Sparse Field Data Research Articles

Surface slip during large Owens Valley earthquakes

AbstractThe 1872 Owens Valley earthquake is the third largest known historical earthquake in California. Relatively sparse field data and a complex rupture trace, however, inhibited attempts to fully resolve the slip distribution and reconcile the total moment release. We present a new, comprehensive record of surface slip based on lidar and field investigation, documenting 162 new measurements of laterally and vertically displaced landforms for 1872 and prehistoric Owens Valley earthquakes. Our lidar analysis uses a newly developed analytical tool to measure fault slip based on cross‐correlation of sublinear topographic features and to produce a uniquely shaped probability density function (PDF) for each measurement. Stacking PDFs along strike to form cumulative offset probability distribution plots (COPDs) highlights common values corresponding to single and multiple‐event displacements. Lateral offsets for 1872 vary systematically from ∼1.0 to 6.0 m and average 3.3 ± 1.1 m (2σ). Vertical offsets are predominantly east‐down between ∼0.1 and 2.4 m, with a mean of 0.8 ± 0.5 m. The average lateral‐to‐vertical ratio compiled at specific sites is ∼6:1. Summing displacements across subparallel, overlapping rupture traces implies a maximum of 7–11 m and net average of 4.4 ± 1.5 m, corresponding to a geologic Mw∼7.5 for the 1872 event. We attribute progressively higher‐offset lateral COPD peaks at 7.1 ± 2.0 m, 12.8 ± 1.5 m, and 16.6 ± 1.4 m to three earlier large surface ruptures. Evaluating cumulative displacements in context with previously dated landforms in Owens Valley suggests relatively modest rates of fault slip, averaging between ∼0.6 and 1.6 mm/yr (1σ) over the late Quaternary.

Next-generation seismic experiments – II: wide-angle, multi-azimuth, 3-D, full-waveform inversion of sparse field data

Next-generation seismic experiments – II: wide-angle, multi-azimuth, 3-D, full-waveform inversion of sparse field data

Field data-based implementation of land management and terraces on the catchment scale for an eco-hydrological modelling approach in the Three Gorges Region, China

In this study, an innovative method to generate spatially-distributed data sets on land management and terraces based on sparse field data for a steep-sloping catchment in the Three Gorges Region in China is introduced and tested using the eco-hydrological model SWAT. The generation of such data sets is necessary for the development and evaluation of Best Management Practices (BMP) towards a reduction of high inputs of sediment and nutrients in water bodies. It is hypothesized that the inclusion of land management as well as terraces in the eco-hydrological modelling approach are individually as well as combined able to increase the model efficiency regarding streamflow and sediment. The results of the study show that the field data sets on land management and terraces can be used to generate useful SWAT input data sets to represent management and conservation practices and the model results are plausible. The effect of land management and terraces on streamflow is identified to be rather small. At the same time a strong effect of the inclusion of the terrace dataset on sediment yields can be observed, which can be seen as an improvement of the process representation within the model. By introducing the new method the study contributes to an improved representation of land management and terraces in data-scarce study regions in eco-hydrological models. At the same time the study confirms the importance of the consideration of BMPs in eco-hydrological modelling, especially towards the representation of the dynamics of sediment and sediment-bound substances.

Exceptional river gorge formation from unexceptional floods.

An understanding of rates and mechanisms of incision and knickpoint retreat in bedrock rivers is fundamental to perceptions of landscape response to external drivers, yet only sparse field data are available. Here we present eye witness accounts and quantitative surveys of rapid, amphitheatre-headed gorge formation in unweathered granite from the overtopping of a rock-cut dam spillway by small-moderate floods (∼100-1,500 m(3) s(-1)). The amount of erosion demonstrates no relationship with flood magnitude or bedload availability. Instead, structural pattern of the bedrock through faults and joints appears to be the primary control on landscape change. These discontinuities facilitate rapid erosion (>270 m headward retreat; ∼100 m incision; and ∼160 m widening over 6 years) principally through fluvial plucking and block topple. The example demonstrates the potential for extremely rapid transient bedrock erosion even when rocks are mechanically strong and flood discharges are moderate. These observations are relevant to perceived models of gorge formation and knickpoint retreat.

Insights into the 3D architecture of an active caldera ring-fault at Tendürek volcano through modeling of geodetic data

The three-dimensional assessment of ring-fault geometries and kinematics at active caldera volcanoes is typically limited by sparse field, geodetic or seismological data, or by only partial ring-fault rupture or slip. Here we use a novel combination of spatially dense InSAR time-series data, numerical models and sand-box experiments to determine the three-dimensional geometry and kinematics of a sub-surface ring-fault at Tendürek volcano in Turkey. The InSAR data reveal that the area within the ring-fault not only subsides, but also shows substantial westward-directed lateral movement. The models and experiments explain this as a consequence of a ‘sliding-trapdoor’ ring-fault architecture that is mostly composed of outward-inclined reverse segments, most markedly so on the volcano's western flanks but includes inward-inclined normal segments on its eastern flanks. Furthermore, the model ring-fault exhibits dextral and sinistral strike-slip components that are roughly bilaterally distributed onto its northern and southern segments, respectively. Our more complex numerical model describes the deformation at Tendürek better than an analytical solution for a single rectangular dislocation in a half-space. Comparison to ring-faults defined at Glen Coe, Fernandina and Bárðarbunga calderas suggests that ‘sliding-trapdoor’ ring-fault geometries may be common in nature and should therefore be considered in geological and geophysical interpretations of ring-faults at different scales worldwide.

A predictive Bayesian data-derived multi-modal Gaussian model of sunken oil mass

Hydrodynamic modeling of sunken oil is hindered by insufficient knowledge of bottom currents. In this paper, the development of a predictive Bayesian model, SOSim, for inferring the location of sunken oil in time, based on sparse, qualitative or quantitative near-real time field data collected immediately following a spill, is described. Mapped output represents unconditional multi-modal Gaussian relative probabilities of finding oil at points across a relatively flat bay bottom, in time. The method of images is extended to address curvilinear reflecting shorelines. The model is demonstrated to locate the entire DBL-152 spill, given field data covering part of the area affected, and to project oil movement near curvilinear shoreline boundaries given simulated field data at two points in time. Limitations include accountability for discontinuous boundary conditions. Further development is recommended, including development of capability for accepting bathymetric data, for modeling continuous oil releases, and for 3-D modeling of suspended oil.

Estimation of net shortwave radiation flux of western Himalayan snow cover during clear sky days using remote sensing and meteorological data

The aim of this letter is to estimate incoming and net shortwave radiation fluxes of large snow-covered area of western Himalaya and to evaluate the results with in situ observations. Radiation fluxes are estimated at spatial levels using remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and Shuttle Radar Topographic Mission (SRTM) digital elevation model (DEM), supplemented with sparse field data obtained from automatic weather stations (AWSs). Snow cover albedo has been estimated from MODIS data using narrowband to broadband conversion method for clear sky days. Geospatial maps of air temperature (Ta) and relative humidity (RH) have been generated for the study area using AWS recorded Ta/RH and DEM. Parameterization techniques have been used for estimating incoming and net shortwave radiation fluxes, which have been validated from in situ AWS observations. The root mean square error (RMSE) in estimation of incoming shortwave radiation flux and net shortwave radiation flux has been found to be 75 and 84.9 W m−2, respectively. Further, the higher radiation fluxes have been observed on south aspect slopes than those observed on north aspect slopes.

Reducing the impact of model scale on simulated, gridded switchgrass yields

Results of gridded ecosystem simulations of bioenergy crops are used for estimating economic viability, environmental impacts, and potential land use change. Gridded model uncertainty propagates through these uses, thus we propose a simple method for estimating regional, spatial model error from sparse field data. We apply this method to the Agricultural-BioGeochemical Cycles (Agro-BGC) model to examine and reduce the model uncertainty associated with grid scale for simulated switchgrass yields in a 6° latitude × 5° longitude (∼300,000 km2) region covering Illinois, United States of America. Based on three evaluation sites, changes in yield with scale result from complex intra-model interactions driven by a combination of meteorological rather than soil or terrain variables. Spatial bias of the regional mean significantly increases with increasing cell size for 11 of 15 measurement dates. This bias is primarily due to grid scale, thus bias correction of output yield reduces the model uncertainty associated with grid scale. The corresponding Root Mean Squared Error and Bias-Corrected RMSE (RMSEBC) have effectively negligible trends with inconsistent signs. The range of RMSEBC for 2-year Average Mature August Yield (AMAY) is 267–285 g C m−2 across 3- to 3600-arcsec resolution (∼90 m–∼100 km) with biases from 9 to 61 g C m−2. AMAY bias significantly increases with increasing cell size. Spatial bias of the regional mean is relatively consistent for resolutions ≤1200 arcsec (∼33 km) (AMAY bias <3%), and larger AMAY biases (4–13%) at coarse resolutions indicate poorly characterized spatial heterogeneity. Including the 68% confidence interval around bias-corrected values, AMAY ranges from 0 to 1116 g C m−2 across a 150-arsec grid, which is similar to the range reported for 24 eastern United States field sites. Spatial bias of the regional mean yield can vary across grid resolution by as much as 31% of the observed regional mean and can dramatically affect calculations dependent on the resolution of the estimate. We conclude that grid scale profoundly affects model accuracy such that regional studies must match evaluation and simulation scales and should utilize multi-scale analyses to determine robustness of results.

Geodiversity: Exploration of 3D geological model space

The process of building a 3D model necessitates the reconciliation of field observations, geophysical interpretation, geological data uncertainty and the prevailing tectonic evolution hypotheses and interpretations. Uncertainty is compounded when clustered data points collected at local scales are statistically upscaled to one or two points for use in regional models. Interpretation is required to interpolate between sparse field data points using ambiguous geophysical data in covered terranes. It becomes clear that multiple interpretations are possible during model construction. The various interpretations are considered as potential natural representatives, but pragmatism typically dictates that just a single interpretation is offered by the modelling process. Uncertainties are introduced into the 3D model during construction from a variety of sources and through data set optimisation that produces a single model. Practices such as these are likely to result in a model that does not adequately represent the target geology.A set of geometrical ‘geodiversity’ metrics are used to analyse a 3D model of the Gippsland Basin, southeastern Australia after perturbing geological input data via uncertainty simulation. The resulting sets of perturbed geological observations are used to calculate a suite of geological 3D models that display a range of geological architectures. The concept of biodiversity has been adapted for the geosciences to quantify geometric variability, or geodiversity, between models in order to understand the effect uncertainty has models geometry. Various geometrical relationships (depth, volume, contact surface area, curvature and geological complexity) are used to describe the range of possibilities exhibited throughout the model suite. End-member models geodiversity metrics are classified in a similar manner to taxonomic descriptions. Further analysis of the model suite is performed using principal component analysis (PCA) to determine important geometrical characteristics. The configuration of the model space is determined through identifying ‘outlier’ model examples, which potentially represent undiscovered model ‘species’.

Spectroscopy of canopy chemicals in humid tropical forests

Remote sensing of canopy chemistry could greatly advance the study and monitoring of functional processes and biological diversity in humid tropical forests. Imaging spectroscopy has contributed to canopy chemical remote sensing, but efforts to develop general, globally-applicable approaches have been limited by sparse and inconsistent field and laboratory data, and lacking analytical methods. We analyzed leaf hemispherical reflectance and transmittance spectra, along with a 21-chemical portfolio, taken from 6136 fully sunlit humid tropical forest canopies, and developed an up-scaling method using a combination of canopy radiative transfer, chemometric and high-frequency noise modeling. By integrating these steps, we found that the accuracy and precision of multi-chemical remote sensing of tropical forest canopies varies by leaf constituent and wavelength range. Under conditions of varying canopy structure and spectral noise, photosynthetic pigments, water, nitrogen, cellulose, lignin, phenols and leaf mass per area (LMA) are accurately estimated using visible-to-shortwave infrared spectroscopy (VSWIR; 400–2500 nm). Phosphorus and base cations are retrieved with lower yet significant accuracy. We also find that leaf chemical properties are estimated far more consistently, and with much higher precision and accuracy, using the VSWIR range rather than the more common and limited visible to near-infrared range (400–1050 nm; VNIR). While VNIR spectroscopy proved accurate for predicting foliar LMA, photosynthetic pigments and water, VSWIR spectra provided accurate estimates for three times the number of canopy traits. These global results proved to be independent of site conditions, taxonomic composition and phylogenetic history, and thus they should be broadly applicable to multi-chemical mapping of humid tropical forest canopies. The approach developed and tested here paves the way for studies of canopy chemical properties in humid tropical forests using the next generation of airborne and space-based high-fidelity imaging spectrometers.

On the 3-D inversion of vertical electrical soundings: Application to the South Ismailia area—Cairo desert road, Cairo, Egypt

A code for 3-D resistivity modelling and inversion of vertical electrical soundings has been developed based on the finite-element technique and regularisation method. Synthetic data were used to test the effectiveness of the code and to examine the resolving capability of the Schlumberger array in investigating 3-D resistivity distributions. The code was applied to experimental data set constituted by 35 Schlumberger soundings collected near the Cairo city in order to study the subsurface resistivity distribution. The results have shown that valuable imaging of the subsurface resistivity distribution can be constructed even when the vertical electrical soundings are acquired in a sparse field data set.

Evaluating uncertainty in predicting spatially variable representative elementary scales in fractured aquifers, with application to Turkey Creek Basin, Colorado

Computational limitations and sparse field data often mandate use of continuum representation for modeling hydrologic processes in large‐scale fractured aquifers. Selecting appropriate element size is of primary importance because continuum approximation is not valid for all scales. The traditional approach is to select elements by identifying a single representative elementary scale (RES) for the region of interest. Recent advances indicate RES may be spatially variable, prompting unanswered questions regarding the ability of sparse data to spatially resolve continuum equivalents in fractured aquifers. We address this uncertainty of estimating RES using two techniques. In one technique we employ data‐conditioned realizations generated by sequential Gaussian simulation. For the other we develop a new approach using conditioned random walks and nonparametric bootstrapping (CRWN). We evaluate the effectiveness of each method under three fracture densities, three data sets, and two groups of RES analysis parameters. In sum, 18 separate RES analyses are evaluated, which indicate RES magnitudes may be reasonably bounded using uncertainty analysis, even for limited data sets and complex fracture structure. In addition, we conduct a field study to estimate RES magnitudes and resulting uncertainty for Turkey Creek Basin, a crystalline fractured rock aquifer located 30 km southwest of Denver, Colorado. Analyses indicate RES does not correlate to rock type or local relief in several instances but is generally lower within incised creek valleys and higher along mountain fronts. Results of this study suggest that (1) CRWN is an effective and computationally efficient method to estimate uncertainty, (2) RES predictions are well constrained using uncertainty analysis, and (3) for aquifers such as Turkey Creek Basin, spatial variability of RES is significant and complex.

A gradient feature weighted Minimax algorithm for registration of multiple portal images to 3DCT volumes in prostate radiotherapy

To develop an accurate, fast, and robust algorithm for registering portal and computed tomographic (CT) images for radiotherapy using a combination of sparse and dense field data that complement each other. Gradient Feature Weighted Minimax (GFW Minimax) method was developed to register multiple portal images to three-dimensional CT images. Its performance was compared with that of three others: Minimax, Mutual Information, and Gilhuijs' method. Phantom and prostate cancer patient images were used. Effects of registration errors on tumor control probability (TCP) and normal tissue complication probability (NTCP) were investigated as a relative measure. Registration of four portals to CTs resulted in 30% lower error when compared with registration with two portals. Computation time increased by nearly 50%. GFW Minimax performed the best, followed by Gilhuijs' method, the Minimax method, and Mutual Information. Using four portals instead of two lowered the registration error. Reduced fields of view images with full feature sets gave similar results in shorter times as full fields of view images. In clinical situations where soft tissue targets are of importance, GFW Minimax algorithm was significantly more accurate and robust. With registration errors lower than 1 mm, margins may be scaled down to 4 mm without adversely affecting TCP and NTCP.

Present and former equilibrium line altitudes in the Taiwanese high mountain range

Previously reported values of former equilibrium line altitudes (ELA) for Taiwan are based on sparse field data or extrapolations from Japan or China. This paper presents new calculations based on recently obtained geological data (Hebenstreit, R, Böse, M, 2003. Geomorphological evidence for a Late Pleistocene glaciation in the high mountains of Taiwan dated with age estimates by optically stimulated luminescence (OSL). Zeitschrift für Geomorphologie N.F. Suppl.-Bd.130, 31–49; Hebenstreit, R., Murray, A.S., Böse, M., this vol. Late Pleistocene and Early Holocene glaciations in Taiwanese mountains. Quaternary International) from three Taiwanese mountain massifs ( Nanhuta Shan, Hsueh Shan and Yushan) using established calculation methods (Benn, D.I., Lehmkuhl, F., 2000. Mass balance and equilibrium-line altitudes of glaciers in high-mountain environments. Quaternary International 65–66, 15–29; Porter, S.C., 2001. Snowline depression in the tropics during the Last Glaciation. Quaternary Science Reviews 20(10), 1067–1091). The relationship of annual precipitation and summer (JJA) temperature (Ohmura, A., Kasser, P., Funk, M., 1992. Climate at the equilibrium line of glaciers. Journal of Glaciology 38(130), 397–411) obtained from a 30 year meteorological database is used to estimate the present theoretical (virtual) equilibrium line altitude (ELA t) at about 4000 m over the southern and 3900 m over the northern part of Taiwan. The ELA was 3350–3500 m during Late Glacial to Early Holocene time (11–8 ka). Including a minimum post-glacial mountain uplift rate of 5 mm/a (Lundberg, N., Dorsey, R.J., 1990. Rapid Quaternary emergence, uplift, and denudation of the Coastal Range, eastern Taiwan. Geology 18(7), 638–641); Lin, C.-H., 1998. Tectonic implications of an aseismic belt beneath the eastern central range of Taiwan: crustal subduction and exhumation. Journal of the Geological Society of China 41(3), 441–460) in the calculation, the ELA depression (ΔELA) was 400–550 m during this period. Data from LGM or earlier are still rare, but glacial landforms and deposits indicate the ELA position at 2775–3195 m and the ΔELA of 705–1125 m.

Robust Water Quality Model Calibration Using an Alternating Fitness Genetic Algorithm

Presented herein is a robust approach to calibrating water quality models for water quality management using sparse field data. The calibration procedure adopts genetic algorithms (GAs) to inversely solve the governing equations, along with an alternating fitness method to maintain solution diversity. The proposed approach is illustrated with a total phosphorus model of the Triadelphia Reservoir in Maryland. A series of deterministic and stochastic alternating fitness GA schemes are implemented and compared with a standard GA. Significantly higher diversity is observed in the solutions obtained by the alternating fitness method than by the standard process. The diversified solutions obtained by the alternating fitness GA method are then classified into several patterns using a parameter pattern recognition model. The best solutions to each pattern are then chosen for further projection analyses, which generate a range of prediction results that provide decision makers with information for formulating sound pollution control schemes.

Rates and processes of bedrock incision by the Upper Ukak River since the 1912 Novarupta ash flow in the Valley of Ten Thousand Smokes, Alaska

The rates and patterns of bedrock channel incision significantly influence landscape evolution and long-term interactions among climate, tectonics, and erosion. Unfortunately, only sparse field data are available to quantify the controls on river incision rates. We exploit the diversion of the upper Ukak River by an ash flow in 1912 to measure rates of incision along a newly formed bedrock channel. Minimum estimates of the rate of incision into intact rock vary from 0.01 to 0.10 m·yr –1 . This variation reflects differences in channel slope, channel width, lithologic facies, and intensity of jointing as well as the effects of upstream knickpoint migration. A streampower–type incision model adequately explains the incision-rate data, provided (1) variations in channel width are prescribed on the basis of field measurements, (2) the slope exponent is significantly less than unity (n = 0.4 ± 0.2), and (3) observed downstream changes in lithologic facies and the intensity of jointing account for the apparent twofold downstream decrease in the coefficient of erosion. Despite the very rapid rate of incision, calibrated stream-power erosion coefficients for the Ukak River (K = 2.4 × 10 –4 m 0.2 ·yr –1 to 9.0 × 10 –4 m 0.2 ·yr –1 ) are within the range of previously published estimates. Two plausible explanations for the low values of the slope exponent n are that incision rate is limited by either (1) a combination of physical weathering and hydrodynamic joint-block extraction or (2) block fracture due to bedload impacts modulated on steeper channel segments by suspension of a significant fraction of the sediment load.

An exploratory analysis of liver element relationships in a case series of common loons ( Gavia immer)

To examine the relationships among liver element concentrations, principal component analysis (PCA) was performed on data from a case series of 54 common loons collected in Michigan during the period from July 1988 to February 1993. Data available for each bird included season and district of collection, age, sex, necropsy findings, and liver concentrations of twelve elements as determined by spectrophotometry. The first three principal components (PC) accounted for 86% of the total variability of the data, which made possible a substantial reduction in dimensionality. Within PC1–PC3, calcium, iron, mercury and lead were the most influential elements in accounting for variation. The possibility of a competitive interaction between mercury and lead for selenium is suggested, with consideration given to possible alterations in bioavailability due to environmental acidification. PCA can generate hypotheses that subsequently can be investigated under conditions which allow causal inference and better control of confounding factors. Consequently, sparse field data can be used efficiently to generate information on risk factors for environmental diseases, and to provide bases for intervention strategies.

The Dalradian rocks of the Lecht, NE Scotland: stratigraphy, faulting, geochemistry and mineralisation

ABSTRACTAir photo interpretation and geochemistry have been used to supplement sparse field data in compiling a reconnaissance geological map of the area around the Lecht. Upper Appin and lower Argyll Group rocks are exposed, the best marker horizons being correlatives of the Appin and Jura Quartzites. Scatter plots, Q mode factor analysis and Pearson correlation coefficients of geochemical data were successfully used in the correlation of the pelite and limestone outcrops. The presence of major recumbent folds is inferred. The area is cut by numerous minor faults which are thought to be related to a major transcurrent fault, the probable north-eastern continuation of the Loch Tay fault, which was active in Lower Old Red Sandstone times.The Lecht manganiferous ironstone is a seepage-bog ore type deposit derived by weathering of the local Dalradian sequence. Despite intensive leaching, this sequence still shows anomalously high levels of several elements, particularly Mn, Ba and Zn. In addition, stratiform sphalerite and manganiferous garnet are present in Blair Atholl Subgroup limestone and pelite horizons, respectively. Mineralogical and geochemical evidence suggests the presence of Zn–Pb–(Ag)–(?Au) exhalative mineralisation within the upper Appin Group Dalradian of the region, of which the Lecht represents the distal manganiferous expression.

Selection of drainage and its phased implementation for salinity control

Soil salinity has often become a long-term problem associated with irrigated agriculture in the arid and semi-arid regions. But the problem can be controlled by good management of surface and groundwater resources. Management of groundwater is achieved through drainage, although drainage may not be necessary for some time after the initial construction of a scheme. This paper introduces a regional model for predicting expected soil salinity conditions and groundwater depths over an irrigation scheme. The model considers all the main hydrological systems which influence soil salinity and makes optimal use of sparse point field data from grid surveys. The model can be used to identify priority areas for reclamation measures, ie areas where conditions combine to produce high salinity levels. Thus drainage development can be phased over a period of time and targeted where it will be most effective.