Slope control on the frequency distribution of shallow landslides and associated soil properties,North Island,New Zealand

The extrapolation of results from field trials to larger areas of land for purposes of regional impact assessment is an important issue in geomorphology, particularly for landform properties that show high stochastic variability in space and time, such as shallow landslide erosion. It is shown in this study, that by identifying the main driver for spatial variability in shallow landslide erosion at field scales, namely slope angle, it is possible to develop a set of generic functions for assessing the impact of landslides on selected soil properties at larger spatial scales and over longer time periods. Research was conducted within an area of pastoral soft‐rock Tertiary hill country in the North Island of New Zealand that is subject to infrequent high intensity rainfall events, producing numerous landslides, most of which are smaller than several hundred square metres in size and remove soil to shallow depths. All landslides were mapped within a 0·6 km² area and registered to a high resolution (2 m) slope map to show that few landslides occur on slopes < 20° and 95% were on slopes > 24°. The areal density of landslides from all historical events showed an approximately linear increase with slope above 24°. Integrating landslide densities with soil recovery data demonstrates that the average value of a soil property fluctuates in a ‘saw‐tooth’ fashion through time with the overall shape of the curve controlled by the frequency of landslide inducing storm events and recovery rate of the soil property between events. Despite such fluctuations, there are gradual declines of 7·5% in average total carbon content of topsoil and 9·5% in average soil depth to bedrock, since the time of forest clearance. Results have application to large‐scale sediment budget and water quality models and to the New Zealand Soil Carbon Monitoring System (CMS). Copyright © 2012 John Wiley & Sons, Ltd.     

Uncertainty in floodplain delineation: expression of flood hazard and risk in a Gulf Coast watershed

This paper investigates the development of flood hazard and flood risk delineations that account for uncertainty as improvements to standard floodplain maps for coastal watersheds. Current regulatory floodplain maps for the Gulf Coastal United States present 1% flood hazards as polygon features developed using deterministic, steady‐state models that do not consider data uncertainty or natural variability of input parameters. Using the techniques presented here, a standard binary deterministic floodplain delineation is replaced with a flood inundation map showing the underlying flood hazard structure. Additionally, the hazard uncertainty is further transformed to show flood risk as a spatially distributed probable flood depth using concepts familiar to practicing engineers and software tools accepted and understood by regulators. A case study of the proposed hazard and risk assessment methodology is presented for a Gulf Coast watershed, which suggests that storm duration and stage boundary conditions are important variable parameters, whereas rainfall distribution, storm movement, and roughness coefficients contribute less variability. The floodplain with uncertainty for this coastal watershed showed the highest variability in the tidally influenced reaches and showed little variability in the inland riverine reaches. Additionally, comparison of flood hazard maps to flood risk maps shows that they are not directly correlated, as areas of high hazard do not always represent high risk. Copyright © 2012 John Wiley & Sons, Ltd.     

Plot‐scale measurement of soil erosion at the experimental area of Sparacia (southern Italy)

Obtaining good quality soil loss data from plots requires knowledge of the factors that affect natural and measurement data variability and of the erosion processes that occur on plots of different sizes. Data variability was investigated in southern Italy by collecting runoff and soil loss from four universal soil‐loss equation (USLE) plots of 176 m², 20 ‘large’ microplots (0·16 m²) and 40 ‘small’ microplots (0·04 m²). For the four most erosive events (event erosivity index, R_e ≥ 139 MJ mm ha^?1 h^?1), mean soil loss from the USLE plots was significantly correlated with R_e. Variability of soil loss measurements from microplots was five to ten times greater than that of runoff measurements. Doubling the linear size of the microplots reduced mean runoff and soil loss measurements by a factor of 2·6–2·8 and increased data variability. Using sieved soil instead of natural soil increased runoff and soil loss by a factor of 1·3–1·5. Interrill erosion was a minor part (0·1–7·1%) of rill plus interrill erosion. The developed analysis showed that the USLE scheme was usable to predict mean soil loss at plot scale in Mediterranean areas. A microplot of 0·04 m² could be used in practice to obtain field measurements of interrill soil erodibility in areas having steep slopes. Copyright © 2003 John Wiley & Sons, Ltd.     

Regional potential evapotranspiration in arid climates based on temperature,topography and calculated solar radiation

Values of evapotranspiration are required for a variety of water planning activities in arid and semi‐arid climates, yet data requirements are often large, and it is costly to obtain this information. This work presents a method where a few, readily available data (temperature, elevation) are required to estimate potential evapotranspiration (PET). A method using measured temperature and the calculated ratio of total to vertical radiation (after the work of Behnke and Maxey, 1969) to estimate monthly PET was applied for the months of April–October and compared with pan evaporation measurements. The test area used in this work was in Nevada, which has 124 weather stations that record sufficient amounts of temperature data. The calculated PET values were found to be well correlated (R²=0·940–0·983, slopes near 1·0) with mean monthly pan evaporation measurements at eight weather stations.In order to extrapolate these calculated PET values to areas without temperature measurements and to sites at differing elevations, the state was divided into five regions based on latitude, and linear regressions of PET versus elevation were calculated for each of these regions. These extrapolated PET values generally compare well with the pan evaporation measurements (R²=0·926–0·988, slopes near 1·0). The estimated values are generally somewhat lower than the pan measurements, in part because the effects of wind are not explicitly considered in the calculations, and near‐freezing temperatures result in a calculated PET of zero at higher elevations in the spring months. The calculated PET values for April–October are 84–100% of the measured pan evaporation values. Using digital elevation models in a geographical information system, calculated values were adjusted for slope and aspect, and the data were used to construct a series of maps of monthly PET. The resultant maps show a realistic distribution of regional variations in PET throughout Nevada which inversely mimics topography. The general methods described here could be used to estimate regional PET in other arid western states (e.g. New Mexico, Arizona, Utah) and arid regions world‐wide (e.g. parts of Africa). Copyright © 1999 John Wiley & Sons, Ltd.     

Mapping of erosion rates in marly badlands based on a coupling of anatomical changes in exposed roots with slope maps derived from LiDAR data

Black marls form very extensive outcrops in the Alps and constitute some of the most eroded terrains, thus causing major problems of sedimentation in artificial storage systems (e.g. reservoirs) and river systems. In the experimental catchments near Draix (France), soil erosion rates have been measured in the past at the plot scale through a detailed monitoring of surface elevation changes and at the catchment scale through continuous monitoring of sediment yield in traps at basin outlets. More recently, erosion rates have been determined by means of dendrogeomorphic techniques in three monitored catchments of the Draix basin. A total of 48 exposed roots of Scots pine have been sampled and anatomical variations in annual growth rings resulting from denudation analysed. At the plot scale, average medium‐term soil erosion rates derived from exposed roots vary between 1·8 and 13·8 mm yr^?1 (average: 5·9 mm yr^?1) and values are significantly correlated with slope angle. The dendrogeomorphic record of point‐scale soil erosion rates matches very well with soil erosion rates measured in the Draix basins. Based on the point‐scale measurements and dendrogeomorphic results obtained at the point scale, a linear regression model involving slope angle was derived and coupled to high‐resolution slope maps obtained from a LiDAR‐generated digital elevation model so as to generate high‐resolution soil erosion maps. The resulting regression model is statistically significant and average soil erosion rates obtained from the areal erosion map (5·8, 5·2 and 6·2 mm yr^?1 for the Roubine, Moulin and Laval catchments, respectively) prove to be well in concert with average annual erosion rates measured in traps at the outlet of these catchments since 1985 (6·3, 4·1 and 6·4 mm yr^?1). This contribution demonstrates that dendrogeomorphic analyses of roots clearly have significant potential and that they are a powerful tool for the quantification and mapping of soil erosion rates in areas where measurements of past erosion is lacking. Copyright © 2011 John Wiley & Sons, Ltd.     

Hillslope scale surface runoff,sediment and nutrient losses associated with tramline wheelings

Research on arable sandy loam and silty clay loam soils on 4° slopes in England has shown that tramlines (i.e. the unseeded wheeling areas used to facilitate spraying operations in cereal crops) can represent the most important pathway for phosphorus and sediment loss from moderately sloping fields. Detailed monitoring over the October–March period in winters 2005–2006 and 2006–2007 included event‐based sampling of surface runoff, suspended and particulate sediment, and dissolved and particulate phosphorus from hillslope segments (each ～300–800 m²) established in a randomized block design with four replicates of each treatment at each of two sites on lighter and heavier soils. Experimental treatments assessed losses from the cropped area without tramlines, and from the uncropped tramline area, and were compared to losses from tramlines which had been disrupted once in the autumn with a shallow tine. On the lighter soil, the effects of removal or shallow incorporation of straw residues was also determined. Research on both sandy and silty clay loam soils across two winters showed that tramline wheelings represented the dominant pathway for surface runoff and transport of sediment, phosphorus and nitrogen from cereal crops on moderate slopes. Results indicated 5·5–15·8% of rainfall lost as runoff, and losses of 0·8–2·9 kg TP ha^?1 and 0·3–4·8 t ha^?1 sediment in tramline treatments, compared to only 0·2–1·7% rainfall lost as runoff, and losses of 0·0–0·2 kg TP ha^?1 and 0·003–0·3 t ha^?1 sediment from treatments without tramlines or those where tramlines had been disrupted. The novel shallow disruption of tramline wheelings using a tine once following the autumn spray operation consistently and dramatically reduced (p < 0·001) surface runoff and loads of sediment, total nitrogen and total phosphorus to levels similar to those measured in cropped areas between tramlines. Results suggest that options for managing tramline wheelings warrant further refinement and evaluation with a view to incorporating them into spatially‐targeted farm‐level management planning using national or catchment‐based agri‐environment policy instruments aimed at reducing diffuse pollution from land to surface water systems. Copyright © 2010 John Wiley & Sons, Ltd.     

Modelling catchment‐scale erosion patterns in the East African Highlands

Prompt location of areas exposed to high erosion is of the utmost importance for soil and water conservation planning. Erosion models can be useful tools to locate sources of sediment and areas of deposition within a catchment, but the reliability of model predictions of spatial patterns of erosion at catchment scale has seldom been validated against observations. This study aimed to evaluate the performance of a simple empirical model (Morgan, Morgan and Finney model, MMF) in predicting spatial patterns of erosion at two small catchments in the East African Highlands: Kwalei (Tanzania) and Gikuuri (Kenya). Erosion maps predicted by the MMF model were compared with erosion maps obtained by direct survey. In Kwalei, erosion features were especially frequent in fields of annual crops. In Gikuuri, slope was the critical erosion factor, with estimated erosion rates >10 kg m^?2 a^?1 on slopes >18 per cent. Predicted erosion rates were mainly transport‐limited and ranged from <0·01 to 13·50 kg m^?2 a^?1 in Kwalei and 9·29 kg m^?2 a^?1 in Gikuuri. The performance of the MMF model in predicting the spatial patterns of erosion was acceptable in Kwalei, but poor in Gikuuri. However, by excluding the elements at the valley bottoms in Gikuuri Catchment, the performance of the model improved dramatically. The spatial pattern of erosion predicted by the MMF model was driven by the accumulation of surface runoff, which did not consider the possibility of re‐infiltration along the slope. As a result, the MMF erosion patterns predicted by the model increased invariably from the ridges to the valley bottoms, hampering the model suitability for locating areas subjected to high and very high erosion. It is concluded that the model predictions could be substantially improved by introducing a more realistic hydrological component for the prediction of surface runoff along the hill‐slope. Copyright © 2005 John Wiley & Sons, Ltd.     

Estimation of spatially distributed surface energy fluxes using remotely‐sensed data for agricultural fields

Land surface energy fluxes are required in many environmental studies, including hydrology, agronomy and meteorology. Surface energy balance models simulate microscale energy exchange processes between the ground surface and the atmospheric layer near ground level. Spatial variability of energy fluxes limits point measurements to be used for larger areas. Remote sensing provides the basis for spatial mapping of energy fluxes. Remote‐sensing‐based surface energy flux‐mapping was conducted using seven Landsat images from 1997 to 2002 at four contiguous crop fields located in Polk County, northwestern Minnesota. Spatially distributed surface energy fluxes were estimated and mapped at 30 m pixel level from Landsat Thematic Mapper and Enhanced Thematic Mapper images and weather information. Net radiation was determined using the surface energy balance algorithm for land (SEBAL) procedure. Applying the two‐source energy balance (TSEB) model, the surface temperature and the latent and sensible heat fluxes were partitioned into vegetation and soil components and estimated at the pixel level. Yield data for wheat and soybean from 1997 to 2002 were mapped and compared with latent heat (evapotranspiration) for four of the fields at pixel level. The spatial distribution and the relation of latent heat flux and Bowen ratio (ratio of sensible heat to latent heat) to crop yield were studied. The root‐mean‐square error and the mean absolute percentage of error between the observed and predicted energy fluxes were between 7 and 22 W m⁻² and 12 and 24% respectively. Results show that latent heat flux and Bowen ratio were correlated (positive and negative) to the yield data. Wheat and soybean yields were predicted using latent heat flux with mean R² = 0·67 and 0·70 respectively, average residual means of −4·2 bushels/acre and 0·11 bushels/acre respectively, and average residual standard deviations of 16·2 bushels/acre and 16·6 bushels/acre respectively (1 bushel/acre ≈ 0·087 m³ ha⁻¹). The flux estimation procedure from the SEBAL‐TSEB model was useful and applicable to agricultural fields. Copyright © 2005 John Wiley & Sons, Ltd.     

Active microwave remote sensing for soil moisture measurement: a field evaluation using ERS‐2

Active microwave remote sensing observations of backscattering, such as C‐band vertically polarized synthetic aperture radar (SAR) observations from the second European remote sensing (ERS‐2) satellite, have the potential to measure moisture content in a near‐surface layer of soil. However, SAR backscattering observations are highly dependent on topography, soil texture, surface roughness and soil moisture, meaning that soil moisture inversion from single frequency and polarization SAR observations is difficult. In this paper, the potential for measuring near‐surface soil moisture with the ERS‐2 satellite is explored by comparing model estimates of backscattering with ERS‐2 SAR observations. This comparison was made for two ERS‐2 overpasses coincident with near‐surface soil moisture measurements in a 6 ha catchment using 15‐cm time domain reflectometry probes on a 20 m grid. In addition, 1‐cm soil moisture data were obtained from a calibrated soil moisture model. Using state‐of‐the‐art theoretical, semi‐empirical and empirical backscattering models, it was found that using measured soil moisture and roughness data there were root mean square (RMS) errors from 3·5 to 8·5 dB and r² values from 0·00 to 0·25, depending on the backscattering model and degree of filtering. Using model soil moisture in place of measured soil moisture reduced RMS errors slightly (0·5 to 2 dB) but did not improve r² values. Likewise, using the first day of ERS‐2 backscattering and soil moisture data to solve for RMS surface roughness reduced RMS errors in backscattering for the second day to between 0·9 and 2·8 dB, but did not improve r² values. Moreover, RMS differences were as large as 3·7 dB and r² values as low as 0·53 between the various backscattering models, even when using the same data as input. These results suggest that more research is required to improve the agreement between backscattering models, and that ERS‐2 SAR data may be useful for estimating fields‐scale average soil moisture but not variations at the hillslope scale. Copyright © 2004 John Wiley & Sons, Ltd.     

Modeling and visualizing uncertainties of flood boundary delineation: algorithm for slope and DEM resolution dependencies of 1D hydraulic models

As flood inundation risk maps have become a central piece of information for both urban and risk management planning, also a need to assess the accuracies and uncertainties of these maps has emerged. Most maps show the inundation boundaries as crisp lines on visually appealing maps, whereby many planners and decision makers, among others, automatically believe the boundaries are both accurate and reliable. However, as this study shows, probably all such maps, even those that are based on high-resolution digital elevation models (DEMs), have immanent uncertainties which can be directly related to both DEM resolution and the steepness of terrain slopes perpendicular to the river flow direction. Based on a number of degenerated DEMs, covering areas along the Eskilstuna River, Sweden, these uncertainties have been quantified into an empirically-derived disparity distance equation, yielding values of distance between true and modeled inundation boundary location. Using the inundation polygon, the DEM, a value representing the DEM resolution, and the desired level of confidence as inputs in a new-developed algorithm that utilizes the disparity distance equation, the slope and DEM dependent uncertainties can be directly visualized on a map. The implications of this strategy should benefit planning and help reduce high costs of floods where infrastructure, etc., have been placed in flood-prone areas without enough consideration of map uncertainties.     

Evaluation of multiple surface soil moisture for Korean regional flux monitoring network sites: Advanced Microwave Scanning Radiometer E,land surface model,and ground measurements

In the past few decades, there have been great developments in remotely sensed soil moisture, with validation efforts using land surface models (LSMs) and ground‐based measurements, because soil moisture information is essential to understanding complex land surface–atmosphere interactions. However, the validation of remotely sensed soil moisture has been very limited because of the scarcity of the ground measurements in Korea. This study validated Advanced Microwave Scanning Radiometer E (AMSR‐E) soil moisture data with the Common Land Model (CLM), one of the most widely used LSMs, and ground‐based measurements at two Korean regional flux monitoring network sites. There was reasonable agreement regarding the different soil moisture products for monitoring temporal trends except National Snow and Ice Data Centre (NSIDC) AMSR‐E soil moisture, albeit there were essential comparison limitations by different spatial scales and soil depths. The AMSR‐E soil moisture data published by the National Aeronautics and Space Administration and Vrije Universiteit Amsterdam (VUA) showed potential to replicate temporal variability patterns (root‐mean‐square errors = 0·10–0·14 m³ m^?3 and wet BIAS = 0·09 ? 0·04 m³ m^?3) with the CLM and ground‐based measurements. However, the NSIDC AMSR‐E soil moisture was problematic because of the extremely low temporal variability and the VUA AMSR‐E soil moisture was relatively inaccurate in Gwangneung site characterized by complex geophysical conditions. Additional evaluations should be required to facilitate the use of recent and forthcoming remotely sensed soil moisture data from Soil Moisture and Ocean Salinity and Soil Moisture Active and Passive missions at representative future validation sites. Copyright © 2011 John Wiley & Sons, Ltd.     

Multitemporal ALSM change detection,sediment delivery,and process mapping at an active earthflow

Remote mapping and measurement of surface processes at high spatial resolution is among the frontiers in Earth surface process research. Remote measurements that allow meter‐scale mapping of landforms and quantification of landscape change can revolutionize the study of landscape evolution on human timescales. At Mill Gulch in northern California, USA, an active earthflow was surveyed in 2003 and 2007 by airborne laser swath mapping (ALSM), enabling meter‐scale quantification of landscape change. We calculate four‐year volumetric flux from the earthflow and compare it to long‐term catchment average erosion rates from cosmogenic radionuclide inventories from adjacent watersheds. We also present detailed maps of changing features on the earthflow, from which we can derive velocity estimates and infer dominant process. These measurements rely on proper digital elevation model (DEM) generation and a simple surface‐matching technique to align the multitemporal data in a manner that eliminates systematic error in either dataset. The mean surface elevation of the earthflow and an opposite slope that was directly influenced by the earthflow decreased 14 ± 1 mm/yr from 2003 to 2007. By making the conservative assumption that these features were the dominant contributor of sediment flux from the entire Mill Gulch drainage basin during this time interval, we calculate a minimum catchment‐averaged erosion rate of 0·30 ± 0·02 mm/yr. Analysis of beryllium‐10 (¹⁰Be) concentrations in fluvial sand from nearby Russian Gulch and the South Fork Gualala River provide catchment averaged erosion rates of 0·21 ± 0·04 and 0·23 ± 0·03 mm/yr respectively. From translated landscape features, we can infer surface velocities ranging from 0·5 m/yr in the wide upper ‘source’ portion of the flow to 5 m/yr in the narrow middle ‘transport’ portion of the flow. This study re‐affirms the importance of mass wasting processes in the sediment budgets of uplifting weak lithologies. Copyright © 2011 John Wiley & Sons, Ltd.     

Test of statistical means for the extrapolation of soil depth point information using overlays of spatial environmental data and bootstrapping techniques

Hydrological modelling depends highly on the accuracy and uncertainty of model input parameters such as soil properties. Since most of these data are field surveyed, geostatistical techniques such as kriging, classification and regression trees or more sophisticated soil‐landscape models need to be applied to interpolate point information to the area. Most of the existing interpolation techniques require a random or regular distribution of points within the study area but are not adequate to satisfactorily interpolate soil catena or transect data. The soil landscape model presented in this study is predicting soil information from transect or catena point data using a statistical mean (arithmetic, geometric and harmonic mean) to calculate the soil information based on class means of merged spatial explanatory variables. A data set of 226 soil depth measurements covering a range of 0–6·5 m was used to test the model. The point data were sampled along four transects in the Stubbetorp catchment, SE‐Sweden. We overlaid a geomorphology map (8 classes) with digital elevation model‐derived topographic index maps (2–9 classes) to estimate the range of error the model produces with changing sample size and input maps. The accuracy of the soil depth predictions was estimated with the root mean square error (RMSE) based on a testing and training data set. RMSE ranged generally between 0·73 and 0·83 m ± 0·013 m depending on the amount of classes the merged layers had, but were smallest for a map combination with a low number of classes predicted with the harmonic mean (RMSE = 0·46 m). The results show that the prediction accuracy of this method depends on the number of point values in the sample, the value range of the measured attribute and the initial correlations between point values and explanatory variables, but suggests that the model approach is in general scale invariant. Copyright © 2009 John Wiley & Sons, Ltd.     

A spatiotemporal probabilistic modelling of storm‐induced shallow landsliding using aerial photographs and logistic regression

Landslides constitute one of the major natural hazards that could cause significant losses of life and property. Mapping or delineating areas prone to landsliding is therefore essential for land‐use activities and management decision making in hilly or mountainous regions. A landslide hazard map can be constructed by a qualitative combination of maps of site conditions, including geology, topography and geomorphology, by statistical methods through correlating landslide occurrence with geologic and geomorphic factors, or by using safety factors from stability analysis. A landslide hazard map should provide information on both the spatial and temporal probabilities of landsliding in a certain area. However, most previous studies have focused on susceptibility mapping, rather than on hazard mapping in a spatiotemporal context. This study aims at developing a predictive model, based on both quasi‐static and dynamic variables, to determine the probability of landsliding in terms of space and time. The study area selected is about 13 km² in North Lantau, Hong Kong. The source areas of the landslides caused by the rainstorms of 18 July 1992 and 4–5 November 1993 were interpreted from multi‐temporal aerial photographs. Landslide data, lithology, digital elevation model data, land cover, and rainfall data were digitized into a geographic information system database. A logistic regression model was developed using lithology, slope gradient, slope aspect, elevation, slope shape, land cover, and rolling 24 h rainfall as independent variables, since the dependent variable could be expressed in a dichotomous way. This model achieved an overall accuracy of 87·2%, with 89·5% of landslide grid cells correctly classified and found to be performing satisfactorily. The model was then applied to rainfalls of a variety of periods of return, to predict the probability of landsliding on natural slopes in space and time. It is observed that the modelling techniques described here are useful for predicting the spatiotemporal probability of landsliding and can be used by land‐use planners to develop effective management strategies. Copyright © 2003 John Wiley & Sons, Ltd.     

Spatial soil moisture scaling structure during Soil Moisture Experiment 2005

Soil moisture state and variability control many hydrological and ecological processes as well as exchanges of energy and water between the land surface and the atmosphere. However, its state and variability are poorly understood at spatial scales larger than the fields (i.e. 1 km²) as well as the ability to extrapolate field scale to larger spatial scales. This study investigates soil moisture profiles, their spatial organization, and physical drivers of variability within the Walnut Creek watershed, Iowa, during Soil Moisture Experiment 2005 and relates the watershed scale findings to previous field‐scale results. For all depths, the watershed soil moisture variability was negatively correlated with the watershed mean soil moisture and followed an exponential relationship that was nearly identical to that for field scales. This relationship differed during drying and wetting. While the overall time stability characteristics were improved with observation depth, the relatively wet and dry locations were consistent for all depths. The most time stable locations, capturing the mean soil moisture of the watershed within ± 0·9% volumetric soil moisture, were typically found on hill slopes regardless of vegetation type. These mild slope locations consistently preserve the time stability patterns from field to watershed scales. Soil properties also appear to impact stability but the findings are sensitive to local variations that may not be well defined by existing soil maps. Copyright © 2010 John Wiley & Sons, Ltd.     

Soil erosion assessment using geomorphological remote sensing techniques: an example from southern Italy

The aim of this study is to assess of the distribution and map the geomorphological effects of soil erosion at the basin scale identifying newly‐formed erosional landsurfaces (NeFELs), by means of an integration of Landsat ETM 7+ remotely sensed data and field‐surveyed geomorphological data. The study was performed on a 228·6 km²‐wide area, located in southern Italy. The study area was first characterized from a lithological, pedological, land‐use and morpho‐topographic point of view and thematic maps were created. Then, the georeferenced Landsat ETM 7+ satellite imagery was processed using the RSI ENVI 4.0 software. The processing consisted of contrast stretching, principal component analysis (PCA), decorrelation stretching and RGB false colour compositing. A field survey was conducted to characterize the features detected on the imagery. Particular attention was given to the NeFELs, which were located using a global positioning system (GPS). We then delimited the Regions of Interest (ROI) on the Landsat ETM 7+ imagery, i.e. polygons representing the ‘ground‐truth’, discriminating the NeFELs from the other features occurring in the imagery. A simple statistical analysis was conducted on the digital number (DN) values of the pixels enclosed in the ROI of the NeFELs, with the aim to determine the spectral response pattern of such landsurfaces. The NeFELs were then classified in the entire image using a maximum likelihood classification algorithm. The results of the classification process were checked in the field. Finally, a spatial analysis was performed by converting the detected landsurfaces into vectorial format and importing them into the ESRI ArcViewGIS 9.0 software. Application of these procedures, together with the results of the field survey, highlighted that some ‘objects’ in the classified imagery, even if displaying the same spectral response of NeFELs, were not landsurfaces subject to intense soil erosion, thus confirming the strategic importance of the field‐checking for the automatically produced data. During the production of the map of the NeFELs, which is the final result of the study, these ‘objects’ were eliminated by means of simple, geomorphologically‐coherent intersection procedures in a geographic information system (GIS) environment. The overall surface of the NeFELs had an area of 22·9 km², which was 10% of the total. The spatial analysis showed that the highest frequency of the NeFELs occurred on both south‐facing and southwest‐facing slopes, cut on clayey‐marly deposits, on which fine‐textured and carbonate‐rich Inceptisols were present and displaying slope angle values ranging from 12° to 20°. The comparison of two satellite imageries of different periods highlighted that the NeFELs were most clearly evident immediately after summer tillage operations and not so evident before them, suggesting that these practices could have played an important role in inducing the erosional processes. Copyright © 2009 John Wiley & Sons, Ltd.     

Block removal and step backwearing as erosion processes on rock shore platforms: a preliminary case study of the chalk shore platforms of south‐east England

Shore platforms frequently exhibit steps or risers facing seaward, landwards or obliquely across‐shore. A combination of soft copy photogrammetry, ortho‐rectification, geo referencing and field measurement of step height are linked in a GIS environment to measure step retreat on chalk shore platforms at sample sites in the south of England over two periods, 1973–2001, 2001–2007. The methods used allow for the identification, delineation and measurement of historic change at high spatial resolution. The results suggest that while erosion of chalk shore platforms by step backwearing is highly variable, it appears to be of similar magnitude to surface downwearing of the same platforms measured by micro‐erosion meters (MEMs) and laser scanning, in a range equivalent to 0·0006 – 0·0050 m y^?1 of surface downwearing. This equates to annual chalk volume loss from the platforms, by the two erosion processes combined, of between 0·0012 m³ m^?2 and 0·0100 m³ m^?2. Results from the more recent years' data suggests that step retreat has variability in both space and time which does not relate solely to climatic variability. The results must be viewed with caution until much larger numbers of measurements have been made of both downwearing and step erosion at higher spatial and temporal resolution. Copyright © 2010 John Wiley & Sons, Ltd.     

Role of in situ cosmogenic nuclides 10be and 26al in the study of diverse geomorphic processes

The central premises of applications of the in situ cosmogenic dating method for studying specific problems in geomorphology are outlined for simple and complex exposure settings. In the light of these general models, we discuss the information that can be derived about geomorphic processes, utilizing concentrations of in situ produced cosmogenic radionuclides ¹⁰Be (half-life=1·5 ma) and ²⁶A1 (half-life=0·7 ma) in a variety of geomorphic contexts: glacial polish and tills; meteorite impact craters; alluvial fans; paleo-beach ridges; marine terraces; sand dunes; and bedrock slopes. We also compare ¹⁰Be-²⁶Al data with results obtained by other dating methods. We conclude that the technique of measuring in situ cosmic ray produced nuclides holds promise for quantitative studies of processes and time-scales in a wide range of geomorphological problems.     

Wood distribution in neotropical forested headwater streams of La Selva,Costa Rica

Surveys of wood along 30 forested headwater stream reaches in La Selva Biological Station in north‐eastern Costa Rica represent the first systematic data reported on wood loads in neotropical streams. For streams with drainage areas of 0·1–8·5 km² and gradients of 0·2–8%, wood load ranged from 3 to 34·7 m³ wood/100 m channel and 41–612 m³ wood/ha channel. These values are within the range reported for temperate streams. The variables wood diameter/flow depth, stream power, the presence of backflooding, and channel width/depth are consistently selected as significant predictors by statistical models for wood load. These variables explain half to two‐thirds of the variability in wood load. These results, along with the spatial distribution of wood with respect to the thalweg, suggest that transport processes exert a greater influence on wood loads than recruitment processes. Wood appears to be more geomorphically effective in altering bed elevations in gravel‐bed reaches than in reaches with coarser or finer substrate. Copyright © 2009 John Wiley & Sons, Ltd.     

Quantifying sediment storage in a high alpine valley (Turtmanntal,Switzerland)

The determination of sediment storage is a critical parameter in sediment budget analyses. But, in many sediment budget studies the quantification of magnitude and time‐scale of sediment storage is still the weakest part and often relies on crude estimations only, especially in large drainage basins (>100 km²). We present a new approach to storage quantification in a meso‐scale alpine catchment of the Swiss Alps (Turtmann Valley, 110 km²). The quantification of depositional volumes was performed by combining geophysical surveys and geographic information system (GIS) modelling techniques. Mean thickness values of each landform type calculated from these data was used to estimate the sediment volume in the hanging valleys and the trough slopes. Sediment volume of the remaining subsystems was determined by modelling an assumed parabolic bedrock surface using digital elevation model (DEM) data. A total sediment volume of 781·3×10⁶–1005·7×10⁶ m³ is deposited in the Turtmann Valley. Over 60% of this volume is stored in the 13 hanging valleys. Moraine landforms contain over 60% of the deposits in the hanging valleys followed by sediment stored on slopes (20%) and rock glaciers (15%). For the first time, a detailed quantification of different storage types was achieved in a catchment of this size. Sediment volumes have been used to calculate mean denudation rates for the different processes ranging from 0·1 to 2·6 mm/a based on a time span of 10 ka. As the quantification approach includes a number of assumptions and various sources of error the values given represent the order of magnitude of sediment storage that has to be expected in a catchment of this size. Copyright © 2009 John Wiley & Sons, Ltd.