A critical review of the problems encountered in attempting to quantify flood damage is used to demonstrate inconsistencies, omissions, and variabilities among previous studies and procedures. A reasonable procedure for updating residential depth – damage data from previous studies is shown to involve use of the all-items consumer price index. Recommended strategies for flood damage estimation involve calibration of synthetic stage – damage data to observed flood damage data.
A spreadsheet model for forecasting solid waste tonnages is described. The model uses generation coefficients from the technical literature associated with individual material components (paper, glass, metals, plastics and rubber, organic materials, construction waste, inerts and other) to express the amount of waste produced per capita and per employee in the labor force. Estimates of quantities being generated by two major groups, namely domestic and industrial/commercial/institutional sources are reflected in the model's output. Using this disaggregated format, the model estimates total waste, recaptured waste (as a result of policy initiatives), and net refuse. Confidence intervals are developed using a regression model related to the business cycle. Two worked examples are given for data obtained in Canada.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.