Development of a GIS-based catastrophe theory model (modified DRASTIC model) for groundwater vulnerability assessment

This study developed a new paradigm for groundwater vulnerability assessment by modifying the standard DRASTIC index (DI) model based on catastrophe theory. The developed paradigm was called the catastrophe theory-based DI (CDI) model. The proposed model was applied to assess groundwater vulnerability to pollution index (GVPI) in Perak Province, Malaysia. The area vulnerability index was modeled by considering the DRASTIC multiple vulnerability causative factors (VCFs) obtained from different data sources. The weights and ranking of the VCFs were computed by using the inner fuzzy membership mechanism of the CDI model. The estimated vulnerability index values of the CDI model were processed in a geographic information system (GIS) environment to produce a catastrophe theory–DRASTIC groundwater vulnerability to pollution index (CDGVPI) map, which demarcated the area into five vulnerability zones. The produced CDGVPI map was validated by applying the water quality status–vulnerability zone relationship (WVR) approach and the relative operating characteristic (ROC) curve method. The performance of the developed CDI model was compared with that of the standard DI model. The validation results of the WVR approach exhibits 89.29% prediction accuracy for the CDI model compared with 75% for the DI model. Meanwhile, the ROC validation results for the CDI and DI models are 88.8% and 78%, respectively. The GIS-based CDI model demonstrated better performance than the DI model. The GVPI maps produced in this study can be used for precise decision making process in environmental planning and groundwater management.     

Mineralogy and thermal properties of V-type Asteroid 956 Elisa: Evidence for diogenitic material from the Spitzer IRS (5-35 μm) spectrum

We present the thermal infrared (5-35 μm) spectrum of 956 Elisa as measured by the Spitzer Infrared Spectrograph (“IRS”; Houck, J.R. et al. [2004]. Astrophys. J. Suppl. 154, 18-24) together with new groundbased lightcurve data and near-IR spectra. From the visible lightcurve photometry, we determine a rotation period of 16.494 ± 0.001 h, identify the rotational phase of the Spitzer observations, and estimate the visible absolute magnitude (H_V) at that rotational phase to be 12.58 ± 0.04. From radiometric analysis of the thermal flux spectrum, we find that at the time of observation 956 Elisa had a projected radius of 5.3 ± 0.4 km with a visible albedo p_V = 0.142 ± 0.022, significantly lower than that of the prototype V-type asteroid, 4 Vesta. (This corresponds to a radius of 5.2 ± 0.4 km at lightcurve mean.) Analysis with the standard thermal model (STM) results in a sub-solar temperature of 292.3 ±  2.8 K and beaming parameter η = 1.16 ± 0.05. Thermophysical modeling places a lower limit of on the thermal inertia of the asteroid’s surface layer (if the surface is very smooth) but more likely values fall between 30 and depending on the sense of rotation.The emissivity spectrum, calculated by dividing the measured thermal flux spectrum by the modeled thermal continuum, exhibits mineralogically interpretable spectral features within the 9-12 μm reststrahlen band, the 15-16.5 μm Si-O-Si stretching region, and the 16-25 μm reststrahlen region that are consistent with pyroxene of diogenitic composition: extant diogenitic pyroxenes fall within the narrow compositional range Wo_2±1En_74±2Fs_24±1. Spectral deconvolution of the 9-12 μm reststrahlen features indicates that up to ≈20% olivine may also be present, suggesting an olivine-diogenite-like mineralogy. The mid-IR spectrum is inconsistent with non-cumulate eucrite as the major component on the surface of 956 Elisa, although cumulate eucrite material may be present at abundances lower than that of the diogenite component.Analysis of new near-IR spectra of 956 Elisa with the Modified Gaussian Model (MGM; Sunshine, J.M., Pieters, C.M., Pratt, S.F. [1990]. J. Geophys. Res. 95 (May), 6955-6966) results in two pyroxene compositions: 75% magnesian low-Ca pyroxene and 25% high-Ca pyroxene. High-Ca pyroxene is not evident in the mid-IR data, but may belong to a component that is underrepresented in the mid-IR spectrum either because of its spatial distribution on the asteroid or because of its particle size. High-Ca pyroxenes that occur as exsolution lamellae may also be more evident spectrally in the NIR than in the mid-IR. In any case, we find that the mid-IR spectrum of 956 Elisa is dominated by emission from material of diogenite-like composition, which has very rarely been observed among asteroids.     

Efficient risk assessment of lifeline networks under spatially correlated ground motions using selective recursive decomposition algorithm

For effective hazard mitigation planning and prompt-but-prudent post-disaster responses, it is essential to evaluate the reliability of infrastructure networks accurately and efficiently. A nonsimulation-based algorithm, termed as a recursive decomposition algorithm (RDA), was recently proposed to identify disjoint cut sets and link sets and to compute the network reliability. This paper introduces a ‘selective’ RDA, which preferentially identifies critical disjoint cut sets and link sets to calculate the probabilities of network disconnection events with a significantly reduced number of identified sets. To this end, the original RDA is improved by replacing the shortest path algorithm with an algorithm that identifies the most reliable path, and by using a graph decomposition scheme based on the probabilities associated with the subgraphs. The critical sets identified by the algorithm are also used to compute conditional probability-based importance measures that quantify the relative importance of network components by their contributions to network disconnection events. This paper also introduces a risk assessment framework for lifeline networks based on the use of the selective RDA, which can consider both interevent and intraevent uncertainties of spatially correlated ground motions. The risk assessment framework and the selective RDA are demonstrated by a hypothetical network example, and the gas and water transmission networks of Shelby County in Tennessee, USA. The examples show that the proposed framework and the selective RDA greatly improve efficiency of risk assessment of complex lifeline networks, which are characterized by a large number of components, complex network topology, and statistical dependence between component failures. Copyright © 2012 John Wiley & Sons, Ltd.     

Stability of Kerogen Classification with Regard to Image Segmentation

This paper investigates the stability of an automatic system for classifying kerogen material from images of sieved rock samples. The system comprises four stages: image acquisition, background removal, segmentation, and classification of the segmented kerogen pieces as either inertinite or vitrinite. Depending upon a segmentation parameter d, called “overlap”, touching pieces of kerogen may be split differently. The aim of this study is to establish how robust the classification result is to variations of the segmentation parameter. There are two issues that pose difficulties in carrying out an experiment. First, even a trained professional may be uncertain when distinguishing between isolated pieces of inertinite and vitrinite, extracted from transmitted-light microscope images. Second, because manual labelling of large amount of data for training the system is an arduous task, we acquired the true labels (ground truth) only for the pieces obtained at overlap d=0.5. To construct ground truth for various values of d we propose here label-inheritance trees. With thus estimated ground truth, an experiment was carried out to evaluate the robustness of the system to changes in the segmentation through varying the overlap value d. The average system accuracy across values of d spanning the range from 0 to 1 was 86.5%, which is only slightly lower than the accuracy of the system at the design value of d=0.5 (89.07%).     

A COMPARISON OF HYDROLOGY AND VEGETATION BETWEEN A CHANNELIZED STREAM AND A NONCHANNELIZED STREAM IN WESTERN TENNESSEE

The purpose of this study was to provide baseline data on floodplain forest structure, composition, and function that would be needed to predict and monitor the consequences of a proposed stream restoration project. This project would involve the “dechannelization” of Stokes Creek, a stream in western Tennessee that was channelized and leveed in the first half of the 1900s. To this end, we collected data on surface hydrology, soil redox potential (Eh), and the structure and composition of the floodplain vegetation of Stokes Creek. To place our findings into a regional context, we also collected comparable vegetation data from plots located along a nonchannelized stream reach of the Wolf River near Moscow, Tennessee. While hydrologic fluctuations of floodplain sites were synchronous with river dynamics for the Wolf River, the hydrology of floodplain sites at Stokes Creek was constrained by the influence of beaver dams, backflooding, and ponding of overland flow behind levees. Consequently, composition of the forest overstory, understory, and herbaceous strata was significantly different between the two sites. For example, Stokes Creek had a noticeable lack of cypress and tupelo sites, and a greater abundance of red maple. Analyses of size-class structure and woody debris quantity reinforced the existing differences between the more natural and human-impacted systems. While the current hydrology apparently has a negative affect on bottomland hardwoods, scattered regeneration stems and soil redox measurements indicate that a dechannelization effort that yielded lower water tables in the Stokes Creek floodplain potentially could increase bottomland hardwood establishment. [Key words: channelization, western Tennessee, bottomland hardwoods, hydrology.]     

Tropical forcing of Australian extreme low minimum temperatures in September 2019

We explore the causes and predictability of extreme low minimum temperatures (T_min) that occurred across northern and eastern Australia in September 2019. Historically, reduced T_min is related to the occurrence of a positive Indian Ocean Dipole (IOD) and central Pacific El Niño. Positive IOD events tend to locate an anomalous anticyclone over the Great Australian Bight, therefore inducing cold advection across eastern Australia. Positive IOD and central Pacific El Niño also reduce cloud cover over northern and eastern Australia, thus enhancing radiative cooling at night-time. During September 2019, the IOD and central Pacific El Niño were strongly positive, and so the observed T_min anomalies are well reconstructed based on their historical relationships with the IOD and central Pacific El Niño. This implies that September 2019 T_min anomalies should have been predictable at least 1–2 months in advance. However, even at zero lead time the Bureau of Metereorolgy ACCESS-S1 seasonal prediction model failed to predict the anomalous anticyclone in the Bight and the cold anomalies in the east. Analysis of hindcasts for 1990–2012 indicates that the model's teleconnections from the IOD are systematically weaker than the observed, which likely stems from mean state biases in sea surface temperature and rainfall in the tropical Indian and western Pacific Oceans. Together with this weak IOD teleconnection, forecasts for earlier-than-observed onset of the negative Southern Annular Mode following the strong polar stratospheric warming that occurred in late August 2019 may have contributed to the T_min forecast bust over Australia for September 2019.

     

Canary in a coal mine: perceptions of climate change risks and response options among Canadian mine operations

A survey documenting how climate change is perceived and responded to by Canadian mine operations was administered to a random sample of practitioners working at mine sites across Canada. Key findings include: (1) Mines are sensitive to climatic hazards; (2) There is concern about climate change among mine practitioners, but the majority have not yet noticed climate change to be affecting operations; (3) Future climate change is expected to have negative impacts for mine operations; (4) Mines are responding to climate change mainly through efforts to reduce greenhouse gas emissions but also through adaptation, although to a lesser degree; and (5) Knowledge of future climate change projections and impacts is limited, potentially constraining understanding of the nature of climate change risks. The survey compliments previous work documenting perceptions among upper level management on climate change in the Canadian mining industry. The results from both surveys are largely consistent, establishing that the mining sector perceives climate change as an emerging risk and is developing response options, but needs to invest more time and resources for adaptation to what are inevitable changes in climate. The results support the need for targeted in-depth research to assess the vulnerability of mining to climate change and to evaluate response options.     

High-resolution subtropical summer precipitation derived from dynamical downscaling of the NCEP/DOE reanalysis: how much small-scale information is added by a regional model?

This study assesses the regional-scale summer precipitation produced by the dynamical downscaling of analyzed large-scale fields. The main goal of this study is to investigate how much the regional model adds smaller scale precipitation information that the large-scale fields do not resolve. The modeling region for this study covers the southeastern United States (Florida, Georgia, Alabama, South Carolina, and North Carolina) where the summer climate is subtropical in nature, with a heavy influence of regional-scale convection. The coarse resolution (2.5° latitude/longitude) large-scale atmospheric variables from the National Center for Environmental Prediction (NCEP)/DOE reanalysis (R2) are downscaled using the NCEP/Environmental Climate Prediction Center regional spectral model (RSM) to produce precipitation at 20?km resolution for 16 summer seasons (1990?C2005). The RSM produces realistic details in the regional summer precipitation at 20?km resolution. Compared to R2, the RSM-produced monthly precipitation shows better agreement with observations. There is a reduced wet bias and a more realistic spatial pattern of the precipitation climatology compared with the interpolated R2 values. The root mean square errors of the monthly R2 precipitation are reduced over 93% (1,697) of all the grid points in the five states (1,821). The temporal correlation also improves over 92% (1,675) of all grid points such that the domain-averaged correlation increases from 0.38 (R2) to 0.55 (RSM). The RSM accurately reproduces the first two observed eigenmodes, compared with the R2 product for which the second mode is not properly reproduced. The spatial patterns for wet versus dry summer years are also successfully simulated in RSM. For shorter time scales, the RSM resolves heavy rainfall events and their frequency better than R2. Correlation and categorical classification (above/near/below average) for the monthly frequency of heavy precipitation days is also significantly improved by the RSM.     

Resilience assessment on coastline changes and urban settlements: A case study in Seribu Islands, Indonesia

The sustainable development in the ocean and costal areas has been an issue for the archipelago nation. Since two decades ago, some archipelago nations have attempted to implement the concept of both scientifically and politically sounding sustainability. The vulnerability assessment is one of the methods that are being used to measure the ocean and coastal sustainability in order to have better evaluation and redesign of the land development as well as policy making. Most of the vulnerability assessment has been conducted based on pressures, damages and changes that involve in the region. A common understanding of the vulnerability assessment is that there are three aspects to be considered: hazards, resilience and damages. These three aspects must be well defined at first in order to have better indicators or sub-indices for the vulnerability index. There are several issues and factors that should be considered before performing the vulnerability assessment. Firstly, each country has different coastal characteristics due to a different geologic process. Secondly, the three aspects of the vulnerability (i.e. hazards, resilience and damages) are impacting on each country at a different scale. Thirdly, the vulnerability of a small island region is different from that of a large island region. Finally, policies and regulations vary in each country.From the data analysis results, it is found that the urban settlement in Seribu Islands is one of the resilient factors in addition to the geological and geomorphological conditions. The resilience factors in Seribu Islands are classified into four categories: 1) settlements area, 2) population density, 3) hard infrastructure such as airfields, ports and roads, 4) geological process such as abrasion and erosion. Based on the island characteristics of Seribu Islands, a unique vulnerability index that fits to this locality is developed. It is shown that the vulnerability index developed in this study can measure the resilience of Seribu Islands. In addition to the aforementioned resilience factors, the unique geographical condition and the geological stability in Seribu Islands made the outer islands become a barrier from oceanographic conditions and made the inner islands protected. However, the population growth made significant changes in terms of ecology, water, sanitation and pollution within the region.