The most effective means of consistently ensuring the safety of a drinking water supply is through the use of a comprehensive risk assessment approach that encompasses all steps in water supply from catchment to consumer. The approach of this book is to promote an understanding of the entire water supply system, including the hazards that can compromise drinking water quality, safety and develops effective measures to assess and manage risks arising from those hazards using spatial model. Comparative evaluation of certain physical, chemical and biological characteristics of raw, treated and potable water at distribution network has been ongoing. Applying a GIS model will provide visual impacts for various hazards using WQI, which has formed a series of prediction maps for risk assessment. The objective of this book is to help researchers, professionals, and end-users working in water supply systems with the identification of relevant hazards by providing a catalogue with potential hazards of technical, environmental or human origin for the entire system.
The book describes the role of Geographical Information System and Remote Sensing in modeling the groundwater distribution pattern and quality in the state of Rajasthan in India. Groundwater table map of various time series (pre and post monsoon), rainfall maps and fluctuating patterns have been generated using the groundwater level data of pre and post monsoon seasons and daily rainfall datasets of Rajasthan. Further, the OCEANSAT - 2 OCM satellite data has been used for generating the Normalized Difference Vegetation Index maps. Groundwater quality maps (WQI maps) of Rajasthan have been generated using groundwater chemical data of the state. The WQI maps indicated that the groundwater quality decreases from the South-East to the North-West of the state. The safest zone is in the South-Eastern part of the study area. Various Geo-statistical techniques have been applied in generating all these maps.
Pinus radiata is the dominant plantation species of New Zealand. Sometimes it can develop wood quality flaw called intra-ring checking. The checks that appear in wood during kiln drying lower value of timber leading to loses for the forest industry. An exhaustive comparative study was conducted to see if the checked wood had some inherent properties that made it more susceptible to checking. It was found that checking could be influenced by tracheid geometry and cell wall thickness. If the wood had large tracheids with thin walls, it was more likely to develop checks during drying. Lignin distribution in the cell wall layers was also seen to play an important role in checking. Lower lignin levels and disruption in the pattern of lignification of the cell wall layers increased the tendency of the wood to develop checks. Similarly, if the tracheids had larger pits then their tendency to check increased. This study(funded by WQI Ltd, New Zealand) was undertaken as a part of collaborative work that was carried out to understand wood quality issues in Pinus radiata, with a vision of improving its wood quality.
The research presents water quality analysis of Bhadravathi in Karnataka State, India. Fourteen physico-chemical and biological parameters were considered for the analysis. The raster maps created using GIS are used to represent the spatial distribution of the parameters for both pre and post-monsoon seasons. Using physico-chemical parameters, Water Quality Index (WQI) was determined. The WQI shows 11% of the surface water samples fall under very good category during pre-monsoon and 78% in post-monsoon. The water sample at New Bridge site shows sign of pollution throughout year with WQI in the range 50-100 and hence unfit for use. In groundwater samples, 20% of samples in the pre-monsoon and 50% samples during post-monsoon fall under good quality. 50% of water samples during pre-monsoon and 60% of samples during post-monsoon fall under good category and water sample at Haladamma temple are found unfit. Further, QUAL2K model predicted the DO and BOD values considerably well along the Bhadra River from Lakkavalli to Bhadravathi Town. However, the Streeter Phelp s model estimated higher DO as compared to QUAL2K model. This is due to provision of outfall effect in Streeter Phelp s model.