Prioritizing Abandoned Coal Mine Reclamation Projects Within the Contiguous United States Using Geographic Information System Extrapolation

Coal mine reclamation projects are very expensive and require coordination of local and federal agencies to identify resources for the most economic way of reclaiming mined land. Location of resources for mine reclamation is a spatial problem. This article presents a methodology that allows the combination of spatial data on resources for the coal mine reclamation and uses GIS analysis to develop a priority list of potential mine reclamation sites within contiguous United States using the method of extrapolation. The extrapolation method in this study was based on the Bark Camp reclamation project. The mine reclamation project at Bark Camp, Pennsylvania, USA, provided an example of the beneficial use of fly ash and dredged material to reclaim 402,600 sq mi of a mine abandoned in the 1980s. Railroads provided transportation of dredged material and fly ash to the site. Therefore, four spatial elements contributed to the reclamation project at Bark Camp: dredged material, abandoned mines, fly ash sources, and railroads. Using spatial distribution of these data in the contiguous United States, it was possible to utilize GIS analysis to prioritize areas where reclamation projects similar to Bark Camp are feasible. GIS analysis identified unique occurrences of all four spatial elements used in the Bark Camp case for each 1 km of the United States territory within 20, 40, 60, 80, and 100 km radii from abandoned mines. The results showed the number of abandoned mines for each state and identified their locations. The federal or state governments can use these results in mine reclamation planning.     

Effects of seismic intensity and socioeconomic status on injury and displacement after the 2007 Peru earthquake

Earthquakes are a major cause of displacement, particularly in developing countries. Models of injury and displacement can be applied to assist governments and aid organisations in effectively targeting preparedness and relief efforts. A stratified cluster survey was conducted in January 2008 to evaluate risk factors for injury and displacement following the 15 August 2007 earthquake in southern Peru. In statistical modelling, seismic intensity, distance to rupture, living conditions, and educational attainment collectively explained 54.9 per cent of the variability in displacement rates across clusters. Living conditions was a particularly significant predictor of injury and displacement, indicating a strong relationship between risk and socioeconomic status. Contrary to expectations, urban, periurban, and rural clusters did not exhibit significantly different injury and displacement rates. Proxies of socioeconomic status, particularly the living conditions index score, proved relevant in explaining displacement, likely due to unmeasured aspects of housing construction practices and building materials.     

Prioritization of coastal properties for conservation in New York State

Conservation of coastal lands reduces non-point source pollution loads into oceans and estuaries, retains natural areas and saves ecological communities from disappearance and change. A recent agreement for protection of Long Island Sound waters in New York and Connecticut established 30 environmental and management goals. One of them is establishment of a listing of existing undeveloped properties and their prioritization for natural resource conservation and outdoor recreation. The optimal prioritization approach poses strong constraints and methodological challenges on selection of data for analysis, assignment of a priority score to each property unit and the assessment of this assignment. To be a practical tool, the prioritization model should be reproducible and include a mechanism for evaluation of obtained prioritization scenarios. Presented study uses Geographic Information System (GIS) to assign conservation priority scores to unprotected and undeveloped parcels greater than five acres in size within New York’s Long Island Sound coastal area. The method combines spatial multi-criteria analysis and statistical methods. The results of this project include identification and prioritization of more than 700 undeveloped properties on New York coast. The most important finding of GIS analysis was the discovery of clusters of vacant parcels that together form large areas available for future conservation. These results offer new conservation tools and strategies to coastal managers and government in New York State.     

SPATIALLY DISTRIBUTED MODELING OF STREAM FLOW DURING STORM EVENTS1

ABSTRACT: The purpose of this paper is to present a new approach for the spatially distributed modeling of water flow during storm events. Distributed modeling of flow during storm events is an important basis for any environmental modeling, including turbidity or sediment transport. During the initial phase of a rainstorm, surface runoff is the main contributor of flow. To provide the spatial components for distributed hydrological modeling a Geographic Information System (GIS) was used to map and visualize contributing areas around a stream channel. Stream segments were defined using the hydrologic response unit (HRU) concept. Lateral flows were derived from GIS output for each segment of the stream and at each time interval of the rain storm and were routed using the kinematic routing equation. This approach is new in hydrological modeling and can be used to enhance many existing simulations. The model is also unique in the fine time scale (i.e., intervals are on the order of minutes). Model results showed good correlation with measured discharge values; however, further studies of contributing area behavior, its relationship with soil types and slope categories, and the influence of watershed size are needed to improve model performance. This model will be used in the future as the basis to model turbidity in streams.