Fuzzy MCDM-based GIS model for subsea oil pipeline route optimization: An integrated approach

Proper pipeline route selection is an integral component of a typical oil exploration and transportation project. Improperly selected routes could have severe consequences including pipe failures, oil spillage, and environmental disasters. Consequently, technologies like geographic information systems (GIS) are increasingly being used to facilitate the oil pipeline route selection procedure—especially for onshore routing projects. Surprisingly, not much has been documented on the application of GIS to offshore pipeline routing. With recent discoveries on the merits of offshore oil exploration, it is necessary to extend the analytical capabilities of GIS to the unique offshore domain. However, concerns have been raised regarding the limitations of GIS in accurately prioritizing diverse selection criteria in typical multi-criteria decision-making (MCDM) problems like route selection. Consequently, this paper addresses the offshore/subsea pipeline routing constraint using a hybrid decision support system (DSS), which integrates a GIS and fuzzy logic-based approximate reasoning (AR) models for optimal performance. The resultant spatial decision support system (SDSS) was successfully applied to a case study in Malaysia. The AR algorithm calculated the significance level of the multiple criteria using various fuzzy linguistic variables and membership functions. The aggregated priority ranking from different pipeline routing experts showed that the overall influence of the environmental criteria (61.4%) significantly exceeded that of other equally important criteria in the study area. These rankings were inputted into the SDSS to simulate various probable routes. Final results accurately highlighted an optimal route, which places a premium on the protection of environmental features in the subsea study area—in alignment with the preferences of majority of the experts.     

GIS-based analytic hierarchy process as a multicriteria decision analysis instrument: a review

Information and communication technology, which has been incorporated and provided in the Geographic Information System (GIS), is valuable and effective geospatial information for the decision makers in improving their decisions in planning and development. The integration of this GIS using the multicriteria decision analysis approach provides an environment to the decision makers in citing areas using land suitability analysis procedures. This review paper particularly examines the GIS-based analytic hierarchy process as a multicriteria analysis/evaluation technique in land suitability analysis by means of literature reviews and surveys.     

Spatial coherency analysis of seismic ground motions from a rock site dense array implemented during the Kefalonia 2014 aftershock sequence

The objective of studies presented in this paper is to analyse the spatial incoherency of seismic ground motions using signals from a velocimeter dense array located on a rock site, recording the aftershock sequence of the two M6 Kefalonia earthquakes that occurred in January/February 2014 (Kefalonia island, Greece). The analyses are carried out with both horizontal and vertical components of velocigrams for small separation distances of stations (<100 m). The coherencies of seismic ground motions identified from strong motion windows are compared with those identified from coda parts of signals. It is realized that there is no significant difference between the coherencies estimated from those two parts of signals. The influence of earthquake event number on the result of coherencies and the dispersions of coherencies estimated from different earthquake events are presented. Finally, coherencies estimated from the dense array are compared with several coherency models proposed and widely used in the literature. The possibility of modifying some parameters of those existing coherency models to fit with in situ coherencies are discussed and presented. Copyright © 2017 John Wiley & Sons, Ltd.     

Quantification of the amplitude variability of the ground motion in Argostoli,Greece. Variability of linear and non-linear structural response of a single degree of freedom system.

The term “spatial variability of seismic ground motions” denotes the differences in the amplitude and phase content of seismic motions. The effect of such spatial variability on the structural response is still an open issue. In-situ experiments may be helpful in order to answer the questions regarding both the quantification of the spatial variability of the ground motion within the dimensions of a structure as well as the effect on its dynamic response. The goal of the present study is to quantify the variability of the seismic ground motion accelerations in the shallow sedimentary basin of Argostoli, Greece, and thereafter to identify its effect on the linear and non-linear elasto-plastic response of a single degree of freedom system in terms of spectral displacements. Around 400 earthquakes are used, recorded by the 21-element very dense seismological array deployed in Argostoli with inter-station spacing ranging from 5 to 160 meters. The seismic motion variability, evaluated in terms of spectral accelerations, is found to be significant and to increase with inter-station distance and frequency. Thereafter, the amplitude variability in terms of spectral displacements, which is indeed the linear response of a single degree of freedom (SDOF) system with various fundamental periods, is compared with the amplitude variability of a SDOF with non-linear elasto-plastic response. The variability of the maximum top displacement of the linear single degree of freedom system is estimated to be on average 12% with larger variabilities to be observed within two narrow frequency ranges (between 1.5 and 1.7 Hz and between 3 and 4 Hz). Such high variabilities are caused by locally edge-generated diffracted surface waves. The non-linear perfectly elasto-platic structural response of the SDOF system shows that although the variability has the same trends as in the case of linear response, it is almost constantly increased by 5%.     

Recommended Sampling Intervals for Arsenic in Private Wells

Geogenic arsenic in drinking water is a worldwide problem. For private well owners, testing (e.g., private or government laboratory) is the main method to determine arsenic concentration. However, the temporal variability of arsenic concentrations is not well characterized and it is not clear how often private wells should be tested. To answer this question, three datasets, two new and one publicly available, with temporal arsenic data were utilized: 6370 private wells from New Jersey tested at least twice since 2002, 2174 wells from the USGS NAWQA database, and 391 private wells sampled 14 years apart from Bangladesh. Two arsenic drinking water standards are used for the analysis: 10 µg/L, the WHO guideline and EPA standard or maximum contaminant level (MCL) and 5 µg/L, the New Jersey MCL. A rate of change was determined for each well and these rates were used to predict the temporal change in arsenic for a range of initial arsenic concentrations below an MCL. For each MCL and initial concentration, the probability of exceeding an MCL over time was predicted. Results show that to limit a person to below a 5% chance of drinking water above an MCL, wells that are ½ an MCL and above should be tested every year and wells below ½ an MCL should be tested every 5 years. These results indicate that one test result below an MCL is inadequate to ensure long-term compliance. Future recommendations should account for temporal variability when creating drinking water standards and guidance for private well owners.     

A spatial decision support system (SDSS) for sustainable tourism planning in Johor Ramsar sites, Malaysia

The need for a sustainable approach in tourism development is very often addressed among the academia, the authorities and the stakeholders, as well as the apparent need for tools, which will guide the decision environment in evaluation and planning. This research aims to identify conservation and compatible areas for tourism development in Johor Ramsar sites, using spatial modeling in geographic information system (GIS). The study describes a methodological approach based on the integrated use of GIS and multi criteria decision evaluation (MCE) to identify nature conservation and development priorities among the wetland areas. A set of criteria was defined to evaluate wetland biodiversity conservation and development. Having defined the criteria, the next step was selecting suitable indicators and variables to measure the selected criteria. Subsequently the criteria were evaluated from conservation and tourism development point of view. These criteria were then weighted using the pair wise comparison technique of MCE and the results were integrated into GIS. Several conservation scenarios were generated so as to simulate different evaluation perspectives. The scenarios were then compared to highlight the most feasible and to propose a conservation and development strategy for the wetland areas. The generation and comparison of conservation and development scenarios highlighted the critical issues of the decision problem. This study represents an important contribution to effective decision-making because it allows one to gradually narrow down a problem.     

Mid-21st century projections in temperature extremes in the southern Colorado Rocky Mountains from regional climate models

This study analyzes mid-21st century projections of daily surface air minimum (T_min) and maximum (T_max) temperatures, by season and elevation, over the southern range of the Colorado Rocky Mountains. The projections are from four regional climate models (RCMs) that are part of the North American Regional Climate Change Assessment Program (NARCCAP). All four RCMs project 2°C or higher increases in T_min and T_max for all seasons. However, there are much greater (>3°C) increases in T_max during summer at higher elevations and in T_min during winter at lower elevations. T_max increases during summer are associated with drying conditions. The models simulate large reductions in latent heat fluxes and increases in sensible heat fluxes that are, in part, caused by decreases in precipitation and soil moisture. T_min increases during winter are found to be associated with decreases in surface snow cover, and increases in soil moisture and atmospheric water vapor. The increased moistening of the soil and atmosphere facilitates a greater diurnal retention of the daytime solar energy in the land surface and amplifies the longwave heating of the land surface at night. We hypothesize that the presence of significant surface moisture fluxes can modify the effects of snow-albedo feedback and results in greater wintertime warming at night than during the day.