The effects of topographic depressions on multiscale overland flow connectivity: A high‐resolution spatiotemporal pattern analysis approach based on connectivity statistics

In watershed modelling, the traditional practice of arbitrarily filling topographic depressions in digital elevation models has raised concerns. Advanced high‐resolution remote sensing techniques, including airborne scanning laser altimetry, can identify naturally occurring depressions that impact overland flow. In this study, we used an ensemble physical and statistical modelling approach, including a 2D hydraulic model and two‐point connectivity statistics, to quantify the effects of depressions on high‐resolution overland flow patterns across spatial scales and their temporal variations in single storm events. Computations for both models were implemented using graphic processing unit‐accelerated computing. The changes in connectivity statistics for overland flow patterns between airborne scanning laser altimetry‐derived digital elevation models with (original) and without (filled) depressions were used to represent the shifts of overland flow response to depressions. The results show that depressions can either decrease or increase (to a lesser degree and shorter duration) the probability that any two points (grid locations) are hydraulically connected by overland flow pathways. We used macro‐connectivity states (Φ) as a watershed‐specific indicator to describe the spatiotemporal thresholds of connectivity variability caused by depressions. Four states of Φ are identified in a studied watershed, and each state represents different magnitudes of connectivity and connectivity changes (caused by depressions). The magnitude of connectivity variability corresponds to the states of Φ, which depend on the topological relationship between depressions, the rising/recession limb, and the total rainfall amount in a storm event. In addition, spatial distributions of connectivity variability correlate with the density of depression locations and their physical structures, which cause changes in streamflow discharge magnitude. Therefore, this study suggests that depressions are “nontrivial” in watershed modelling, and their impacts on overland flow should not be neglected. Connectivity statistics at different spatial scales and time points within a watershed provide new insights for characterizing the distributed and accumulated effects of depressions on overland flow.     

Computing spatially distributed sediment delivery ratios: inferring functional sediment connectivity from repeat high‐resolution digital elevation models

High‐resolution digital elevation models (DEMs) from repeat LiDAR (light detection and ranging) or SfM (structure from motion) surveys have become an important tool in process geomorphology. The spatial pattern of negative and positive changes of surface elevation on raster DEMs of difference (DoD) can be interpreted in terms of geomorphic processes, and has been used for morphological budgeting. We show how the application of flow routing algorithms and flow accumulation opens new opportunities for the analysis of DoD. By accumulating the values of the DoD along downslope flowpaths delineated on a DEM, these algorithms lend themselves to computing the net balance, i.e. sediment yield (SY), for the contributing area of each cell. Doing the same for the negative subset of the DoD yields a minimum estimate of erosion (E) within the contributing area. The division of SY by E yields (a maximum estimate of) the sediment delivery ratio (SDR), that is the proportion of material eroded within the contributing area of each cell that has been exported from that area. The resulting SDR is a spatially distributed measure of functional sediment connectivity. In this letter, we develop the computationally simple approach by means of an example DoD from a lateral moraine section in the Upper Kaunertal Valley, Austrian Central Alps. We also discuss advantages, assumptions and limitations, and outline potential applications to connectivity research using field‐, laboratory‐, and model‐based DoD. Copyright © 2018 John Wiley & Sons, Ltd.     

Range imaging: a new method for high‐resolution topographic measurements in small‐ and medium‐scale field sites

Topographic measurements are essential for the study of earth surface processes. Three‐dimensional data have been conventionally obtained through terrestrial laser scanning or photogrammetric methods. However, particularly in steep and rough terrain, high‐resolution field measurements remain challenging and often require new creative approaches. In this paper, range imaging is evaluated as an alternative method for obtaining surface data in such complex environments. Range imaging is an emerging time‐of‐flight technology, using phase shift measurements on a multi‐pixel sensor to generate a distance image of a surface. Its suitability for field measurements has yet not been tested. We found ambient light and surface reflectivity to be the main factors affecting error in distance measurements. Low‐reflectivity surfaces and strong illumination contrasts under direct exposure to sunlight lead to noisy distance measurements. However, regardless of lighting conditions, the accuracy of range imaging was markedly improved by averaging multiple images of the same scene. For medium ambient lighting (shade) and a light‐coloured surface the measurement uncertainty was approximately 9 mm. To further test the suitability of range imaging for field applications we measured a reach of a steep mountain stream with a horizontal resolution of approximately 1 cm (in the focal plane of the camera), allowing for the interpolation of a digital elevation model on a 2 cm grid. Comparison with an elevation model obtained from terrestrial laser scanning for the same site revealed that both models show similar degrees of topographic detail. Despite limitations in measurement range and accuracy, particularly at bright ambient lighting, range imaging offers three‐dimensional data in real time and video mode without the need of post‐processing. Therefore, range imaging is a useful complement or alternative to existing methods for high‐resolution measurements in small‐ to medium‐scale field sites. Copyright © 2012 John Wiley & Sons, Ltd.     

Landform‐oriented flow‐routing algorithm for the dual‐structure loess terrain based on digital elevation models

The loess landform in the Loess Plateau of China is with typical dual structure, namely, the upper smooth positive terrain and the lower cliffy negative terrain (P–N terrain for short). Obvious differences in their morphological feature, geomorphological mechanism, and hydrological process could be found in the both areas. Based on the differences, a flow‐routing algorithm that separately addresses the dual‐structure terrain would be necessary to encompass this spatial variation in their hydrological behaviour. This paper proposes a mixed flow‐routing algorithm to address aforementioned problems. First, the loess landform surface is divided into P–N terrains based on digital elevation models. Then, specific catchment area is calculated with the new algorithm to simulate the water flows in both positive and negative terrain areas. The mixed algorithm consists of the multiple flow‐routing algorithm (multiple‐flow direction) for positive areas and the D8 algorithm for negative areas, respectively. The approach is validated in two typical geomorphologic areas with low hills and dense gullies in the northern Shaanxi Loess Plateau. Four indices are used to examine the results, which show that the new algorithm is more suitable for loess terrain in simulating the spatial distribution of water accumulation, as well as in modeling the flow characteristics of the true surface by considering the morphological structures of the terrain. Copyright © 2013 John Wiley & Sons, Ltd.     

Wavelet‐based regularization of the extracted topographic index from high‐resolution topography for hydro‐geomorphic applications

High‐resolution topography, e.g. 1‐m digital elevation model (DEM) from light detection and ranging (LiDAR), offers opportunity for accurate identification of topographic features of relevance for hydrologic and geomorphologic modelling. Yet, the computation of some derived topographic properties, such as the topographic index (TI), is characterized by daunting challenges that hamper the full exploration of topography‐based models. Particular problems, for example, arise when a distributed (or semi‐distributed) rainfall–runoff model is applied to high‐resolution DEMs. Indeed, the characteristic dependency between landscape resolution and the computed TI distribution results in the formation of un‐physical, unconnected saturated zones, which in turn cause unrealistic representations of rainfall–runoff dynamics. In this study, we present a methodology based on a multi‐resolution wavelet transformation that, by means of a soft‐thresholding scheme on the wavelet coefficients, filters the noise of high‐resolution topography to construct regularized sets of locally smoother topography on which the TI is computed. While the methodology needs a somewhat arbitrary definition of the wavelet coefficients threshold, our study shows that when the information content (entropy) of the TI distribution is used as a filtering efficiency metric, a critical threshold automatically emerges in the landscape reconstruction. The methodology is demonstrated using 1‐m LiDAR data for the Elder Creek River basin in California. While the proposed case study uses a TOPMODEL approach, the methodology can be extended to different topography‐based models and is not limited to hydrological applications. Copyright © 2012 John Wiley & Sons, Ltd.     

Optimal use of high‐resolution topographic data in flood inundation models

In this paper we explore the optimum assimilation of high‐resolution data into numerical models using the example of topographic data provision for flood inundation simulation. First, we explore problems with current assimilation methods in which numerical grids are generated independent of topography. These include possible loss of significant length scales of topographic information, poor representation of the original surface and data redundancy. These are resolved through the development of a processing chain consisting of: (i) assessment of significant length scales of variation in the input data sets; (ii) determination of significant points within the data set; (iii) translation of these into a conforming model discretization that preserves solution quality for a given numerical solver; and (iv) incorporation of otherwise redundant sub‐grid data into the model in a computationally efficient manner. This processing chain is used to develop an optimal finite element discretization for a 12 km reach of the River Stour in Dorset, UK, for which a high‐resolution topographic data set derived from airborne laser altimetry (LiDAR) was available. For this reach, three simulations of a 1 in 4 year flood event were conducted: a control simulation with a mesh developed independent of topography, a simulation with a topographically optimum mesh, and a further simulation with the topographically optimum mesh incorporating the sub‐grid topographic data within a correction algorithm for dynamic wetting and drying in fixed grid models. The topographically optimum model is shown to represent better the ‘raw’ topographic data set and that differences between this surface and the control are hydraulically significant. Incorporation of sub‐grid topographic data has a less marked impact than getting the explicit hydraulic calculation correct, but still leads to important differences in model behaviour. The paper highlights the need for better validation data capable of discriminating between these competing approaches and begins to indicate what the characteristics of such a data set should be. More generally, the techniques developed here should prove useful for any data set where the resolution exceeds that of the model in which it is to be used. Copyright © 2002 John Wiley & Sons, Ltd.     

Innovative analysis and use of high‐resolution DTMs for quantitative interrogation of Earth‐surface processes

This is the era of digital landscapes; the widespread availability of powerful sensing technologies has revolutionized the way it is possible to interrogate landscapes in order to understand the processes sculpting them. Vastly greater areas have now been acquired at ‘high resolution’: currently tens of metres globally to millimetric precision and accuracy locally. This permits geomorphic features to be visualized and analysed across the scales at which Earth‐surface processes operate. Especially exciting is the capturing of process dynamics in repeated surveying, which will only become more important with low‐cost accessible data generation through techniques such as Structure from Motion (SfM). But the key challenge remains; to interpret high resolution Digital Terrain Models (DTMs), particularly by extracting geomorphic features in robust and objective ways and then linking the observed features to the underlying physical processes. In response to the new data and challenges, recent years have seen improved processing of raw data into DTMs, development of data fusion techniques, novel quantitative analysis of topographic data, and innovative geomorphological mapping. The twelve papers collected in this volume sample this progress in interrogating Earth‐surface processes through the analysis of DTMs. They cover a wide range of disciplines and spatio‐temporal scales, from landslide prone landscapes, to agriculturally modified regions, to mountainous landscapes, and coastal zones. They all, however, showcase the quantitative exploitation of information contained in high‐resolution topographic data that we believe will underpin the improvement of our understanding of many elements of Earth‐surface processes. Most of the papers introduced here were first presented in a conference session at the European Geosciences Union General Assembly in 2011. Copyright © 2014 John Wiley & Sons, Ltd.     

Evaluation of remotely‐sensed DEMs and modification based on plausibility rules and initial sediment budgets of an artificially‐created catchment

To quantify landscape change resulting from processes of erosion and deposition and to establish spatially distributed sediment budgets, ‘models of change’ can be established from a time series of digital elevation models (DEMs). However, resolution effects and measurement errors in DEMs may propagate to these models. This study aimed to evaluate and to modify remotely‐sensed DEMs for an improved quantification of initial sediment mass changes in an artificially‐created catchment. DEMs were constructed from photogrammetry‐based, airborne (ALS) and ground‐based laser scanning (TLS) data. Regions of differing morphological characteristics and vegetation cover were delineated. Three‐dimensional (3D) models of volume change were established and mass change was derived from these models. DEMs were modified region‐by‐region for rill, interrill and alluvial areas, based on logical and hydro‐geomorphological principles. Additional DEMs were constructed by combining multi‐source, modified data. Models were evaluated by comparison with d‐GPS reference data and by considering sediment budget plausibility. Comprehensive evaluation showed that DEM usability depends on a relation between the technique used to obtain elevation data, surface morphology and vegetation cover characteristics. Photogrammetry‐based DEMs were suited to quantification of change in interrill areas but strongly underestimated surface lowering in erosion rills. TLS DEMs were best suited to rill areas, while ALS DEMs performed best in vegetation‐covered alluvial areas. Agreement with reference data and budget plausibility were improved by modifications to photogrammetry‐ and TLS‐based DEMs. Results suggest that artefacts in DEMs can be reduced and hydro‐geomorphic surface structures can be better represented by applying region‐specific modifications. Photogrammetry‐based DEMs can be improved by combining higher and lower resolution data in defined structural units and applying modifications based on principles given by characteristic hydro‐geomorphic evolution. Results of the critical comparative evaluation of remotely‐sensed elevation data can help to better interpret DEM‐based quantifications of earth‐surface processes. Copyright © 2012 John Wiley & Sons, Ltd.     

Effect of digital elevation model spatial resolution on depression storage

Surface water storage—including wetlands and other small waterbodies—has largely been disregarded in traditional hydrological models. In this paper, the grid resampling method is adopted to study the influence of the digital elevation model (DEM) grid resolution on depression storage (DS) considering different rainfall return periods. It is observed that the DEM grid size highly affects DS, and the higher the grid resolution is, the larger the DS value. However, when the grid resolution reaches a certain value, the maximum DS value decreases. This suggests that a critical grid resolution value exists at which the water storage capacity of depressions is maximized, namely, 20 m in this work (except for the overall area simulation under infiltration). This phenomenon is further verified in two test cases with and without the infiltration process, that is, calculations of the local area and without infiltration area, respectively. This research may facilitate the accurate computation of the DS process, which is greatly affected by the grid resolution, thereby improving the reliability of hydrological models.     

A simple algorithm for generating streamflow networks for grid‐based,macroscale hydrological models

A simple algorithm for generating streamflow networks for macroscale hydrological models (MHMs) from digital elevation models (DEMs) is presented. Typically these hydrological models are grid based, with the simulated runoff produced within each cell routed through a stream network which connects the centers of cells in the direction of the major streams. Construction of such stream networks is a time consuming task, which has generally been done by hand with the aid of maps. Results indicate that the algorithm works satisfactorily in areas of both high and low relief, and for a wide range of model cell resolutions, although some manual adjustments may be necessary. Copyright © 1999 John Wiley & Sons, Ltd.     

Sediment production in large gullies of the Mediterranean area (NE Spain) from high‐resolution digital elevation models and geographical information systems analysis

Recent studies in the Mediterranean area have shown gully erosion to have a very significant contribution to total soil loss. In the Penedès vineyard region (NE Spain), between 15 and 27% of the land is affected by large gullies and gully‐wall retreat seems to be an ongoing process. Multi‐date digital elevation model (DEM) analysis has allowed computation of sediment production by gully erosion, showing that the sediment production rates are very high by the, up‐to‐date, usual global standards. Here, we present a study carried out using large‐scale multi‐date (1975 and 1995) aerial photographs (1 : 5000 and 1 : 7000) to monitor sediment yield caused by large gullies in the Penedès region (NE Spain). High‐resolution DEMs (1 m grid) were derived and analysed by means of geographical information systems techniques to determine the gully erosion rates. Rainfall characteristics within the same study period were also analysed in order to correlate with the soil loss produced. Mass movement was the main process contributing to total sediment production. This process could have been favoured by rainfalls recorded during the period: 58% of the events were of an erosive character and showed high kinetic energy and erosivity. A sediment production rate of 846 ± 40 Mg ha^?1 year^?1, a sediment deposition rate of 270 ± 18 Mg ha^?1 year^?1 and a sediment delivery ratio of 68·1% were computed for a gully area of 0·10 km². The average net erosion within the study period (1975–95) was 576 ± 58 Mg ha^?1 year^?1. In comparison with other methods, the proposed method also includes sediment produced by processes other than only overland flow, i.e. downcutting, headcutting, and mass movements and bank erosion. Copyright © 2003 John Wiley & Sons, Ltd.     

A distributed TOPMODEL for modelling impacts of land‐cover change on river flow in upland peatland catchments

There is global concern about headwater management and associated impacts on river flow. In many wet temperate zones peatlands can be found covering headwater catchments. In the UK there is major concern about how environmental change, driven by human interventions, has altered the surface cover of headwater blanket peatlands. However, the impact of such land‐cover changes on river flow is poorly understood. In particular, there is poor understanding of the impacts of different spatial configurations of bare peat or well‐vegetated, restored peat on river flow peaks in upland catchments. In this paper, a physically based, distributed and continuous catchment hydrological model was developed to explore such impacts. The original TOPMODEL, with its process representation being suitable for blanket peat catchments, was utilized as a prototype acting as the basis for the new model. The equations were downscaled from the catchment level to the cell level. The runoff produced by each cell is divided into subsurface flow and saturation‐excess overland flow before an overland flow calculation takes place. A new overland flow module with a set of detailed stochastic algorithms representing overland flow routing and re‐infiltration mechanisms was created to simulate saturation‐excess overland flow movement. The new model was tested in the Trout Beck catchment of the North Pennines of England and found to work well in this catchment. The influence of land cover on surface roughness could be explicitly represented in the model and the model was found to be sensitive to land cover. Copyright © 2014 John Wiley & Sons, Ltd.     

Grid‐resolution effects on a model for integrating urban and rural areas

The impact of grid‐cell size on calibrated parameters and on the performance of a variable source area model intended for urbanizing catchments is studied in this research. The model uses TOPMODEL concepts that were modified to consider urban areas in both the topographic index and the mechanism of surface runoff generation. The revised model known as TOPURBAN, was applied to a small catchment of roughly 8 km² in southern Ontario. Ten different grid‐cell sizes ranging from 10 m to 100 m were selected to study scale effects in this catchment with mild to moderate relief, on three separate time periods. The model performed adequately with calibration efficiencies for all three time periods in the range of 0\65 to 0\85. The verification efficiencies were not as high and ranged from 0\4 to 0\6. Larger cell sizes produced higher averages of topographic index, and this resulted in larger calibrated transmissivities. The most important parameter in determining the quantity of urban runoff was slightly affected by grid resolution. During the calibration process, this parameter was also found to interact with important parameters that dealt primarily with rural runoff generation. As cell size increased, contributions from urban areas increased and overland flow contributions from rural areas decreased. Results showed that in this integrated model of urban and rural areas, predicted processes based on calibrated parameters were dependent on grid resolution. Calibration of internal state variables is recommended to draw conclusions on the influences between urban and rural areas on the overall flow. Copyright © 2000 John Wiley & Sons, Ltd.     

Use of a three‐dimensional laser scanner to digitally capture the topography of sand dunes in high spatial resolution

We herein report the results of a ?eld study that was designed to test the feasibility of using ground‐based LIDAR to map the topography of a sand dune in high spatial resolution. A portable Cyrax 2500 three‐dimensional (3D) laser scanner was used to digitally capture the topography of a barchan, roughly 4 m tall and 50 m long, located in the White Sands National Monument, New Mexico. We performed eleven scans around the barchan and obtained the elevation relative to the inter‐dune ?at at roughly ¹/₄ million points on the dune surface. The elevation point data were then interpolated to yield a continuous surface model of the dune topography with c. 10 cm spatial resolution and c. 6 mm position accuracy. The results from this ?eld study clearly demonstrate the potential of ground‐based LIDAR as a mapping tool for use in aeolian research and other earth science applications. The 3D surface model of the dune can describe the morphology with hitherto unprecedented detail. Moreover, the surface of the dune is mapped with a minimum of foot traf?c on the dune itself. Copyright © 2004 John Wiley & Sons, Ltd.     

Comparison of the performance of flow‐routing algorithms used in GIS‐based hydrologic analysis

Flow direction and specific catchment area were calculated for different flow‐routing algorithms using TAPES‐G and TauDEM. A fuzzy classification was used along with eight topo–climatic attributes to delineate six landscape classes from a 10‐m USGS DEM. A series of maps and tabular outputs were produced to compare flow‐routing predictions in different parts of the study area in the Santa Monica Mountains of southern California. The matched pair t‐test was used to compare the performance of pairs of specific catchment area grids across six user‐defined fuzzy landscape classes. The results show that (1) the ‘source’ cells predicted with the D∞, DEMON, and FD8 algorithms were confined to hilltops; (2) two single flow‐routing algorithms (Rho8, D8) produced poor results; and (3) the choice of flow‐routing algorithm has potentially important consequences for the calculation of upslope contributing areas, sediment transport capacity, topographic wetness, and several other topographic indices. Copyright © 2007 John Wiley & Sons, Ltd.     

A simple two‐parameter model for scaling hillslope surface runoff

The objective of this research was to develop and parameterise a physically justified yet low‐parameter model to quantify observed changes in surface runoff ratios with hillslope length. The approach starts with the assumption that a unit of rainfall‐excess runoff generated at a point is a fraction β of precipitation P (m) which travels some variable distance down a slope before reinfiltrating, depending on the local rainfall, climate, soils, etc. If this random distance travelled Y is represented by a distribution, then a survival function will describe the probability of this unit of runoff travelling further than some distance x (m). The total amount of per unit width runoff Q (m²) flowing across the lower boundary of a slope of length λ (m) may be considered the sum of all the proportions of the units of rainfall excess runoff integrated from the lower boundary x = 0 to the upper boundary x = λ of the slope. Using these assumptions we derive a model Q(λ) = βPμλ/(μ + λ), (μ > 0, 0 ≤ β ≤ 1, λ ≥ 0) that describes the change in surface runoff with slope length, where μ (m) is the mean of the random variable Y. Dividing both sides of this equation by Pλ yields a simple two‐parameter equation for the dimensionless hillslope runoff ratio Q_h(λ) = βμ/(μ + λ). The model was parameterised with new rainfall and runoff data collected from three replicates of bounded 2 m wide plots of four different lengths (0.5, 1.0, 2.0 and 4.0 m) for 2 years from a forested SE Australian site, and with 32 slope length–runoff data sets from 12 other published studies undertaken between 1934 and 2010. Using the parameterised model resulted in a Nash and Sutcliffe statistic between observed and predicted runoff ratio (for all data sets combined) of 0.93, compared with –2.1 when the runoff ratio was fixed at the value measured from the shortest plot. Copyright © 2014 John Wiley & Sons, Ltd.     

A distributed monthly hydrological model for integrating spatial variations of basin topography and rainfall

Hydrological models at a monthly time‐scale are important tools for hydrological analysis, such as in impact assessment of climate change and regional water resources planning. Traditionally, monthly models adopt a conceptual, lumped‐parameter approach and cannot account for spatial variations of basin characteristics and climatic inputs. A large requirement for data often severely limits the utility of physically based, distributed‐parameter models. Based on the variable‐source‐area concept, we considered basin topography and rainfall to be two major factors whose spatial variations play a dominant role in runoff generation and developed a monthly model that is able to account for their influences in the spatial and temporal dynamics of water balance. As a hybrid of the Xinanjiang model and TOPMODEL, the new model is constructed by innovatively making use of the highly acclaimed simulation techniques in the two existing models. A major contribution of this model development study is to adopt the technique of implicit representation of soil moisture characteristics in the Xinanjiang model and use the TOPMODEL concept to integrate terrain variations into runoff simulation. Specifically, the TOPMODEL topographic index ln(a/tanβ) is converted into an index of relative difficulty in runoff generation (IRDG) and then the cumulative frequency distribution of IRDG is used to substitute the parabolic curve, which represents the spatial variation of soil storage capacity in the Xinanjiang model. Digital elevation model data play a key role in the modelling procedures on a geographical information system platform, including basin segmentation, estimation of rainfall for each sub‐basin and computation of terrain characteristics. Other monthly data for model calibration and validation are rainfall, pan evaporation and runoff. The new model has only three parameters to be estimated, i.e. watershed‐average field capacity WM, pan coefficient η and runoff generation coefficient α. Sensitivity analysis demonstrates that runoff is least sensitive to WM and, therefore, it can be determined by a prior estimation based on the climate and soil properties of the study basin. The other two parameters can be determined using optimization methods. Model testing was carried out in a number of nested sub‐basins of two watersheds (Yuanjiang River and Dongjiang River) in the humid region in central and southern China. Simulation results show that the model is capable of describing spatial and temporal variations of water balance components, including soil moisture content, evapotranspiration and runoff, over the watershed. With a minimal requirement for input data and parameterization, this terrain‐based distributed model is a valuable contribution to the ever‐advancing technology of hydrological modelling. Copyright © 2006 John Wiley & Sons, Ltd.