Mixed estimation methods for Halphen distributions with applications in extreme hydrologic events

The Halphen family of distributions is a flexible and complete system to fit sets of observations independent and identically distributed. Recently, it is shown that this family of distributions represents a potential alternative to the generalized extreme value distributions to model extreme hydrological events. The existence of jointly sufficient statistics for parameter estimation leads to optimality of the method of maximum likelihood (ML). Nevertheless, the ML method requires numerical approximations leading to less accurate values. However, estimators by the method of moments (MM) are explicit and their computation is fast. Even though MM method leads to good results, it is not optimal. In order to combine the advantages of the ML (optimality) and MM (efficiency and fast computations), two new mixed methods were proposed in this paper. One of the two methods is direct and the other is iterative, denoted respectively direct mixed method (MMD) and iterative mixed method (MMI). An overall comparison of the four estimation methods (MM, ML, MMD and MMI) was performed using Monte Carlo simulations regarding the three Halphen distributions. Generally, the MMI method can be considered for the three Halphen distributions since it is recommended for a majority of cases encountered in hydrology. The principal idea of the mixed methods MMD and MMI could be generalized for other distributions with complicated density functions.     

Implications for place attachment in coastal Reserve management

This study determined the characteristics of North Carolina Coastal Reserve and North Carolina National Estuarine Research Reserve (jointly referred to as Reserve) visitors, visitor opinions of site conditions, visitor understanding of site management objectives, and patterns of visitation. The latter were investigated to obtain a proxy of place attachment and its effects on knowledge of ownership and perceptions of management. Data were collected on demographics, use patterns, visitor perceptions, and visitor knowledge during the period of 25 May-28 October, 2007. Visitors were educated, wealthy, older, racially homogeneous, and frequent returnees. The majority of respondents supported existing management activities and the implementation of additional use restrictions should site conditions deteriorate. Data indicated that respondents were unaware of which agency manages the Reserve sites or its mission. These findings suggest that management needs to engage in more education of the visiting public. Sensitizing the public to the mission of the Reserve and increasing place attachment could decrease negative visitor impacts.     

The behavior of total lightning activity in severe Florida thunderstorms

The development of a new observational system called LISDAD (Lightning Imaging Sensor Demonstration and Display) has enabled a study of severe weather in central Florida. The total flash rates for storms verified to be severe are found to exceed 60 fpm, with some values reaching 500 fpm. Similar to earlier results for thunderstorm microbursts, the peak flash rate precedes the severe weather at the ground by 5–20 min. A distinguishing feature of severe storms is the presence of lightning ‘jumps' — abrupt increases in flash rate in advance of the maximum rate for the storm. The systematic total lightning precursor to severe weather of all kinds — wind, hail, tornadoes — is interpreted in terms of the updraft that sows the seeds aloft for severe weather at the surface and simultaneously stimulates the ice microphysics that drives the intracloud lightning activity.     

Predicting river water temperatures using stochastic models: case study of the Moisie River (Québec,Canada)

Successful applications of stochastic models for simulating and predicting daily stream temperature have been reported in the literature. These stochastic models have been generally tested on small rivers and have used only air temperature as an exogenous variable. This study investigates the stochastic modelling of daily mean stream water temperatures on the Moisie River, a relatively large unregulated river located in Québec, Canada. The objective of the study is to compare different stochastic approaches previously used on small streams to relate mean daily water temperatures to air temperatures and streamflow indices. Various stochastic approaches are used to model the water temperature residuals, representing short‐term variations, which were obtained by subtracting the seasonal components from water temperature time‐series. The first three models, a multiple regression, a second‐order autoregressive model, and a Box and Jenkins model, used only lagged air temperature residuals as exogenous variables. The root‐mean‐square error (RMSE) for these models varied between 0·53 and 1·70 °C and the second‐order autoregressive model provided the best results. A statistical methodology using best subsets regression is proposed to model the combined effect of discharge and air temperature on stream temperatures. Various streamflow indices were considered as additional independent variables, and models with different number of variables were tested. The results indicated that the best model included relative change in flow as the most important streamflow index. The RMSE for this model was of the order of 0·51 °C, which shows a small improvement over the first three models that did not include streamflow indices. The ridge regression was applied to this model to alleviate the potential statistical inadequacies associated with multicollinearity. The amplitude and sign of the ridge regression coefficients seem to be more in agreement with prior expectations (e.g. positive correlation between water temperature residuals of different lags) and make more physical sense. Copyright © 2006 John Wiley & Sons, Ltd.     

Rural women and technology in South Africa: Case studies from KwaZulu-Natal Province

This article contributes to a greater understanding of the linkages between women's roles, responsibilities and their use of technology in poor rural communities. The ways in which poor rural women conceptualize technology is examined. Furthermore, how they use their knowledge and skills to develop, modify and adapt the techniques and technical processes in which they are involved are also explored. Additionally, the links between indigenous and modern technologies in relation to gender considerations in poor rural contexts are examined. This article draws from findings of primary research undertaken in two marginalized rural communities in Kwazulu-Natal, South Africa. The study reveals that the use of technologies are highly gendered and differentiated among women. Poor rural women utilize a range of technologies in both productive and reproductive activities which are central to their livelihood strategies, especially at the household level. Furthermore, although women are adapting and innovating technologies their expertise remains largely unrecognized. A range of problems and constraints exist which limit women's access to and use of technologies. A key tension identified in the study is that between the use of locally-based, indigenous technologies and modern, external technologies. This revised version was published online in July 2006 with corrections to the Cover Date.     

Multi-unit building address geocoding: An approach without indoor location reference data

Accurately mapped locations within multi-unit properties are useful for several organizations in today's society. Published work on geocoding methods either require detailed location reference data or does not apply to multi-unit buildings. In this research, a generalizable method is realized to map apartment addresses to their explicit locations without access to indoor location reference data based on publicly available address- and geospatial-building information. The performance of this approach is measured by conducting a comparative study between a linear interpolation baseline and gradient-boosted decision trees model. The proposed method can successfully geocode addresses across different building shapes and sizes. Furthermore, the model significantly outperforms the baseline in terms of positional accuracy proving the feasibility of approximating apartment locations by their address- and geospatial-building information.     

A Multiple Criteria Decision Modelling approach to selection of estimation techniques for fitting extreme floods

The problem of fitting a probability distribution, here log-Pearson Type III distribution, to extreme floods is considered from the point of view of two numerical and three non-numerical criteria. The six techniques of fitting considered include classical techniques (maximum likelihood, moments of logarithms of flows) and new methods such as mixed moments and the generalized method of moments developed by two of the co-authors. The latter method consists of fitting the distribution using moments of different order, in particular the SAM method (Sundry Averages Method) uses the moments of order 0 (geometric mean), 1 (arithmetic mean), –1 (harmonic mean) and leads to a smaller variance of the parameters. The criteria used to select the method of parameter estimation are: