Hirad Abghari

The trend analysis of the river flow is one of the important subjects for the studies about climate change and its impact on surface water resources. The North Atlantic Oscillation (NAO) has been recognized as one of the major patterns of atmospheric variability in the Northern Hemisphere which its impacts are stronger in the cold months of the year. A few studies carried out in Iran showed that the precipitation variability is related to the corresponding change in the NAO index. Thus, it is expected that this precipitation variability drivers large variations in the river flow regime. In this study, the trend in annual, seasonal and monthly river discharge are detected by the Mann-Kendall, Sen, Kendall and Spearman non-parametric tests at 12 hydrometric stations in Hamedan province during recent decades. The temporal trends in rainfall at 7 raingauge stations and their relationships with the river discharge are also investigated. Consequently, the correlation between the NAO and r...

Seasonal flood damage is irreparable face. The annual event is a rapid and devastating floods in different parts of the world and cause loss of life and property is tangible and non-tangible. Therefore, the feed rate of the total flow rate and flood areas has contributed This study investigates the extent and rate of runoff from the sub output of the HEC-HMS model has Watershed Nushan Urmia. In this study after providing the information needed to produce the output hydrograph for each sub-basin, SCS hydrologic simulation in relation to the conversion of rainfall-runoff from the sub Main channel and flood outflow hydrograph method to extract lag and the use of sub-critical areas were identified.

Sudden changes in recentyears meteorological parameters such as precipitation and evapotranspiration, impact on water resources are abundant. Therefore, evaluation of these anomalies to determine hydrologic trends and time series management They can communicate with each other and discuss the importance of sustainable management of water resources in the country This study aims to analyze the flow of water catchment areas upstream Dez,Karun River water is supplied from the main branches. So gauging station Zang, Caesar and tight five considered and evaluated, and the slope of my Tests-Kendal and sen were used Analysis on all five flow stations and Tang Zang monthly and annual series showed an increasing trend. However, during the 50 years at the three stations of the discharge increases and the increase in the station, wait till it is narrowed to five eyes. The annual and monthly runoff series at the station in October, November and December at the level of 95% and 90% levels were s...

The rainfall-runoff process and flooding are hydrologic phenomena that are difficult to study due to the influence of different parameters. So far, different methods and models are provided to analyze these phenomena. Therefore, the purpose of this study is evaluation of artificial neural networks (ANNs) for storm runoff coefficient forecasting using two transfer functions, hyperbolic tangent and sigmoid, in hidden layer and linear in output layer. For this reason, Barariyeh watershed was chosen in Neishabour and the data of 33 events were collected during 1952 to 2006. The factor analysis (FA) were used for determination of independent variables in storm runoff coefficient forecasting in which four variables were selected as independent variables, including average rainfall amount, third, first and fourth quartiles rainfall intensity and also five variables including  index and first to fourth quartiles rainfall intensity. ANN was performed using sigmoid and hyperbolic tangent fun...

More over the water distribution network are important as giving service; also they are noticeable as extreme costs that perform for design, produce and performance, operation, maintenance, improvement and renewal. According as the projects usually have financial restriction, economic problems are introduced as one of the most important and the most parameters determinant and the design which has least design,

Artificial intelligence modeling of nonstationary rainfall-runoff has some restrictions in simulation accuracy due to the complexity and nonlinearity of training patterns. Preprocessing of trainings dataset could determine homogeneity of rainfall-runoff patterns before modeling. In this presentation, a new hybrid model of Artificial Intelligence in conjunction with clustering is introduced and applied to flow prediction. Simulation of Nazloochaei river flow in

Population growth and progressive extension of urbanization in different places of Iran cause an increasing demand for primary needs. The water, this vital liquid is the most important natural need for human life. Providing this natural need is requires the design and construction of water distribution networks, that incur enormous costs on the country's budget. Any reduction in these costs

Identification of susceptible areas to landslide occurrence is one of the basic measures to reduce the possible risk and hazard management. The main goal of this research was to compare applicability of two statistical landslide hazard zonation models (valuing area accumulation and Analytical Hierarchy Process) in the ziarat watershed, Gorgan, Golestan province. By review of previous works and field works, the Nine factors such as: slope, aspect, elevation, lithology, landuse, distance of river, distance of road, distance of fault and rainfall, identified effective factors in landslide hazard and used for analysis risk by GIS software. the occurred land slides in the study area were gathered and rectified by GPS. These Nine maps were crossed with the occurred landslide map and Landslides amounts and their areas were computed in each class. After determining the rate of each factor (element), land slide zonation was performed in GIS by combining density level and AHP Models. The effi...

Soil erosion from socio-economic and environmental aspects of view is important, and decision making for applying proper watershed management practices is essential to control or mitigate it. In recent years, the Soil and Water Assessment Tool (SWAT) model as widely-used tool have been applied to simulate flow discharge, sediment yield, and to evaluate watershed management practices in reducing runoff and sediment yield. This research aims to simulate monthly flow discharge and sediment yield using the SWAT model to identify critical sub-watersheds yielding specific sediment in Nazlochai watershed, located in the West of the Urmia Lake. In this study, a monthly streamflow and sediment discharges data series were used during 1997–2007 for model calibration and 1993–96 for validation. To evaluate model efficiency, some statistical criteria consist of the determination coefficient (R2), the Root Mean Square Error (RMSE), the Nash-Sutcliffe Efficiency (NSE), and the Mean Bias Error (MBE...

Hydrologic simulation of watersheds is required for estimation of peak flow and flood volume for design of dams and other water structures. In this study, we apply the Stanford Watershed Model-IV (SWM-IV) and HMS Soil Moisture Accounting (SMA) models for evaluating mean daily flows, peak flows, monthly and annual flood volume from the Khosrow Shirin Watershed, situated at the north-western of Fars Province in Iran. A 5-yr record (2002-2007) of rainfall and discharge data is available from the Dehkadeh Sefid hydrometric station situated at the outlet of this watershed. Sensitivity analysis of twelve model parameters was performed to determine the important effective parameters. Available data from 2002-2005 (hydrological years) were used for model calibration and 2005-2007 records of data for model validation. Simulations of HMS SMA for mean daily flow, peak flow and monthly discharge volume and SWM-IV for annual flood volume had higher efficiency. The results of this study emphasize...

Lack of enough measured instantaneous flow data is one of the most important problems to estimate design flood with required return periods in most parts of the World, and due to this problem it is not possible to have reliable design of hydraulic structures such as dams, bridges and …. Therefore, it is necessity to find reliable methods to estimate and reconstruct instantaneous peak flow series using daily measured data. It must be mentioned that in most of the gauging stations the length of daily measured flow data is longer than the instantaneous measured flow data. The aim of this research is to evaluate applicability of some empirical methods including Fuller (1914), Sangal (1983) and Heinz Dieter (2003) approaches, and also the new ANN (Artificial Neural Network) technique to prolong instantaneous peak flow data series using daily measured flow data. To do this, a number of gauging stations located in arid and semi-arid regions of Iran were selected and instantaneous peak flow...

This research was designed to evaluate applicability of some empirical methods including Fuller (1914), Sangal (1983) and Fill and Steiner (2003) approaches as well as the ANN (Artificial Neural Networks) technique to prolong instantaneous peak flow data series using daily measured flow data. To do this, after initial consideration, a number of 12 gauging stations located in arid and semi-arid regions of the north half of Iran were selected and the related data was collected. Then, the applied empirical methods were calibrated for the related stations, and the instantaneous peak flow was estimated for some specific years. To be able to have a reliable comparison, the same years were also used in testing phase of the ANN modeling. Comparing the results shows higher ability of ANN over the empirical methods for this specific application, although there was a considerable improvement of the results for empirical methods after calibration. Reliable results produced by ANN method, compar...

Hydrological models can help us to predict stream flows and associated runoff volumes of rainfall events within a watershed. There are many different reasons why we need to model the rainfall-runoff processes of for a watershed. However, the main reason is the limitation of hydrological measurement techniques and the costs of data collection at a fine scale. Generally, we are

Intelligence models consist of distributed parallel processors that learn to reproduce the relationship between input and output signals and present the best topology of patterns simulation. Due to nonlinearity of hydrological events the learning process has restrictions . In this study, using a combination of Wavelet theory and a Multi Layer Perceptron Network, two Wavelet Neural Network models for monthly

The prediction of rainfall is essential for design and management of water resources systems. The objective of this paper is generate monthly rainfall time series and compare three linear stochastic generators for simulation of monthly rainfall at Gharalar rain gauge stations around Urmia, Iran. Monthly rainfall data for thirty years from 1972-2002 were considered for stochastic modeling. Monthly rainfall was

Hydrologic simulation of watersheds is required for estimation of peak flow and flood volume for design of dams and other water structures. In this study, we apply the Stanford Watershed Model-IV (SWM-IV) and HMS Soil Moisture Accounting (SMA) models for evaluating mean daily flows, peak flows, monthly and annual flood volume from the Khosrow Shirin Watershed, situated at the north-western of Fars Province in Iran. A 5-yr record (2002-2007) of rainfall and discharge data is available from the Dehkadeh Sefid ...

Prediction of maximum daily flow is essential for planning of water resources systems. This study presents the use of an Artificial Neural Network (ANN) to maximum daily flow prediction in the Khosrow Shirin watershed, in north-west Fars province in Iran. Precipitation from four meteorological stations was used to develop a Multi Layer Perceptron (MLP) optimized with the Levenberg-Marquardt (MLP_LM) training algorithm and using a tangent sigmoid activation function. Different methods to construct the input vectors were ...