IRAN-WATER RESOURCES RESEARCH
Year:2009 | Volume:5 | Issue:1 (13)|Papers Count:9

Probabilistic design is a new approach in the design of water resources systems. Accordingly, a framework for a flood warning system design is proposed in this study. The flood warning reliability assessment model, introduced by other authors, is then completed and presented in detail. The model is applied to the Madarsou river flood warning system in northeastern Iran, which was installed in 2005. In this case, one control cross section, three vulnerable areas, three time intervals of 30, 90 and 180 minutes for forecasting the flood crest height, two forecaster triggering stages (i.e.2.5m and 2.7m) and three warning thresholds (i.e.3m, 3.5m and 4m) are considered. Regardless of the warning thresholds, the longest potential lead-time is obtained for the 30 minute forecasting intervals. The potential lead-time decreases by increasing the system reliability, for higher trigger stages. The trade-off discussion between potential lead-time and system reliability helps decision makers to find out the optimum operational point based on the accepted risk. The analysis results for 30 minutes forecasting intervals in Madarsou showed that by increasing the lead time up to 9.28 hours, the number of missed flood increases from 15.10 to 17.78. Indeed, the discussion on the model reliability and the lead time trade-off depends on the system performance and the acceptable risks for a region.

Groundwater level variations can essentially affect the execution of many engineering projects. Accordingly, due to the projects underway in Tabriz district and especially Tabriz Underground Project (METRO), spatiotemporal prediction of the groundwater level is crucial. Due to the aquifer complexity in the Tabriz area, there are problems in using classical mathematical models. In this research a combination of the artificial neural networks and Geostatistic models were applied as a new method for spatiotemporal prediction of groundwater levels using selected piezometers. For this purpose, the different neural networks were examined for groundwater level forecasting in central piezometer and an optimal ANN architecture was identified. This ANN structure was then used for modeling the selected piezometers. The results of these models were used as the inputs of the geostatistics model for forecasting spatial groundwater level in the study area. Two year monthly groundwater level prediction data in selected piezometers resulted by ANN modeling were among these input data. In order to obtain a high efficiency model, different methods of the geostatistic model were used. Finally the obtained model was tested by water level data in piezometers other than those used for model calibration. The results of this hybrid model were acceptable.

Environmental pollution caused by heavy metals is a global concern. The main source of heavy metals in soil is the urban and industrial wastewater, synthetic phosphate fertilizers, sewage sludge, and metal extraction mines. The level of heavy metals absorption in plants not only depends on the concentration of the metals and the physical and chemical composition of the soil, but also varies in different parts of each plant. The main objective of this study was analyzing the impact of various levels of Cadmium concentration in soil and EDTA in irrigation water on its absorption and accumulation in various parts of five cucurbit types. The experiments were carried out under laboratory conditions, using the factorial in randomized blocks design by five treatments and three repetitions. The treatments included the Cd concentration in 4 levels (i.e. soil without adding Cd as control treatment, soil with 50 mg kg-1 Cd, soil with 50 mg kg-1 Cd and irrigation water with 0.5 molar EDTA, and soil with 100 mgkg-1 Cd and irrigation water with 0.5 molar EDTA). The results showed that the level of Cadmium accumulation in the plant species is in direct proportion to the level of Cadmium concentration in soil. Adding EDTA to the irrigation water (third and fourth treatments) effectively increased the amount of Cadmium absorption and accumulation in plants. All plant specimens showed significant increases in the rate of absorption and amount of Cadmium accumulation compared to the second treatment. The increase was recorded as 53% in root, 122% in leaf, 31% in stem, and 27% in root. The results also showed that in all treatments except the control treatment Cadmium accumulation is in excess of permissible limits for human consumptions.

Leakage of petroleum compounds from Tehran Oil Refinery (TOR) has caused soil contaminations in this area. These compounds can enter the groundwater and cause direct or indirect hazardous effects.This research is focused on Poly Aromatic Hydrocarbons (PAHs), the main group of petroleum compounds. Gas Chromatography (GC) analysis are made on 19 samples collected in grid sampling from sides and center of the stream adjacent to the TOR. Also according to the geotechnical properties of the area and considering the physical and hazardous quality of the contaminants, clean up levels are assessed for the groundwater preservation. Among 16 poly aromatic priority pollutants, four compounds which have the highest concentrations in the area and also have carcinogenic effects are evaluated. These compounds are benzo [a] pyren (BaP), benzo [k] fluoranthene (BaK), benzo [a] anthracene (BaC), and chrysene (Chr).This study showed that the concentration of BaP, BkF, and BaA were higher than the allowable concentrations. Also in case of BaP, maximum evaluated concentration (638ppm) was 50 times higher than the allowable concentration (13.2 ppm).Different dispersing mechanisms are also evaluated and applicable methods are discussed in order to control the contaminants. In addition, based on geotechnical properties of the soil and considering physical specifications of the contaminants, biologic methods and phyto-remediation via phyto-transformation and rhizosphere-bioremediation are recommended to clean up the site.

The stochastic simulation models of weather factors (weather generators) are used in a wide range of studies including risk assessment of climatic and hydrological extreme events, water resources, and agricultural risk management. Such studies often need access to the long-term series of weather data which is not collected continuously in many meteorological stations in Iran. Due to this shortage of data (particularly, the daily data), stochastic weather generators can be used as an alternative for extending data series. These generators are used to produce the synthetic weather data which is statistically similar to the observed data. In this study, the two well-known weather generators, i.e., ClimGen and LARS-WG were evaluated in simulating the weather factors for fifteen climatic zones of the country. The weather factors include the daily total precipitation, the minimum and maximum air temperatures, and the total solar radiation. For this purpose, the process of generating synthetic weather data was divided into three distinct steps including model calibration, model validation, and long-term simulation of weather data. To evaluate the agreement between the observed and the generated data, two indices were used, Root Mean Square Error (RMSE) and Coefficient of Determination (CD). Moreover, the three statistical tests including z-student test, F test and X-test were used to compare the various characteristics of the simulated and observed data such as the lengths of wet and dry series, the distribution of precipitation, and the lengths of hot and frost spells. The results showed that LARS-WG tends to match more closely to the observed precipitation data. The ClimGen performed better for the observed maximum and minimum air temperatures. Neither of the two weather generators succeeded in simulating total solar radiation.

Rockfill dams can be applied as suitable tools for flood control purposes. The appropriate understanding of their hydraulic principles is though inevitable. Through flow in rockfill dams has been investigated by many researches.Flood discharge greater than design discharge however might cause simultaneous through and over flows in such dams which have not yet been studied. In this paper unsubmerged simultaneous through and over flow in flood control rockfill dams has been investigated experimentally. The upstream and downstream side slopes, the material size, the upstream and downstream depth, and the length of the dam have been considered as effective parameters. A flume 10m long, 45cm high, and 30cm wide is used for this experiment. Two hundred and forty physical models have been studied for four lengths (i.e.50, 70, 90, and 110 cm), two side slopes (i.e.45 and 90 degrees), three material sizes (i.e.1.45, 2.1, and 3.05 em), and ten flow rates (ranging from 4 to 16 L.s-1). Based on the experimental results, a non-linear regressive equation for discharge estimation with a correlation coefficient of 0.936 and root-mean-square-errors of 0.001 has been proposed.Results also showed that flow rate has been directly affected by the ratio of dam height to upstream head, the ratio of material size to dam height and submerged ratio was inversely affected by the ratio of dam length to dam height and the upstream and downstream side slopes.

Unequal river bed level at the river junctions are common in nature. The study of scour and sedimentation at such junctions however have not received the attention of researchers because of the complexity of the experimental setup. In many studies it has been assumed that the bed level has no significant effect on the scour and sedimentation patterns. It has been reported by a few investigators that the flow patterns and the zone of maximum shear stress in junction of unequal bed level is different from that of equal bed level cases. This study investigated the effect of this variable. First the general non-dimensional equations were developed using the dimensional analysis. Many experimental tests were then conducted under three different river bed discordances and different hydraulic conditions. The data from these experimental tests was compared with the results of the previous study. The results indicated that generally as the river bed discordance increases, the scour hole and point bar dimensions decreases. Using the experimental data, the effects of each non-dimensional parameter on scour depth were investigated and finally relations were developed for prediction of scour dimensions.

The sustainability of irrigated agriculture depends upon the consistency of high irrigation efficiency. Thus a proper understanding of factors affecting spray losses (Ls) in sprinkler irrigation is important in an optimum water resources use. In this research a new equation is introduced for exact estimation of Ls by characterizing weather parameters under hot and semi-arid conditions for semi portable hand-move sprinkler system in south-east region of Khouzestan province. The standard ISO 7749.2 has been taken into account to determine Ls. Field tests were conducted under the outdoor single sprinkler method. The obtained equation from the multiple and nonlinear regression model showed that Ls exceeded 21.9% when the wind speed and vapour pressure deficit increased more than 3.5 m/s and 6 kpa, respectively.

In this study, monthly and annual mean discharge records of Latian basin are analyzed. The Kendall-tau test is first used to detect the trend of discharge, temperature, and precipitation records. Then the correlations between these parameters are determined.Models for annual mean discharge and daily mean discharge in each month are generated based on this information using linear regression. The results show that despite the increasing trend in temperature, there is no significant trend for the annual discharge during the past four decades. Due to the increase in temperature the amount of monthly discharge has increased in cold seasons and decreased in warm seasons during the past four decades.