Understanding and managing the morphology of branches incising into sand-clay deposits in the Dutch Rhine Delta

In the Rhine-Meuse delta in the south-western part of the Netherlands,the morphology of the river branches is highly dependent on the erodibility of the subsoil.Erosion processes that were initiated after closure of the Haringvliet estuary branch by a dam(in 1970),caused a strong incision of several connecting branches.Due to the geological evolution of this area the lithology of the subsoil shows large variations in highly erodible sand and poorly erodible peat and clay layers.This study shows how the geological information can be used to create 3D maps of the erodibility of the sub-soil, and how this information can be used to schematize the sub-soil in computational models for morphological simulations.Local incisement of sand patches between areas with poorly erodible bed causes deep scour holes,hence increasing the risk on river-bank instability(flow slides) and damage to constructions such as groynes,quays,tunnels, and pipelines.Various types of mathematical models,ranging from 1D(SOBEK) to quasi-3D(Delft3D) have been applied to study the future development of the river bed and possible management options.The results of these approaches demonstrate that models require inclusion of a layer-bookkeeping approach for sub-soil schematization, non-uniform sediment fractions(sand-mud),tidal and river-discharge boundary conditions,and capacity-reduction transport modeling.For risk-reducing river management it has been shown how the development of the river bed can be addressed on a large scale and small scale.For instance,the use of sediment feeding and fixation of bed can be proposed for large-scale management,while monitoring and interventions at initiation of erosion can be proposed as response to small-scale developments that exceed predefined intervention levels.     

近地等离子体片中磁场扰动和离子速度扰动的统计研究

利用THEMIS THC卫星观测数据统计分析近地等离子体片中磁场扰动和等离子体整体流的速度扰动的关系,研究Alfven波动的活动性.研究结果表明:1)等离子体整体流的速度扰动幅度依赖于平均速度的大小,速度扰动幅度随平均速度的增加而增加;2)速度扰动幅度与磁场扰动幅度存在较强的正相关性;3)磁场扰动幅度与AE指数密切相关,磁场扰动幅度随着AE指数增加而增加,而速度扰动幅度与AE指数之间没有明显的相关性;4)Alfven比与AE指数的相关系数较小,但能够看出Alfven比随着AE指数增加而减小的趋势;5)速度扰动幅度和磁场扰动幅度与尾向距离及距中性片距离的关系不明显.     

A spatial cross‐correlation model of spectral accelerations at multiple periods

Many seismic loss problems (such as disruption of distributed infrastructure and losses to portfolios of structures) are dependent upon the regional distribution of ground‐motion intensity, rather than intensity at only a single site. Quantifying ground‐motion over a spatially‐distributed region therefore requires information on the correlation between the ground‐motion intensities at different sites during a single event. The focus of the present study is to assess the spatial correlation between ground‐motion spectral accelerations at different periods. Ground motions from eight well‐recorded earthquakes were used to study the spatial correlations. On the basis of obtained empirical correlation estimates, we propose a geostatistics‐based method to formulate a predictive model that is suitable for simulation of spectral accelerations at multiple sites and multiple periods, in the case of crustal earthquakes in active seismic regions. While the calibration of this model and investigation of its implications were somewhat complex, the model itself is very simple to use for making correlation predictions. A user only needs to evaluate a simple equation relying on three sets of coefficients provided here to compute a correlation coefficient for spectral values at two periods and at a specified separation distance. These results may then be used in evaluating the seismic risk of portfolios of structures with differing fundamental periods. Copyright © 2012 John Wiley & Sons, Ltd.     

Estimation of phosphorus loads with sparse data for agricultural watersheds in the Czech Republic

Abstract

Agricultural watersheds in the Czech Republic are one of the primary sources of non-point-source phosphorus (P) loads in receiving waters. Since such non-point sources are generally located in headwater catchments, streamflow and P concentration data are sparse. We show how very short daily streamflow and P concentration records can be combined with nearby longer existing daily streamflow records to result in reliable estimates of daily and annual P concentrations and loads. Maintenance of variance streamflow record extension methods (MOVE) can be employed to extend short streamflow records. Constituent load regressions are used to predict daily P constituent loads from streamflow and other time varying characteristics. Annual P loads are then estimated for individual watersheds. Resulting annual P load estimates ranged from 0.21 to 95.4 kg year^-1 with a mean value of 11.77 kg year^-1. Similarly annual P yield estimates ranged from 0.01 to 0.3 kg ha^-1 year^-1 with an average yield of 0.07 kg ha^-1 year^-1. We document how short records of daily streamflow and P concentrations can be combined with a national network of daily streamflow records in the Czech Republic to arrive at meaningful and reliable estimates of annual P loads for small agricultural watersheds.

Citation Beránková, T., Vogel, R. M., Fiala, D. & Rosendorf, P. (2010) Estimation of phosphorus loads with sparse data for agricultural watersheds in the Czech Republic. Hydrol. Sci. J. 55(8), 1417–1426.     

Comparison of direct statistical and indirect statistical-deterministic frameworks in downscaling river low-flow indices

ABSTRACT

This work explores the ability of two methodologies in downscaling hydrological indices characterizing the low flow regime of three salmon rivers in Eastern Canada: Moisie, Romaine and Ouelle. The selected indices describe four aspects of the low flow regime of these rivers: amplitude, frequency, variability and timing. The first methodology (direct downscaling) ascertains a direct link between large-scale atmospheric variables (the predictors) and low flow indices (the predictands). The second (indirect downscaling) involves downscaling precipitation and air temperature (local climate variables) that are introduced into a hydrological model to simulate flows. Synthetic flow time series are subsequently used to calculate the low flow indices. The statistical models used for downscaling low flow hydrological indices and local climate variables are: Sparse Bayesian Learning and Multiple Linear Regression. The results showed that direct downscaling using Sparse Bayesian Learning surpassed the other approaches with respect to goodness of fit and generalization ability.

Editor D. Koutsoyiannis; Associate editor K. Hamed     

Kinematics of active earthflows revealed by digital image correlation and DEM subtraction techniques applied to multi‐temporal LiDAR data

Earthflow‐type landslides are persistent natural hazards having deep socio‐economic and environmental consequences. They have significantly contributed to the geomorphic evolution of mountainous slopes in Europe since the Late Glacial. An understanding of their complex kinematics is crucial to better constrain the processes governing their occurrence and mobility. In this work we explored the possibility to quantify displacement vectors on a spatially distributed basis and to quantify volumetric transfer at the slope scale with regard to a large flow‐type landslide located in the northern Apennines of Italy. For this purpose we applied digital image correlation (DIC) and digital elevation model differencing (DEMoD) techniques to multi‐temporal airborne LiDAR surveys of 2006, 2007 and 2009. The DIC was applied to greyscale slope gradient maps retrieved after precise co‐registration of LiDAR surveys. Thereby, movement patterns over various sectors of the landslide were reconstructed and quantified, most notably up to 20 m in the head zone, up to 51 m in the lower main track, and up to about 27 m at the landslide toe. The DEMoD analysis revealed significant mass transfer from the source to the tracks and toe zone, with the upper flow tracks acting as temporal storage of large amounts of material. The mass balance indicated that significant amounts of advancing landslide debris were eroded by a local stream. An integrated analysis of DEMoD and DIC results allowed for a discussion of governing processes, such as the transition from slide to flow, the influence of underlying topography on earthflow mobility, and the role of undrained loading as a mechanism of toe zone reactivation. In conclusion, the successful application of DIC and DEMoD to the case study underlines the added value of high‐resolution DEMs in the analysis of earthflow kinematics toward a better understanding of their role in the geomorphic evolution of slopes. Copyright © 2012 John Wiley & Sons, Ltd.     

On the quest for chaotic attractors in hydrological processes

Abstract

In the last two decades, several researchers have claimed to have discovered low-dimensional determinism in hydrological processes, such as rainfall and runoff, using methods of chaotic analysis. However, such results have been criticized by others. In an attempt to offer additional insights into this discussion, it is shown here that, in some cases, merely the careful application of concepts of dynamical systems, without doing any calculation, provides strong indications that hydrological processes cannot be (low-dimensional) deterministic chaoti. Furthermore, it is shown that specific peculiarities of hydrological processes on fine time scales, such as asymmetric, J-shaped distribution functions, intermittency, and high autocorrelations, are synergistic factors that can lead to misleading conclusions regarding the presence of (low-dimensional) deterministic chaos. In addition, the recovery of a hypothetical attractor from a time series is put as a statistical estimation problem whose study allows, among others, quantification of the required sample size; this appears to be so huge that it prohibits any accurate estimation, even with the largest available hydrological records. All these arguments are demonstrated using appropriately synthesized theoretical examples. Finally, in light of the theoretical analyses and arguments, typical real-world hydrometeorological time series, such as relative humidity, rainfall, and runoff, are explored and none of them is found to indicate the presence of chaos.     

Turbidity dynamics in karstic systems. Example of Ribaa and Bittit springs in the Middle Atlas (Morocco)

Abstract

The identification of the turbidity mechanisms in two karstic springs (Ribaa and Bittit) located in the Middle Atlas Plateau in Morocco was performed by means of correlation and spectral analyses applied to time series of rainfall, flow rates, and turbidity. Time series analyses of rainfall and discharges revealed high inertia and storage capacities of the karstic systems. However, the occurrence of turbidity in the springs proved independent of discharges. A causal relationship between rainfall and the occurrence of turbidity in the form of waves was established. Accordingly, turbidity was assumed to be related to the hydrodynamic conditions prevailing in the karst. Turbulent quickflows in the karst transmissive conduits, following heavy rainfall, are thought to provoke the resuspension of solid particles deposited in the conduits, as well as their transport towards outlets. An external origin has also been contemplated, concerning infiltration waters may be loaded with suspended matters washed from the watershed.     

Automatic sub-pixel co-registration of Landsat-8 Operational Land Imager and Sentinel-2A Multi-Spectral Instrument images using phase correlation and machine learning based mapping

ABSTRACT

This study investigates misregistration issues between Landsat-8/ Operational Land Imager and Sentinel-2A/ Multi-Spectral Instrument at 30?m resolution, and between multi-temporal Sentinel-2A images at 10?m resolution using a phase-correlation approach and multiple transformation functions. Co-registration of 45 Landsat-8 to Sentinel-2A pairs and 37 Sentinel-2A to Sentinel-2A pairs were analyzed. Phase correlation proved to be a robust approach that allowed us to identify hundreds and thousands of control points on images acquired more than 100 days apart. Overall, misregistration of up to 1.6 pixels at 30?m resolution between Landsat-8 and Sentinel-2A images, and 1.2 pixels and 2.8 pixels at 10?m resolution between multi-temporal Sentinel-2A images from the same and different orbits, respectively, were observed. The non-linear random forest regression used for constructing the mapping function showed best results in terms of root mean square error (RMSE), yielding an average RMSE error of 0.07?±?0.02 pixels at 30?m resolution, and 0.09?±?0.05 and 0.15?±?0.06 pixels at 10?m resolution for the same and adjacent Sentinel-2A orbits, respectively, for multiple tiles and multiple conditions. A simpler 1st order polynomial function (affine transformation) yielded RMSE of 0.08?±?0.02 pixels at 30?m resolution and 0.12?±?0.06 (same Sentinel-2A orbits) and 0.20?±?0.09 (adjacent orbits) pixels at 10?m resolution.     

利用外部DEM辅助山区SAR立体像对匹配及地形制图

SAR立体像对的匹配是利用雷达摄影测量技术提取地形高程信息的关键,匹配精度将直接影响结果 DEM的高程精度。针对山区SAR立体像对匹配过程中同名点选取困难的问题,引入外部粗分辨率DEM作为辅助数据,将该DEM高程转换为视差,为匹配提供初值,同时采用金字塔匹配策略,不仅可以缩小搜索范围,提高搜索效率,而且能够减少粗差的产生。试验结果表明,采用外部DEM辅助之后,匹配粗差点数量相对于传统的雷达摄影测量处理结果明显减少,从而有效地提高了高程信息提取重建的精度。