Use of multi‐platform,multi‐temporal remote‐sensing data for calibration of a distributed hydrological model: an application in the Arno basin,Italy

Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed in calibration and validation of the water balance and flood forecasting. Remotely sensed data are easily available on large areas and with a frequency compatible with land cover changes. In this paper, remotely sensed images from different types of sensor have been utilized as a support to the calibration of the distributed hydrological model MOBIDIC, currently used in the experimental system of flood forecasting of the Arno River Basin Authority. Six radar images from ERS‐2 synthetic aperture radar (SAR) sensors (three for summer 2002 and three for spring–summer 2003) have been utilized and a relationship between soil saturation indexes and backscatter coefficient from SAR images has been investigated. Analysis has been performed only on pixels with meagre or no vegetation cover, in order to legitimize the assumption that water content of the soil is the main variable that influences the backscatter coefficient. Such pixels have been obtained by considering vegetation indexes (NDVI) and land cover maps produced by optical sensors (Landsat‐ETM). In order to calibrate the soil moisture model based on information provided by SAR images, an optimization algorithm has been utilized to minimize the regression error between saturation indexes from model and SAR data and error between measured and modelled discharge flows. Utilizing this procedure, model parameters that rule soil moisture fluxes have been calibrated, obtaining not only a good match with remotely sensed data, but also an enhancement of model performance in flow prediction with respect to a previous calibration with river discharge data only. Copyright © 2006 John Wiley & Sons, Ltd.     

Predicting floodplain inundation: raster‐based modelling versus the finite‐element approach

We compare two approaches to modelling floodplain inundation: a raster‐based approach, which uses a relatively simple process representation, with channel flows being resolved separately from the floodplain using either a kinematic or diffusive wave approximation, and a finite‐element hydraulic model aiming to solve the full two‐dimensional shallow‐water equations. A flood event on a short (c. 4 km) reach of the upper River Thames in the UK is simulated, the models being validated against inundation extent as determined from satellite synthetic aperture radar (SAR) imagery. The unconstrained friction parameters are found through a calibration procedure, where a measure of fit between predicted and observed shorelines is maximized. The raster and finite‐element models offer similar levels of performance, both classifying approximately 84% of the model domain correctly, compared with 65% for a simple planar prediction of water surface elevation. Further discrimination between models is not possible given the errors in the validation data. The simple raster‐based model is shown to have considerable advantages in terms of producing a straightforward calibration process, and being robust with respect to channel specification. Copyright © 2001 John Wiley & Sons, Ltd.     

ROC‐based calibration of flood inundation models

The use of spatial patterns of flood inundation (often obtained from remotely sensed imagery) to calibrate flood inundation models has been widespread over the last 15 years. Model calibration is most often achieved by employing one or even several performance measures derived from the well‐known confusion matrix based on a binary classification of flooding. However, relatively early on, it has been recognized that the use of commonly reported performance measures for calibrating flood inundation models (such as the F measure) is hampered because the calibration procedure commonly utilizes only one possible solution of a wet/dry classification of a remote sensing image [most often acquired by a synthetic aperture radar (SAR)] to calibrate or validate models and are biased towards either over‐prediction or under‐prediction of flooding. Despite the call in several studies for an alternative statistic, to this date, very few, if any, unbiased performance measure based on the confusion matrix has been proposed for flood model calibration/validation studies. In this paper, we employ a robust statistical measure that operates in the receiver operating characteristics (ROC) space and allows automated model calibration with high identifiability of the best model parameter set but without the need of a classification of the SAR image. The ROC‐based method for flood model calibration is demonstrated using two different flood event test cases with flood models of varying degree of complexity and boundary conditions with varying degree of accuracy. Verification of the calibration results and optional SAR classification is successfully performed with independent observations of the events. We believe that this proposed alternative approach to flood model calibration using spatial patterns of flood inundation should be employed instead of performance measures commonly used in conjunction with a binary flood map. © 2013 California Institute of Technology. Hydrological Processes © 2013 John Wiley & Sons, Ltd.     

Delineating floodplain and upland areas for hydrologic models: a comparison of methods

A spatially distributed representation of basin hydrology and transport processes in hydrologic models facilitates the identification of critical source areas and the placement of management and conservation measures. Floodplains are critical landscape features that differ from neighbouring uplands in terms of their hydrological processes and functions. Accordingly, an important step in watershed modelling is the representation of floodplain and upland areas within a watershed. The aim of this study is (1) to evaluate four floodplain–upland delineation methods that use readily available topographic data (topographic wetness index, slope position, uniform flood stage, and variable flood stage) with regard to their suitability for hydrological models and (2) to introduce an evaluation scheme for the delineated landscape units. The methods are tested in three U.S. watersheds ranging in size from 334 to 629 km² with different climatic, hydrological, and geomorphological characteristics. Evaluation of the landscape delineation methods includes visual comparisons, error matrices (i.e. cross‐tabulations of delineated vs reference data), and geometric accuracy metrics. Reference data were obtained from the Soil Survey Geographic (SSURGO) database and Federal Emergency Management Agency (FEMA) flood maps. Results suggest that the slope position and the variable flood stage method work very well in all three watersheds. Overall percentages of floodplain and upland areas allocated correctly were obtained by comparing delineated and reference data. Values range from 83 to 93% for the slope position and from 80 to 95% for the variable flood stage method. Future studies will incorporate these two floodplain–upland delineation methods into the subwatershed‐based hydrologic model Soil and Water Assessment Tool (SWAT) to improve the representation of hydrological processes within floodplain and upland areas. Copyright © 2016 John Wiley & Sons, Ltd.     

Flood frequency under the influence of trends in the Pearl River basin,China: changing patterns,causes and implications

Using a nonstationary flood frequency model, this study investigates the impact of trends on the estimation of flood frequencies and flood magnification factors. Analysis of annual peak streamflow data from 28 hydrological stations across the Pearl River basin, China, shows that: (1) northeast parts of the West and the North River basins are dominated by increasing annual peak streamflow, whereas decreasing trends of annual peak streamflow are prevailing in other regions of the Pearl River basin; (2) trends significantly impact the estimation of flood frequencies. The changing frequency of the same flood magnitude is related to the changing magnitude or significance/insignificance of trends, larger increasing frequency can be detected for stations with significant increasing trends of annual peak streamflow and vice versa, and smaller increasing magnitude for stations with not significant increasing annual peak streamflow, pointing to the critical impact of trends on estimation of flood frequencies; (3) larger‐than‐1 flood magnification factors are observed mainly in the northeast parts of the West River basin and in the North River basin, implying magnifying flood processes in these regions and a higher flood risk in comparison with design flood‐control standards; and (4) changes in hydrological extremes result from the integrated influence of human activities and climate change. Generally, magnifying flood regimes in the northeast Pearl River basin and in the North River basin are mainly the result of intensifying precipitation regime; smaller‐than‐1 flood magnification factors along the mainstream of the West River basin and also in the East River basin are the result of hydrological regulations of water reservoirs. Copyright © 2014 John Wiley & Sons, Ltd.     

Channel–floodplain connectivity during an extreme flood event: implications for sediment erosion,deposition, and delivery

The term connectivity has emerged as a powerful concept in hydrology and geomorphology and is emerging as an innovative component of catchment erosion modeling studies. However, considerable confusion remains regarding its definition and quantification, especially as it relates to fluvial systems. This confusion is exacerbated by a lack of detailed case studies and by the tendency to treat water and sediment separately. Extreme flood events provide a useful framework to assess variability in connectivity, particularly the connection between channels and floodplains. The catastrophic flood of January 2011 in the Lockyer valley, southeast Queensland, Australia provides an opportunity to examine this dimension in some detail and to determine how these dynamics operate under high flow regimes. High resolution aerial photographs and multi‐temporal LiDAR digital elevation models (DEMs), coupled with hydrological modeling, are used to assess both the nature of hydrologic and sedimentological connectivity and their dominant controls. Longitudinal variations in flood inundation extent led to the identification of nine reaches which displayed varying channel–floodplain connectivity. The major control on connectivity was significant non‐linear changes in channel capacity due to the presence of notable macrochannels which contained a > 3000 average recurrence interval (ARI) event at mid‐catchment locations. The spatial pattern of hydrological connectivity was not straight‐forward in spite of bankfull discharges for selected reaches exceeding 5600 m³ s^–1. Data indicate that the main channel boundary was the dominant source of sediment while the floodplains, where inundated, were the dominant sinks. Spatial variability in channel–floodplain hydrological connectivity leads to dis‐connectivity in the downstream transfer of sediments between reaches and affected sediment storage on adjacent floodplains. Consideration of such variability for even the most extreme flood events, highlights the need to carefully consider non‐linear changes in key variables such as channel capacity and flood conveyance in the development of a quantitative ‘connectivity index’. Copyright © 2013 John Wiley & Sons, Ltd.     

Validation of a full hydrodynamic model for large‐scale hydrologic modelling in the Amazon

A key aspect of large river basins partially neglected in large‐scale hydrological models is river hydrodynamics. Large‐scale hydrologic models normally simulate river hydrodynamics using simplified models that do not represent aspects such as backwater effects and flood inundation, key factors for some of the largest rivers of the world, such as the Amazon. In a previous paper, we have described a large‐scale hydrodynamic approach resultant from an improvement of the MGB‐IPH hydrological model. It uses full Saint Venant equations, a simple storage model for flood inundation and GIS‐based algorithms to extract model parameters from digital elevation models. In the present paper, we evaluate this model in the Solimões River basin. Discharge results were validated using 18 stream gauges showing that the model is accurate. It represents the large delay and attenuation of flood waves in the Solimões basin, while simplified models, represented here by Muskingum Cunge, provide hydrographs are wrongly noisy and in advance. Validation against 35 stream gauges shows that the model is able to simulate observed water levels with accuracy, representing their amplitude of variation and timing. The model performs better in large rivers, and errors concentrate in small rivers possibly due to uncertainty in river geometry. The validation of flood extent results using remote sensing estimates also shows that the model accuracy is comparable to other flood inundation modelling studies. Results show that (i) river‐floodplain water exchange and storage, and (ii) backwater effects play an important role for the Amazon River basin hydrodynamics. Copyright © 2011 John Wiley & Sons, Ltd.     

Near real time satellite imagery to support and verify timely flood modelling

The study investigates the capability of coarse resolution synthetic aperture radar (SAR) imagery to support flood inundation models. A hydraulic model of a 98‐km reach of the River Po (Northern Italy) was calibrated on the October 2000 high‐magnitude flood event with extensive and high‐quality field data. During the June 2008, low‐magnitude flood event a SAR image was acquired and processed in near real time (NRT) in order to provide adequate data for quick verification and recalibration of the hydraulic model. Copyright © 2009 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.     

A data assimilation approach to discharge estimation from space

River discharge is currently monitored by a diminishing network of gauges, which provide a spatially incomplete picture of global discharges. This study assimilated water level information derived from a fused satellite Synthetic Aperture Radar (SAR) image and digital terrain model (DTM) with simulations from a coupled hydrological and hydrodynamic model to estimate discharge in an un‐gauged basin scenario. Assimilating water level measurements led to a 79% reduction in ensemble discharge uncertainty over the coupled hydrological hydrodynamic model alone. Measurement bias was evident, but the method still provided a means of improving estimates of discharge for high flows. The study demonstrates the potential of currently available synthetic aperture radar imagery to reduce discharge uncertainty in un‐gauged basins when combined with model simulations in a data assimilation framework, where sufficient topographic data are available. The work is timely because in the near future the launch of satellite radar missions will lead to a significant increase in the volume of data available for space‐borne discharge estimation. Copyright © 2009 John Wiley & Sons, Ltd.     

Levee effects upon flood levels: an empirical assessment

This study used stream gauge records to assess the impact of levees on flood levels, providing an empirical test of theoretical and model predictions of the effects on local flood response. Focusing upon a study area in Illinois and Iowa for which levee records were available, we identified 203 gauges with ≥ 50 years hydrological record, including 15 gauges where a levee was constructed during the period of record. At these sites, step‐change analysis utilizing regression residuals tested levee‐related stage changes and levels of significance and quantified the magnitudes of stage changes. Despite large differences in stream sizes, levee alignments, and degree of floodplain constriction, the post‐levee rating‐curve adjustments showed consistent signatures. For all the study sites, stages for below bankfull (non‐flood) conditions were unaffected by levee construction. For above bankfull (flood) conditions, stages at sites downstream of their associated levees also were statistically indistinguishable before versus after levee construction. However, at all sites upstream of levees or within leveed reaches, stages increased for above bankfull conditions. These increases were abrupt, statistically significant, and generally large in magnitude – ranging up to 2.3 m (Wabash River at Mt. Carmel, IL). Stage increases began when discharge increased above bankfull flow and generally increased in magnitude with discharge until the associated levee(s) were overtopped. Detailed site assessments and supplementary data available from some sites helped document the dominant mechanisms by which levees can increase flood levels. Levee construction reduces the area of the floodplain open to storage of flood waters and reduces the width of the floodplain open to conveyance of flood flow. Floodplain conveyance often is underestimated or ignored, but Acoustic Doppler Current Profiler (ADCP) measurements analysed here confirm previous studies that up to 70% or more of the total discharge during large floods (~3% chance flood) can move over the floodplain. Upstream of levees and levee‐related floodplain constriction, backwater effects reduce flow velocities relative to pre‐levee conditions and, thus, increase stages for a given discharge. The empirical results here confirm a variety of theoretical predictions of levee effects but suggest that many one‐dimensional model‐based predictions of levee‐related stage changes may underestimate actual levee impacts. Copyright © 2011 John Wiley & Sons, Ltd.     

Two‐dimensional hydraulic flood modelling using a finite‐element mesh decomposed according to vegetation and topographic features derived from airborne scanning laser altimetry

Airborne scanning laser altimetry (LiDAR) is an important new data source that can provide two‐dimensional river flood models with spatially distributed floodplain topography for model bathymetry, together with vegetation heights for parameterization of model friction. Methods are described for improving such models by decomposing the model's finite‐element mesh to reflect floodplain vegetation features such as hedges and trees having different frictional properties to their surroundings, and significant floodplain topographic features having high height curvatures. The decomposition is achieved using an image segmentation system that converts the LiDAR height image into separate images of surface topography and vegetation height at each point. The vegetation height map is used to estimate a friction factor at each mesh node. The spatially distributed friction model has the advantage that it is physically based, and removes the need for a model calibration exercise in which free parameters specifying friction in the channel and floodplain are adjusted to achieve best fit between modelled and observed flood extents. The scheme was tested in a modelling study of a flood that occurred on the River Severn, UK, in 1998. A satellite synthetic aperture radar image of flood extent was used to validate the model predictions. The simulated hydraulics using the decomposed mesh gave a better representation of the observed flood extent than the more simplistic but computationally efficient approach of sampling topography and vegetation friction factors on to larger floodplain elements in an undecomposed mesh, as well as the traditional approach using no LiDAR‐derived data but simply using a constant floodplain friction factor. Use of the decomposed mesh also allowed velocity variations to be predicted in the neighbourhood of vegetation features such as hedges. These variations could be of use in predicting localized erosion and deposition patterns that might result in the event of a flood. Copyright © 2003 John Wiley & Sons, Ltd.     

Floodplain friction parameterization in two‐dimensional river flood models using vegetation heights derived from airborne scanning laser altimetry

Two‐dimensional (2‐D) hydraulic models are currently at the forefront of research into river flood inundation prediction. Airborne scanning laser altimetry is an important new data source that can provide such models with spatially distributed floodplain topography together with vegetation heights for parameterization of model friction. The paper investigates how vegetation height data can be used to realize the currently unexploited potential of 2‐D flood models to specify a friction factor at each node of the finite element model mesh. The only vegetation attribute required in the estimation of floodplain node friction factors is vegetation height. Different sets of flow resistance equations are used to model channel sediment, short vegetation, and tall and intermediate vegetation. The scheme was tested in a modelling study of a flood event that occurred on the River Severn, UK, in October 1998. A synthetic aperture radar image acquired during the flood provided an observed flood extent against which to validate the predicted extent. The modelled flood extent using variable friction was found to agree with the observed extent almost everywhere within the model domain. The variable‐friction model has the considerable advantage that it makes unnecessary the unphysical fitting of floodplain and channel friction factors required in the traditional approach to model calibration. Copyright © 2003 John Wiley & Sons, Ltd.     

Flood delineation in a large and complex alluvial valley, lower Pa´nuco basin, Mexico

Determining the extent of flooding is an important role of the hydrological research community and provides a vital service to planners and engineers. For large river systems located within distant settings it is practical to utilize a remote sensing approach. This study combines a remote sensing and geomorphic approach to delineate the extent of a large hurricane generated flood event in the lower Pánuco basin (98,227 km²), the seventh largest river system draining into the Gulf of Mexico. The lower Pánuco basin is located within the coastal plain of eastern Mexico and has a complex alluvial valley. Data sources included a Landsat 5TM and Landsat 7ETM⁺ scene, and topographic and particle size data from fieldwork and laboratory analysis. The Landsat 5TM image was acquired after the peak of a large flood event in 1993, whereas the Landsat 7ETM⁺ scene was acquired during the dry season in 2000. The increasing number of days between flood crest and the date of flood image acquisition along the river valley provided the opportunity to examine several methods of flood delineation and to consider differences in floodplain geomorphology. Backswamp environments were easily delineated in flooded reaches within the Panuco and Tamuin valleys, whereas in the Moctezuma valley more sophisticated methods were required because of the greater time between image acquisition and flood peak, and the complex floodplain topography. This included Principal Component (PC) analysis and image classification. Within the floodplain, residual Holocene terraces complicated flood mapping. Classification of both images allowed consideration of the influence of permanent standing water. Although the flooded areas were greater in the lower reaches of the study area, because this portion of the valley contained large floodplain lakes, the amount of inundation was actually lower. Remote sensing offers the ability to examine large alluvial valleys in distant settings but does not imply that geomorphic criteria should be excluded. Indeed, because of heterogeneous floodplain topography this study illustrates the importance of including field based geomorphic analysis so that the complexity of distinct floodplain environments are considered. The findings from this study are significant because most remote sensing data obtained for the purpose of flood mapping will not coincide with the flood crest. Thus, this study provides an appropriate method for mapping flood inundation in large and complex floodplain settings after flood crest recession.     

Salt accumulation in semi-arid floodplain soils with implications for forest health

Dieback of native Eucalyptus largiflorens forests is an increasing problem on the floodplains of the lower River Murray, southern Australia. Salinisation of floodplain soils, as a result of the changed hydrological management of the River Murray, appears to be a primary cause of the dieback. Regulation of the River Murray has reduced the frequency of large flood events by a factor of approximately three and caused groundwater levels beneath floodplains to rise. The higher water tables have resulted in increased discharge of the naturally saline groundwater in the floodplains by evapotranspiration, and the decreased incidence of large floods has reduced floodwater recharge and hence leaching of salt from floodplain soils. Use of soil physical properties for a range of floodplain soils, combined with measurements of groundwater discharge from bare and vegetated sites, suggests that the time-scale for complete soil salinisation can, at worst, be less than 20 years. Moreover, salt accumulation at most sites will continue to occur as the present flooding regime (of which there is limited scope for improvement) appears incapable of providing the leaching required to counteract accumulation. The analyses carried out here suggest that the ‘critical’ water table depth (below which groundwater discharge is balanced or exceeded by floodwater recharge) needs to be increased by 14–55% (the more clayey the soil, the larger the increase) to prevent salt accumulation. Failure to implement schemes which lower the water tables beneath the floodplain may, in the long term, cause serious damage to these important riparian forests.     

An integrated approach for investigating geomorphic response to extreme events: methodological framework and application to the October 2011 flood in the Magra River catchment,Italy

A high‐magnitude flash flood, which took place on 25 October 2011 in the Magra River catchment (1717 km²), central‐northern Italy, is used to illustrate some aspects of the geomorphic response to the flood. An overall methodological framework is described for using interlinked observations and analyses of the geomorphic impacts of an extreme event. The following methods and analyses were carried out: (i) hydrological and hydraulic analysis of the event; (ii) sediment delivery by event landslide mapping; (iii) identification and estimation of wood recruitment, deposition, and budgeting; (iv) interpretation of morphological processes by analysing fluvial deposits; (v) remote sensing and geographic information system (GIS) analysis of channel width changes. In response to the high‐magnitude hydrological event, a large number of landslides occurred, consisting of earth flows, soil slips, and translational slides, and a large quantity of wood was recruited, in most part deriving from floodplain erosion caused by bank retreat and channel widening. The most important impact of the flood event within the valley floor was an impressive widening of the overall channel bed and the reactivation of wide portions of the pre‐event floodplain. Along the investigated (unconfined or partly confined) streams (total investigated length of 93.5 km), the channel width after the flood was up to about 20 times the channel width before the event. The study has shown that a synergic use of different methods and types of evidence provides fundamental information for characterizing and understanding the geomorphic effects of intense flood events. The prediction of geomorphic response to a flood event is still challenging and many limitations exist; however a robust geomorphological analysis can contribute to the identification of the most critical reaches. Copyright © 2016 John Wiley & Sons, Ltd.     

A probabilistic framework for floodplain mapping using hydrological modeling and unsteady hydraulic modeling

ABSTRACT

Prediction of design hydrographs is key in floodplain mapping using hydraulic models, which are either steady state or unsteady. The former, which require only an input peak, substantially overestimate the volume of water entering the floodplain compared to the more realistic dynamic case simulated by the unsteady models that require the full hydrograph. Past efforts to account for the uncertainty of boundary conditions using unsteady hydraulic modeling have been based largely on a joint flood frequency–shape analysis, with only a very limited number of studies using hydrological modeling to produce the design hydrographs. This study therefore presents a generic probabilistic framework that couples a hydrological model with an unsteady hydraulic model to estimate the uncertainty of flood characteristics. The framework is demonstrated on the Swannanoa River watershed in North Carolina, USA. Given its flexibility, the framework can be applied to study other sources of uncertainty in other hydrological models and watersheds.     

Defining the floodplain in hydrologically‐variable settings: implications for flood risk management

Flood risk management is an essential responsibility of state governments and local councils to ensure the protection of people residing on floodplains. Globally, floodplains are under increasing pressure from growing populations. Typically, the engineering‐type solutions that are used to predict local flood magnitude and frequency based on limited gauging data are inadequate, especially in settings which experience high hydrological variability. This study highlights the importance of incorporating geomorphological understanding into flood risk management in southeast Queensland (SEQ), an area badly affected by extreme flood events in 2011 and 2013. The major aim of this study is to outline the hydrological and sedimentological characteristics of various ‘inundation surfaces’ that are typical of catchments in the sub‐tropics. It identifies four major inundation surfaces; within‐channel bench [Q ~ 2.33 yr average recurrence interval (ARI)]; genetic floodplain (Q = 20 yr ARI); hydraulic floodplain (20 yr < Q ≤ 200 yr ARI) and terrace (Q > 1000 yr ARI). These surfaces are considered typical of inundation areas within, and adjacent to, the large macrochannels common to this region and others of similar hydrological variability. An additional area within genetic floodplains was identified where flood surfaces coalesce and produce an abrupt reduction in channel capacity. This is referred to here as a Spill‐out Zone (SOZ). The associated vulnerability and risk of these surfaces is reviewed and recommendations made based on incorporating this geomorphological understanding into flood risk assessments. These recommendations recognize the importance to manage for risks associated with flow inundation and sediment erosion, delivery and deposition. The increasing availability of high resolution topographic data opens up the possibility of more rapid and spatially extensive assessments of key geomorphic processes which can readily be used to predict flood risk. Copyright © 2016 John Wiley & Sons, Ltd.     

Semi‐automated GIS techniques for detecting floodplain earthworks

Levees, channels and water storages built on the world's floodplain wetlands control flows for irrigation, flood mitigation and erosion management. Assessing their distribution and hydrological impacts through time and across broad extents is limited by significant costs and technical challenges. We tested the effectiveness of three new semi‐automated geographic information systems and traditional visual interpretation techniques for detecting earthworks. We used commercially or freely available two‐dimensional and three‐dimensional spatial imagery within 19 quadrats in an agricultural floodplain of the Murray–Darling Basin, southeastern Australia. Semi‐automated digital elevation model (DEM) analysis performed best for spatial accuracy (78% of earthworks correctly predicted within 25 m), overall classification accuracy (97.7%) and kappa (0.64), compared with traditional visual interpretation techniques using Landsat TM (52%, 96.3%, 0.39), SPOT (53%, 95.8%, 0.27) and aerial photography (72%, 97.2%, 0.31). DEM analysis also outperformed semi‐automated image segmentation (16%, 93%, 0.29) and integrated analysis (75%, 96.0%, 0.43) that used spectral information. Semi‐automated techniques were slow (DEM analysis: 27 418 s/km²; integrated analysis: 27 737 s/km²; and image segmentation: 1439 s/km²) compared with visual interpretation (Landsat TM: 109 s/km²; SPOT: 166 s/km²; and aerial photography: 276 s/km²); however, processing speed of semi‐automated techniques can be further increased without compromising accuracy. Semi‐automated techniques also offered operational autonomy following model calibration. High quality, cost‐effective earthwork mapping techniques, particularly the semi‐automated techniques in this study, are critical for understanding and managing ecosystem health, flood risk and water security in developed floodplains worldwide and should be implemented by governing institutions. Copyright © 2012 John Wiley & Sons, Ltd.