Climate Change Vulnerability Assessment System Developed

The National Institute of Environmental Research announced that it developed a climate change adaptation toolkit, which is used to assess climate change effect and analyze vulnerability. Combining information on climate, air environment, society, economy and geography, the toolkit enables local governments to analyze the climate change effect and vulnerability without difficulty.

Based on the classification by UK Climate Impacts Program, the system makes 16 categories and analyzes information by si (city), gun (county) and gu (borough). The 16 categories include agriculture/livestock industry, horticulture/forestry, water resources/water quality, industry, health, ecosystem, air quality, fisheries, tourism/leisure, marine ecology, disaster, transport/communication, energy, construction/public works/architecture, education, and governance/public sector.

In addition, linked to the Geographic Information Systems, it can provide various information and assessment result with regard to vulnerability efficiently. Vulnerability index calculation system enables users to analyze vulnerability in a convenient way.

According to the National Action Plan on Climate Change Adaptation (December 2008), climate change vulnerability map by each sector will be completed until 2012. With the use of the assessment system, damage can be minimized by preparing for sectors which have significant climate change vulnerability.

The climate change adaptation toolkit based on GIS obtained a patent in March 2010 and the system will be distributed to related departments and local governments with conducting user training program.

[Source: Republic of Korea Ministry of Environment press release]

Knowledge-based Soil Attribute Mapping in GIS: Corrections and Extensions to the Expector Method

Transactions in GIS, Volume 14, Number 2, April 2010

Timothy S. Farewell and Daniel M. Farewell

“The Expector Method provides an excellent basis for modelling soil and other environmental classes or properties using a combination of expert knowledge and empirical data. The ideas are based on probability theory, and hence can be given a rigorous mathematical underpinning. Nevertheless, concerns have arisen regarding the published algebra used in deriving the equations underlying the model. We present corrections to key equations, improved notation to encourage future use of this methodology, and a simplification of the map purity extension to the formula that allows different weights to be applied to the evidence layers. We illustrate the methodology with an example of mapping soil parent materials.”

An ArcGIS Extension for Estimating Nitrate Fate and Transport

2010 ESRI Southeast Regional User Group Conference

Fernando Rios, Ming Ye, Raoul Fernandes, Tingting Zhao,and Paul Lee

“Estimating groundwater nitrate fate and transport is an important task in water resources and environmental management because excess nitrate loads may have negative impacts on human and environmental health. A project has been initiated and funded by the Florida Department of Environmental Protection to develop an ArcGIS tool for estimating nitrate loads to surface water bodies from onsite wastewater treatment systems (OWTS). A key feature of this project is the reduced data demands and simplicity of use compared to traditional groundwater contamination transport modeling. This arises from the use of a simplified conceptual model of groundwater flow in the surficial aquifer and an analytical solution to the advectiondispersion equation and denitrification reaction. Denitrification is modeled using physico-statistical methods based on literature and site-specific data. Another key feature of the software is that it leverages the power of ArcGIS to take into account the spatial location of the OWTS. In the first stage of the project the groundwater flow model was developed and implemented. By using a digital elevation model (DEM) as the starting point, an approximation to the hydraulic gradient is derived which is then calibrated with very limited number of field water table data and combined with information on the physical properties of the surficial aquifer to determine the magnitude and direction of flow. The flow model keeps data requirements to a minimum by only requiring a DEM, aquifer conductivity and porosity, and information on the location of target water bodies.”