Ore and Skarn Mineralogy of the Yamato Mine,Yamaguchi Prefecture,Japan, with Emphasis on Silver‐, Bismuth‐, Cobalt‐, and Tin‐bearing Sulfides

Assemblages and chemical compositions of ore minerals from the Yamato mine, Yamaguchi Prefecture, Japan, were investigated in detail to clarify its characteristics as a skarn deposit. Special attention was paid to silver‐, bismuth‐, cobalt‐, and tin‐bearing sulfide minerals and native gold at the mine, which are described here for the first time. Samples of arsenopyrite‐dominant massive ore, and garnet‐rich, clinopyroxene‐garnet‐rich, and wollastonite‐bearing skarn ores were collected from the mine dump. Arsenopyrite is the most abundant ore mineral (>80 vol.%) in the massive ore, in association with both As‐poor/free and As‐bearing pyrite. The major ore minerals in the skarn specimens are pyrite, pyrrhotite, arsenopyrite, chalcopyrite, galena, and sphalerite, along with minor argentite, Ag‐Pb‐Bi sulfate, matildite, bismuthinite, native bismuth, molybdenite, scheelite, stannite, stannoidite, cassiterite, cobaltite, gersdorffite, and Co‐rich violarite. In addition, native gold is observed in the interstices of gangue minerals. Based on the mineral assemblages and textures of the specimens examined, the major ore minerals formed in the early stage of mineralization, and the Bi‐, Ag‐, Co‐, Ni‐, As‐ and Sn‐mineralization occurred in the middle stage. Native gold was deposited in the late stage. The estimated formation temperature of the middle mineralization stage was 312±5 °C, according to iron and zinc partitioning between stannite and coexisting sphalerite. The mineralogical properties and mineralization process of the Yamato mine are consistent with those of common skarn‐ and vein‐type ore deposits associated with ilmenite‐series granitoids in the San‐yo and San‐in districts.     

Metamorphic and cooling history of the Shimanto accretionary complex,Kyushu, Southwest Japan: Implications for the timing of out‐of‐sequence thrusting

Illite crystallinity, K–Ar dating of illite, and fission‐track dating of zircon are analyzed in the hanging wall (Sampodake unit) and footwall (Mikado unit) of a seismogenic out‐of‐sequence thrust (Nobeoka thrust) within the Shimanto accretionary complex of central Kyushu, southwest Japan. The obtained metamorphic temperatures, and timing of metamorphism and cooling, reveal the tectono‐metamorphic evolution of the complex, and related development of the Nobeoka thrust. Illite crystallinity data indicate that the Late Cretaceous Sampodake unit was metamorphosed at temperatures of around 300 to 310°C, while the Middle Eocene Mikado unit was metamorphosed at 260 to 300°C. Illite K–Ar ages and zircon fission‐track ages constrain the timing of metamorphism of the Sampodake unit to the early Middle Eocene (46 to 50 Ma, mean = 48 Ma). Metamorphism of the Mikado unit occurred no earlier than 40 Ma, which is the youngest depositional age of the unit. The Nobeoka thrust is inferred to have been active during about 40 to 48 Ma, as the Sampodake unit started its post metamorphic cooling after 48 Ma and was thrust over the Mikado unit at about 40 Ma along the Nobeoka thrust. These results indicate that the Nobeoka thrust was active for more than 10 million years.     

The use of caesium‐137 to estimate agricultural erosion on steep slopes in a tropical watershed

The estimation of erosion and sediment delivery rates in tropical mountain watersheds is difficult and most of the methods widely used for estimating soil erosion over large areas have serious limitations. The ¹³⁷Cs approach has potential for quantifying soil erosion because it can provide retrospective estimates of long‐term (since 1963) net sediment redistribution relatively quickly. Despite its great potential, ¹³⁷Cs has not yet been used in an extensive, reconnaissance level survey of erosion in complex tropical mountain environments. The objective of this study was to examine the applicability of the ¹³⁷Cs method to estimate erosion on steep tropical agricultural lands (23 to 80% slopes) in the Nizao watershed, a humid, tropical mountain area of the Dominican Republic. In this study we (i) examine the variation of ¹³⁷Cs in ten reference sites—eight coffee groves and two forested sites—and (ii) estimate erosion from 14 cultivated fields. The soil pool of ¹³⁷Cs ranged from to 150 to 192 mBq cm⁻² on reference sites with minimal erosion. Variability among reference sites was less than expected for such complex mountain terrain. The variability within coffee and forested reference (average CV=28%) sites was similar to the variability found on grassland and forested reference sites in the temperate zone. The estimated annual soil loss from 14 sampled fields ranged from 6 to 61 t ha⁻¹ year⁻¹ with an overall mean of 26 t ha⁻¹ year⁻¹. Overall, the soil erosion estimates found using the ¹³⁷Cs method were much lower than those often assumed for such steep tropical hillsides. These erosion estimates account for soil loss since 1963 only and it seems likely that soil losses may have been much higher in earlier decades immediately after initial forest clearing earlier in the 20th century. Copyright © 2000 John Wiley & Sons, Ltd.     

Including spatial distribution in a data‐driven rainfall‐runoff model to improve reservoir inflow forecasting in Taiwan

Multi‐step ahead inflow forecasting has a critical role to play in reservoir operation and management in Taiwan during typhoons as statutory legislation requires a minimum of 3‐h warning to be issued before any reservoir releases are made. However, the complex spatial and temporal heterogeneity of typhoon rainfall, coupled with a remote and mountainous physiographic context, makes the development of real‐time rainfall‐runoff models that can accurately predict reservoir inflow several hours ahead of time challenging. Consequently, there is an urgent, operational requirement for models that can enhance reservoir inflow prediction at forecast horizons of more than 3 h. In this paper, we develop a novel semi‐distributed, data‐driven, rainfall‐runoff model for the Shihmen catchment, north Taiwan. A suite of Adaptive Network‐based Fuzzy Inference System solutions is created using various combinations of autoregressive, spatially lumped radar and point‐based rain gauge predictors. Different levels of spatially aggregated radar‐derived rainfall data are used to generate 4, 8 and 12 sub‐catchment input drivers. In general, the semi‐distributed radar rainfall models outperform their less complex counterparts in predictions of reservoir inflow at lead times greater than 3 h. Performance is found to be optimal when spatial aggregation is restricted to four sub‐catchments, with up to 30% improvements in the performance over lumped and point‐based models being evident at 5‐h lead times. The potential benefits of applying semi‐distributed, data‐driven models in reservoir inflow modelling specifically, and hydrological modelling more generally, are thus demonstrated. Copyright © 2012 John Wiley & Sons, Ltd.     

Concurrent imaging of chlorophyll fluorescence,Chlorophyll a content and green fluorescent proteins‐like proteins of symbiotic cnidarians

Research on photosynthetic cnidarians has been mainly focused on the symbiosis established between the cnidarian host and its dinoflagellates endosymbionts from genus Symbiodinium. Despite the potential of imaging techniques for assessing the spatial distribution of key parameters of cnidarian photobiology, such as photochemical activity, chlorophyll a content or green fluorescent proteins (GFPs), to our best knowledge, no study has ever attempted to simultaneous map these three features. In this study, we developed a modified imaging pulse amplitude fluorometer by applying excitation light of different wavelengths and selectively detecting short spectral bands through bandpass filters. The imaging system was used to sequentially excite and quantify chlorophyll variable fluorescence (maximum quantum yield of photosystem II, F_v/F_m), Chl a content (normalized difference vegetation index) and relative content of GFPs. The spatial distribution of these photophysiological parameters was mapped both horizontally, across the surface of the soft corals Sarcophyton cf. glaucum and Sinularia flexibilis and the zoanthid Protopalythoa sp., and vertically, throughout a vertical section of S. cf. glaucum. Results showed bleached areas within each individual coral colony and registered photophysiological changes with S. cf. glaucum tissue depth. Analysis of Protopalythoa sp. polyps’ expansion revealed differential surface patterns of NDVI and GFP concentration, and a negative relation between these latter parameters within each polyp. This novel non‐invasive approach allowed a high‐resolution characterization of the spatial relationship between these key parameters through the analysis of image information on a pixel‐by‐pixel basis, which has great potential for investigating the physiological state of symbiotic associations.     

Application of snowmelt runoff model for water resource management

Snow‐covered areas (SCAs) are the fundamental source of water for the hydrological cycle for some region. Accurate measurements of river discharge from snowmelt can help manage much needed water required for hydropower generation and irrigation purposes. This study aims to apply the snowmelt runoff model (SRM) in the Upper Indus basin by the Astore River in northern Pakistan for the years 2000 to 2006. The Shuttle Radar Topographic Mission (SRTM) data are used to generate the Digital Elevation Model (DEM) of the region. Various variables (snow cover depletion curves (SCDCs), temperature and precipitation) and parameters (degree‐day factor, recession coefficient, runoff coefficients, time lag, critical temperature and temperature lapse rate) are used as input in the SRM. However, snow cover data are direct and an important input to the SRM. Satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to estimate the SCA. Normalized difference snow index (NDSI) algorithm is applied for snow cover mapping and to differentiate snow from other land features. Nash–Sutcliffe coefficient of determination (R²) and volume difference (D_V) are used for quality assessment of the SRM. The results of the current research show that for the study years (2000–2006), the average value of R² is 0·87 and average volume difference D_V is 1·18%. The correlation coefficient between measured and computed runoff is 0·95. The results of the study further show that a high level of accuracy can be achieved during the snowmelt season. The simulation results endorse that the SRM in conjunction with MODIS snow cover product is very useful for water resource management in the Astore River and can be used for runoff forecasts in the Indus River basin in northern Pakistan. Copyright © 2011 John Wiley & Sons, Ltd.     

A new approach for linking event‐based upland sediment sources to downstream suspended sediment transport

In this study, we proposed a new approach for linking event sediment sources to downstream sediment transport in a watershed in central New York. This approach is based on a new concept of spatial scale, sub‐watershed area (SWA), defined as a sub‐watershed within which all eroded soils are transported out without deposition during a hydrological event. Using (rainfall) event data collected between July and November, 2007 from several SWAs of the studied watershed, we developed an empirical equation that has one independent variable, mean SWA slope. This equation was then used to determine event‐averaged unit soil erosion rate, Q_S/A, (in kg/km²/hr) for all SWAs in the studied watershed and calculate event‐averaged gross erosion E_ea (in kg/hr). The event gross erosion E_t (in kilograms) was subsequently computed as the product of E_ea and the mean event duration, T (in hours) determined using event hydrographs at the outlet of the studied watershed. Next, we developed two linear sediment rating curves (SRCs) for small and big events based on the event data obtained at the watershed outlet. These SRCs, together with T, allowed us to determine event sediment yield SY_e (in kilograms) for all events during the study period. By comparing E_t with SY_e, developing empirical equations (i) between E_t and SY_e and (ii) for event sediment delivery ratio, respectively, we revealed the event dynamic processes connecting sediment sources and downstream sediment transport. During small events, sediment transport in streams was at capacity and dominated by the deposition process, whereas during big events, it was below capacity and controlled by the erosion process. The key of applying this approach to other watersheds is establishing their empirical equations for Q_S/A and appropriately determining their numbers of SWAs. Copyright © 2011 John Wiley & Sons, Ltd.     

Petrography and geochemistry of manganiferous rocks in the Mankwadzi area in the southern Kibi‐Winneba metavolcanic belt,Ghana: Implications for genesis of Mn formations in the Birimian of West Africa

Manganiferous rocks in the Mankwadzi area in the southernmost portion of the Kibi‐Winneba metavolcanic belt, one of several Mn occurrences in the Paleoproterozoic Birimian of Ghana, are hosted in hornblende schist and amphibolite. These rocks are, in places, intruded by hornblende dyke. In outcrop, the manganiferous rocks appear to be conformable with the host schist and amphibolite, are macroscopically dark, fine‐grained and structurally massive to distinctly banded. Observed alternating light and dark occasionally macro‐folded bands suggest post‐depositional deformation of both light and dark bands. Microscopic observations revealed that the light bands are dominantly Si‐rich and the dark bands mainly of opaque minerals. Whole rock analyses of the manganiferous rocks show high contents of MnO (16.75–27.4 wt%) suggesting that the opaque minerals are likely rich in Mn. The analyzed rock samples show moderate to strong enrichments in light rare earth elements compared to heavy rare earth elements. Whereas the manganiferous rocks show perceptibly negative Eu anomaly, host hornblende schist and hornblende dyke do not. Eu anomaly in amphibolite samples is, however, uncertain as the three samples analyzed gave positive, negative and no Eu anomalies. Based on the field characteristics, microscopic and geochemical features, we suggest that the Mn occurrence in the Mankwadzi area originated via sedimentary deposition and was later modified by metamorphism, hydrothermal and/or supergene processes similar to manganiferous occurrences at Nsuta and Tambao in the Birimian of West Africa.     

Application of diffracted wave analysis to time‐lapse seismic data for CO2 leakage detection

Time‐lapse seismic analysis is utilized in CO₂ geosequestration to verify the CO₂ containment within a reservoir. A major risk associated with geosequestration is a possible leakage of CO₂ from the storage formation into overlaying formations. To mitigate this risk, the deployment of carbon capture and storage projects requires fast and reliable detection of relatively small volumes of CO₂ outside the storage formation. To do this, it is necessary to predict typical seepage scenarios and improve subsurface seepage detection methods. In this work we present a technique for CO₂ monitoring based on the detection of diffracted waves in time‐lapse seismic data. In the case of CO₂ seepage, the migrating plume might form small secondary accumulations that would produce diffracted, rather than reflected waves. From time‐lapse data analysis, we are able to separate the diffracted waves from the predominant reflections in order to image the small CO₂ plumes. To explore possibilities to detect relatively small amounts of CO₂, we performed synthetic time‐lapse seismic modelling based on the Cooperative Research Centre for Greenhouse Gas Technologies (CO2CRC) Otway project data. The detection method is based on defining the CO₂ location by measuring the coherency of the signal along diffraction offset‐traveltime curves. The technique is applied to a time‐lapse stacked section using a stacking velocity to construct offset‐traveltime curves. Given the amount of noise found in the surface seismic data, the predicted minimum detectable amount of CO₂ is 1000–2000 tonnes. This method was also applied to real data obtained from a time‐lapse seismic physical model. The use of diffractions rather than reflections for monitoring small amounts of CO₂ can enhance the capability of subsurface monitoring in CO₂ geosequestration projects.     

Evidence of Self‐Organized Criticality in riverbank mass failures: a matter of perspective?

A growing body of field, theoretical and numerical modelling studies suggests that predicting river response to even major changes in input variables is difficult. Rivers are seen to adjust rapidly and variably through time and space as well as changing independently of major driving variables. Concepts such as Self‐Organized Criticality (SOC) are considered to better reflect the complex interactions and adjustments occurring in systems than traditional approaches of cause and effect. This study tests the hypothesis that riverbank mass failures which occurred both prior to, and during, an extreme flood event in southeast Queensland (SEQ) in 2011 are a manifestation of SOC. Each wet‐flow failure is somewhat analogous to the ‘avalanche’ described in the initial sand‐pile experiments of Bak et al. (Physical Review Letters, 1987, 59(4), 381–384) and, due to the use of multitemporal LiDAR, the time period of instability can be effectively constrained to that surrounding the flood event. The data is examined with respect to the key factors thought to be significant in evaluating the existence of SOC including; non‐linear temporal dynamics in the occurrence of disturbance events within the system; an inverse power‐law relation between the magnitude and frequency of the events; the existence of a critical state to which the system readjusts after a disturbance; the existence of a cascading processes mechanism by which the same process can initiate both low‐magnitude and high‐magnitude events. While there was a significant change in the frequency of mass failures pre‐ and post‐flood, suggesting non‐linear temporal dynamics in the occurrence of disturbance events, the data did not fit an inverse power‐law within acceptable probability and other models were found to fit the data better. Likewise, determining a single ‘critical’ state is problematic when a variety of feedbacks and multiple modes of adjustment are likely to have operated throughout this high magnitude event. Overall, the extent to which the data supports a self‐organized critical state is variable and highly dependent upon inferential arguments. Investigating the existence of SOC, however, provided results and insights that are useful to the management and future prediction of these features. Copyright © 2014 John Wiley & Sons, Ltd.