Geology topics

Kenneth H. Reckhow

Publications and source records attributed to Kenneth H. Reckhow.

4 recordsLinked to original sources

USGS2016

Water data to answer urgent water policy questions: Monitoring design, available data, and filling data gaps for determining whether shale gas development activities contaminate surface water or groundwater in the Susquehanna River Basin

Throughout its history, the United States has made major investments in assessing natural resources, such as soils, timber, oil and gas, and water. These investments allow policy makers, the private sector and the American public to make informed decisions about cultivating, harvesting or conserving these resources to maximize their value for public welfare, environmental conservation and the economy. As policy issues evolve, new priorities and challenges arise for natural resource assessment, and new approaches to monitoring are needed. For example, new technologies for oil and gas development or alternative energy sources may present new risks for water resources both above and below ground. There is a need to evaluate whether today’s water monitoring programs are generating the information needed to answer questions surrounding these new policy priorities. The Northeast-Midwest Institute (NEMWI), in cooperation with the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Program, initiated this project to explore the types and amounts of water data needed to address water-quality related policy questions of critical concern to today’s policy makers and whether those data are currently available. The collaborating entities identified two urgent water policy questions and conducted case studies in the Northeast-Midwest region to determine the water data needed, water data available, and the best ways to fill the data gaps relative to those questions. This report details the output from one case study and focuses on the Susquehanna River Basin, a data-rich area expected to be a best-case scenario in terms of water data availability.

Maryland, New York, Pennsylvania↗

USGS2015

Water data to answer urgent water policy questions: Monitoring design, available data and filling data gaps for determining the effectiveness of agricultural management practices for reducing tributary nutrient loads to Lake Erie

Throughout its history, the United States has made major investments in assessing natural resources, such as soils, timber, oil and gas, and water. These investments allow policy makers, the private sector and the American public to make informed decisions about cultivating, harvesting or conserving these resources to maximize their value for public welfare, environmental conservation and the economy. As policy issues evolve, new priorities and challenges arise for natural resource assessment, and new approaches to monitoring are needed. For example, informed conservation and use of the nation’s finite fresh water resources in the context of increasingly intensive land development is a priority for today’s policy decisionmakers. There is a need to evaluate whether today’s water monitoring programs are generating the information needed to answer questions surrounding these new policy priorities. The Northeast-Midwest Institute (NEMWI), in cooperation with the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Program, initiated this project to explore the types and amounts of water data needed to address water-quality related policy questions of critical concern to today’s policy makers. The collaborating entities identified two urgent water policy questions and conducted case studies in the Northeast-Midwest region to determine the water data needed, water data available, and the best ways to fill the data gaps relative to those questions. This report details the output from one case study and focuses on the Lake Erie drainage basin, a data-rich area expected to be a best-case scenario in terms of water data availability.

Indiana, Michigan, New York, Ohio, Pennsylvania↗

USGS2010

On the application of multilevel modeling in environmental and ecological studies

This paper illustrates the advantages of a multilevel/hierarchical approach for predictive modeling, including flexibility of model formulation, explicitly accounting for hierarchical structure in the data, and the ability to predict the outcome of new cases. As a generalization of the classical approach, the multilevel modeling approach explicitly models the hierarchical structure in the data by considering both the within- and between-group variances leading to a partial pooling of data across all levels in the hierarchy. The modeling framework provides means for incorporating variables at different spatiotemporal scales. The examples used in this paper illustrate the iterative process of model fitting and evaluation, a process that can lead to improved understanding of the system being studied.

Ecology↗

USGS2005

Nonlinear regression modeling of nutrient loads in streams: A Bayesian approach

A Bayesian nonlinear regression modeling method is introduced and compared with the least squares method for modeling nutrient loads in stream networks. The objective of the study is to better model spatial correlation in river basin hydrology and land use for improving the model as a forecasting tool. The Bayesian modeling approach is introduced in three steps, each with a more complicated model and data error structure. The approach is illustrated using a data set from three large river basins in eastern North Carolina. Results indicate that the Bayesian model better accounts for model and data uncertainties than does the conventional least squares approach. Applications of the Bayesian models for ambient water quality standards compliance and TMDL assessment are discussed.

Water Resources Research↗