Surface Water Metabolism Potential in a Tropical Estuary,Hilo Bay,Hawai’i,USA, During Storm and Non-storm Conditions

Surface water gross primary production potential (pGPP), respiration (RESP), metabolism potential (pMET), and CO₂ fluxes in Hilo Bay, Hawai’i, USA, were examined along two river plumes during storm (high-flow) and non-storm (low-flow) conditions. Significant differences in pGPP, RESP, and pMET were found between low- and high-flow conditions, with lowest rates of all processes occurring during high-flow conditions. CO₂ fluxes were influenced by metabolic processes at all but one site, with the bay’s surface waters being autotrophic and a sink for atmospheric CO₂ during low-flow conditions and less autotrophic and a source of atmospheric CO₂ during high-flow conditions. Significant differences in pMET were found between the two river plumes during low-flow conditions at spatial scales of 1.5 km; however, no differences between river plumes were found during high-flow conditions. Our study suggests that an increase in storms associated with global climate change could impact surface water metabolic dynamics of tropical estuaries.     

Urban cadastral mapping using very high resolution remote sensing data

With growing urban expanses, one of the pre-requisites for effective governance is Urban Information Systems (UIS) with content down to individual properties (and individuals). The basic input i.e., a map, in UIS should show individual property boundaries showing the plan outline of all structures existing within, at a scale of 1:1000 and larger with sub-metre to centimeters planimetric and geometric accuracy. With very high resolution remote sensing data of the order of 1m available in hand, it is possible to prepare maps with high resolution spatial content. The present exercise demonstrates a method of preparing a geometrically and planimetrically accurate urban cadastral map on very large scale for a small area of about 5 sq km. IKONOS merged data with 1m resolution is used for the purpose. Mapping was done in conjunction with on-site measurements and sketches. Guides are used to maintain shape symmetry and accuracy of buildings and other features. Working out cost of mapping per unit area is another objective in the present exercise. For want of fully or semi-automatic methods of information extraction from very high resolution remote sensing data, it is imperative that mapping should be carried out in conjunction with some on-site measurements wherever necessary.     

A simplified analytical model for run-out prediction of flow slides in municipal solid waste landfills

Flow slides in municipal solid waste (MSW) landfills are common geoenvironmental issues in the urban environment and can pose a serious threat to the surrounding population and infrastructure. Prediction of the maximum run-out distance of flow slides in MSW landfills is therefore an essential part of hazard and risk assessment in engineering design. Based on the framework for simple analysis originally developed by Hungr (1995), we propose a simplified analytical model for calculating dam breaks in a plastic fluid along a single inclined base. In the proposed model, a quarter-elliptical shape is used to describe the approximate configuration of the flow slide. Following this step, the physical laws relating to the conservation of mass and energy are used to calculate the potential flow. Of additional note is a boundary condition in mathematics relating to this simplified analytical model, which is also reported in this study. Taking the obvious mobility characteristics of the MSW at point of failure into consideration, a three-phase simplified model along double inclined bases has been further developed for run-out prediction of the flow slide in MSW landfill. The proposed three-phase model is then applied to estimate the maximum run-out distance of two typical flow failures of landfills located in Sarajevo and Bandung, which demonstrate the capability of the proposed simplified analytical model for use in hazard assessments of landfills.     

An artificial neural network-based response surface method for reliability analyses of <Emphasis Type="Italic">c</Emphasis>-φ slopes with spatially variable soil

This paper presents an artificial neural network (ANN)-based response surface method that can be used to predict the failure probability of c-φ slopes with spatially variable soil. In this method, the Latin hypercube sampling technique is adopted to generate input datasets for establishing an ANN model; the random finite element method is then utilized to calculate the corresponding output datasets considering the spatial variability of soil properties; and finally, an ANN model is trained to construct the response surface of failure probability and obtain an approximate function that incorporates the relevant variables. The results of the illustrated example indicate that the proposed method provides credible and accurate estimations of failure probability. As a result, the obtained approximate function can be used as an alternative to the specific analysis process in c-φ slope reliability analyses.     

Non-linear Responses of a Coastal Aquatic Ecosystem to Large Decreases in Nutrient and Organic Loadings

Between 1991 and 2000, Boston Harbor, a bay–estuary in the northeast USA, experienced a decrease in loadings of total nitrogen (TN), total phosphorus (TP), and particulate organic carbon (PC) of between ∼80% and ∼90%. The average concentrations of TN and TP in the harbor water column were decreased in linear proportion to the loadings. The changes to the chlorophyll-a (chl-a), PC, and bottom water DO concentrations were curvilinear relative to the loadings, with larger changes at low than high loadings. For TN and TP, the starts of the decreases in concentrations coincided with the starts of the decreases in loadings. For the three variables that showed curvilinear responses, the starts of the changes lagged by 2 to 3 years the starts of the decreases in TN loadings. Total suspended solid concentrations and water clarity in the harbor were unchanged. The study shows that for systems such as Boston Harbor, decreases in nutrient loadings will have quite different effects depending on the base loadings to the system.