Cooperative design of a water quality monitoring system for the Big Thompson River Watershed, Colorado

1999 Fall.Includes bibliographic references (pages 78-80).Water from the Big Thompson River and the Colorado-Big Thompson Project (a trans-mountain diversion of Colorado River water to the Big Thompson River) is a valuable resource to the North Front Range region of Colorado. The water is utilized for many purposes (e.g. municipal, irrigation, industrial, recreation, and ecosystem health). Over half a million people depend on the Big Thompson system for drinking water. In recent years a slow decline in water quality has been observed at some locations, particularly in reservoirs lower in the watershed. This trend, coupled with increased pressure to provide accurate data about water quality, has lead a group of stakeholders in the Big Thompson Watershed to seek a better way in which to monitor and manage their water, through cooperation. Stakeholders within the Big Thompson Watershed, who make up a group called the Big Thompson Watershed Forum (BTWF), formed a partnership with Colorado State University to design a water quality monitoring network. The design process was broken down into five steps: objectives, variables, monitoring locations, sampling frequency, and cost analysis. Each step was completed in a cooperative manner, through a series of meetings with BTWF members. The meetings provided an opportunity for members of the BTWF to shape the monitoring system based upon concerns and priorities specific to the watershed. The resulting water quality network is governed by five objectives. The objectives address regulatory requirements within the watershed, eutrophication of reservoirs, and the estimation of loads, spatial trends, and temporal trends. A variable list of 38 water quality parameters was defined as the minimum group of variables that meet the informational goals laid out in the objectives. The list included 12 inorganic variables, nine metals, five organic parameters, seven microbiological variables, and five field parameters. Monitoring locations were defined based on the objective list, already existing monitoring sites, and watershed hydrology (e.g. mixing distance, confluence locations, diversions). Thirty-nine monitoring locations were chosen; 29 moving water sites and 10 reservoir sites. Each site was given a priority rating of high or low. The group of 31 high priority sites is the smallest network that satisfies the needs of all BTWF participants. The seven low priority monitoring locations will be sampled if financially feasible. Sampling frequency was determined on a seasonal basis. Three seasons were determined based on annual flow and water temperature cycles. It was originally hoped that historical data could be used to estimate background variability, allowing the sample size required for a specified level of accuracy in mean and trend detection to be determined. Only 11, of the 38 variables on the variable list, had historical data available, and only three, of the 11, had enough data to accurately estimate background variability. Sampling frequencies for variables with inadequate historical data were based a maximum frequency set for each season. During seasons one and two, no variable is to be sampled at a frequency higher than twice a month except for biological parameters. The maximum frequency during season three is monthly. The cost estimate step was utilized as a feasibility check on the monitoring program. The aim for the cooperative monitoring program was more thorough information for the same or less cost. If the monitoring program cost exceeded the sum of all current monitoring budgets, adjustments were made in variables, monitoring sites, and sampling frequency. The final cost estimate was $405,259.00 per year, roughly the same as the$401,500.00 currently spent. In order for an undertaking such as this design and monitoring program to succeed, all participants must be willing to compromise and devote large amounts of time in order to allow for a truly cooperative effort. Those individuals most active in the design process typically represented local entities. The resulting monitoring network therefore gave higher priority to local water quality concerns, highlighting the differences between local informational needs and those defined by state and federal governments. The monitoring system currently includes a set of objectives, variable list, monitoring network, and sample frequency. They have been developed, discussed, and agreed upon by all BTWF participants. The completion of the monitoring network indicates that the BTWF is on its way towards the final goal of a long-term monitoring program operated by, and benefiting all agencies involved

Local Policy Scan on Climate Change Adaptation

The Climate Change Adaptation Policy Scan provides a snapshot of the current state of community-level activities in the United States and Canada for addressing climate change impacts on public health. The report was developed using a combination of literature review, expert interviews, and case studies to identify best practices, common challenges, and keys to success. This report is intended to be useful to public health officials and community organizations; city and county public agencies, especially those involved in city planning and sustainability; and scholars in these fields. The information provided for the emerging area of climate adaptation policy development is organized into four areas. The first two topic areas, Climate Change and Public Health and Strategies for Responding to Climate Change, summarize the information gathered from literature, expert interviews, and case studies. The third area, Background Research, details the three data sources used to develop the report, and the fourth area, Research Method, describes the data collection process

Local Climate Action Planning

XIV, 286p. 22 illus.online resource

Identification of water-quality trends using sediment cores from Dillon Reservoir, Summit County, Colorado /

Shipping list no.: 2001-0297-P."National Water-Quality Assessment Program."Includes bibliographical references (p. 21-22).Mode of access: Internet

Changes in nutrient and pesticide concentrations in urban and agricultural areas of the South Platte River Basin, Colorado, Wyoming, and Nebraska, 1994-2000 /

Shipping list no.: 2003-0190-P."National Water-Quality Assessment Program."Includes bibliographical references (p. 12).Mode of access: Internet

Water-quality data analysis of the upper Gunnison River watershed, Colorado, 1989-99 /

"National Water-Quality Assessment Program."Includes bibliographical references (p. 48-50).Mode of access: Internet

Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19

Background: We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients. Methods: The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV). Results: Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60 years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%. Conclusions: Age was the strongest determinant of risk of death, with a ∼30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death. The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death