Water resources data for California

Mode of access: Internet.

Water resources data for Pennsylvania.

Mode of access: Internet.

Water resources data for Washington

Mode of access: Internet.

Water resources data for Wyoming

Mode of access: Internet.

Water resources data for Oregon.

Beginning 1964/65-

Maximum utilization of scarce data in hydrologic design /

Mode of access: Internet.

An intensive survey of the Kaskaskia River Basin : data summary, summer 1996 and 1997 /

"IEPA/BOW/00-001"--Cover.

An intensive survey of the Vermilion River Basin (Wabash River drainage) 1997 : data collection methods and summary /

"The Illinois Environmental Protection Agency monitors surface waters (i.e. lakes and streams) through a variety of programs. The most extensive is the Ambient Water Quality Monitoring Network (AWQMN) which consists of 203 stream stations statewide sampled on a 6 week cycle since October 1977." -- p. 1.

Availability of the Colchester coal for mining in northern and western Illinois /

This report is the fourth in a series to assess the availability of coal resources for future mining in Illinois.

The continuous-record streamflow data-collection program in Maine.

Mode of access: Internet.

A Guide to Surface Features Related to Underground Coal Mining

The purpose of this guide is to assist investigators conducting geologic hazard assessments with the understanding, detection, and characterization of surface features related to subsidence from underground coal mining. Subsidence related to underground coal mining can present serious problems to new and/or existing infrastructure, utilities, and facilities. For example, heavy equipment driving over the ground surface during construction processes may punch into voids created by sinkholes or cracks, resulting in injury to persons and property. Abandoned underground mines also may be full of water, and if punctured, can flood nearby areas. Furthermore, the integrity of rigid structures such as buildings, dams and bridges may be compromised if mining subsidence results in differential movement at the ground surface. Subsidence of the ground surface is a phenomenon associated with the removal of material at depth, and may occur coincident with mining, gradually over time, or sometimes suddenly, long after mining operations have ceased (Gray and Bruhn, 1984). The spatial limits of underground coal mines may extend for great distances beyond the surface operations of a mine, in some cases more than 10 miles for an individual mine. When conducting geologic hazard assessments, several remote investigation methods can be used to observe surface features related to underground mining subsidence. LiDAR-derived DEMs are generally the most useful method available for identifying these features because the bare earth surface can be viewed. However, due to limitations in the availability of LiDAR data, other methods often need to be considered when investigating surface features related to underground coal mining subsidence, such as Google Earth and aerial imagery. Mine maps, when available, can be viewed in tandem with these datasets, potentially improving the confidence of any possible mining subsidence-related features observed remotely. However, maps for both active and abandoned mines may be incomplete or unavailable. Therefore, it is important to be able to recognize possible surface features related to underground mining subsidence. This guide provides examples of surface subsidence features related to the two principal underground coal mining methods used in the United States: longwall mining and room and pillar mining. The depth and type of mining, geologic conditions, hydrologic conditions, and time are all factors that may influence the type of features that manifest at the surface. This guide provides investigators a basic understanding about the size, character and conditions of various surface features that occur as a result of underground mining subsidence.

Quantifying ice-shelf basal melt and ice-stream dynamics using high-resolution DEM and GPS time series

Thesis (Ph.D.)--University of Washington, 2016-06

How cost efficient are Australia's mining industries?

This paper uses a stochastic translog cost frontier model and a panel data of five key mining industries in Australia over 1968-1969 to 1994-1995 to investigate the sources of output growth and the effects of cost inefficiency on total factor productivity (TFP) growth. The results indicate that mining output growth was largely input-driven rather than productivity-driven. Although there were some gains from technological progress and economics of scale in production, cost inefficiency which barely exceeded 1.1% since the mid-1970s in the mining industries was the main factor causing low TFP growth. (C) 2002 Elsevier Science B.V. All rights reserved.