Author
J. M. Yan
Bio: J. M. Yan is an academic researcher. The author has contributed to research in topics: Water flow. The author has an hindex of 1, co-authored 1 publications receiving 4 citations.
Topics: Water flow
Papers
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01 Jun 2004
4 citations
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TL;DR: A numerical model is presented for simulation of the flow of water and air and contaminant transport through unsaturated soils with the main focus being on the effects of chemical reactions and it is shown that the model is capable of predicting the effectsof chemical reactions with very high accuracy.
40 citations
TL;DR: In this article, the effects of the spatial variability of soil hydraulic properties on contaminant fate are modeled with a dual domain concept in which a first order kinetic expression is used to describe the transfer of the solute between the two domains.
13 citations
01 Jan 2004
TL;DR: In this article, a GIS based spatial decision support system for modelling contaminant intrusion into water distribution system is presented, which combines the geometry algorithm with contaminant zone to obtain the potential pollution areas of water distribution pipe.
Abstract: The paper presents a GIS based spatial decision support system for modelling contaminant intrusion into water distribution system. Three models have been developed to simulate the process and risk of contamination. A seepage model predicts the contaminant zone of pollution sources and the change of concentration during migration through soil. A pipe condition assessment model ranks the condition of water pipe in terms of the potential of contaminant ingress. An ingress model combines the geometry algorithm with contaminant zone to obtain the potential pollution areas of water distribution pipe. The three models were integrated with ArcView GIS for supporting decision making for risk mitigation. Zone VIII of water supply system in Guntur, India was selected for the case study. The contaminant ingress potential and potential pollution area of water pipes were displayed as thematic maps in GIS. The areas resulting in high risk were identified from the GIS maps. The availability of resources for maintenance activities are limited in developing countries. Thus GIS based spatial decision support system helps to achieve maximum risk reduction.
1 citations