Back-trajectories Show Export of Airborne Fungal Spores (Ganoderma sp.) From Forests to Agricultural and Urban Areas in England

We propose here the hypothesis that all of United Kingdom (UK) is likely to be affected by Ganoderma sp. spores, an important plant pathogen. We suggest that the main sources of this pathogen, which acts as a bioaerosol, are the widely scattered woodlands in the country, although remote sources must not be neglected. The hypothesis is based on related studies on bioaerosols and supported by new observations from a non-forest site and model calculations to support our hypothesis. Hourly concentrations of Ganoderma sp. spores were measured from 2006 to 2010 using a 7-day volumetric spore trap at the city of Worcester. The concentrations peak during the night and early in the morning. This suggests that the main spore sources are located a few hours away with respect to air masses transport and reach urban areas thanks to air masses transport. The back-trajectory analysis was applied to determine the location of Ganoderma sp. spore sources. The analysis of back-trajectories demonstrated that 78% of the air masses reached Worcester from a 180° arc direction from the East to West. Three episodes were selected for detailed investigation and they revealed that during the episodes air masses always passed main UK woodlands before the arrival in Worcester, independently of their origin, but the long distance transport under certain conditions might be possible. Our studies suggest that the sources of UK Ganoderma sp. spores are mainly to be found in UK. Hence our studies suggest that research and mitigation strategies in UK should give their main attention to national sources, without neglecting the contribution from long distance transport.

Small farmers and sustainability: institutional barriers to investment and innovation in the Malaysian palm oil industry in Sabah

The Malaysian palm oil industry is well known for the social, environmental and sustainability challenges associated with its rapid growth over the past ten years. Technologies exist to reduce the conflict between national development aims of economic uplift for the rural poor, on the one hand, and ecological conservation, on the other hand, by raising yields and incomes from areas already under cultivation. But the uptake of these technologies has been slow, particularly in the smallholder sector. In this paper we explore the societal and institutional challenges that influence the investment and innovation decisions of micro and small enterprise (MSE) palm oil smallholders in Sabah, Malaysia. Based on interviews with 38 smallholders, we identify a number of factors that reduce the smallholders' propensity to invest in more sustainable practices. We discuss why more effective practices and innovations are not being adopted using the concepts of, firstly, institutional logics to explore the internal dynamics of smallholder production systems, including attitudes to sustainability and innovation; and, secondly, institutional context to explore the pressures the smallholders face, including problems of access to land, labour, capital, knowledge and technical resources. These factors include limited access to global market information, corruption and uncertainties of legal title, weak economic status and social exclusion. In discussing these factors we seek to contribute to wider theoretical debates about the factors that block innovation and investment in business improvements in marginal regions and in marginalised groups.

Planeamento espacial marinho das áreas marinhas protegidas: o caso de estudo da ára protegida de gestão de recursos: Caloura - ilhéu de Vila Franca do Campo

Tese de Doutoramento, Ciências do Mar (Ecologia Marinha), 26 de Novembro de 2013, Universidade dos Açores.

Land cover mapping analysis and urban growth modeling using remote sensing techniques

The rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urban growth in Greater Cairo Region (GCR) as one of the fast growing mega cities in the world using remote sensing data. Knowing the current and estimated urbanization situation in GCR will help decision makers in Egypt to adjust their plans and develop new ones. These plans should focus on resources reallocation to overcome the problems arising in the future and to achieve a sustainable development of urban areas, especially after the high percentage of illegal settlements which took place in the last decades. The study focused on a period of 30 years; from 1984 to 2014, and the major transitions to urban were modelled to predict the future scenarios in 2025. Three satellite images of different time stamps (1984, 2003 and 2014) were classified using Support Vector Machines (SVM) classifier, then the land cover changes were detected by applying a high level mapping technique. Later the results were analyzed for higher accurate estimations of the urban growth in the future in 2025 using Land Change Modeler (LCM) embedded in IDRISI software. Moreover, the spatial and temporal urban growth patterns were analyzed using statistical metrics developed in FRAGSTATS software. The study resulted in an overall classification accuracy of 96%, 97.3% and 96.3% for 1984, 2003 and 2014’s map, respectively. Between 1984 and 2003, 19 179 hectares of vegetation and 21 417 hectares of desert changed to urban, while from 2003 to 2014, the transitions to urban from both land cover classes were found to be 16 486 and 31 045 hectares, respectively. The model results indicated that 14% of the vegetation and 4% of the desert in 2014 will turn into urban in 2025, representing 16 512 and 24 687 hectares, respectively.

Analysis of temporal and spatial variations of forest. A case of study in notheastern Armenia

The forest has a crucial ecological role and the continuous forest loss can cause colossal effects on the environment. As Armenia is one of the low forest covered countries in the world, this problem is more critical. Continuous forest disturbances mainly caused by illegal logging started from the early 1990s had a huge damage on the forest ecosystem by decreasing the forest productivity and making more areas vulnerable to erosion. Another aspect of the Armenian forest is the lack of continuous monitoring and absence of accurate estimation of the level of cuts in some years. In order to have insight about the forest and the disturbances in the long period of time we used Landsat TM/ETM + images. Google Earth Engine JavaScript API was used, which is an online tool enabling the access and analysis of a great amount of satellite imagery. To overcome the data availability problem caused by the gap in the Landsat series in 1988- 1998, extensive cloud cover in the study area and the missing scan lines, we used pixel based compositing for the temporal window of leaf on vegetation (June-late September). Subsequently, pixel based linear regression analyses were performed. Vegetation indices derived from the 10 biannual composites for the years 1984-2014 were used for trend analysis. In order to derive the disturbances only in forests, forest cover layer was aggregated and the original composites were masked. It has been found, that around 23% of forests were disturbed during the study period.

Facies, depositional environment, and palaeoecology of the Middle Triassic Cassina Beds (Meride Limestone, Monte San Giorgio, Switzerland).

The Ladinian Cassina beds belong to the fossiliferous levels of the world-famous Middle Triassic Monte San Giorgio Lagerstatte (UNESCO World Heritage List, Canton Ticino, Southern Alps). Although they are a rich archive for the depositional environment of an important thanatocoenosis, previous excavations focused on vertebrates and particularly on marine reptiles. In 2006, the Museo Cantonale di Storia Naturale (Lugano) started a new research project focusing for the first time on microfacies, micropalaeontological, palaeoecological and taphonomic analyses. So far, the upper third of the sequence has been excavated on a surface of around 40 m(2), and these new data complete those derived from new vertebrate finds (mainly fishes belonging to Saurichthys, Archaeosemionotus, Eosemionotus and Peltopleurus), allowing a better characterization of the basin. Background sedimentation on an anoxic to episodically suboxic seafloor resulted in a finely laminated succession of black shales and limestones, bearing a quasi-anaerobic biofacies, which is characterized by a monotypic benthic foraminiferal meiofauna and has been documented for the first time from the whole Monte San Giorgio sequence. Event deposition, testified by turbidites and volcaniclastic layers, is related to sediment input from basin margins and to distant volcanic eruptions, respectively. Fossil nekton points to an environment with only limited connection to the open sea. Terrestrial macroflora remains document the presence of emerged areas covered with vegetation and probably located relatively far away. Proliferation of benthic microbial mats is inferred on the basis of microfabrics, ecological considerations and taphonomic (both biostratinomic and diagenetic) features of the new vertebrate finds, whose excellent preservation is ascribed to sealing by biofilms. The occurrence of allochthonous elements allows an insight into the shallow-waters of the adjoining time-equivalent Salvatore platform. Finally, the available biostratigraphic data are critically reviewed.

A study of selected factors influencing the reproductive performance of the common tern (Sterna hirundo) at Port Colborne, Ontario in 1973 and 1974

Several study areas were investigated at two Port Colborne terneries during the summers of 1973 and 1974 in an attempt to determine the influence of clutch size, time of clutch initiation, position in the colony, proximity to Ring-billed Gulls, vegetation and nesting substrate on the reproductive performance of the Common Tern. Hatching success and reproductive success (the number of chicks fledged per egg laid) were generally higher for 3-egg than 2-egg clutches but fledging (the number of chicks fledged per egg hatched) success was usually independant of clutch size. Hatching, fledging and reproductive success declined as a function of time of clutch initiation. Mean clutch sizes also generally declined as a function of time. Nests located in the center of the colony exhibited higher fledging success than those on the periphery. Rock-based clutches had a lower hatching success than clutches initiated on sand or dried vegetation. Reproductive performance did not appear to be related to proximity to Ring-billed Gulls or vegetation within the study area.

Assessment of Energy Conservation in Indian Cement Industry and Forecasting of Co2 Emissions

Cement industry ranks 2nd in energy consumption among the industries in India. It is one of the major emitter of CO2, due to combustion of fossil fuel and calcination process. As the huge amount of CO2 emissions cause severe environment problems, the efficient and effective utilization of energy is a major concern in Indian cement industry. The main objective of the research work is to assess the energy cosumption and energy conservation of the Indian cement industry and to predict future trends in cement production and reduction of CO2 emissions. In order to achieve this objective, a detailed energy and exergy analysis of a typical cement plant in Kerala was carried out. The data on fuel usage, electricity consumption, amount of clinker and cement production were also collected from a few selected cement industries in India for the period 2001 - 2010 and the CO2 emissions were estimated. A complete decomposition method was used for the analysis of change in CO2 emissions during the period 2001 - 2010 by categorising the cement industries according to the specific thermal energy consumption. A basic forecasting model for the cement production trend was developed by using the system dynamic approach and the model was validated with the data collected from the selected cement industries. The cement production and CO2 emissions from the industries were also predicted with the base year as 2010. The sensitivity analysis of the forecasting model was conducted and found satisfactory. The model was then modified for the total cement production in India to predict the cement production and CO2 emissions for the next 21 years under three different scenarios. The parmeters that influence CO2 emissions like population and GDP growth rate, demand of cement and its production, clinker consumption and energy utilization are incorporated in these scenarios. The existing growth rate of the population and cement production in the year 2010 were used in the baseline scenario. In the scenario-1 (S1) the growth rate of population was assumed to be gradually decreasing and finally reach zero by the year 2030, while in scenario-2 (S2) a faster decline in the growth rate was assumed such that zero growth rate is achieved in the year 2020. The mitigation strategiesfor the reduction of CO2 emissions from the cement production were identified and analyzed in the energy management scenarioThe energy and exergy analysis of the raw mill of the cement plant revealed that the exergy utilization was worse than energy utilization. The energy analysis of the kiln system showed that around 38% of heat energy is wasted through exhaust gases of the preheater and cooler of the kiln sysetm. This could be recovered by the waste heat recovery system. A secondary insulation shell was also recommended for the kiln in the plant in order to prevent heat loss and enhance the efficiency of the plant. The decomposition analysis of the change in CO2 emissions during 2001- 2010 showed that the activity effect was the main factor for CO2 emissions for the cement industries since it is directly dependent on economic growth of the country. The forecasting model showed that 15.22% and 29.44% of CO2 emissions reduction can be achieved by the year 2030 in scenario- (S1) and scenario-2 (S2) respectively. In analysing the energy management scenario, it was assumed that 25% of electrical energy supply to the cement plants is replaced by renewable energy. The analysis revealed that the recovery of waste heat and the use of renewable energy could lead to decline in CO2 emissions 7.1% for baseline scenario, 10.9 % in scenario-1 (S1) and 11.16% in scenario-2 (S2) in 2030. The combined scenario considering population stabilization by the year 2020, 25% of contribution from renewable energy sources of the cement industry and 38% thermal energy from the waste heat streams shows that CO2 emissions from Indian cement industry could be reduced by nearly 37% in the year 2030. This would reduce a substantial level of greenhouse gas load to the environment. The cement industry will remain one of the critical sectors for India to meet its CO2 emissions reduction target. India’s cement production will continue to grow in the near future due to its GDP growth. The control of population, improvement in plant efficiency and use of renewable energy are the important options for the mitigation of CO2 emissions from Indian cement industries

Ayer mineros, hoy eco-guías y concesionarios: tensiones en torno a la conservación ambiental, el uso de la tierra y el trabajo en Guasca, Cundinamarca

En Guasca, Cundinamarca, se han configurado cambios profundos en el uso de los recursos naturales y el trabajo. En la misma área donde operó una mina de cal a cielo abierto por más de sesenta años, hoy en día existe una reserva biológica. Este proceso ha conllevado transformaciones y negociaciones entre las formas locales de uso de los recursos naturales y los usos propuestos por la conservación ambiental. Por su parte, el trabajo en la vereda se ha visto afectado por el cambio reciente en el usufructo de los recursos ambientales y las precariedades económicas del agro en Colombia. El argumento central de este texto es que la declaratoria de áreas protegidas privadas, como práctica suscrita al discurso ambientalista global, más que un proceso neutro, es una fuente de tensión constante entre pobladores locales y administradores de las zonas de conservación ecológica por cuenta del manejo territorial y ambiental, el entendimiento del uso de los recursos naturales y la naturaleza, la propiedad, el empleo y la descentralización del poder estatal. Así las cosas, este trabajo se preocupa por analizar las tensiones e implicaciones que supone la declaratoria de áreas protegidas para las poblaciones locales, en particular en su economía, trabajo y formas de apropiarse de la naturaleza y sus recursos.

Forest Policy Scenario Analysis: Sensitivity of Songbird Community to Changes in Forest Cover Amount and Configuration

Changes in mature forest cover amount, composition, and configuration can be of significant consequence to wildlife populations. The response of wildlife to forest patterns is of concern to forest managers because it lies at the heart of such competing approaches to forest planning as aggregated vs. dispersed harvest block layouts. In this study, we developed a species assessment framework to evaluate the outcomes of forest management scenarios on biodiversity conservation objectives. Scenarios were assessed in the context of a broad range of forest structures and patterns that would be expected to occur under natural disturbance and succession processes. Spatial habitat models were used to predict the effects of varying degrees of mature forest cover amount, composition, and configuration on habitat occupancy for a set of 13 focal songbird species. We used a spatially explicit harvest scheduling program to model forest management options and simulate future forest conditions resulting from alternative forest management scenarios, and used a process-based fire-simulation model to simulate future forest conditions resulting from natural wildfire disturbance. Spatial pattern signatures were derived for both habitat occupancy and forest conditions, and these were placed in the context of the simulated range of natural variation. Strategic policy analyses were set in the context of current Ontario forest management policies. This included use of sequential time-restricted harvest blocks (created for Woodland caribou (Rangifer tarandus) conservation) and delayed harvest areas (created for American marten (Martes americana atrata) conservation). This approach increased the realism of the analysis, but reduced the generality of interpretations. We found that forest management options that create linear strips of old forest deviate the most from simulated natural patterns, and had the greatest negative effects on habitat occupancy, whereas policy options that specify deferment and timing of harvest for large blocks helped ensure the stable presence of an intact mature forest matrix over time. The management scenario that focused on maintaining compositional targets best supported biodiversity objectives by providing the composition patterns required by the 13 focal species, but this scenario may be improved by adding some broad-scale spatial objectives to better maintain large blocks of interior forest habitat through time.

Assessing range-wide habitat suitability for the Lesser Prairie-Chicken

Population declines of many wildlife species have been linked to habitat loss incurred through land-use change. Incorporation of conservation planning into development planning may mitigate these impacts. The threatened Lesser Prairie-Chicken (Tympanuchus pallidicinctus) is experiencing loss of native habitat and high levels of energy development across its multijurisdictional range. Our goal was to explore relationships of the species occurrence with landscape characteristics and anthropogenic effects influencing its distribution through evaluation of habitat suitability associated with one particular habitat usage, lekking. Lekking has been relatively well-surveyed, though not consistently, in all jurisdictions. All five states in which Lesser Prairie-Chickens occur cooperated in development of a Maxent habitat suitability model. We created two models, one with state as a factor and one without state. When state was included it was the most important predictor, followed by percent of land cover consisting of known or suspected used vegetation classes within a 5000 m area around a lek. Without state, land cover was the most important predictor of relative habitat suitability for leks. Among the anthropogenic predictors, landscape condition, a measure of human impact integrated across several factors, was most important, ranking third in importance without state. These results quantify the relative suitability of the landscape within the current occupied range of Lesser Prairie-Chickens. These models, combined with other landscape information, form the basis of a habitat assessment tool that can be used to guide siting of development projects and targeting of areas for conservation.

Detection of flood extent in urban areas using high resolution TerraSAR-X data

Flooding is a major hazard in both rural and urban areas worldwide, but it is in urban areas that the impacts are most severe. An investigation of the ability of high resolution TerraSAR-X data to detect flooded regions in urban areas is described. An important application for this would be the calibration and validation of the flood extent predicted by an urban flood inundation model. To date, research on such models has been hampered by lack of suitable distributed validation data. The study uses a 3m resolution TerraSAR-X image of a 1-in-150 year flood near Tewkesbury, UK, in 2007, for which contemporaneous aerial photography exists for validation. The DLR SETES SAR simulator was used in conjunction with airborne LiDAR data to estimate regions of the TerraSAR-X image in which water would not be visible due to radar shadow or layover caused by buildings and taller vegetation, and these regions were masked out in the flood detection process. A semi-automatic algorithm for the detection of floodwater was developed, based on a hybrid approach. Flooding in rural areas adjacent to the urban areas was detected using an active contour model (snake) region-growing algorithm seeded using the un-flooded river channel network, which was applied to the TerraSAR-X image fused with the LiDAR DTM to ensure the smooth variation of heights along the reach. A simpler region-growing approach was used in the urban areas, which was initialized using knowledge of the flood waterline in the rural areas. Seed pixels having low backscatter were identified in the urban areas using supervised classification based on training areas for water taken from the rural flood, and non-water taken from the higher urban areas. Seed pixels were required to have heights less than a spatially-varying height threshold determined from nearby rural waterline heights. Seed pixels were clustered into urban flood regions based on their close proximity, rather than requiring that all pixels in the region should have low backscatter. This approach was taken because it appeared that urban water backscatter values were corrupted in some pixels, perhaps due to contributions from side-lobes of strong reflectors nearby. The TerraSAR-X urban flood extent was validated using the flood extent visible in the aerial photos. It turned out that 76% of the urban water pixels visible to TerraSAR-X were correctly detected, with an associated false positive rate of 25%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 58% and 19% respectively. These findings indicate that TerraSAR-X is capable of providing useful data for the calibration and validation of urban flood inundation models.

Predicted soil organic carbon stocks and changes in the Brazilian Amazon between 2000 and 2030

Currently we have little understanding of the impacts of land use change on soil C stocks in the Brazilian Amazon. Such information is needed to determine impacts'6n the global C cycle and the sustainability of agricultural systems that are replacing native forest. The aim of this study was to predict soil carbon stocks and changes in the Brazilian Amazon during the period between 2000 and 2030, using the GEFSOC soil carbon (C) modelling system. In order to do so, we devised current and future land use scenarios for the Brazilian Amazon, taking into account: (i) deforestation, rates from the past three decades, (ii) census data on land use from 1940 to 2000, including the expansion and intensification of agriculture in the region, (iii) available information on management practices, primarily related to well managed pasture versus degraded pasture and conventional systems versus no-tillage systems for soybean (Glycine max) and (iv) FAO predictions on agricultural land use and land use changes for the years 2015 and 2030. The land use scenarios were integrated with spatially explicit soils data (SOTER database), climate, potential natural vegetation and land management units using the recently developed GEFSOC soil C modelling system. Results are presented in map, table and graph form for the entire Brazilian Amazon for the current situation (1990 and 2000) and the future (2015 and 2030). Results include soil organic C (SOC) stocks and SOC stock change rates estimated by three methods: (i) the Century ecosystem model, (ii) the Rothamsted C model and (iii) the intergovernmental panel on climate change (IPCC) method for assessing soil C at regional scale. In addition, we show estimated values of above and belowground biomass for native vegetation, pasture and soybean. The results on regional SOC stocks compare reasonably well with those based on mapping approaches. The GEFSOC system provided a means of efficiently handling complex interactions among biotic-edapho-climatic conditions (> 363,000 combinations) in a very large area (similar to 500 Mha) such as the Brazilian Amazon. All of the methods used showed a decline in SOC stock for the period studied; Century and RothC simulated values for 2030 being about 7% lower than those in 1990. Values from Century and RothC (30,430 and 25,000 Tg for the 0-20 cm layer for the Brazilian Amazon region were higher than those obtained from the IPCC system (23,400 Tg in the 0-30 cm layer). Finally; our results can help understand the major biogeochemical cycles that influence soil fertility and help devise management strategies that enhance the sustainability of these areas and thus slow further deforestation. (C) 2007 Elsevier B.V. All rights reserved.

Mediterranean ecosystems: problems and tools for conservation

Mediterranean ecosystems rival tropical ecosystems in terms of plant biodiversity. The Mediterranean Basin (MB) itself hosts 25 000 plant species, half of which are endemic. This rich biodiversity and the complex biogeographical and political issues make conservation a difficult task in the region. Species, habitat, ecosystem and landscape approaches have been used to identify conservation targets at various scales: ie, European, national, regional and local. Conservation decisions require adequate information at the species, community and habitat level. Nevertheless and despite recent improvements/efforts, this information is still incomplete, fragmented and varies from one country to another. This paper reviews the biogeographic data, the problems arising from current conservation efforts and methods for the conservation assessment and prioritization using GIS. GIS has an important role to play for managing spatial and attribute information on the ecosystems of the MB and to facilitate interactions with existing databases. Where limited information is available it can be used for prediction when directly or indirectly linked to externally built models. As well as being a predictive tool today GIS incorporate spatial techniques which can improve the level of information such as fuzzy logic, geostatistics, or provide insight about landscape changes such as 3D visualization. Where there are limited resources it can assist with identifying sites of conservation priority or the resolution of environmental conflicts (scenario building). Although not a panacea, GIS is an invaluable tool for improving the understanding of Mediterranean ecosystems and their dynamics and for practical management in a region that is under increasing pressure from human impact.

Improving flood models using LiDAR: progress and problems

Airborne scanning laser altimetry (LiDAR) is an important new data source for river flood modelling. LiDAR can give dense and accurate DTMs of floodplains for use as model bathymetry. Spatial resolutions of 0.5m or less are possible, with a height accuracy of 0.15m. LiDAR gives a Digital Surface Model (DSM), so vegetation removal software (e.g. TERRASCAN) must be used to obtain a DTM. An example used to illustrate the current state of the art will be the LiDAR data provided by the EA, which has been processed by their in-house software to convert the raw data to a ground DTM and separate vegetation height map. Their method distinguishes trees from buildings on the basis of object size. EA data products include the DTM with or without buildings removed, a vegetation height map, a DTM with bridges removed, etc. Most vegetation removal software ignores short vegetation less than say 1m high. We have attempted to extend vegetation height measurement to short vegetation using local height texture. Typically most of a floodplain may be covered in such vegetation. The idea is to assign friction coefficients depending on local vegetation height, so that friction is spatially varying. This obviates the need to calibrate a global floodplain friction coefficient. It’s not clear at present if the method is useful, but it’s worth testing further. The LiDAR DTM is usually determined by looking for local minima in the raw data, then interpolating between these to form a space-filling height surface. This is a low pass filtering operation, in which objects of high spatial frequency such as buildings, river embankments and walls may be incorrectly classed as vegetation. The problem is particularly acute in urban areas. A solution may be to apply pattern recognition techniques to LiDAR height data fused with other data types such as LiDAR intensity or multispectral CASI data. We are attempting to use digital map data (Mastermap structured topography data) to help to distinguish buildings from trees, and roads from areas of short vegetation. The problems involved in doing this will be discussed. A related problem of how best to merge historic river cross-section data with a LiDAR DTM will also be considered. LiDAR data may also be used to help generate a finite element mesh. In rural area we have decomposed a floodplain mesh according to taller vegetation features such as hedges and trees, so that e.g. hedge elements can be assigned higher friction coefficients than those in adjacent fields. We are attempting to extend this approach to urban area, so that the mesh is decomposed in the vicinity of buildings, roads, etc as well as trees and hedges. A dominant points algorithm is used to identify points of high curvature on a building or road, which act as initial nodes in the meshing process. A difficulty is that the resulting mesh may contain a very large number of nodes. However, the mesh generated may be useful to allow a high resolution FE model to act as a benchmark for a more practical lower resolution model. A further problem discussed will be how best to exploit data redundancy due to the high resolution of the LiDAR compared to that of a typical flood model. Problems occur if features have dimensions smaller than the model cell size e.g. for a 5m-wide embankment within a raster grid model with 15m cell size, the maximum height of the embankment locally could be assigned to each cell covering the embankment. But how could a 5m-wide ditch be represented? Again, this redundancy has been exploited to improve wetting/drying algorithms using the sub-grid-scale LiDAR heights within finite elements at the waterline.