The assessment of physico-chemical parameters of Shiroro Lake and its major tributaries

The physico-chemical parameters of the surface water of Shiroro Lake and its major tributaries at their entry point to the reservoir were assessed over a period of eighteen months. As in other African inland water bodies there were seasonal variations in the parameters measured. The hydrological regime of the lake, precipitation chemistry, bedrock chemistry and hydro-electric power generation influence and determine the inputs of dissolved organic carbon, nutrient levels and water quality of the lake. The added nutrients to the lake by means of the major tributary rivers and inundation of surrounding areas also influence the water quality of the lake. The wet season mean values for water and air temperature were significantly (P <0.05) higher than dry season mean values in all stations. However, for pH, Dissolved oxygen and Phosphate-phosphorus the dry season mean values were higher than wet season mean values

Survey of food network in Ovan Lake

Lake Ovan with about 9 hectares is regarded a semi-shallow lake with an average depth 5.2 meter. It is situated in Ghazvin Province, with a 1910 m high in mountainous regime. A monthly sampling was done at 3 stations studying the physicochemical and biological parameters in water and sediment at the Lake for a year. The temperature annual was measured 12.3°C and other parameters are pH as 8.8, oxygen 10, with total mean phosphate and nitrate as 0.14 & 0.8 mg/lit respectively. The chl.a mean was also measured 1.94 mg/lit. The ratio of N to P was calculated as 1:59, indicating a limiting factor for growth. Considering the trophic statues of the lake taking into account as above parameters, it is a mesotrophic lake with medium trophy. Altogether, 53 phytoplankton species were identified mostly diatoms, green algae and cyanobacteria. Although, 14 zooplankton species were identified with daphnia dominating the group. Macrobenthoses were also surveyed and 11 families were identified comprising mainly by Annelids, Gastropod, Bivalves and Insect Larvae. Other organisms were 2 dominate water plant including Phragmites australis covering at the edge of the lake and potamogeton sp in the inner parts, and also 2 fish species, common carp and Pike Perch. The diversity Shannon—Wiener index was calculated for main taxa groups with all figures lower than 3. Regarding the fish potential production of the lake based on Bramic & Lemke and morphoedophic index, it was calculated to be 20.4 kg/ha fish and a total of about 150 kg for the entire lake.

Study of salinity gradients in the Persian Gulf and an experimental model for electric energy extraction from them using nano-membranes

Salinity gradient power (SGP) is the energy that can be obtained from the mixing entropy of two solutions with a different salt concentration. River estuary, as a place for mixing salt water and fresh water, has a huge potential of this renewable energy. In this study, this potential in the estuaries of rivers leading to the Persian Gulf and the factors affecting it are analysis and assessment. Since most of the full water rivers are in the Asia, this continent with the potential power of 338GW is a second major source of energy from the salinity gradient power in the world (Wetsus institute, 2009). Persian Gulf, with the proper salinity gradient in its river estuaries, has Particular importance for extraction of this energy. Considering the total river flow into the Persian Gulf, which is approximately equal to 3486 m3/s, the amount of theoretical extractable power from salinity gradient in this region is 5.2GW. Iran, with its numerous rivers along the coast of the Persian Gulf, has a great share of this energy source. For example, with study calculations done on data from three hydrometery stations located on the Arvand River, Khorramshahr Station with releasing 1.91M/ energy which is obtained by combining 1.26m3 river water with 0.74 m3 sea water, is devoted to itself extracting the maximum amount of extractable energy. Considering the average of annual discharge of Arvand River in Khorramshahr hydrometery station, the amount of theoretical extractable power is 955 MW. Another part of parameters that are studied in this research, are the intrusion length of salt water and its flushing time in the estuary that have a significant influence on the salinity gradient power. According to the calculation done in conditions HWS and the average discharge of rivers, the maximum of salinity intrusion length in to the estuary of the river by 41km is related to Arvand River and the lowest with 8km is for Helle River. Also the highest rate of salt water flushing time in the estuary with 9.8 days is related to the Arvand River and the lowest with 3.3 days is for Helle River. Influence of these two parameters on reduces the amount of extractable energy from salinity gradient power as well as can be seen in the estuaries of the rivers studied. For example, at the estuary of the Arvand River in the interval 8.9 days, salinity gradient power decreases 9.2%. But another part of this research focuses on the design of a suitable system for extracting electrical energy from the salinity gradient. So far, five methods have been proposed to convert this energy to electricity that among them, reverse electro-dialysis (RED) method and pressure-retarded osmosis (PRO) method have special importance in practical terms. In theory both techniques generate the same amount of energy from given volumes of sea and river water with specified salinity; in practice the RED technique seems to be more attractive for power generation using sea water and river water. Because it is less necessity of salinity gradient to PRO method. In addition to this, in RED method, it does not need to use turbine to change energy and the electricity generation is started when two solutions are mixed. In this research, the power density and the efficiency of generated energy was assessment by designing a physical method. The physical designed model is an unicellular reverse electro-dialysis battery with nano heterogenic membrane has 20cmx20cm dimension, which produced power density 0.58 W/m2 by using river water (1 g NaCl/lit) and sea water (30 g NaCl/lit) in laboratorial condition. This value was obtained because of nano method used on the membrane of this system and suitable design of the cell which led to increase the yield of the system efficiency 11% more than non nano ones.

Investigation and prediction of sea level variations in the northern coasts of Persian Gulf using artificial neural network

Sea- level variations have a significant impact on coastal areas. Prediction of sea level variations expected from the pre most critical information needs associated with the sea environment. For this, various methods exist. In this study, on the northern coast of the Persian Gulf have been studied relation to the effectiveness of parameters such as pressure, temperature and wind speed on sea leve and associated with global parameters such as the North Atlantic Oscillation index and NAO index and present statistic models for prediction of sea level. In the next step by using artificial neural network predict sea level for first in this region. Then compared results of the models. Prediction using statistical models estimated in terms correlation coefficient R = 0.84 and root mean square error (RMS) 21.9 cm for the Bushehr station, and R = 0.85 and root mean square error (RMS) 48.4 cm for Rajai station, While neural network used to have 4 layers and each middle layer six neurons is best for prediction and produces the results reliably in terms of correlation coefficient with R = 0.90126 and the root mean square error (RMS) 13.7 cm for the Bushehr station, and R = 0.93916 and the root mean square error (RMS) 22.6 cm for Rajai station. Therefore, the proposed methodology could be successfully used in the study area.