Predicting quantiles of water quality from catchment characteristics

Water quality is often highly variable both in space and time, which poses challenges for modelling the more extreme concentrations. This study developed an alternative approach to predicting water quality quantiles at individual locations. We focused on river water quality data that were collected over 25 years, at 102 catchments across the State of Victoria, Australia. We analysed and modelled spatial patterns of the 10th, 25th, 50th, 75th and 90th percentiles of the concentrations of sediments, nutrients and salt, with six common constituents: total suspended solids (TSS), total phosphorus (TP), filterable reactive phosphorus (FRP), total Kjeldahl nitrogen (TKN), nitrate-nitrite (NO_x), and electrical conductivity (EC). To predict the spatial variation of each quantile for each constituent, we developed statistical regression models and exhaustively searched through 50 catchment characteristics to identify the best set of predictors for that quantile. The models predict the spatial variation in individual quantiles of TSS, TKN and EC well (66%–96% spatial variation explained), while those for TP, FRP and NO_x have lower performance (37%–73% spatial variation explained). The most common factors that influence the spatial variations of the different constituents and quantiles are: annual temperature, percentage of cropping land area in catchment and channel slope. The statistical models developed can be used to predict how low- and high-concentration quantiles change with landscape characteristics, and thus provide a useful tool for catchment managers to inform planning and policy making with changing climate and land use conditions.     

Determination of subcatchment and watershed boundaries in a complex and highly urbanized landscape

Urban development significantly alters the landscape by introducing widespread impervious surfaces, which quickly convey surface run‐off to streams via stormwater sewer networks, resulting in “flashy” hydrological responses. Here, we present the inadequacies of using raster‐based digital elevation models and flow‐direction algorithms to delineate large and highly urbanized watersheds and propose an alternative approach that accounts for the influence of anthropogenically modified land cover. We use a semi‐automated approach that incorporates conventional drainage networks into overland flow paths and define the maximal run‐off contributing area. In this approach, stormwater pipes are clustered according to their slope attributes, which define flow direction. Land areas drained by each cluster and contributing (or exporting) flow to a topographically delineated catchment were determined. These land masses were subsequently added or removed from the catchment, modifying both the shape and the size. Our results in a highly urbanized Toronto, Canada, area watershed indicate a moderate net increase in the directly connected watershed area by 3% relative to a topographically forced method; however, differences across three smaller scale subcatchments are greater. Compared to topographic delineation, the directly connected watershed areas of both the upper and middle subcatchments decrease by 5% and 8%, respectively, whereas the lower subcatchment area increases by 15%. This is directly related to subsurface storm sewer pipes that cross topographic boundaries. When directly connected subcatchment area is plotted against total streamflow and flashiness indices using this method, the coefficients of variation are greater (0.93 to 0.97) compared to the use of digital elevation model‐derived subcatchment areas (0.78 to 0.85). The accurate identification of watershed and subcatchment boundaries should incorporate ancillary data such as stormwater sewer networks and retention basin drainage areas to reduce water budget errors in urban systems.     

Analytical study of ground motion caused by seismic wave propagation across faulted rock masses

Studying seismic wave propagation across rock masses and the induced ground motion is an important topic, which receives considerable attention in design and construction of underground cavern/tunnel constructions and mining activities. The current study investigates wave propagation across a rock mass with one fault and the induced ground motion using a recursive approach. The rocks beside the fault are assumed as viscoelastic media with seismic quality factors, Q_p and Q_s. Two kinds of interactions between stress waves and a discontinuity and between stress waves and a free surface are analyzed, respectively. As the result of the wave superposition, the mathematical expressions for induced ground vibration are deduced. The proposed approach is then compared with the existing analysis for special cases. Finally, parametric studies are carried out, which includes the influences of fault stiffness, incident angle, and frequency of incident waves on the peak particle velocities of the ground motions.     

Dynamic modelling of retrogressive landslides with emphasis on the role of clay sensitivity

This paper presents a detailed numerical study of the retrogressive failure of landslides in sensitive clays. The dynamic modelling of the landslides is carried out using a novel continuum approach, the particle finite element method, complemented with an elastoviscoplastic constitutive model. The multiwedge failure mode in the collapse is captured successfully, and the multiple retrogressive failures that have been widely observed in landslides in sensitive clays are reproduced with the failure mechanism, the kinematics, and the deposition being discussed in detail. Special attention has been paid to the role of the clay sensitivity on each retrogressive failure as well as on the final retrogression distance and the final run‐out distance via parametric studies. Moreover, the effects of the viscosity of sensitive clays on the failure are also investigated for different clay sensitivities.     

Correction to: Post-earthquake response by small UAV helicopters

Natural Hazards - The original publication has the following mistakes which we hereby correct: In Fig. 3 the “UAV routs” should be replaced by “UAV routes”. On page...     

Petrochronology of oxidized granulites from southern Peru

Sapphirine–quartz granulites from the Cocachacra region of the Arequipa Massif in southern Peru record early Neoproterozoic ultrahigh‐temperature metamorphism. Phase equilibrium modelling and zircon petrochronology are used to quantify timing and pressure–temperature (P–T) conditions of metamorphism. Modelling of three magnetite‐bearing sapphirine–quartz samples indicates peak temperatures of >950°C at ~0.7 GPa and a clockwise P–T evolution. Elevated concentrations of Al in orthopyroxene are also consistent with ultrahigh‐temperature conditions. Neoblastic zircon records ages of c. 1.0–0.9 Ga that are interpreted to record protracted ultrahigh‐temperature metamorphism. Th/U ratios of zircon of up to 100 reflect U‐depleted whole‐rock compositions. Concentrations of heavy rare earth elements in zircon do not show systematic trends with U–Pb age but do correlate with variable whole‐rock compositions. Very large positive Ce anomalies in zircon from two samples probably relate to strongly oxidizing conditions during neoblastic zircon crystallization. Low concentrations of Ti‐in‐zircon (<10 ppm) are interpreted to result from reduced titania activities due to the strongly oxidized nature of the granulites and the sequestration of titanium‐rich minerals away from the reaction volume. Whole‐rock compositions and oxidation state have a strong influence on the trace element composition of metamorphic zircon, which has implications for interpreting the geological significance of ages retrieved from zircon in oxidized metamorphic rocks.     

Wetlands and low-gradient topography are associated with longer hydrologic transit times in Precambrian Shield headwater catchments

The estimation of hydrologic transit times in a catchment provides insights into the integrated effects of water storage, mixing dynamics, and runoff generation processes. There has been limited effort to estimate transit times in southern boreal Precambrian Shield landscapes, which are characteristically heterogeneous with surface cover including till, thin soils, bedrock outcrops, and depressional wetland features that play contrasting hydrologic roles. This study presents approximately 3.5 years of precipitation and streamflow water isotope data and estimates mean transit times (MTTs) and the young water fraction (p_y) across six small catchments in the Muskoka-Haliburton region of south-central Ontario. The main objectives were to define a typical range of MTTs for headwater catchments in this region and to identify landscape variables that best explain differences in MTTs/p_y using airborne light detection and ranging and digital terrain analysis. Of the transit time distributions, the two parallel linear reservoir and gamma distributions best describe the hydrology of these catchments, particularly because of their ability to capture more extreme changes related to events such as snowmelt. The estimated MTTs, regardless of the modelling approach or distribution used, are positively associated with the percent wetland area and negatively with mean slope in the catchments. In this landscape, low-gradient features such as wetlands increase catchment scale water storage when antecedent conditions are dryer and decrease transit times when there is a moisture surplus, which plausibly explains the increases in MTTs and mean annual runoff from catchments with significant coverage of these landscape features.     

Changes in hillslope hydrology in a perched,shallow soil system due to clearcutting and residual biomass removal

Sustainable fuels legislation and volatility in energy prices have put additional pressures on the forestry sector to intensify the harvesting of biomass for “advanced biofuel” production. To better understand how residual biomass removal after harvest affects forest hydrology in relatively low slope terrain, a Before-After-Control-Impact (BACI) study was conducted in the USDA Forest Service's Marcell Experimental Forest, Minnesota, USA. Hydrological measurements were made from 2010–2013 on a forested hillslope that was divided into three treatment blocks, where one block was harvested and residual biomass removed (Biomass Removed), the second was harvested and residual biomass left (Biomass Left), and the last block was left as an Unharvested Control. The pre-harvest period (2 years) was 2010–11 and post-harvest (2 years) was 2012–13. Water table elevation at the upslope and downslope position, subsurface runoff, and soil moisture were measured between May–November. Mixed effect statistical models were used to compare both the before-after and “control” treatment ratios (ratios between harvested hillslopes and the Unharvested Control hillslope). Subsurface runoff significantly increased (p < .05) at both harvested hillslopes but to a greater degree on the Biomass Left hillslope. Greater subsurface runoff volumes at both harvested hillslopes were driven by substantial increases during fall, with additional significant increases during summer on the Biomass Left hillslope. The hydrological connectivity, inferred from event runoff ratios, increased due to harvesting at both hillslopes but only significantly on the Biomass Left hillslope. The winter harvest minimized soil disturbance, resulting in no change to the effective hydraulic conductivity distribution with depth. Thus, the observed hydrological changes were driven by increased effective precipitation and decreased evapotranspiration, increasing the duration that both harvested hillslopes were hydrologically active. The harvesting of residual biomass appears to lessen hydrological connectivity relative to leaving residual biomass on the hillslope, potentially decreasing downstream hydrological impacts of similar forestry operations.     

Developing constitutive models from EPR‐based self‐learning finite element analysis

A constitutive model that captures the material behavior under a wide range of loading conditions is essential for simulating complex boundary value problems. In recent years, some attempts have been made to develop constitutive models for finite element analysis using self‐learning simulation (SelfSim). Self‐learning simulation is an inverse analysis technique that extracts material behavior from some boundary measurements (eg, load and displacement). In the heart of the self‐learning framework is a neural network which is used to train and develop a constitutive model that represents the material behavior. It is generally known that neural networks suffer from a number of drawbacks. This paper utilizes evolutionary polynomial regression (EPR) in the framework of SelfSim within an automation process which is coded in Matlab environment. EPR is a hybrid data mining technique that uses a combination of a genetic algorithm and the least square method to search for mathematical equations to represent the behavior of a system. Two strategies of material modeling have been considered in the SelfSim‐based finite element analysis. These include a total stress‐strain strategy applied to analysis of a truss structure using synthetic measurement data and an incremental stress‐strain strategy applied to simulation of triaxial tests using experimental data. The results show that effective and accurate constitutive models can be developed from the proposed EPR‐based self‐learning finite element method. The EPR‐based self‐learning FEM can provide accurate predictions to engineering problems. The main advantages of using EPR over neural network are highlighted.