Assessment of Pollution Load in Terms of Water Quality Index and Modelling of Taladanda Canal and Mahanadi River in Paradip Area, Odisha, India

The modelling of water quality is an integrated source of good management, which benefits the environment and its people. In the present study, the quality of water was measured in terms of physicochemical analysis and WQI. This analysis facilitates the eco-management study of the water. In this article, we have measured the quality of the water in Taladanda canal and river Mahanadi nearby Paradip area in terms of WQI for the year 2017. Five different sampling stations were selected from Taladanda canal and nine sampling points were selected from river Mahanadi. It was found that the water quality index in most of the areas was much higher, however, the water is of poor quality. But in PPL site areas, the quality of water was found to be very poor and not suitable for human use. The pollution load was found to be much higher in the Taladanda canal and moderate in Mahanadi River near the Paradip area.

Hydro-Climatic Modelling of an Ungauged Basin in Kumasi, Ghana

The Owabi catchment which is about 69 km2 provides about 20 % of water needs of the Kumasi metropolis has been in recent times prone to high anthropogenic activities that threaten water resource management. The Soil-Water-Assessment-Tool (SWAT) was used to assess the extent of these activities on the hydrology on the catchment from 1986 to 2015. Specifically, the model simulated historic and projected stream-flow and water balance. Initial results revealed the forest and topography played major role in water loss at the catchment as evapotranspiration and surface runoff were the dominant modulating processes. Monthly calibration/validation of the model yielded satisfactory results with NSE (0.66/0.67), R2 (0.67/0.67), PBIAS (8.2 %/8.0 %) and RSR (0.59/0.58). Nine sensitive parameters of which the catchment slope (CN2) ranked principal were found to control runoff amounts into the river. The model uncertainty was also quite low as the 95PPU enveloped about 50 % of the observed streamflow within a width of 0.45–0.55. Furthermore, future streamflow predictions were modelled under RCP2.6, RCP4.5 and RCP8.5 climatic scenarios, and two landuse scenarios, landuse category 1 and 2 (LU1 and LU2). An increasing trend of the downscaled rainfall totals between 2021 to 2050 for all RCPs were observed. This will positively impact streamflow generation at the catchment under LU1. There is an expected deficit of streamflow amounts under LU2 relative to LU1, and a marginal reduction as compared to the baseline. In general, the model proved efficient in determining the hydrology parameters in the catchment and therefore has potential to be used for further modelling of water quality and pollution to aid effective water resource decisions at the catchment.