An intelligent system for vulnerability and remediation assessment of flooded residential buildings

Floods are natural phenomena which are a threat to human settlements. Flooding can result in costly repairs to buildings, loss of business and, in some cases, loss of life. The forecasts for climate change show a further increased risk of flooding in future years. Accordingly, the flooding of residential property has been observed as on the rise in the UK. It is difficult to prevent floods from occurring, but the effects of flooding can be managed in an attempt to reduce risks and costs of repair. This can be achieved through ensuring a good understanding of the problem, and thereby establishing good management systems which are capable of dealing with all aspects of the flood. The use of an intelligent system for assessment and remediation of buildings subjected to flooding damage can facilitate the management of this problem. Such a system can provide guidance for the assessment of vulnerability and the repair of flood damaged residential buildings; this could save time and money through the use of the advantages and benefits offered by knowledge base systems. A prototype knowledge base system has been developed in this research. The system comprises three subsystems: degree of vulnerability assessment subsystem; remediation options subsystem; and foundation damage assessment subsystem. The vulnerability assessment subsystem is used to calculate the degree of vulnerability, which will then be used by the remediation options subsystem to select remediation options strategy. The vulnerability assessment subsystem can subsequently be used to calculate the degree to which the building is vulnerable to damage by flooding even if it is not flooded. Remediation options subsystem recommended two strategy options: either ordinary remediation options in the case of vulnerability being low or, alternatively, resilience remediation options in the case of vulnerability being high. The foundation damage assessment subsystem is working alone and is used to assess the damage caused by flooding to the building s foundation, and to thereby recommend a repair option based on the damage caused and foundation type. The system has been developed based on the knowledge acquired from different sources and methods, including survey questionnaires, documents, interviews, and workshops. The system is then evaluated by experts and professionals in the industry. The developed system makes a contribution in the management and standardisation of residential building flooded damage and repair

Soil erosion on arable land: an unresolved global environmental threat

Rationale and scope: Although soil erosion was recognised as a serious problem in antiquity and research into erosion started in the early 20th century, it remains a substantial problem for agriculture and the environment across the globe. It disrupts agricultural production, threatening food production, increases the severity of floods and droughts and impacts on soil biology and biogeochemical cycling. This review describes the different processes and manifestations of erosion on arable land and the availability of global data. It points out that while there is a good understanding of the processes of erosion, the causes are complex and even if agronomic and landscape solutions are available, their implementation is challenging and needs tailored approaches to account for the specific local socio-economic, political, and institutional contexts

Experimental study on head loss due to cluster of randomly distributed non-uniform roughness elements in supercritical flow

Accurate estimation of head loss introduced via randomly placed roughness elements found in natural or constructed streams (e.g., fish passages) is essential in order to estimate flow variables in mountain streams, understand formation of niches for aquatic life, and model flow structure. Owing to the complexity of the involved processes and the often missing detailed data regarding the roughness elements, the head loss in such streams is mostly approximated using empirical models. In our study, we utilize flume experiments to analyze the effects of the spatial distribution of roughness elements on water surface levels and head loss and, moreover, use the produced data to test three empirical models estimating head loss. The experiments were performed in a 15 m long, 0.9 m wide flume with a slope of 5% under large Froude numbers (2.5–2.8). Flow velocities and water levels were measured with different flow rates at 58 points within a 3.96 m test section of the flume. We could show that different randomly arranged patterns of roughness elements significantly affected head loss (differences up to 33.6%), whereas water jumps occurred when flow depths were in the same size range as the roughness elements. The roughness element position and its size influenced water surface profiles. None of the three tested empirical models were able to well reproduce the differences in head loss due to the different patterns of roughness elements, with overestimated head loss from 12 to 94.7%, R2 from 41 to 73%, NSE from −21.1 to 0.09, and RRMSE from 18.4 to 93%. This generally indicates that these empirical models are conditionally suitable to consider head loss effects of random patterns of roughness elements

Does soil thinning change soil erodibility? An exploration of long-term erosion feedback systems

Soil erosion rates on arable land frequently exceed the pace at which new soil is formed. This imbalance leads to soil thinning (i.e. truncation), whereby subsoil horizons and their underlying parent material become progressively closer to the land surface. As soil erosion is a selective process and subsurface horizons often have contrasting properties to the original topsoil, truncation-induced changes to soil properties might affect erosion rates and runoff formation through a soil erosion feedback system. However, the potential interactions between soil erosion and soil truncation are poorly understood due to a lack of empirical data and the neglection of long-term erodibility dynamics in erosion simulation models. Here, we present a novel model-based exploration of the soil erosion feedback system over a period of 500 years using measured soil properties from a diversified database of 265 agricultural soil profiles in the UK. For this, we adapted the Modified Morgan–Morgan–Finney model (MMMF) to perform a modelling experiment in which topography, climate, land cover, and crop management parameters were held constant throughout the simulation period. As selective soil erosion processes removed topsoil layers, the model gradually mixed subsurface soil horizons into a 0.2 m plough layer and updated soil properties using mass-balance mixing models. Further, we estimated the uncertainty in model simulations with a forward error assessment. We found that modelled erosion rates in 99 % of the soil profiles were sensitive to truncation-induced changes in soil properties. The soil losses in all except one of the truncation-sensitive profiles displayed a decelerating trend, which depicted an exponential decay in erosion rates over the simulation period. This was largely explained by decreasing silt contents in the soil surface due to selective removal of this more erodible particle size fraction and the presence of clayey or sandy substrata. Moreover, the soil profiles displayed an increased residual stone cover, which armoured the land surface and reduced soil detachment. Contrastingly, the soils with siltier subsurface horizons continuously replenished the plough layer with readily erodible material, which prevented the decline of soil loss rates over time. Although our results are limited by the edaphoclimatic conditions represented in our data, as by our modelling assumptions, we have demonstrated how modelled soil losses can be sensitive to erosion-induced changes in soil properties. These findings are likely to affect how we calculate soil lifespans and make long-term projections of land degradation

Non-inversion conservation tillage as an underestimated driver of tillage erosion

Tillage erosion is a widely underestimated process initiating soil degradation especially in case of large agricultural fields located in rolling topography. It is often assumed that, conservation, non-inversion tillage causes less tillage erosion than conventional inversion tillage. In this study, tillage erosion was determined on three paired plots comparing non-inversion chisel versus inversion mouldboard tillage. The experiments were performed at three sites in Northeast Germany with gentle, moderate, and steep slope, while tillage depth (0.25 m) and speed (≈ 6 km h−1) were kept constant during all experiments. The results indicate that non-inversion tillage produces significantly more soil movement compared to inversion tillage. The soil translocation distance was by a factor of 1.3–2.1 larger in case of chisel tillage. The largest difference in translocation distance and tillage transport coefficient (ktil) was found on the gentle slope exhibiting the lowest soil cohesion. Our results together with an evaluation of ktil values derived from literature and standardised for 0.25 m tillage depth contradict the general assumption that non-inversion tillage reduces tillage erosion. In tillage erosion dominated areas, non-inversion tillage applied with high tillage speed and depth potentially increases tillage erosion and fails its purpose to serve as soil conservation measure

A conceptual-model-based sediment connectivity assessment for patchy agricultural catchments

The accelerated sediment supply from agricultural soils to riverine and lacustrine environments leads to negative off-site consequences. In particular, the sediment connectivity from agricultural land to surface waters is strongly affected by landscape patchiness and the linear structures that separate field parcels (e.g. roads, tracks, hedges, and grass buffer strips). Understanding the interactions between these structures and sediment transfer is therefore crucial for minimising off-site erosion impacts. Although soil erosion models can be used to understand lateral sediment transport patterns, model-based connectivity assessments are hindered by the uncertainty in model structures and input data. Specifically, the representation of linear landscape features in numerical soil redistribution models is often compromised by the spatial resolution of the input data and the quality of the process descriptions. Here we adapted the Water and Tillage Erosion Model and Sediment Delivery Model (WaTEM/SE-DEM) using high-resolution spatial data (2 m x 2 m) to analyse the sediment connectivity in a very patchy mesoscale catchment (73 km(2)) of the Swiss Plateau. We used a global sensitivity analysis to explore model structural assumptions about how linear landscape features (dis)connect the sediment cascade, which allowed us to investigate the uncertainty in the model structure. Furthermore, we compared model simulations of hillslope sediment yields from five sub-catchments to tributary sediment loads, which were calculated with long-term water discharge and suspended sediment measurements. The sensitivity analysis revealed that the assumptions about how the road network (dis)connects the sediment transfer from field blocks to water courses had a much higher impact on modelled sediment yields than the uncertainty in model parameters. Moreover, model simulations showed a higher agreement with tributary sediment loads when the road network was assumed to directly connect sediments from hillslopes to water courses. Our results ultimately illustrate how a high-density road network combined with an effective drainage system increases sediment connectivity from hillslopes to surface waters in agricultural landscapes. This further highlights the importance of considering linear landscape features and model structural uncertainty in soil erosion and sediment connectivity research

A millennium of arable land use – the long-term impact of tillage and water erosion on landscape-scale carbon dynamics

In the last decades, soils and their agricultural management have received great scientific and political attention due to their potential to act as a sink of atmospheric carbon dioxide (CO2). Agricultural management has strong potential to accelerate soil redistribution, and, therefore, it is questioned if soil redistribution processes affect this potential CO2 sink function. Most studies analysing the effect of soil redistribution upon soil organic carbon (SOC) dynamics focus on water erosion and analyse only relatively small catchments and relatively short time spans of several years to decades. The aim of this study is to widen this perspective by including tillage erosion as another important driver of soil redistribution and by performing a model-based analysis in a 200 km2 sized arable region of northeastern Germany for the period since the conversion from forest to arable land (approx. 1000 years ago). The spatially explicit soil redistribution and carbon (C) turnover model SPEROS-C was applied to simulate lateral soil and SOC redistribution and SOC turnover. The model parameterisation uncertainty was estimated by simulating different realisations of the development of agricultural management over the past millennium. The results indicate that, in young moraine areas, which are relatively dry but have been intensively used for agriculture for centuries, SOC patterns and dynamics are substantially affected by tillage-induced soil redistribution processes. To understand the landscape-scale effect of these redistribution processes on SOC dynamics, it is essential to account for long-term changes following land conversion as typical soil-erosioninduced processes, e.g. dynamic replacement, only take place after former forest soils reach a new equilibrium following conversion. Overall, it was estimated that, after 1000 years of arable land use, SOC redistribution by tillage and water results in a current-day landscape-scale C sink of up to 0.66 ‰ yr−1 of the current SOC stocks