.Materials and MethodsIn the present study, the use of the Latian reservoir in real conditions was simulated using the HEC-ResSim model. The simulation was carried out according to the river's inflow from 1968 to 2018, downstream water needs, energy production capacity by turbines, physical characteristics and reservoir building. The implementation of the HEC-ResSim model is summarized in three steps. The Watershed Setup module is used to introduce the general outline of the watershed. In this module, the shape and geographical location of the basin and related elements such as rivers, reservoirs, hydrometric stations and other projects in it should be specified. The Reservoir Network module is used to introduce the desired reservoir network and to enter the physical characteristics and how to use them. The Simulation module is designed to introduce the simulation period and display the model outputs.  In this module, the simulation time and period and the operation pattern should be determined.Results and DiscussionAccording to the results obtained from the reservoir simulation model, the average storage capacity of Latian dam for the simulation period was estimated to be 41 million cubic meters, which shows a significant drop of 49% compared to the normal level (83 million cubic meters). Additionally, for the same period, it was estimated that the average discharge was equivalent to 5.4 cubic meters per second and the average inflow to the reservoir of the Latian dam was equal to 5.7 cubic meters per second. This is in contrast to the period's average demand, which for the area downstream of the Latian Dam is 12.1 cubic meters. The findings indicate that the reservoir of the dam frequently, and particularly at the conclusion of the simulation period, is unable to satisfy the needs of the downstream. Additionally, according to the findings of the current study, the Latian dam power plant's (Kalan) average annual hydro-electric energy production was projected to be 68,000 MWh, and the results show that in accordance with the policy of operating the Latian dam in the majority ofthe years, the Kalan power plant is able to supply the electricity required in the study area. According to the results, the average reservoir volume of Latian dam for the entire period in the first and second scenario was estimated to be 49 and 63 million cubic meters, respectively. Also, by applying the first and second water saving scenarios, the Latian dam reservoir will be able to generate 66,000 and 63,000 MWh of energy annually.ConclusionIn this study, the functioning and operation of the Latian dam reservoir was used by applying the Hec-ResSim reservoir simulation model. After entering data such as the elevation and length of the dam, surface-volume-elevation curve, evaporation from the surface of the reservoir, elevation and uncontrolled outlet coefficient, dam storage areas, rule curve, were simulated by the model. In the present study, the values of inactive volume and conservation volume of Latian Dam were estimated as 28 and 83 million cubic meters, respectively. The average water release of Latian dam for the first and second 25 years of operation was equal to 6.1 and 3.7 cubic meters per second, respectively, which met 50 and 32% of the downstream demand on average. The results indicate that the success rate of Latian dam in supplying drinking, industry and downstream environment for the period of operation is 42%. Also, 16 years out of 50 years of operation, Kalan hydropower plant has fully met 100% of the needs. On average, the large power plant is able to provide 80% of the energy needs of the study area for the entire simulation period

Neutron diffraction residual stress measurements on girth-welded 304 stainless steel pipes with weld metal deposited up to half and full pipe wall thickness

The residual stress distribution has been measured in two girth-welded austenitic stainless steel pipe weldments using time-of-flight neutron diffraction. One had weld filler metal deposited up to half the pipe wall thickness, and one had weld metal deposited up to full pipe wall thickness. The aim of the work is to evaluate the evolution in residual stress profile on filling the weld, on which there is little experimental data, and where the selection of the correct hardening model used in finite element modelling can benefit greatly from an understanding of the intermediate residual stresses partway through the welding operation. The measured residual stresses are compared with those calculated by finite element modelling and measured using X-ray diffraction. The results show a change in the measured hoop stress at the weld toe from tension to compression between the half-and fully-filled weld. The finite element results show an overprediction of the residual stress, which may be a consequence of the simple isotropic hardening model applied. The results have implications for the likely occurrence of stress corrosion cracking in this important type of pipe-to-pipe weldment

Numerical Estimation of Drinking Water Quality Index Using Tree Methods and Combined Wavelet Approaches and Principal Component Analysis

Introduction Surface and underground waters are one of the world's most important problems and environmental concerns. In the last few decades, due to the rapid growth of the population, the water needs have increased, followed by the input load to the water. In order to classify the quality of underground water and water level according to the type of consumption, there are many methods, one of the most used methods is the use of quality indicators. Considering the facilities available in water quality monitoring stations and the need to save time and money, using alternative methods of modern data mining methods can be good for predicting and classifying water quality. The process of water extraction for domestic use, agricultural production, mineral industrial production, electricity production, and ester methods can lead to the deterioration of water quality and quantity, which affects the aquatic ecosystem, that is, the set of organisms that live and interact. Therefore, it is very important to evaluate the quality of surface water in water-environmental management and in monitoring the concentration of pollutants in rivers. The aim of the current research was to estimate the numerical values of the drinking water quality index (WQI) using the tree method and investigate the effect of wavelet transformation, the Bagging method, and principal component analysis. Materials and Methods In this research, to calculate the WQI index from the quality parameters of the Bagh Kalaye hydrometric station including total hardness (TH), alkalinity (pH), electrical conductivity (EC), total dissolved solids (TDS), calcium (Ca), sodium (Na), Magnesium (Mg), potassium (K), chlorine (Cl), carbonate (CO3), bicarbonate (HCO3) and sulfate (SO4) were used in the statistical period of 23 years (1998-2020). Quantitative values calculated with the WQI index were considered as target outputs. By using the relief and correlation method, the types of input combinations were determined. The random tree method was used to estimate the numerical values of the WQI index. Then, the capability of the combined approach of wavelet, principal component analysis, and Bagging method with random tree base algorithm was evaluated. To compare the values obtained from the data mining methods with the values calculated from the WQI index, the evaluation criteria of correlation coefficient (R), root mean square error (RMSE), mean absolute error (MAE), and modified Wilmot coefficient (Dr) were used. Results and Discussion The use of the wavelet transform method and the Bagging method has improved the modeling results. Considering that the Bagging classification method with the random tree base algorithm is a combination of the results of several random trees, so using this method has increased the accuracy of the RT model. So, in general, it was concluded that the use of wavelet transformation and classification methods increases accuracy and reduces errors. The best scenario with the highest accuracy and the lowest error was related to scenario 10 of the W-B-RT model with Total Hardness, Electrical Conductivity, Total Dissolved Solid, Sulphate, Calcium, Bicarbonate, Magnesium, Chlorine, Sodium, and potassium parameters. The results showed that the effect impact of pH in estimating the numerical value of the WQI index is considered lower than other parameters. When the principal component analysis method was used, by reducing the value of the eigenvalue from F1 to F12, the value of the factor also decreased; As a result,so F1, F2, and F3 factors were selected as the basic components. Considering 3 main factors, modeling was done employed and R=0.98, RMSE=2.17, MAE=1.52, and Dr=0.97 were obtained. In general, the results showed that the PCA method, despite reducing the dimension of the input vectors and simplifying it, can improve the accuracy and speed of the model and is introduced as the best method for estimating the numerical value of the WQI index. Conclusion The results obtained from the present research showed that the use of wavelet transform, Bagging and PCA methods had a positive effect on improving the results and increasing higherthe accuracy. In estimating the numerical values of WQI index, PCA-B-RT method considering 3 main factors, with correlation coefficient equal to 0.98, root mean square error equal to 2.17, average absolute value error equal to 1.52 and tThe modified Wilmot coefficient equal to 0.97 had the highest accuracy. Considering that all the methods used in the estimation of quantitative values had acceptable accuracy, therefore, in case of lack of data and lack of access to all chemical parameters, it is possible to obtain appropriate and acceptable results by using a limited number of parameters and data mining methods achieved

Regional frequency analysis of minimum flow by L-moments method [Minimum akımların l-momentleryöntemi ile bölgesel frekans analizi]

In this study, it was aimed to determine regional frequency analysis for selected 26 stations out of 41 streamflow gauging stations located in Sefidrud Dam watershed in north of Iran.7-day low flows are considered as indices for hydrological drought analysis. The study area was identified as heterogeneous based on the homogeneity measurement (H1=13.68) by a software with code written in FORTRAN language. Therefore Fuzzy Cluster Analysis (FCA) algorithm is applied to distinguish the homogeneous sub regions by taking into consideration the physiographic and hydrologic characteristics of the watershed. Two regions were identified as the result of FCA analysis namely; east region and west region. According to the L-Moment analysis, East region of the watershed was found homogeneous and the West region of the watershed became homogeneous after removing the Gilvan, Yengikend and Firuzabad streamflow stations. The Generalized Logistic (GLO) and Pearson Type III (PIII) distributions were selected as the best fit regional distributions for the east and west sub-regions, respectively. The best fit distribution is selected with the smallest absolute value of the Z statistic (ZDIST) based on the goodness-of-fit-test. The selected best fit distributions are advised to use in the regional low-flow forecasting of Sefidrud watershed. © Ankara Üniversitesi Ziraat Fakültesi