► The materials and methods were combined. ► Full form of any abbreviation, were used when using first time in manuscript. ► The authors paid 325$ for editing the manuscript by a professional editing ...service.
The goal of the present research is forecasting the inflow of Dez dam reservoir by using Auto Regressive Moving Average (ARMA) and Auto Regressive Integrated Moving Average (ARIMA) models while increasing the number of parameters in order to increase the forecast accuracy to four parameters and comparing them with the static and dynamic artificial neural networks. In this research, monthly discharges from 1960 to 2007 were used. The statistics related to first 42years were used to train the models and the 5 past years were used to forecast. In ARMA and ARIMA models, the polynomial was derived respectively with four and six parameters to forecast the inflow. In the artificial neural network, the radial and sigmoid activity functions were used with several different neurons in the hidden layers. By comparing root mean square error (RMSE) and mean bias error (MBE), dynamic artificial neural network model with sigmoid activity function and 17 neurons in the hidden layer was chosen as the best model for forecasting inflow of the Dez dam reservoir. Inflow of the dam reservoir in the 12 past months shows that ARIMA model had a less error compared with the ARMA model. Static and Dynamic autoregressive artificial neural networks with activity sigmoid function can forecast the inflow to the dam reservoirs from the past 60months.
Abstract Introduction: The limitation of the country's water resources and the aggravation of this limitation, which is caused by the continuous increase in the demand, has caused the maximum use of ...the available water resources and the increase in productivity and, as a result, the increase in production per unit area. The present research was conducted with the aim of evaluating the water quality of Dez River in terms of efficiency in pressurized irrigation systems. Methods: For quality assessment of Dez River water in terms of efficiency in pressurized irrigation systems, 7 hydrometric stations were selected including Sepid dashte Sezar, Sepid dashte zaz, Tange pange sezar, Tange pange bakhtiari, Dezful, Harmaleh, and Bamdezh. Qualitative data of Dez River water along a decade (2005-2014) were taken from Khuzestan water and power authority. Findings: The Qualitative analysis using piper diagram showed that water quality in Sepid dashte Sezar, Sepid dashte zaz and Tange pange sezar stations was calcium bicarbonate. Although, in Harmaleh and Bamdezh stations the most of samples were neutral. The results showed that salinity amount was increased from the upstream to the downstream of the river. Whereas, Bamdezh station had low to medium limitation at 95 percent of times for drip irrigation usage. Dez River had no limitation for infiltration due to suitable averages of SAR and EC. Besides, cations and anions coefficient of correlation was variable between 0.67 to 0.78 and -0.249 to 0.6 respectively. Chlorine in the river water from Harmaleh station toward the downstream of the river, had low to medium limitation for sprinkler irrigation usage. The most limitation of bicarbonate was observed at 97.5 percent of times in Sepid dashte Sezar station for using sprinkler irrigation. In addition, sodium amount in Harmaleh and Bamdezh stations compared to Dezful station increased 134 and 233 percent respectively. Langelier Saturation Index (LSI) was negative in the entire stations and calcium carbonate sediment won’t be created.
•Development of a hybrid soft computing model to predict the Runoff.•Preprocessing the signal of the time series of input variables using the Wavelet technique.•Design an MLPNN model and train it ...using the PSO technique.
A high-accuracy estimation of the runoff has always been an extremely relevant and challenging subject in hydrology science.Therefore, in the current research, a novel hybrid decomposition-integration-optimization based model is developed to enhance the estimation precision of the runoff. The suggested predictive model is a combination of successive variational mode decomposition (SVMD) technique and Multi-Layer Perceptron neural network (MLP) model integrated with particle swarm optimization (PSO) meta-heuristic algorithm (i.e., hybrid SVMD-MLP-PSO model). To test its performance, the mean monthly runoff data recorded from Sep 1986-Aug 2017 in Dez River basin (MRDRm), southwest of Iran, are used. The performance of the recommended model is also matched with other different hybrid and single models including MLP-PSO, SVMD-MLP, and MLP as the benchmark model. In all models, the sequence-to-one regression module of forecasting (i.e., without using meteorological parameters recorded in the study region) is utilized. In the SVMD based hybrid models, the optimal value of compactness of mode (α) for the original MRDRm time series is achieved at 100. Then, the PACF(partial autocorrelation function) diagram related to the lag length from each decomposed intrinsic mode function (IMF) sub-signals sequence generated is operated to select the ideal input variables. Performance evaluation metrics prove that the hybrid SVMD-MLP-PSO model under the best predictor and meta-parameters, outperformed with an R2 of 0.89, modified 2012 version of Kling-Gupta efficiency (KGEʹ) of 0.83, volumetric efficiency (VE) of 0.91, Nash–Sutcliffe efficiency (NSE) of 0.88, and RMSE of 13.91 m3/s. Comparatively, the standalone MLP as the benchmark model results in an R2 of 0.24, VE of 0.33, KGEʹ of 0.2, NSE of 0.29, and RMSE of 153.39 m3/s.
Variation of rainfall origin in different parts of Iran along with latitude, distance and proximity to moisture sources, etc. causes rainfall behaviors such as intensity and continuity to have ...temporal and spatial changes .Using statistical methods and discharge data of Dez river, severe floods of this river were extracted to identify the effective factors in their creation.In this research, the information of all effective atmospheric levels has been analyzed using a combination of illustrative and appropriate maps.And Synoptic and thermodynamic properties of heavy cloud precipitation in Dez catchment At the same time, the synoptic patterns lead to the prolongation of the systems on the catchment And its effect on flow rate was identified and presented.The purpose of this study was to identify the pattern or patterns of durable rainfall systems in the Dez River Basin. There is a deep landing in the eastern Mediterranean that has caused the cold European air to fall in the west of the ship, as well as the transfer of moisture from the Arabian Sea and the Persian Gulf in the east. And the conditions for creating an ascent in the Dez River Basin are the most important elements of the pattern of heavy and durable rainfall in this basin. Water resources planning, prevention and timely information, and flood control and control are among the results that can be expected from this research.
The sedimentation phenomenon in multi-purpose dam reservoirs causes problems in agricultural water supply, hydropower generation, flood, and drought management.
In this regard, developing fast and ...straightforward methods to estimate the amount of sediment in dam reservoirs is of great importance. The present study aimed to evaluate a sediment rating curve model’s development using a time scale classification approach. Data of hydrometric Talezang Station and the Dez Dam Reservoir hydrography in southwestern Iran were used in this research. The data classified into monthly and seasonal time scales and groups of wet, dry, and flood seasons. Consequently, the results compared with the conventional model of the sediment rating curve (SRC) apply different precision criteria. The results indicate that the classification in monthly and seasonal time scales and wet, dry, and flood seasons improve the sediment load-rating model’s precision by 21, 16, and 3%, respectively. According to the reservoir hydrographic operation and the conventional model of sediment rating curve calculations, the volume of sedimentation during 40-year period is estimated 609 and 497 MCM, respectively. However, the data classification in monthly and seasonal time scales and wet, dry, and flood seasons led to the estimation of volumes of 539, 525, and 521 MCM, respectively. Therefore, it is concluded that temporal classification on a monthly scale can effectively improve the conventional sediment rating curve estimation and leads to an actual volume estimation.
Investir em avaliação de políticas educacionais tem sido uma constante nos governos cearenses dos últimos 20 anos. O intuito é aprimorar práticas metodológicas, gestão escolar e ampliar o desempenho ...no Sistema Permanente de Avaliação da Educação Básica do Ceará (SPAECE). Afinal, a avaliação pode contribuir para melhorias no processo de tomada de decisão dos gestores e, assim, qualificar o serviço público. O presente artigo se dedica a investigar o “Prêmio Escola Nota Dez” como metodologia de avaliação educacional e busca avaliar o seu efeito nas práticas de gestão escolar e melhoria dos indicadores, tendo como locus duas escolas municipais do Ceará, uma de Sobral e outra de Aquiraz. Estruturado sob o modelo metodológico quadripolar, o referencial teórico apoia-se nos conceitos de Max Weber para burocracia, meritocracia e eficiência na administração pública, fazendo uma relação com o pensamento de Ralph Tyler sobre avaliação por objetivos. Os resultados apontam que o Prêmio Escola Nota Dez favorece o desenvolvimento de ações de cooperação técnico-pedagógicas entre as escolas premiada e apoiada, e contribui para a melhoria do processo de gestão educacional e do desempenho dos estudantes.
Water scarcity poses a significant global challenge, particularly in developing nations like Iran. Consequently, there is a pressing requirement for ongoing monitoring and prediction of water ...quality, utilizing advanced techniques characterized by low implementation costs, shorter timeframes, and high accuracy. In the present study, the investigation and forecasting of the monthly time series of a single-variable river water quality index have been addressed using ten water quality parameters. Daily monitoring data from four stations in the Dez River from 2010 to 2020 have been utilized to obtain the river water quality index value from the dataset. The Shannon entropy method has been employed to assign weights to each water quality parameter. Utilizing the integrated autoregressive integrated moving average (ARIMA) model, which ranks among the most extensively employed models for time series forecasting, and five deep learning models including Simple_RNN, LSTM, CNN, GRU, and MLP, the water quality index for the following year is predicted. The performance of the prediction models is evaluated using RMSE, MAE, MSE, and MAPE as evaluation metrics. The results indicate that the ARIMA model performs worse than the deep learning models, with the MSE, RMSE, MAE, and MAPE values for this model being 81.66, 9.037, 6.376, and 6.749, respectively. The deep learning models show results close to each other, demonstrating similar statistical index values. The outcomes of this study assist relevant decision-makers in planning and implementing necessary actions to enhance water quality, particularly freshwater resources in rivers.
Introduction
Water allocation in arid and semi-arid regions is considered a human challenge all around the world. The need for optimum utilization of water resources, especially in agricultural use, ...is very important. Agriculture, which uses the greatest percentage of most water resources, has also penetrated in human life and culture. The aim of this study is to provide an approach to allocate and optimize water use in Dez basin using WEAP model.
Methodology
The date regarding the users of water resources in Dez basin including the agricultural, domestic and industrial water demands, the precipitation, and the flow of rivers were collected from 2009 to 2014. All data were averaged monthly. The conceptual model was defined in WEAP. In term of model calibration, 60 percent of runoff data were used. The other 30 percent of remaining data were employed for the validation part. The optimum utilization policy of water resources in various scenarios were defined in WEAP. The scenarios were tested based on cropping pattern changes, reducing agricultural area, and the changes in irrigated and rain-fed ratio. All scenarios were compared by the reference scenario. In this scenario, the lowest percentage of need was related to the Western Dose. In this scenario, the course was 100 percent selected for drinking and industrial purposes in cities (Dezful, Andimeshk, Shoosh, Safi Abad, Dezab, Mardrood, Hor, Hamza and Saleh Shahr) and the entire villages of the region and some small industries due to the priority of providing higher, water use efficiency. On the other hand, due to the water withdrawal, regardless of the needs of the downstream and the transition to Karkheh, the percentage of providing low consumption needs as well as the percentage of the environmental need was not satisfactory. In order to improve the status of the reference scenario and the basin, two scenarios were defined. Considering that the agricultural sector is the largest water consumer in the region, it would be possible to significantly balance the supply-demand balance between water supply and demand by reducing the consumption in this sector. The scenarios were designed to reduce water consumption in agriculture and increase its economic efficiency in the basin. In all scenarios, the objective function was to optimize the benefit by cost ratio. In the scenarios implemented, the confidence level of other water uses, including the needs of the plain, downstream, environmental requirements, and energy requirements, was calculated to be 100%. In the second scenario, the water consumption of each product was studied in each plain. Regarding the diversity of products, in each plain, the products with high crop yields were considered and given the amount of water consumed by each plant. Moreover, the performance and the guaranteed price of purchasing those high-value products were identified and replaced with low-cost products. Finally, in the third scenario, by varying the percentage of irrigated and rain-fed products, the study of the amount of water saved versus the decline in the production of products was studied. Then, by evaluating the price of water versus crop products, the efficiency of this scenario was examined. Also, for each plain, the optimal percentage of irrigated and rain-fed area was determined. The optimal water and dry crop percentage was estimated based on the performance of these products and the amount of water consumed.
•First multi-centennial reconstruction of the Dez River discharge in Iran.•The instrumental period has a high frequency of extreme droughts and floods.•The recent extended low-flow period is not ...unprecedented in last 500 years.
Long-term river discharge records are essential for water resource management, especially in semi-arid regions. However, the short instrumental records in Iran and the limited availability of local paleoclimate proxies to extend these records hinder our understanding of the full range of hydrologic variability. To help overcome these constraints, we have used annually-resolved tree-ring width chronologies from a network of sites spanning the eastern Mediterranean to the Tibetan Plateau to develop the first multi-centennial (∼500 years) river discharge reconstruction for the Dez River basin, a catchment that supports substantial water extraction in southwestern Iran. A Hierarchical Bayesian Regression (HBR) model accompanied by parsimonious predictor selection was used to derive the most robust model output. The selection method retained 26 precipitation-sensitive tree-ring width chronologies, mainly from regions with similar hydroclimate features to the Dez River basin. The resulting reconstruction of the most downstream gauging station accounts for 62% of the variance in river discharge observations, closely matching known historical events and other regional reconstructions. Notably, the underlying recurrence pattern of extreme flow conditions suggests floods were more frequent than low flow extremes (i.e., droughts) during much of the 18th and early 19th centuries. In contrast, during the early 17th century, droughts were more frequent. Worryingly, the frequency of both floods and droughts has increased simultaneously since the beginning of the twentieth century. Our reconstruction could be used to assess current water allocation strategies under conditions similar to past extended dry periods. When combined with future projections, they can help provide more robust assessment scenarios for water management.
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