Verification and adjustment of regional regression models for urban storm-runoff quality using data collected in Little Rock, Arkansas

Regional regression equations have been developed to estimate urban storm-runoff loads and mean concentrations using a national data base. Four statistical methods using at-site data to adjust the regional equation predictions were developed to provide better local estimates. The four adjustment procedures are a single-factor adjustment, a regression of the observed data against the predicted values, a regression of the observed values against the predicted values and additional local independent variables, and a weighted combination of a local regression with the regional prediction. Data collected at five representative storm-runoff sites during 22 storms in Little Rock, Arkansas, were used to verify, and, when appropriate, adjust the regional regression equation predictions. Comparison of observed values of storm-runoff loads and mean concentrations to the predicted values from the regional regression equations for nine constituents (chemical oxygen demand, suspended solids, total nitrogen as N, total ammonia plus organic nitrogen as N, total phosphorus as P, dissolved phosphorus as P, total recoverable copper, total recoverable lead, and total recoverable zinc) showed large prediction errors ranging from 63 percent to more than several thousand percent. Prediction errors for 6 of the 18 regional regression equations were less than 100 percent and could be considered reasonable for water-quality prediction equations. The regression adjustment procedure was used to adjust five of the regional equation predictions to improve the predictive accuracy. For seven of the regional equations the observed and the predicted values are not significantly correlated. Thus neither the unadjusted regional equations nor any of the adjustments were appropriate. The mean of the observed values was used as a simple estimator when the regional equation predictions and adjusted predictions were not appropriate.

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Data for and adjusted regional regression models of volume and quality of urban storm-water runoff in Boise and Garden City, Idaho, 1993-94

10.3133/wri954228 ◽

1995 ◽

Keyword(s):

Regression Models ◽

Storm Water ◽

Water Runoff ◽

Garden City ◽

Storm Water Runoff ◽

Regional Regression ◽

Urban Storm

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Procedures for adjusting regional regression models of urban-runoff quality using local data

Open-File Report ◽

10.3133/ofr9339 ◽

1993 ◽

Cited By ~ 2

Author(s):

A.B. Hoos ◽

J.K. Sisolak

Keyword(s):

Regression Models ◽

Urban Runoff ◽

Local Data ◽

Regional Regression ◽

Urban Runoff Quality ◽

Runoff Quality

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Urban Storm Runoff Quality in Southeast Michigan

Journal of the Environmental Engineering Division ◽

10.1061/jeegav.0000998 ◽

1980 ◽

Vol 106 (1) ◽

pp. 153-162

Author(s):

Peter G. Collins ◽

James W. Ridgway

Keyword(s):

Storm Runoff ◽

Runoff Quality ◽

Urban Storm

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Urban Homeownership and Mental Health: Mediating Effect of Perceived Sense of Control

City and Community ◽

10.1111/j.1540-6040.2012.01415.x ◽

2012 ◽

Vol 11 (4) ◽

pp. 409-430 ◽

Cited By ~ 12

Author(s):

Kim R. Manturuk

Keyword(s):

Mental Health ◽

Low Income ◽

Urban Areas ◽

Regression Models ◽

Mediating Effect ◽

Sense Of Control ◽

Using Data ◽

The Relationship ◽

Subjective Trust ◽

Control Part

What are the mechanisms responsible for homeowners’ better mental health? Social disorganization theory suggests that the relationship between homeownership and mental health is mediated by perceived sense of control, trust in neighbors, and residential stability. This hypothesis is tested using data collected from respondents in 30 low–wealth urban areas. Using propensity score matching and regression models, I find that low–income homeowners report a greater sense of control and trust in their neighbors than comparable renters. Homeownership likewise has an impact on mental health, but the effect is entirely mediated by perceived sense of control. Part of that mediating effect is related to avoiding serious delinquency in mortgage payments. However, subjective trust and residential mobility did not mediate the relationship between homeownership and mental health. The study findings are discussed in light of the need for a cohesive theory of homeownership, particularly given changing economic realities.

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