Upstream and downstream controls of recent avulsions on the Taquari megafan,Pantanal, south‐western Brazil

Avulsion, the natural relocation of a river, is a key process in the evolution of subaerial fans, river floodplains and deltas. The causes of avulsion are poorly understood, which is partly due to the scarcity of field studies of present avulsions. At present, two avulsions are occurring on the middle and lower Taquari megafan, Pantanal basin, south‐western Brazil. Here we present an analysis of the causes of these avulsions based on field and remote sensing data and show that avulsions on megafans can be controlled by both upstream and downstream processes. The middle fan avulsion (started in 1997–1998) is a result of upstream control: overbank aggradation was caused by the (variable) input of sandy sediment into the system, which caused channel‐belt superelevation and also created an easily erodible subsurface favouring bank retreat, crevassing, and scour of deep floodplain channels. The sandy subsurface in this area is inferred to have been a major factor in the causation of this avulsion under conditions of little gradient advantage. The lower fan avulsion (started c. 1990) results from interplay of upstream and downstream controls, the latter being related to the local base level (the Paraguay River floodplain) at the toe of the fan. Channel and overbank aggradation on the lower fan was influenced by fan sub‐lobe progradation and channel backfilling. Fan sub‐lobe progradation caused a significant gradient advantage of the avulsion channel over the parent channel. Avulsions are commonly supposed to be preferentially triggered by high‐magnitude floods, when there is considerable channel‐belt superelevation. However, both avulsions studied by us were triggered by small to average floods, with modest channel‐belt superelevation. We conclude that flood magnitude and channel‐belt superelevation have been overrated as causes of avulsion, and demonstrate additional causes that influence the growth of crevasses into avulsions. Copyright © 2012 John Wiley & Sons, Ltd.     

Hydraulic and sedimentary processes causing anastomosing morphology of the upper Columbia River, British Columbia, Canada

The upper Columbia River, British Columbia, Canada, shows typical anastomosing morphology — multiple interconnected channels that enclose floodbasins — and lateral channel stability. We analysed field data on hydraulic and sedimentary processes and show that the anastomosing morphology of the upper Columbia River is caused by sediment (bedload) transport inefficiency, in combination with very limited potential for lateral bank erosion because of very low specific stream power (≤ 2.3 W/m²) and cohesive silty banks. In a diagram of channel type in relation to flow energy and median grain size of the bed material, data points for the straight upper Columbia River channels cluster separately from the data points for braided and meandering channels. Measurements and calculations indicate that bedload transport in the anastomosing reach of the upper Columbia River decreases downstream. Because of lateral channel stability no lateral storage capacity for bedload is created. Therefore, the surplus of bedload leads to channel bed aggradation, which outpaces levee accretion and causes avulsions because of loss of channel flow capacity. This avulsion mechanism applies only to the main channel of the system, which transports 87% of the water and > 90% of the sediment in the cross-valley transect studied. Because of very low sediment transport capacity, the morphological evolution of most secondary channels is slow. Measurements and calculations indicate that much more bedload is sequestered in the relatively steep upper anastomosing reach of the upper Columbia River than in the relatively gentle lower anastomosing reach. With anastomosing morphology and related processes (e.g., crevassing) being best developed in the upper reach, this confirms the notion of upstream rather than downstream control of upper Columbia River anastomosis.     

Methodological framework to select plant species for controlling rill and gully erosion: application to a Mediterranean ecosystem

Many studies attribute the effects of vegetation in reducing soil erosion rates to the effects of the above‐ground biomass. The effects of roots on topsoil resistance against concentrated flow erosion are much less studied. However, in a Mediterranean context, where the above‐ground biomass can temporarily disappear because of fire, drought or overgrazing, and when concentrated flow erosion occurs, roots can play an important role in controlling soil erosion rates. Unfortunately, information on Mediterranean plant characteristics, especially root characteristics, growing on semi‐natural lands, and knowledge of their suitability for gully erosion control is often lacking. A methodological framework to evaluate plant traits for this purpose is absent as well. This paper presents a methodology to assess the suitability of plants for rill and gully erosion control and its application to 25 plant species, representative for a semi‐arid Mediterranean landscape in southeast Spain. In this analysis determination of suitable plants for controlling concentrated flow erosion is based on a multi‐criteria analysis. First, four main criteria were determined, i.e. (1) the potential of plants to prevent incision by concentrated flow erosion, (2) the potential of plants to improve slope stability, (3) the resistance of plants to bending by water flow and (4) the ability of plants to trap sediments and organic debris. Then, an indicator or a combination of two indicators was used to assess the scores for the four criteria. In total, five indicators were selected, i.e. additional root cohesion, plant stiffness, stem density, the erosion‐reducing potential during concentrated flow and the sediment and organic debris obstruction potential. Both above‐ and below‐ground plant traits were taken into account and measured to assess the scores for the five indicators, i.e. stem density, sediment and organic debris obstruction potential, modulus of elasticity of the stems, moment of inertia of the stems, root density, root diameter distribution, root area ratio and root tensile strength. The scores for the indicators were represented on amoeba diagrams, indicating the beneficial and the weak plant traits, regarding to erosion control. The grasses Stipa tenacissima L. and Lygeum spartum L. and the shrub Salsola genistoides Juss. Ex Poir. amongst others, were selected as very suitable plant species for rill and gully erosion control. Stipa tenacissima can be used to re‐vegetate abandoned terraces as this species is adapted to drought and offers a good protection to concentrated flow erosion and shallow mass movements. Lygeum spartum can be used to vegetate concentrated flow zones or to obstruct sediment inflow to channels at gully outlets. Stipa tenacissima and Salsola genistoides can be used to stabilize steep south‐facing slopes. The methodology developed in this study can be applied to other plant species in areas suffering from rill and gully erosion. Copyright © 2009 John Wiley & Sons, Ltd.     

Prediction of Indoor Air Quality from Soil-Gas Data at Industrial Buildings

Subslab or shallow soil-gas data are often compared with indoor air concentration data in vapor intrusion (VI) evaluations. If no indoor air data are available or confounding sources are present, or if future scenarios are considered, the soil-gas data may be used to estimate the indoor air concentrations due to VI. The typical approach in risk assessments is to use the 95th percentile values from a set of concentration data. For VI studies, however, this rarely is an option because the data sets tend to be quite small. Therefore, various guidance documents urge the use of maximum soil-gas values. This may be reasonable for small residential buildings, but can lead to very conservatively biased estimates if applied to large industrial buildings with localized areas of contamination, especially given that the sampling locations may not be randomly selected and instead are biased toward worst-case locations. By this approach, VI guidance implicitly tolerates a large percentage of false positive decision errors to minimize the number of false negative decision errors. In this paper, implications of using maximum values are discussed and illustrated with data sets from a number of large industrial buildings at various sites. An alternative approach to using maximum soil-gas values is proposed that serves to reduce the number of false positive results while controlling the number of false negatives to an acceptable level.     

Evaluation of a global ensemble flood prediction system in Peru

ABSTRACT

Flood early warning systems play a more substantial role in risk mitigation than ever before. Hydrological forecasts, which are an essential part of these systems, are used to trigger action against floods around the world. This research presents an evaluation framework, where the skills of the Global Flood Awareness System (GloFAS) are assessed in Peru for the years 2009–2015. Simulated GloFAS discharges are compared against observed ones for 10 river gauges. Forecasts skills are assessed from two perspectives: (i) by calculating verification scores at every river section against simulated discharges and (ii) by comparing the flood signals against reported events. On average, river sections with higher discharges and larger upstream areas perform better. Raw forecasts provide correct flood signals for 82% of the reported floods, but exhibit low verification scores. Post-processing of raw forecasts improves most verification scores, but reduces the percentage of the correctly forecasted reported events to 65%.     

Estimation of Hydraulic Conductivity and Its Uncertainty from Grain-Size Data Using GLUE and Artificial Neural Networks

Various approaches exist to relate saturated hydraulic conductivity (K _s) to grain-size data. Most methods use a single grain-size parameter and hence omit the information encompassed by the entire grain-size distribution. This study compares two data-driven modelling methods??multiple linear regression and artificial neural networks??that use the entire grain-size distribution data as input for K _s prediction. Besides the predictive capacity of the methods, the uncertainty associated with the model predictions is also evaluated, since such information is important for stochastic groundwater flow and contaminant transport modelling. Artificial neural networks (ANNs) are combined with a generalised likelihood uncertainty estimation (GLUE) approach to predict K _s from grain-size data. The resulting GLUE-ANN hydraulic conductivity predictions and associated uncertainty estimates are compared with those obtained from the multiple linear regression models by a leave-one-out cross-validation. The GLUE-ANN ensemble prediction proved to be slightly better than multiple linear regression. The prediction uncertainty, however, was reduced by half an order of magnitude on average, and decreased at most by an order of magnitude. This demonstrates that the proposed method outperforms classical data-driven modelling techniques. Moreover, a comparison with methods from the literature demonstrates the importance of site-specific calibration. The data set used for this purpose originates mainly from unconsolidated sandy sediments of the Neogene aquifer, northern Belgium. The proposed predictive models are developed for 173 grain-size K _s-pairs. Finally, an application with the optimised models is presented for a borehole lacking K _s data.     

Flood disaster subcultures in The Netherlands: the parishes of Borgharen and Itteren

The Netherlands knows a persistent threat of flooding. To adapt to this dangerous reality, the Dutch have cultivated what disaster research literature has labeled ‘disaster subcultures’ or a set of cultural (tangible and intangible) tools to deal with the recurrent hazard. While there is abundant attention for the way the Dutch ‘coastal’ and ‘low-lying’ communities deal with the recurrent threat of (coastal) flooding, less is known about the way the Dutch ‘high-lands’ deal with the yearly threat of (fluvial) flooding. This article presents the findings of an explorative research endeavor (2011–2013) aimed at discerning if the disaster subculture concept has contemporary relevance in the Netherlands, particularly with respect to flooding, and if so, whether applying this lens would reveal more about the nature of existing disaster subcultures. Because less is known about the Dutch ‘high-lands,’ we chose to look into the existence and attributes of disaster subcultures in the parishes Borgharen and Itteren, which experience a systematic threat of flooding. Our findings suggest that the disaster subculture lens is valuable as it enables the empirical appreciation of disaster subcultures, even in a small country like the Netherlands, and it unveiled elements of these neighboring parishes’ flood reality that otherwise might have gone unnoticed and that seem central to understanding these two parishes’ levels of vulnerability and resilience. It is our contention that the concept ‘disaster subculture’ makes a greater understanding possible of the cultural context from which vulnerability and resilience to specific and recurrent threats emerge.     

A Temporal Variant‐Invariant Validation Approach for Agent‐based Models of Landscape Dynamics

Agent‐based modeling provides a means for addressing the way human and natural systems interact to change landscapes over time. Until recently, evaluation of simulation models has focused on map comparison techniques that evaluate the degree to which predictions match real‐world observations. However, methods that change the focus of evaluation from patterns to processes have begun to surface; that is, rather than asking if a model simulates a correct pattern, models are evaluated on their ability to simulate a process of interest. We build on an existing agent‐based modeling validation method in order to present a temporal variant‐invariant analysis (TVIA). The enhanced method, which focuses on analyzing the uncertainty in simulation results, examines the degree to which outcomes from multiple model runs match some reference to how land use parcels make the transition from one land use class to another over time. We apply TVIA to results from an agent‐based model that simulates the relationships between landowner decisions and wildfire risk in the wildland‐urban interface of the southern Willamette Valley, Oregon, USA. The TVIA approach demonstrates a novel ability to examine uncertainty across time to provide an understanding of how the model emulates the system of interest.     

EPR and magnetism of the nanostructured natural carbonaceous material shungite

The X-band EPR and magnetic susceptibility in the temperature range 4.2–300 K study of the shungite-I, natural nanostructured material from the deposit of Shunga are reported. Obtained results allow us to assign the EPR signal to conduction electrons, estimate their number, N _P, and evaluate the Pauli paramagnetism contribution to shungite susceptibility. A small occupation (~5%) of the localized nonbonding π states in the zigzag edges of the open-ended graphene-like layers and/or on σ (sp ^2+x ) orbitals in the curved parts of the shungite globules has been also revealed. The observed temperature dependence of the EPR linewidth can be explained by the earlier considered interaction of conduction π electrons with local phonon modes associated with the vibration of peripheral carbon atoms of the open zigzag-type edges and with peripheral carbon atoms cross-linking different nanostructures. The relaxation time T ₂ and diffusion time T _D are found to have comparable values (2.84 × 10⁻⁸ and 1.73 × 10⁻⁸ s at 5.2 K, respectively), and similar dependence on temperature. The magnetic measurements have revealed the suppression of orbital diamagnetism due to small amount of large enough fragments of the graphene layers.