Water quality data for Fall Creek,New York,USA: 1972–1995

The 33 086 ha mixed land use Fall Creek watershed in upstate New York is part of the Great Lakes drainage system. Results from more than 3500 water samples are available in a data set that compiles flow data and measurements of various water quality analytes collected between 1972 and 1995 in all seasons and under all flow regimes in Fall Creek and its tributaries. Data is freely accessible at https://ecommons.cornell.edu/handle/1813/8148 and includes measurements of suspended solids, pH, alkalinity, calcium, magnesium, potassium, sodium, chloride, nitrate nitrogen (NO3-N), sulphate sulphur (SO4-S), phosphorus (P) fractions molybdate reactive P (MRP) and total dissolved P (TDP), percent P in sediment, and ammonium nitrogen (NH4-N). Methods, sub-watershed areas, and coordinates for sampling sites are also included. The work represented in this data set has made important scientific contributions to understanding of hydrological and biogeochemical processes that influence loading in mixed use watersheds and that have an impact on algal productivity in receiving water bodies. In addition, the work has been foundational for important regulatory and management decisions in the region.     

Modelling the effect of changing precipitation inputs on deep soil water utilization

Forests in the Southeastern United States are predicted to experience future changes in seasonal patterns of precipitation inputs as well as more variable precipitation events. These climate change‐induced alterations could increase drought and lower soil water availability. Drought could alter rooting patterns and increase the importance of deep roots that access subsurface water resources. To address plant response to drought in both deep rooting and soil water utilization as well as soil drainage, we utilize a throughfall reduction experiment in a loblolly pine plantation of the Southeastern United States to calibrate and validate a hydrological model. The model was accurately calibrated against field measured soil moisture data under ambient rainfall and validated using 30% throughfall reduction data. Using this model, we then tested these scenarios: (a) evenly reduced precipitation; (b) less precipitation in summer, more in winter; (c) same total amount of precipitation with less frequent but heavier storms; and (d) shallower rooting depth under the above 3 scenarios. When less precipitation was received, drainage decreased proportionally much faster than evapotranspiration implying plants will acquire water first to the detriment of drainage. When precipitation was reduced by more than 30%, plants relied on stored soil water to satisfy evapotranspiration suggesting 30% may be a threshold that if sustained over the long term would deplete plant available soil water. Under the third scenario, evapotranspiration and drainage decreased, whereas surface run‐off increased. Changes in root biomass measured before and 4 years after the throughfall reduction experiment were not detected among treatments. Model simulations, however, indicated gains in evapotranspiration with deeper roots under evenly reduced precipitation and seasonal precipitation redistribution scenarios but not when precipitation frequency was adjusted. Deep soil and deep rooting can provide an important buffer capacity when precipitation alone cannot satisfy the evapotranspirational demand of forests. How this buffering capacity will persist in the face of changing precipitation inputs, however, will depend less on seasonal redistribution than on the magnitude of reductions and changes in rainfall frequency.     

Evaluating soil water routing approaches in watershed-scale,ecohydrologic modelling

Soil water dynamics are central in linking and regulating natural cycles in ecohydrology, however, mathematical representation of soil water processes in models is challenging given the complexity of these interactions. To assess the impacts of soil water simulation approaches on various model outputs, the Soil and Water Assessment Tool was modified to accommodate an alternative soil water percolation method and tested at two geographically and climatically distinct, instrumented watersheds in the United States. Soil water was evaluated at the site scale via measured observations, and hydrologic and biophysical outputs were analysed at the watershed scale. Results demonstrated an improved Kling–Gupta Efficiency of up to 0.3 and a reduction in percent bias from 5 to 25% at the site scale, when soil water percolation was changed from a threshold, bucket-based approach to an alternative approach based on variable hydraulic conductivity. The primary difference between the approaches was attributed to the ability to simulate soil water content above field capacity for successive days; however, regardless of the approach, a lack of site-specific characterization of soil properties by the soils database at the site scale was found to severely limit the analysis. Differences in approach led to a regime shift in percolation from a few, high magnitude events to frequent, low magnitude events. At the watershed scale, the variable hydraulic conductivity-based approach reduced average annual percolation by 20–50 mm, directly impacting the water balance and subsequently biophysical predictions. For instance, annual denitrification increased by 14–24 kg/ha for the new approach. Overall, the study demonstrates the need for continued efforts to enhance soil water model representation for improving biophysical process simulations.     

Implementation of a coupled plastic damage distinct lattice spring model for dynamic crack propagation in geomaterials

This paper studies dynamic crack propagation by employing the distinct lattice spring model (DLSM) and 3‐dimensional (3D) printing technique. A damage‐plasticity model was developed and implemented in a 2D DLSM. Applicability of the damage‐plasticity DLSM was verified against analytical elastic solutions and experimental results for crack propagation. As a physical analogy, dynamic fracturing tests were conducted on 3D printed specimens using the split Hopkinson pressure bar. The dynamic stress intensity factors were recorded, and crack paths were captured by a high‐speed camera. A parametric study was conducted to find the influences of the parameters on cracking behaviors, including initial and peak fracture toughness, crack speed, and crack patterns. Finally, selection of parameters for the damage‐plasticity model was determined through the comparison of numerical predictions and the experimentally observed cracking features.     

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.     

A multiscale work-analysis approach for geotechnical structures

This paper presents a second-order work analysis in application to geotechnical problems by using a novel effective multiscale approach. To abandon complicated equations involved in conventional phenomenological models, this multiscale approach employs a micromechanically-based formulation, in which only four parameters are involved. The multiscale approach makes it possible a coupling of the finite element method (FEM) and the micromechanically-based model. The FEM is used to solve the boundary value problem (BVP) while the micromechanically-based model is utilized at the Gauss point of the FEM. Then, the multiscale approach is used to simulate a three-dimensional triaxial test and a plain-strain footing. On the basis of the simulations, material instabilities are analyzed at both mesoscale and global scale. The second-order work criterion is then used to analyze the numerical results. It opens a road to interpret and understand the micromechanisms hiding behind the occurrence of failure in geotechnical issues.     

A multi‐method approach to dating the burial and skeleton of Kiacatoo Man,New South Wales,Australia

Kiacatoo Man, a large, rugged Aboriginal adult buried in the Lachlan riverine plains of southeastern Australia, was discovered in 2011. Laser‐ablation uranium series analysis on bone yielded a minimum age for the burial of 27.4 ± 0.4 ka (2σ). Single‐grain, optically stimulated luminescence ages on quartz sediment in which the grave had been dug gave a weighted mean age of 26.4 ± 1.5 ka (1σ). Luminescence samples from the grave infill and from sediment beneath the grave exhibit overdispersed dose distributions consistent with bioturbation or other disturbance, which has obscured the burial signal. The overlap between the minimum (U‐series) and maximum (luminescence) ages places the burial between 27.0 and 29.4 ka (2σ). Luminescence ages obtained from the channel belt of between 28 ± 2 and 25 ± 3 ka indicate that fluvial sedimentation was occurring before the Last Glacial Maximum, which is consistent with the broader geomorphic setting. Together, these results are internally and regionally consistent, and indicate that Kiacatoo Man was one of the more ancient individuals so far identified in Australia. His remains are important to our understanding of patterns of biological variation and other processes that have shaped people in the Murray‐Darling Basin through time. Copyright © 2019 John Wiley & Sons, Ltd.     

Solution for a plane strain rough‐walled hydraulic fracture driven by turbulent fluid through impermeable rock

The impact of turbulent flow on plane strain fluid‐driven crack propagation is an important but still poorly understood consideration in hydraulic fracture modeling. The changes that hydraulic fracturing has experienced over the past decade, especially in the area of fracturing fluids, have played a major role in the transition of the typical fluid regime from laminar to turbulent flow. Motivated by the increasing preponderance of high‐rate, water‐driven hydraulic fractures with high Reynolds number, we present a semianalytical solution for the propagation of a plane strain hydraulic fracture driven by a turbulent fluid in an impermeable formation. The formulation uses a power law relationship between the Darcy‐Weisbach friction factor and the scale of the fracture roughness, where one specific manifestation of this generalized friction factor is the classical Gauckler‐Manning‐Strickler approximation for turbulent flow in a rough‐walled channel. Conservation of mass, elasticity, and crack propagation are also solved simultaneously. We obtain a semianalytical solution using an orthogonal polynomial series. An approximate closed‐form solution is enabled by a choice of orthogonal polynomials embedding the near‐tip asymptotic behavior and thus giving very rapid convergence; a precise solution is obtained with 2 terms of the series. By comparison with numerical simulations, we show that the transition region between the laminar and turbulent regimes can be relatively small so that full solutions can often be well approximated by either a fully laminar or fully turbulent solution.