Abstract:In this paper regression models are developed for predicting water temperature and the concentration of dissolved oxygen in rivers monitored by the Newfoundland and Labrador Real-Time Water Quality Monitoring (RTWQM) network. The developed models can be used to predict mean, maximum and minimum water temperatures and dissolved oxygen at the monthly, weekly and daily time scales. A nonlinear logistic model is found to best represent the S-shaped relationship between water temperature at the real-time stations and air temperature collected from meteorological stations 5-50 kilometers away. There is a clear tendency for monthly and weekly models to be more accurate for prediction than the daily models. Both linear and nonlinear exponential decay models were found to best represent the relationship between water temperature and dissolved oxygen at the real-time stations. A novel graphical method of linking air temperature to water temperature and dissolved oxygen has been developed and may prove to be a valuable simple tool in the assessment of the health of the rivers in the real-time network.Résumé : Ce papier décrit des modèles de régression qui prédisent la température de l'eau et la concentration d'oxygène dissous dans les rivières surveillées par le réseau Terre-Neuve-et-Labrador Real-Time Water Quality. On peut utiliser les modèles développés pour prédire les températures d'eau moyennes, maximales et minimales et les niveaux d'oxygène dissous dans l'eau aux échelles mensuelles, hebdomadaires et quotidiennes. Un modèle non-linéaire logistique représente mieux la relation entre la température de l'eau aux stations en temps réel et la température de l'air provenant des stations météorologiques de 5 à 50 kilomètres de distance. Il y a une tendance claire pour les modèles mensuels et hebdomadaires d'être plus précis pour la prédiction que les modèles quotidiens. Les modèles linéaires et non-linéaires de décroissance exponentielle représentent mieux la relation entre la température de l'eau et l'oxygène dissous aux stations en temps réel. Une nouvelle méthode graphique de relier la température de l'air à la température de l'eau et l'oxygène dissous a été développée; cette méthode devrait se révéler un outil précieux et simple pour évaluer la santé des rivières dans le réseau en temps réel.

No abstract

Design flood estimation is an important task that is required in the planning and design of many civil engineering projects. In this study, the flood records of more than 23 gauged river basins in Sarawak, Malaysia, are examined using an index-flood estimation procedure based on L-moments. Two homogeneous regions were identified and the Generalized Extreme Value and the Generalized Logistic distributions are found to describe the distribution of extreme flood events appropriately within the respective regions. A regional growth curve is subsequently developed for each of the regions. These curves can be used for the estimation of design floods in ungauged basins in Sarawak within the limitations identified for the method. The results presented herein are useful for practicing engineers in Sarawak while the general methodology may be used in any other regions, provided flood records are available.

No abstract

No abstract

The probability distributions of annual peak flows used in flood risk analysis quantify the risk that a design flood will be exceeded. But the parameters of these distributions are themselves to a degree uncertain and this uncertainty increases the risk that the flood protection provided will in fact prove to be inadequate. The increase in flood risk due to parameter uncertainty is small when a fairly long record of data is available and the annual flood peaks are serially independent, which is the standard assumption in flood frequency analysis. But standard tests for serial independence are insensitive to the type of grouping of high and low values in a time series, which is measured by the Hurst coefficient. This grouping increases the parameter uncertainty considerably. A study of 49 annual peak flow series for Canadian rivers shows that many have a high Hurst coefficient. The corresponding increase in flood risk due to parameter uncertainty is shown to be substantial even for rivers with a long record, and therefore should not be neglected. The paper presents a method of rationally combining parameter uncertainty due to serial correlation, and the stochastic variability of peak flows in a single risk assessment. In addition, a relatively simple time series model that is capable of reproducing the observed serial correlation of flood peaks is presented.(KEY TERMS: flood risk analysis; Hurst coefficient; parameter uncertainty; time series; mixed noise model; predictive distribution.)

in section 5. Bayes estimates (under a square-error loss funclion) of the reliability (survivor) function. Section 4 gives estimates using the two Bayes approximation procedures. The results and comparison of these estimates with that of the MLE are presented

The feasibility of using enzyme activities for indicating the state of marine fish waste composting was examined in this study and the evolution of the composting process for a 60 day period was evaluated. Results indicated that stable and mature fish waste compost has been generated. During the composting process, oxidoreductase enzyme (dehydrogenase) and hydrolase enzyme (β-glucosidase and phosphatase) activities decreased with time since available organic compounds decreased. A good correlation among enzyme activities and different physiochemical parameters including oxygen uptake rate, carbon/nitrogen ratio, and germination index led to the conclusion that both hydrolytic and dehydrogenase enzyme activities could be feasible indicators of the state and evolution of the composting process.