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The main objective of the study is to identify the vulnerable areas for river‐line and flash flood hazard and its mitigation through GIS Database Management System (DBMS…
The main objective of the study is to identify the vulnerable areas for river‐line and flash flood hazard and its mitigation through GIS Database Management System (DBMS) of geo‐hydrometeorological parameters. The Dabka watershed constitutes a part of the Kosi Basin in the Lesser Himalaya, India in district Nainital has been selected for the case illustration.
The Dabka DBMS is constituted of three GIS (Geographic Information System) modules, i.e. geo‐informatics (consists of geomorphology, soils, geology and land use pattern, slope analysis, drainage density and drainage frequency), weather informatics (consists of daily, monthly and annual weather data about temperature, rainfall, humidity and evaporation) and hydro‐informatics (consist of runoff, sediment delivery, and denudation). The geo‐informatics and weather informatics modules carried out by comprehensive field work and GIS mapping than both modules used to carry out hydro‐informatics module. Through the integration and superimposing of spatial data and attribute data with their GIS layers of all these modules prepared Flood Hazard Index (FHI) to identify the level of vulnerability for flood hazards and their socio‐economic and environmental risks.
The results suggest that geo‐environmentally most stressed areas of barren land (i.e. river‐beds, flood plain, denudational hills, sites of debris flow, gullies, landslide prone areas etc.) have extreme vulnerability for flood hazard due to high rate of runoff, sediment load delivery and denudation during rainy season (i.e. respectively 84.56 l/s/km2, 78.60 t/km2 and 1.21 mm/year) whereas in geo‐environmentally least stressed dense forest areas (i.e. oak, pine and mixed forests) have low vulnerability due to low rate of stream runoff, sediment load delivery and denudation (i.e. respectively 20.67 l/s/km2, 19.50 t/km2 and 0.20 mm/year). The other frazzled geo‐environment which also found high vulnerable for flood hazard and their risks is agricultural land areas due to high rate of stream runoff, sediment load delivery and denudation rates (i.e. respectively 53.15 l/s/km2, 90.00 t/km2 and 0.92 mm/year).
For hydro‐informatics module it is quite difficult to monitor water and sediment discharge data from each and every stream of the Himalayan terrain due the steep and rugged topography. It requires strategic planning and trained man power as well as sufficient funds; therefore representative micro‐watershed approach of varied ecosystem followed for a three years (2006‐2008) period.
The study will have great scientific relevance in the field of river‐line flood and flash flood hazard and its socio‐economic and environmental risks prevention and management in Himalaya and other mountainous terrain of the world.
This study generated primary data on hydro‐informatics and weather informatics to integrate with geo‐informatics data for flood hazard assessment and mitigation as constitutes a part of multidisciplinary project, Department of Science and Technology (D.S.T.) Government of India.
The purpose of the study is to assess the environmental and socio‐economic impacts and risks of climate change through GIS database management system (DBMS) on land…
The purpose of the study is to assess the environmental and socio‐economic impacts and risks of climate change through GIS database management system (DBMS) on land use‐informatics and climate‐informatics. The Dabka watershed constitutes a part of the Kosi Basin in the Lesser Himalaya, India in district Nainital has been selected for the case illustration.
Land use‐informatics consists of land use mapping and change diction, i.e. decadal changes and annual changes. Climate‐informatics consists of climate change detection through daily, monthly and annual weather data for a period of 25 years.
The exercise revealed that oak and pine forests have decreased, respectively, by 25 percent (4.48 km2) and 3 percent (0.28 km2) thus bringing a decline of 4.76 km2 forest in the watershed during 1990 to 2010. But, due to climate change the mixed forest taking place of oak forest in certain pockets and consequently the mixed forest in the catchment increased by 18 percent (2.3 km2) during the same period which reduced the overall loss of forests in the region but its not eco‐friendly as the oak forest. Barren land increased 1.21 km2 (56 percent), riverbed increased 0.78 km2 (52 percent) and cultivated land increased about 0.63 km2 (3 percent) during the period of 1990 to 2010. Out of the total seven classes of the land use land cover, five classes (i.e. Oak, Pine, Mixed, Barren and Riverbed) are being changed dominantly due to climate change factor and anthropogenic factors plays a supporting role whereas only two classes (scrub land and agricultural land) are being changed dominantly by anthropogenic factors and climate change factors plays a supporting role. Expansion of mixed forest land brought out due to upslope shifting of existing forest species due to climate change factor only because upslope areas getting warmer than past with the rate of 9°C‐12°C/two decades. Consequently, the results concluded that the high rate of land use change accelerating several environmental problems such as high runoff, flash flood, river‐line flood and soil erosion during monsoon season and drought during non‐monsoon period. These environmental problems cause great loss to life and property and poses serious threat to the process of development with have far‐reaching economic and social consequences.
This study generated primary data on land use‐informatics and climate‐informatics to integrate each‐other for impact assessment and mitigation through sustainable land use as constitutes a part of a multidisciplinary project, Department of Science and Technology (D.S.T.) Government of India.
This research focuses on suggesting an optimized model for selecting best employees using advanced multi-criteria decision making method to a supply chain firm, who is…
This research focuses on suggesting an optimized model for selecting best employees using advanced multi-criteria decision making method to a supply chain firm, who is planning to start a new cold chain business vertical.
Study has been conducted in a supply chain firm in North India, who wants to expand its business with the help of efficient team members. In total 38 applicants were considered for the study, as selected by the firm after initial screening from pool of talent. AHP-LP and TOPSIS-LP integrated approach were applied separately for evaluation and implementation of personnel selection model. Further, both the approaches were compared to find the best fit and optimized model.
As per the findings, both AHP and TOPSIS can be used to select the best candidate among the alternatives available. TOPSIS was found easier to implement as it involves ranking of applicants with respect to each skills required for respective job profile only once, whereas AHP involves pair-wise comparison among candidates with respect to each skills required for respective job profile and normalization of each comparison, resulting in the formation of number of comparison matrices. However, AHP is more reliable as it considers consistency check for each level of pair-wise comparison. Hence, there is a chance to avoid or revise the human judgment error. Integrated ranking and optimization approach minimizes the cost by suggesting the relevant positions to be filed to make an efficient team.
Group of interviewers are involved in the decision-making process, hence there are chances of biasness in ranking method which can influence the group decision. Research is limited to a particular geography of North India therefore needs to be tested for other regions also in order to generalize. The research will help the third party logistics (3PL) and other related firms in efficient team selection.
The researcher focuses on formalizing a method for potential candidate selection by considering the constraints of the organization. It has been observed that limited researches have been done on the application of AHP-LP or TOPSIS-LP integrated approach for selection process. Hence, this research proposes two integrated ranking-optimization method and suggests the best fit by comparing both the approaches.