Discussion of “Consequences of dike breaches and dike overflow in a bifurcating river system” by Anouk Bomers,Ralph M. J. Schielen and Suzanne J. M. H. Hulscher

In this discussion, the authors will point out that even if Bomers et al. (Nat Hazards 97:309–334, 2019) tackle an important problem, ignoring the uncertainties related to the roughness coefficients, Manning coefficients, the downstream boundary and most importantly the errors of the chosen software, HEC-RAS, are serious shortcomings of their study.

     

Landslide kinematics inferred from in situ measurements: the Cliets rock-slide (Savoie,French Alps)

This paper presents an analysis of two large rock toppling/sliding events which occurred in January 2014 and February 2019 at the Cliets unstable slope (Savoie, French Alps). To understand the mechanism involved and its control by external forcings, a multi-technique analysis approach is used combining geological observations, meteorological data analysis, topographic measurements and simple physical modeling. The pre-failure stage of the events is more particularly analyzed. No direct relationships are found between triggering factors and surface motion though a kinematics analysis highlights the transition toppling-sliding. It showed that, at first order, this transition occurred 4 years before the first failure of 2014, while it happened 2 months before the second failure of 2019. From this date, the environment is considered like a block sliding on an inclined plane. By applying a frictional model (Helmstetter et al. in Journal of Geophysical Research: Solid Earth 109(B2), 2004), we illustrated that the two events belong to an unstable velocity-weakening sliding regime. The time to failure (Voight in Science 243(4888):200–203, 1989) is forecasted with the model, and the results are consistent with the observations. They confirm that the gravitational factor is predominant over the triggering factors for the two events.

     

Co-seismic landslide detection after M 7.4 earthquake on June 23, 2020, in Oaxaca,Mexico, based on rapid mapping method using high and medium resolution synthetic aperture radar (SAR) images

Landslides are the fourth most common natural disasters in the world, with Costa Rica and southern Mexico being the most affected regions of Central America (Froude and Petley, 2018). In this work, we propose a semi-automated method to detect earthquake-triggered landslides for rapid mapping after a disaster event using open Sentinel-1 data. We used high-resolution TerraSAR-X data and very high-resolution Spot-7 images to compare and evaluate the accuracy of landslide distribution maps generated from the semi-automated method, applied to the M 7.1 earthquake on June 23, 2017, in Oaxaca, Mexico. The outcomes showed better accuracy in descending orbits due to ‘windward-leeward’ physiographic conditions, with a 50.56% quality percentage. This shows a reasonably good capacity to detect co-seismic landslides. However, the breaching factor was also high because several features, such as bare soils and agricultural areas, were incorrectly identified as co-seismic landslides. Finally, this semi-automated method establishes a basis for future improvements in methodologies applied to construct rapid mapping inventories using medium SAR scales.

     

On the seismic response of a propped r.c. diaphragm wall in a saturated clay

A series of nonlinear dynamic FE simulations have been performed to investigate the seismic performance of a flexible propped retaining wall in a saturated clay. The simulations have been carried out considering different acceleration time histories at the bedrock and two different inelastic soil models: the classical elastoplastic Modified Cam Clay model and the advanced hypoplastic model for clays proposed by Ma?ín (Int J Numer Anal Methods Geomech 29:311–336, 2005) equipped with the intergranular strains extension. The results of the simulations highlight the major role played by the choice of the constitutive model for the soil on the predicted seismic response, in terms of predicted wall displacements and structural loads. In particular, the results show that a key role is played by the model ability to correctly reproduce soil dilatancy as a function of the current stress state and loading history. This has a major impact on the inelastic volumetric deformations accumulated during the undrained seismic shearing and on the development of excess pore water pressures around the excavations.

     

Soil-gas radon anomalies in three study areas of Central-Northern Calabria (Southern Italy)

One of the most critical issues in the management of post-earthquake emergency is the prompt identification of the most damaged urban areas. Rapid detection of damage distribution is crucial for Civil Protection during the management of the first emergency phase, in order to both address assistance teams and identify priorities in planning the usability inspections, thus permitting people to go back, as safe as possible, to their houses. Generally, the estimation of building usability is performed by means of a building-by-building survey based on a form to be filled out by expert technicians (Masi et al. 2016). Different countries adopt different forms whose result in terms of usability is dependent essentially on building damage and, in some cases, vulnerability conditions of buildings. When the affected area is large, usability inspections can require a lot of time and a huge number of expert technicians. Therefore, great efforts have been made during past earthquakes in order to define rapid procedures to identify areas not severely damaged and then potentially with a low percentage of unusable buildings. In this framework, many experiences have been carried out worldwide in order to identify, in the immediate aftermath of an earthquake, the damage distribution through remote sensing approaches, possibly combined to field survey data (e.g., Saito and Spence 2004; Yamazaki et al. 2004; Chesnel et al. 2007; Zhai et al. 2016; An et al. 2016; Huang et al. 2016).

     

Acceleration of thermodynamic computations in fluid flow applications

Reservoir simulators model the highly nonlinear partial differential equations that represent flows in heterogeneous porous media. The system is made up of conservation equations for each thermodynamic species, flash equilibrium equations and some constraints. With advances in Field Development Planning (FDP) strategies, clients need to model highly complex Improved Oil Recovery processes such as gas re-injection and CO2 injection, which requires multi-component simulation models. The operating range of these simulation models is usually around the mixture critical point and this can be very difficult to simulate due to phase mislabeling and poor nonlinear convergence. We present a Machine Learning (ML) based approach that significantly accelerates such simulation models. One of the most important physical parameters required in order to simulate complex fluids in the subsurface is the critical temperature (T_crit). There are advanced iterative methods to compute the critical point such as the algorithm proposed by Heidemann and Khalil (AIChE J 26,769–799, 1980) but, because these methods are too expensive, they are usually replaced by cheaper and less accurate methods such as the Li-correlation (Reid and Sherwood 1966). In this work we use a ML workflow that is based on two interacting fully connected neural networks, one a classifier and the other a regressor, that are used to replace physical algorithms for single phase labelling and improve the convergence of the simulator. We generate real time compositional training data using a linear mixing rule between the injected and the in-situ fluid compositions that can exhibit temporal evolution. In many complicated scenarios, a physical critical temperature does not exist and the iterative sequence fails to converge. We train the classifier to identify, a-priori, if a sequence of iterations will diverge. The regressor is then trained to predict an accurate value of T_crit. A framework is developed inside the simulator based on TensorFlow that aids real time machine learning applications. The training data is generated within the simulator at the beginning of the simulation run and the ML models are trained on this data while the simulator is running. All the run-times presented in this paper include the time taken to generate the training data and train the models. Applying this ML workflow to real field gas re-injection cases suffering from severe convergence issues has resulted in a 10-fold reduction of the nonlinear iterations in the examples shown in this paper, with the overall run time reduced 2- to 10-fold, thus making complex FDP workflows several times faster. Such models are usually run many times in history matching and optimization workflows, which results in compounded computational savings. The workflow also results in more accurate prediction of the oil in place due to better single phase labelling.

     

Cost-sensitive rainfall thresholds for shallow landslides

The risk management of rainfall-induced landslides requires reliable rainfall thresholds to issue early warning alerts. The practical application of these thresholds often leads to misclassifications, either false negative or false positive, which induce costs for the society. Since missed-alarm (false negative) and false-alarm (false positive) cost may be significantly different, it is necessary to find an optimal threshold that accounts for and minimises such costs, tuning the false-alarm and missed-alarm rates. In this paper, we propose a new methodology to develop cost-sensitive rainfall thresholds, and we also analyse several factors that produce uncertainty, such as the accuracy of rainfall intensity values at landslide location, the time of occurrence, the minimum rainfall amount to define the non-triggering event, and the variability of cost scenarios. Starting from a detailed mapping of landslides that occurred during five large-scale rainfall events in the Italian Central Alps, we first developed rainfall threshold curves with a ROC-based approach by using both rain gauge and bias-adjusted weather radar data. Then, based on a reference cost scenario in which we quantified several cost items for both missed alarms and false alarms, we developed cost-sensitive rainfall threshold curves by using cost-curve approach (Drummond and Holte 2000). Finally, we studied the sensitivity of cost items. The study confirms how important is the information regarding rainfall intensity at the landslide site for the development of rainfall thresholds. Although the use of bias-corrected radar strongly improves these values, a large uncertainty related to the exact time of landslide occurrence still remains, negatively affecting the analysis. Accounting for the different missed-alarm and false-alarm misclassification costs is important because different combinations of these costs make an increase or decrease of the rainfall thresholds convenient. In our reference cost scenario, the most convenient threshold is lower than ROC-based thresholds because it seeks to minimise the number of missed alarms, whereas the missed-alarm costs are almost seven times greater than false-alarm costs. However, for different cost scenarios, threshold may vary significantly, as much as half an order of magnitude.

     

Bringing geography to the community: community-based learning and the geography classroom

Community-based learning is a pedagogical technique designed to bring students out of the classroom and into their communities. Students typically pair with local nonprofit organizations to complete work which ties into their scholarship. Faculty, students, and community members can all benefit from these partnerships, and university-community relations are strengthened by them. These connections deepen the educational experience and improve student success and retention, and build civic engagement skills that benefit the university community and the student’s home community (Strait, Turk, and Nordyke in: JR Strait, K Nordyke (eds), Pedagogy Of Civic Engagement, High-Impact Practices, and e-Service- L Earning, Stylus Publishing, Virginian, 2015; Bednarz in Journal of Geography in Higher Education 32:87–100, 2008; Mohan in Journal of Geography in Higher Education 19:129–142, 1995). Spatial citizenship, while vital to such engagement and to effective community participation, is seldom taught in traditional pedagogy (Kanwischer, Schulze, and Gryl in: Thomas Jekel, Adrijana Car, Josef Strobl, and Gerald Griesebner (eds), Spatial citizenship—dimensions of a curriculum, Wichmann Verlag, Berlin, 2012). Connecting place to pedagogy with spatially-enabled learning helps students investigate complex global concepts at a manageable local scale. Geography is an intrinsic part of scholarship, to varying degrees, and spatial thinking can bring added dimension and value to the educational process (Vogler in: Thomas Jekel, Adrijana Car, Josef Strobl, and Gerald Griesebner (eds), Wichmann Verlag, Berlin, 2012). The intersectionalities which exist within the community, when examined with a spatial lens, are the core of community geography, a praxis-focused method of engaged scholarship (Shannon in Progress in Human Geography, 10.1177/0309132520961468, 2020). Community-based learning is not clearly defined, yet some established models exist. Place-based learning communities move cohorts of students through a curriculum that is centered on local community issues, with the community as both laboratory and lens, and building place attachment (Schweizer, Davis, and Thompson in Environmental Communication 7:42–62, 2013). Service learning, while less clearly defined, typically involves direct work with community organizations, identifying, investigating, and contributing to solutions for local issues (Strait, Turk, and Nordyke in: JR Strait, K Nordyke (eds), Pedagogy Of Civic Engagement, High-Impact Practices, and e-Service- L Earning, Stylus Publishing, Virginian, 2015; Cal Corps Public Service in Designing Community-Based Courses, 1–45, 2015). Built around the concept of place, the added dimension of improved spatial citizenship benefits both community and students. This paper will review community-based learning as practiced through upper-division service learning courses in geography at two universities, and the development of a new course, as methods of engagement with local communities through a spatial lens.

     

Seismic precursors to a 2017 Nuugaatsiaq,Greenland, earthquake–landslide–tsunami event

High-frequency (5–20 Hz) seismic signals precursory to and embedded within the June 17, 2017 M_L?=?4 earthquake–landslide event are analyzed. This event in western Greenland generated a tsunami in Karrat fjord inundating Nuugaatsiaq village 32 km distant. Spectrogram and wavelet analyses of seismic data from the Greenland Ice Sheet Monitoring Network (GLISN) corroborate observations of seismic precursors at Nuugaatsiaq reported by Poli (Geophys Res Lett 44:8832–8836, 2017) and Caplan-Auerbach (in: AGU fall meeting abstracts, 2017) and reveal additional high-frequency arrivals being generated after the apparent initiation of fault rupture. New observations of seismic precursors 181 km from the Event at Upernavik, Greenland are correlated with those seen at Nuugaatsiaq. Wavelet analysis presents?>?100 significant energy peaks accelerating up to and into the earthquake–landslide event. The precursor events show a distinct, power law distribution, characterized by b values of ~?2.4. Results are compared and contrasted with small precursors observed in the studies of a natural chalk cliff landslide at Mesnil-Val, Haute Normandie, France. The earthquake–landslide appears to have been initiated by seismic precursors located at the fault scarp, leading to a small seismic foreshock and small landslide initiation, followed by a larger earthquake at the fault scarp, precipitating the primary landslide into the Karrat Fjord, which caused the subsequent tsunami.

     

Influence of frozen conditions on the oxygen diffusion coefficient in unsaturated porous materials

The efficiency of soil covers used as oxygen barriers to control the generation of acid drainage from sulfidic mine wastes can be evaluated in terms of the diffusive oxygen flux reaching the underlying wastes. Oxygen diffusion has been extensively investigated over the last few decades for unsaturated porous materials that are not frozen. However, little attention has been paid to materials that are fully or partially frozen, and thus, the diffusion of oxygen through soil covers during the winter freezing period has been generally neglected. This paper presents a laboratory method developed to evaluate the effective diffusion coefficient of oxygen (D_e) in frozen, inert materials. The method is a modified version of the conventional double-chamber cell in which the temperature and unfrozen volumetric water content of the sample are measured in addition to the more commonly monitored change in oxygen concentration. Several tests were conducted on non-reactive materials: that is, a sand at multiple degrees of saturation (S_r?=?20, 30, 39, and 42%), a silt (S_r?=?47%), and a mixture of the two (S_r?=?90%). Experimental data were interpreted using the POLLUTE code. Values of D_e for frozen materials were slightly lower than those obtained at ambient laboratory temperatures. In addition to the development of an empirical method for determining D_e, a preliminary model based on the model proposed by Aachib et al. (Water Air Soil Pollut 156:163–193, 2004) was created for the prediction of D_e in frozen materials by defining the involved parameters as temperature-dependent. The results indicate that predicated values of D_e are slightly higher than experimental values, suggesting that there remains room for improvement in the model.

     

Punctuated,long-lived emplacement history of the Renard 2 kimberlite,Canada, revealed by new high precision U-Pb groundmass perovskite dating

Kimberlites are rare volatile-rich ultramafic magmas thought to erupt in short periods of time (<1 Myr) but there is a growing body of evidence that the emplacement history of a kimberlite can be significantly more protracted. In this study we report a detailed geochronology investigation of a single kimberlite pipe from the Renard cluster in north-central Québec. Ten new high precision ID-TIMS (isotope dilution – thermal ionization mass spectrometry) U-Pb groundmass perovskite dates from the main pipe-infilling kimberlites and several small hypabyssal kimberlites from the Renard 2 pipe indicate kimberlite magmatism lasted at least ~20 Myr. Two samples of the main pipe-infilling kimberlites yield identical weighted mean ²⁰⁶Pb/²³⁸U perovskite dates with a composite date of 643.8 ± 1.0 Myr, interpreted to be the best estimate for main pipe emplacement. In contrast, six hypabyssal kimberlite samples yielded a range of weighted mean ²⁰⁶Pb/²³⁸U perovskite dates between ~652-632 Myr. Multiple dates determined from these early-, syn- and late-stage small hypabyssal kimberlites in the Renard 2 pipe demonstrate this rock type (commonly used to date kimberlites) help to constrain the duration of kimberlite intrusion history within a pipe but do not necessarily reliably record the emplacement age of the main diatreme in the Renard cluster. Our results provide the first robust geochronological data on a single kimberlite that confirms the field relationships initially observed by Wagner (1914) and Clement (1982); the presence of antecedent (diatreme precursor) intrusions, contemporaneous (syn-diatreme) intrusions, and consequent (post-diatreme) cross-cutting intrusions. The results of this detailed U-Pb geochronology study indicate a single kimberlite pipe can record millions of years of magmatism, much longer than previously thought from the classical viewpoint of a rapid and short-duration emplacement history.

     

Experimental investigation of microstructural changes in soils eroded by suffusion using X-ray tomography

Internal erosion is a complex phenomenon which represents one of the main risks to the safety of earthen hydraulic structures such as embankment dams, dikes or levees. Its occurrence may cause instability and failure of these structures with consequences that can be dramatic. The specific mode of erosion by suffusion is the one characterized by seepage flow-induced erosion, and the subsequent migration of the finest soil particles through the surrounding soil matrix mostly constituted of large grains. Such a phenomenon can lead to a modification of the initial microstructure and, hence, to a change in the physical, hydraulic and mechanical properties of the soil. A direct comparison of the mechanical behaviour of soil before and after erosion is often used to investigate the impact of internal erosion on soil strength (shear strength at peak and critical state) using triaxial tests. However, the obtained results are somehow contradictory, as for instance in Chang’s study (Chang and Zhang in Geotech Test J 34(6):579–589, 2011), where it is concluded that the drained strength of eroded soil decreases compared to non-eroded soil, while both Xiao and Shwiyhat (Geotech Test J 35(6):890–900, 2012) and Ke and Takahashi (Geotech Test J 37(2):347–364, 2014) have come to the opposite conclusion. A plausible explanation of these contradictions might be attributed to the rather heterogeneous nature of the suffusion process and to the way the coarse and fine grains are rearranged afterwards leading to a heterogeneous soil structure, a point that, for now, is not taken into account, nor even mentioned, in the existing analyses. In the present study, X-ray computed tomography (X-ray CT) is used to follow the microstructure evolution of a granular soil during a suffusion test, and, therefore, to capture the induced microstructural changes. The images obtained from X-ray CT reveal indeed that fine particles erosion is obviously not homogeneous, highlighting the existence of preferential flow paths that lead to a heterogeneous sample in terms of fine particles, void ratio and inter-granular void ratio distribution.

     

A two-surface plasticity model for cyclic behavior of saturated clay

This paper presents a two-surface plasticity model for describing some important features of saturated clay under cyclic loading conditions, such as closed hysteresis loops, cyclic shakedown and degradation, and different stress–strain relations for two-way loading. The model, namely ACC-2-C, is based on the elastoplastic model ACC-2 (an adapted Modified Cam Clay model with two yield surfaces) developed by Hong et al. (Acta Geotech 11(4):871–885, 2015). The small-strain nonlinearity concept is adopted to achieve the nonlinear characteristics of clay during unloading–loading stage. The new hardening law related to accumulated deviatoric plastic strain is proposed for the inner surface to describe the cyclic shakedown and degradation. Following the advantages of the ACC-2 model, the constitutive equations are simply formulated based on the consistency condition for the inner yield surface. The model is conveniently implemented in a finite element code using a stress integration scheme similar to the Modified Cam Clay model. The simulation results are highly consistent with experimental data from drained and undrained isotropic cyclic triaxial tests in normally consolidated saturated clay under both one-way and two-way loadings.

     

Four loss estimates for the Gorkha M7.8 earthquake,April 25, 2015, before and after it occurred

The number of fatalities in the Gorkha M7.8 earthquake of April 25, 2015, has been estimated at four different times as follows. In March 2005, the fatality estimate in this journal was 21,000–42,000 with an assumed magnitude of 8.1 (Wyss in Nat Hazard 34:305–314, 2005). Within hours after this earthquake, the estimated number of fatalities by QLARM was 2000–10,000 using a point source model and M7.9. Four hours later, the estimate was 20,000–100,000, based on a first approximation line source model and assuming children were in school. Children out of school, as this was a weekend day, reduced the fatalities by approximately a factor of two, but was not taken into account for the calculation. The final line source estimates based on M7.8 and M7.9 calculates 800–9300 and 1100–11,200 fatalities, respectively. The official count is about 10,000 fatalities. These estimates were performed using QLARM, a computer tool and world data set on the distribution of people in settlements and containing a model of the buildings present. It is argued here that the loss estimate 10 years before the event being within a factor of 2.1 of the eventual loss count is useful for mitigation planning. With varying quality of information on the source and the attenuation, the estimates of fatalities shortly after the earthquake are accurate enough to be useful for first responders. With full knowledge of the rupture properties and the regional attenuation of seismic waves, the numbers of human losses are estimated correctly.

     

Assessment of groundwater quality with special emphasis on nitrate contamination in parts of Gautam Budh Nagar district,Uttar Pradesh,India

Progressive developments in industrial and agricultural activities are causing a critical stress on groundwater quality in developing countries. The objective of this paper is to assess and evaluate the contamination level of groundwater caused by leachate in 11 villages of the Gautam Budh Nagar district in Uttar Pradesh, India. We systematically sampled 22 groundwater samples and 13 leachate samples to ascertain the source of pollution on groundwater quality. The standard analytical methods given by the American Public Health Association (APHA) (Standard methods for examination of water and wastewater, 23rd edn. APHA, AWWA, WPCF, Washington, 2017) were used for quantitative estimation of hydrochemical parameters of collected samples. The results of the analysis of groundwater samples indicate that pH values range from 7.31 to 8.97. The mean magnesium concentration in groundwater samples is 58.93 ± 21.44 mg/L. Out of the groundwater samples taken, approximately 41% and 73% of samples analysis results have been found beyond the acceptable limit with respect to the parameters of turbidity and total dissolved solids, respectively, according to the Bureau of Indian Standards (Indian standard specification for drinking water (IS:10500). BIS, Manak Bhawan, New Delhi, 2012) for drinking water. Around 95.4% of groundwater samples and 92.3% of leachate samples have high nitrate concentrations above the standard limit of BIS (45 mg/L), respectively. The Piper plot shows that 50% of the samples belong to the Ca²⁺–Mg²⁺–HCO₃⁻ type. Ternary and Durov’s diagrams indicate that the mean concentrations of ions are in the order of Na⁺ > Mg²⁺ > Ca²⁺ > K⁺ (for cations) and HCO₃⁻> NO₃⁻ > Cl⁻ > SO₄²⁻ > CO₃²⁻ > F⁻ (for anions) in groundwater of the study area. The spatial variation of the hydrochemical parameters shows that groundwater is heavily contaminated with respect to nitrate. Analytical results indicate that the groundwater of villages Achheja, Bisrakh road, Dujana, Badalpur and Sadopur is not suitable for drinking.

     

Getting Canadians prepared for natural disasters: a multi-method analysis of risk perception,behaviors, and the social environment

As part of our broader research agenda on the psychology of risk communication and of risk management, we use a socio-ecological approach, inspired by Bronfenbrenner (Am Psychol 32:513–531, 1977. https://doi.org/10.1037/0003-066x.32.7.513), to better understand how Canadians perceive and prepare for risks originating from natural disasters. In this article, we present three empirical mixed-method studies as layers of analysis—a national survey, a social-spatial multi-level analysis, and a series of qualitative interviews—to bring a better understanding of how to engage Canadians in disaster preparedness and risk management. From our data, we examined how individuals perceived and understood natural disaster risks in Canada and how these fit in their social and life contexts. Given the increasingly diverse Canadian population, we used a cultural lens to contrast immigrants to Canadian-born individuals. After introducing the conceptual background and presenting our empirical studies, we conclude with a discussion on the implications for risk communication and management for natural disasters. Our findings suggest that Canadians could benefit from culturally targeted disaster risk reduction strategies that engage individuals–communities–government at all levels and are more attuned to the realities and specificities of life stressors.

     

Statistical approaches to the discrimination of mantle- and crust-derived low-Cr garnets using major and trace element data

Diamond exploration focuses on geochemical analysis of indicator minerals that are more abundant than diamond itself. Among such indicators, low-Cr (Cr₂O₃ < 1 wt%) garnets from mantle eclogites are problematic since they overlap compositionally with many lower-crust-derived garnets also transported by kimberlite. Misclassification of these garnets may create “false positive” mantle signatures and possible misdirection of exploration efforts. Statistical solutions using major elements in low-Cr garnet (Hardman et al. in J Geochem Explor 186:24–35, 2018) provide improved error rates for the discrimination of low-Cr crustal and mantle garnets recovered from kimberlite. In this study we analysed a large suite of garnets (n = 571) from both crustal and mantle settings, already characterised for major elements, for a wide range of trace elements by laser ablation inductively-coupled plasma mass spectrometry and use these new data along with literature data (n = 169) to evaluate the effectiveness of adding trace elements to garnet-based diamond exploration programs. A new garnet classification scheme, initially using a major-element based filter, uses garnet Sr contents and Eu anomalies to help identify low-Cr garnets that are misclassified using major element methods. Combined with existing methods, our new trace element classifiers offer improvement in classification error rates for low-Cr, crustal and mantle garnets to as low as 4.7% for calibration data.

     

Diamond exploration and regional prospectivity of Western Australia

Pre-1.6 Ga rocks comprise around 45% of the onshore area of Western Australia (WA), constituting the West Australian Craton (WAC) (including the Archean Yilgarn and Pilbara Cratons) and the western part of the North Australian Craton (NAC). These areas provide the conditions suitable for diamond formation at depth, and numerous diamondiferous lamproite and kimberlite fields are known. As emplacement ages span close to 2500 Ma, there are significant opportunities for diamond-affinity rocks being present near-surface in much of the State, including amongst Phanerozoic rocks. WA’s size, terrain, infrastructure and climate, mean that many areas remain underexplored. However, continuous diamond exploration since the 1970s has resulted in abundant data. In order to advance future exploration, a comprehensive database of results of diamond exploration sampling (Geological Survey of Western Australia 2018) has been assessed. The Yilgarn and Pilbara Cratons have spinel indicators almost exclusively dominated by chromite (>90% of grains), whereas (Mg,Fe,Ti)-bearing Al-chromites account for more of the indicator spinels in the NAC, up to 50% of grains at the Northern Territory (NT) border. Increasing dominance of Al in chromites is interpreted as a sign of weathering or a shallower source than Al-depleted Mg-chromites. Garnet compositions across the State also correlate with geological subdivisions, with lherzolitic garnets showing more prospective compositions (Ca-depleted) in WAC samples compared to the NAC. WAC samples also show a much broader scatter into strongly diamond-prospective G10 and G10D compositions. Ilmenites from the NAC show Mg-enriched compositions (consistent with kimberlites), over and above those present in NT data. However, ilmenites from the WAC again show the most diamond-prospective trends. Numerous indicator mineral concentrations throughout the State have unknown sources. Due in part to the presence of diamondiferous lamproites, it is cautioned that some accepted indicator mineral criteria do not apply in parts of WA. For example Ca-depleted garnets, Mg-depleted ilmenites and Cr-depleted and Al-absent clinopyroxenes are all sometimes associated with strongly diamondiferous localities. Quantitative prospectivity analysis has also been carried out based on the extent and results of sampling, age of surface rocks relative to ages of diamond-prospective rocks, and the underlying mantle structure. Results show that locations within the NAC and with proximity to WA’s diamond mines score well. However, results point to parts of the WAC being more prospective, consistent with mineral chemical data. Most notable are the Hamersley Basin, Eastern Goldfields Superterrane and the Goodin Inlier of the Yilgarn Craton. Despite prolific diamond exploration, WA is considerably underexplored and the ageing Argyle mine and recent closure of operations at Ellendale warrant a re-evaluation of diamond potential. Results of mineral chemistry and prospectivity analysis make a compelling case for renewed exploration.

     

Insights into the petrogenesis of the West Kimberley lamproites from trace elements in olivine

The Miocene lamproites of the West Kimberley region, Western Australia include olivine-leucite lamproites (≤10 wt% MgO) containing olivine and leucite microphenocrysts, and diamondiferous olivine lamproites (20–30 wt% MgO) containing olivine phenocrysts and larger (1–10 mm) olivine as mantle xenocrysts and dunite micro-xenoliths. Olivine phenocrysts and thin (<100 μm) magmatic rims define trends of decreasing Cr and Ni, and increasing Ca and Mn, with decreasing olivine Mg#, consistent with fractional crystallisation of olivine (and minor chromite). Many phenocrysts are zoned, and those with cores of similar Mg# and trace element abundances to the mantle xenocrysts may be xenocrysts overgrown by later olivine crystallised from the lamproite magma. Magmatic olivines Mg#_91–92 are estimated to have been in equilibrium with olivine lamproite magma(s) containing ~22–24 wt% MgO. The xenocrystic mantle olivines Mg_90–92.5 in the olivine lamproites are inferred from trace element abundances to be mostly derived from garnet peridotite with equilibration temperatures estimated from the Al-in-olivine thermometer (Bussweiler et al. 2017) to be ~1000–1270 °C at depths of 115–190 km. Olivines from the deeper lithosphere are less depleted (lower Mg#, higher Na, Al, P, Ti, Zr etc) than those at shallower depths, a feature suggested to reflect the combined effects of metasomatic re-enrichment of the craton roots (Ti, Fe, Zr etc) and increasing temperature with depth of origin (Na, Al, Ca). The West Kimberley lamproite olivines are not enriched in Li, as might be expected if their source regions contained continental sedimentary material as has been previously inferred from lamproite large-ion-lithophile trace elements, and Sr and Pb isotopes.