Overestimation Of Density Research Articles

Investigation over the capability of MIKE 3 flow model FM to simulate the hydrodynamics and salinity distribution of hypersaline lakes: Lake Urmia (Iran) as case study

ABSTRACTLake Urmia, located in northwestern Iran, a hypersaline lake, divided into north and south basins by a causeway. The lake has been facing a serious environmental crisis, due to water mismanagement in the basin. To address this problem, an analysis of the hydrodynamic behavior and of salinity distribution is important. The three-dimensional numerical model MIKE 3 Flow Model FM was employed in this study. Model sensitivity analyses revealed that wind speed, friction coefficient, and vertical eddy viscosity are effective parameters on both flow velocities and salinity distribution, while bottom roughness height has minor effects on surface velocities. Reduced value for vertical eddy viscosity improves the simulation of the velocity field and has an adverse effect on salinity distribution. The UNESCO density function leads to an overestimation of density. Yet, final model results are accurate enough to reproduce the salinity distribution over the lake, revealing that the salinity difference between North and South basins of Lake Urmia increases significantly in the wet season, due to southern rivers inflows by snowmelt. For the simulated periods of 1986–1987 and 2004–2005, natural and man-induced drought hydrological conditions, the direction of flows was from south to north, with a much lower net flow in the latter period. This decrease in the exchanged flows causes higher salinity difference among basins. Results indicate that the present model could be run for any time period in both normal and drought conditions and can satisfactorily simulate the hydrodynamic characteristics and salinity distribution of Lake Urmia for management purposes.

SOTALIA GUIANENSIS POPULATION DENSITY ESTIMATIVE IN THE BAY OF ANTONINA, BRAZIL

The present work aimed to estimate the population density of Sotalia guianensis in the Bay of Antonina, southern Brazilian coast, by linear transects, distance method. The average group size in the total area was 2.57 individuals/group. The study area is 28.1 km2 and it was divided in two sub-areas, an outer area closer to the sea and another more enclosed with a higher fresh water input. In the Sector I, the one with greater marine influence, the density estimation found was D = 3.01 animals/ km2 (Variation Coefficient, VC 24.67%), whereas in Sector II there was no estuarine dolphin record. Also, during the rainy season a higher density value was found in the bay (D = 4.99 individuals/ km2, VC 15.93%). When the area division was ignored an overestimation of density was found (D = 3.80 animals/km2; VC 15.71%) due to the data extrapolation beyond the sampled area, including areas not much used by the dolphins. This superestimation due to the few estuarine dolphins records in the Bay of Antonina and also to the method used, which was biased by existing of sand banks at low tide which made it impossible to access all transects.