Kor as an important large river in Marvdasht zone, has been utilized for agriculture, water supply, storage, industry and other consumption, Certainly hydrologic study is an important issue in these projects. Data deficiency in most of watersheds has forced us to use indirect methods such empirical relations for flood runoff prediction. Preventing over and underestimation in predictions, it is necessary to calibrate equations for the slightly watershed. In this research we are going to calibrate some common empirical equations like Horton and fuller. For this reason regionalization with cluster analysis to determine homogenous regions will be done at first. Statistical probability analysis, another issue to estimate peak flood runoff at different return period, and evaluation of Doroodzan dam effect on the statistical characteristics of river regime, also will be assessed in this research.

In recent years, using non-structural methods especially forecasting flood has increased the success of flood control as well as structural methods. The main purpose of this research is to estimate the effect of watershed management on flood forecast lead time in Golabdare-Darband basin using HEC-HMS model.We defined five scenarios for different land uses, including conditions of 1955, 1988 and 2001, suitable and unsuitable watershed management. The land use that was used in this paper is similar to the land use of 2001. The HEC-HMS model is calibrated using recorded rainfall and flood hydro graph and it is verified. Floods of different return periods are simulated. The forecast lead time is estimated for five scenarios using the 25-year peak flood (for the scenario of 1988) as a threshold flood warning. The result shows that the lead time increases by decreasing in return periods. The Comparison of forecast lead time between five scenarios shows the forecast lead time is longest for 1988 land use. The forecast lead time of unsuitable management was decreased to 35 percent of the forecast lead time of 1988 scenario. The shortest of forecast lead time was for unsuitable management of the watershed.

Surat is a highly developed, thickly populated cosmopolitan character city with full of various activities going on day and night. Any natural calamity which causes loss of lives to property and infrastructure along with effects on industrial processes going on has serious impact on economy of the state. Therefore, it becomes highly necessary that flood events are studied and analyzed properly in order to propose adequate flood control and protection measures in time to come. Many research organizations like Central Water Commission (CWC), Gujarat Engineering Research Institute (GERI), Central Water Power and Research Station (CWPRS), are already involved in study of flood phenomena of Tapi River. It appears to be of vital importance to initiate studies as an extension in lights of finding of such studies, using modern computer, model and software technology. In this research paper in detail, morphological processes in Tapi River Basin studied. It is also studied presently available mathematical models by proving them for Tapi flood data and to develop an “Optimization Process” to minimize the flood impacts. It is further attempted to validate the model with studies on physical model development with studies on physical model developed/constructed by any Govt. or Semi Govt. organization like CWC, GERI, and CWPRS etc. Subsequent to construction of Ukai dam large urban developments have taken place along Tapi river banks. With the moderation of flood at Ukai reservoir, no major floods were experienced at Surat and Hazira till 1994. During 1994, 1998 and 2006 floods of the order of 14870 m3/s (5.25 lakh cfs), 19820 m3/s (7.00cfs) and 28315 m3/s (9.10lakh cfs) were experienced. Large portion of Surat area was inundated along with large scale flooding at Bhata, Bharatpur, Surat, and surrounding areas. There were heavy damages of industrial and urban properties costing 21000 Crores. This paper presents CHARIMA mathematical model for prediction of water levels in Tapi Creek under influence of flood and tide. This mathematical model is capable of handling unsteady floods in river channel network validated for September 1998 flood situation and then applied for predictions with 28315 m3/s (10 lakh cfs flood discharge). On the basis of the results this study the necessary measures to be taken for flood forecast and flood protection schemes to minimi Tapi river flood impacts on Surat, Gujarat, India, have been suggested.

It is necessary to forecast the volume of inflow to reservoir operation in flood conditions, which is of double importance in mountainous basins with a rain-snow regime. The main purpose of the present study was to evaluate the accuracy of GEFSv12 reforecast data as an input to the HEC-HMS precipitation-runoff conceptual model in forecasting and warning issuance for floods entering the Dez dam resrvoir, southwest Iran. For this purpose, after deriving precipitation and temperature parameters (including control values and ensemble members) up to 10-days lead time, the flood ensemble forecast was produced. In the study, in case of exceeding the threshold discharge (1620 and 2640 m3/sec with return period of 2 and 5 years, respectively) by a relative majority of forecasting members, the flood warning was issued. Although, flood forecast in basins with the rain-snow regime is very complicated, the results of evaluation indexes showed that a considerable improvement of forecast accuracy might be expected 5 days ahead (5-days lead time). Then again, there was no direct relationship between the reduction of forecast lead time and the enhancement of forecast accuracy. The results of the probabilistic study of the members’ agreement percent in exceeding the threshold discharge of 2640 m3/sec indicated warning issuance within the forecast lead time of 4-7 days ahead.

Flood is considered as one of the most destructive natural hazards in the world that results in a lot of costs, especially in developed countries. Therefore, dealing with this hazard and its risk, two kinds of essential actions should be applied, including structural and non-structural methods. Forecasting and flood warning techniques are effective non-structural methods that developing them is related to different methods of people participating and their educating. In this paper, these methods are prioritized based on their effects on the development of forecasting and flood warning in Iran. First, alternatives (methods of people participating and their educating) and criteria are determined. Afterwards, experts’ opinions about the situation of each alternative to each criterion are collected and an appropriate decision making method is applied to rank the alternatives. Finally, the method of holding meeting with people in flood plains is ranked as the first alternative. Creating observation markers from previous occurred floods is selected as the second alternative. Visiting plants and industrial sectors in flood plains and giving necessary warnings to industrial owners, installing signs to show flood potential on the public building, paper publication in newspapers, presenting flood instructions in the form of manual, brochures, etc., trial maneuvers, face-to-face interaction, methods for distributing flood information through manuals, brochures, etc., as well as awareness advertisements on the radio, and interviewing with flood managers are ranked third, fourth, fifth, sixth, seventh, eighth, ninth, and tenth, respectively.

This study presents a novel approach for real-time flood control by optimizing operation of a reservoir during the flood. However, the fundamental operational challenge of using this method is to determine optimized decisions of the reservoir management before the occurrence of flood, and optimal use of the pre-release to reduce the flood damages. In addition to this optimization challenge, since the timely forecasts are derived by employing the probabilistic methods, they would always associate with uncertainty. As a result, quantifying and considering these uncertainties in the flood control would result in reducing the risk of flood damage that can be evaluated by minimizing the expected value of the damage. Timely and continuous forecasting of inflow and reservoir operation management will be implemented before the occurrence of flood until it ends. In order to address the above challenges, a novel simulation-optimization methodology, by taking into account uncertainty, is developed; and illustrated on a case study of Dez reservoir, as a highly important reservoir system in south-west of Iran, to optimize the performance of this reservoir, during the floods. Accordingly, a new water resource management has been proposed and tested. The results derived from the proposed method, indicate a significant reduction in the peak release from the reservoir and the improved operation of the Dez reservoir in controlling the flood at real-time, which will reduce damages in the downstream area.

Aware of the economic performance of the business in the future will help potential investors and Creditors in economic decisions. Investment decision taken on the basis of forecasted earnings. Therefore the accuracy of these predictions is important. Prior research has shown that cost forecast error is more than sales forecast error and has more effect on the earning forecast error and claimed that this error is due to ignoring the cost behavior. This research was investigated cost behavior forecast accuracy by studying 104 company from 2010-2015. Samples were separated to companies with symmetrical (equal) favorable and unfavorable sales forecast error and were compared. T test and Mann-Whitney tests were used for this purpose. The results showed that managers are not predicting the cost variability correctly; however, due to the symmetry of the earning forecast error in firms with equal sales forecasting error, it can be concluded that managers generally pay attention to cost behavior in their predictions. In other words, according to the proportion of sales forecast error and cost forecast error, the main reason for the earning forecast error is the error in predicting sales.

Real-time forecasting of daily inflows to reservoirs with a prediction horizon that extends several steps into the future is crucial for water resource planning and management. Despite numerous studies on inflow prediction using machine learning methods, few studies have investigated the predictive capabilities of these approaches with long lead time (several steps ahead) or gained insights through systematic comparisons of model predictive performance in the short term. In this study, the daily inflow to the Seimareh reservoir was predicted for the next 7 days using the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the Long Short-Term Memory (LSTM) network. For this purpose, daily data on precipitation, temperature and inflow to the Seimareh reservoir from 2012 to 2018 were used for modeling. The results showed that the performance of the LSTM model was better than that of ANFIS in the daily forecast in several steps. Specifically, the maximum and minimum values of the Nash coefficient in the forecast horizon for the next seven days were 0.971 and 0.628 for the LSTM model and 0.858 and 0.393 for the ANFIS model, respectively. The optimal setting of the parameters, including the number of neurons in each layer, the number of epochs and the stack size in the LSTM model, is the key to the model's high potential to predict the inflow for the next seven days. Finally, the performance of the LSTM model in predicting the inflow to Seimareh during the 2019 flood was evaluated and it was found to predict flood discharges with acceptable accuracy up to the forecast horizon of the next seven days. These results indicate that the LSTM model is suitable for forecasting daily inflow and can help make strategic decisions in water resource management, especially under flood conditions.