Logistic regression model for sinkhole susceptibility due to damaged sewer pipes

The occurrence of anthropogenic sinkholes in urban areas can lead to severe socioeconomic losses. A damaged underground sewer pipe is regarded as one of the primary causes of such a phenomenon. This study adopted the best subsets regression method to produce a logistic regression model that evaluates the susceptibility for sinkholes induced by damaged sewer pipes. The model was developed by analyzing the sewer pipe network as well as cases of sinkholes in Seoul, South Korea. Among numerous sewer pipe characteristics tested as explanatory variables, the length, age, elevation, burial depth, size, slope, and materials of the sewer pipe were found to influence the occurrence of sinkhole. The proposed model reasonably estimated the sinkhole susceptibility in the area studied, with an area value under the receiver-operating characteristics curve of 0.753. The proposed methodology will serve as a useful tool that can help local governments to choose a cavity inspection regime, and to prevent sinkholes induced by damaged sewer pipes.     

Estimating urban above ground biomass with multi-scale LiDAR

Background

Urban trees have long been valued for providing ecosystem services (mitigation of the “heat island” effect, suppression of air pollution, etc.); more recently the potential of urban forests to store significant above ground biomass (AGB) has also be recognised. However, urban areas pose particular challenges when assessing AGB due to plasticity of tree form, high species diversity as well as heterogeneous and complex land cover. Remote sensing, in particular light detection and ranging (LiDAR), provide a unique opportunity to assess urban AGB by directly measuring tree structure. In this study, terrestrial LiDAR measurements were used to derive new allometry for the London Borough of Camden, that incorporates the wide range of tree structures typical of an urban setting. Using a wall-to-wall airborne LiDAR dataset, individual trees were then identified across the Borough with a new individual tree detection (ITD) method. The new allometry was subsequently applied to the identified trees, generating a Borough-wide estimate of AGB.

Results

Camden has an estimated median AGB density of 51.6 Mg ha^–1 where maximum AGB density is found in pockets of woodland; terrestrial LiDAR-derived AGB estimates suggest these areas are comparable to temperate and tropical forest. Multiple linear regression of terrestrial LiDAR-derived maximum height and projected crown area explained 93% of variance in tree volume, highlighting the utility of these metrics to characterise diverse tree structure. Locally derived allometry provided accurate estimates of tree volume whereas a Borough-wide allometry tended to overestimate AGB in woodland areas. The new ITD method successfully identified individual trees; however, AGB was underestimated by ≤?25% when compared to terrestrial LiDAR, owing to the inability of ITD to resolve crown overlap. A Monte Carlo uncertainty analysis identified assigning wood density values as the largest source of uncertainty when estimating AGB.

Conclusion

Over the coming century global populations are predicted to become increasingly urbanised, leading to an unprecedented expansion of urban land cover. Urban areas will become more important as carbon sinks and effective tools to assess carbon densities in these areas are therefore required. Using multi-scale LiDAR presents an opportunity to achieve this, providing a spatially explicit map of urban forest structure and AGB.

     

Assessment of regional drought vulnerability and risk using principal component analysis and a Gaussian mixture model

Due to the complex characteristics of drought, drought risk needs to be quantified by combining drought vulnerability and drought hazard. Recently, the major focus in drought vulnerability has been on how to calculate the weights of indicators to comprehensively quantify drought risk. In this study, principal component analysis (PCA), a Gaussian mixture model (GMM), and the equal-weighting method (EWM) were applied to objectively determine the weights for drought vulnerability assessment in Chungcheong Province, located in the west-central part of South Korea. The PCA provided larger weights for agricultural and industrial factors, whereas the GMM computed larger weights for agricultural factors than did the EWM. The drought risk was assessed by combining the drought vulnerability index (DVI) and the drought hazard index (DHI). Based on the DVI, the most vulnerable region was CCN9 in the northwestern part of the province, whereas the most drought-prone region based on the DHI was CCN12 in the southwest. Considering both DVI and DHI, the regions with the highest risk were CCN12 and CCN10 in the southern part of the province. Using the proposed PCA and GMM, we validated drought vulnerability using objective weighting methods and assessed comprehensive drought risk considering both meteorological hazard and socioeconomic vulnerability.

     

Resistivity of reservoir sandstones and organic rich shales on the Barents Shelf:Implications for interpreting CSEM data

Marine controlled source electromagnetic(CSEM)data have been utilized in the past decade during petroleum exploration of the Barents Shelf,particularly for de-risking the highly porous sandstone reservoirs of the Upper Triassic to Middle Jurassic Realgrunnen Subgroup.In this contribution we compare the resistivity response from CSEM data to resistivity from wireline logs in both water-and hydrocarbon-bearing wells.We show that there is a very good match between these types of data,particularly when reservoirs are shallow.CSEM data,however,only provide information on the subsurface resistivity.Careful,geology-driven interpretation of CSEM data is required to maximize the impact on exploration success.This is particularly important when quantifying the relative re-sistivity contribution of high-saturation hydrocarbon-bearing sandstone and that of the overlying cap rock.In the presented case the cap rock comprises predominantly organic rich Upper Jurassic-Early Cretaceous shales of the Hekkingen Formation(i.e.a regional source rock).The resistivity response of the reservoir and its cap rock become merged in CSEM data due to the transverse resistance equivalence principle.As a result of this,it is imperative to understand both the relative contributions from reservoir and cap rock,and the geological sig-nificance of any lateral resistivity variation in each of the units.In this contribution,we quantify the resistivity of organic rich mudstone,i.e.source rock,and reservoir sandstones,using 131 exploration boreholes from the Barents Shelf.The highest resistivity(＞10,000 Ωm)is evident in the hydrocarbon-bearing Realgrunnen Subgroup which is reported from 48 boreholes,43 of which are used for this study.Pay zone resistivity is primarily controlled by reservoir quality(i.e.porosity and shale fraction)and fluid phase(i.e.gas,oil and water saturation).In the investigated wells,the shale dominated Hekkingen Formation exhibits enhanced resistivity compared to the background(i.e.the underlying and overlying stratigraphy),though rarely exceeds 20Ωm.Marine mudstones typically show good correlation between measured organic richness and resistivity/sonic velocity log signatures.We conclude that the resistivity contribution to the CSEM response from hydrocarbon-bearing sandstones out-weighs that of the organic rich cap rocks.     

Application of probabilistic neural network to design breakwater armor blocks

This study presents a probabilistic neural network (PNN) technique for predicting the stability number of armor blocks of breakwaters. The PNN is prepared using the experimental data of Van der Meer. The predicted stability numbers of the PNN are compared with those of previous studies, i.e. by an empirical formula and a previous neural network model. The agreement index between the measured and predicted stability numbers by PNN are better than those by the previous studies. The PNN offers a way to interpret the network's structure in the form of a probability density function and it is easy to implement. Therefore, it can be an effective tool for designers of rubble mound breakwaters.     

Coastal environmental assessment and management by ecological simulation in Yeoja Bay, Korea

An eco-hydrodynamic model was used to estimate the carrying capacity of pollutant loads and response of water quality to environmental change in Yeoja Bay, Korea. An energy-system model also was used to simulate the fluctuation in nutrients and organic matter in the bordering wetland. Most water quality factors showed a pulsed pattern, and the concentrations of nutrients and organic matter of seawater increased when input loads of nutrients increased due to freshwater discharge. The well-developed tidal zones and wetlands in the northern area of the bay were highly sensitive to input loads. Residence times of water, chemical oxygen demand (COD), and dissolved inorganic nitrogen (DIN) within the bay were estimated to be about 16 days, 43.2 days, and 50.2 days, respectively. Water quality reacted more sensitively to the effects of nitrogen and phosphorus input than to COD. A plan to reduce the present levels of COD and dissolved inorganic phosphorus (DIP) by 20–30% and DIN by at least 50% in pollutant loads is needed for satisfying the target water quality criteria. The natural removal rate of nutrients in wetlands by reeds was assessed to be approximately 10%.     

Radium tracing of submarine groundwater discharge (SGD) and associated nutrient fluxes in a highly-permeable bed coastal zone, Korea

In order to estimate submarine groundwater discharge (SGD) and SGD-driven nutrient fluxes, we measured the concentrations of nutrients, ²²⁴Ra, and ²²⁶Ra in seawater, river water, and coastal groundwater of Yeongil Bay (in the southeastern coast of Korea) in August 2004 and February 2005. The bottom sediments over the shallow areas of this bay are composed mainly of coarse sands. Large excess concentrations of ²²⁴Ra, ²²⁶Ra, and Si supplied from SGD were observed in August 2004, while these excess concentrations were not apparent in February 2005. Based on the mass balance for ²²⁴Ra, ²²⁶Ra, and Si, which showed conservative mixing behavior in seawater, SGD was estimated to be approximately 6 × 10⁶ m³ day^− 1 (seepage rate = 0.2 m day^− 1) in shallow areas (< 9 m water depth) in August 2004, which is much higher than the SGD level typically found in other coastal regions worldwide. During the summer period, SGD-driven nutrients in this bay contributed approximately 98%, 12%, and 76% of the total inputs for dissolved inorganic nitrogen (DIN), phosphorus (DIP), and silicate (DSi), respectively. Our study implies that the ecosystem in this highly permeable bed coastal zone is influenced strongly by SGD during summer, while such influences are negligible in winter.     

Compliance costs and the small fisher: A study of exiters from the New Zealand fishery

Over 3000 predominantly small-scale fishers have exited the New Zealand's quota management system (QMS) between its inception in 1986 and 2000. This study, based on the Ministry of Fisheries database and a questionnaire sent to the exiters, establishes that compliance costs in general, and those specifically related to the QMS, were one of the most consistent reasons for exit. Uncertainty about future QMS policy and the high cost of quota were also significant factors. It appears that the small fishers’ perception of high compliance cost can be supported by industry data.     

Review of recent findings on the water masses and circulation in the East Sea (Sea of Japan)

Recent findings on water masses, biogeochemical tracers, deep currents and basin-scale circulation in the East/Japan Sea, and numerical modeling of its circulation are reviewed. Warming continues up to 2007 despite an episode of bottom water formation in the winter of 2000–2001. Water masses have definitely changed since the 1970s and further changes are expected due to the continuation of warming. Accumulation of current data in deep waters of the East/Japan Sea reveals that the circulation in the East/Japan Sea is primarily cyclonic with sub-basin scale cyclonic and anticyclonic cells in the Ulleung Basin (Tsushima Basin). Our understanding of the circulation of intermediate water masses has been deepened through high-resolution numerical studies, and the implementation of data assimilation has had initial success. However, the East/Japan Sea is unique in terms of the fine vertical structures of physical and biogeochemical properties of cold water mass measured at the highest precision and their rapid change with the global warming, so that full understanding of the structures and their change requires in-depth process studies with continuous monitoring programs.     

Fostering Environmental Sensitivity by Observing Everyday Environments

This study examined the effects of observing and reflecting on everyday environments in the development of environmental sensitivity, defined as a holistic capability composed of predisposition, knowledge, and behavior subdimensions. We encouraged participants to use diverse sources, such as texts, photographs, and animation, to record their observations and thinking. As a result, the activity in this study was beneficial in enhancing students’ environmental sensitivity. Students’ mean scores on the environmental sensitivity questionnaire improved, and their reflective journals reported increased interest in everyday environments, enhanced knowledge about diverse environmental elements, and strengthened will to act pro-environmentally. The usefulness of the geospatial platform was also reported.