Snow model sensitivity analysis to understand spatial and temporal snow dynamics in a high‐elevation catchment

In this paper, we addressed a sensitivity analysis of the snow module of the GEOtop2.0 model at point and catchment scale in a small high‐elevation catchment in the Eastern Italian Alps (catchment size: 61 km²). Simulated snow depth and snow water equivalent at the point scale were compared with measured data at four locations from 2009 to 2013. At the catchment scale, simulated snow‐covered area (SCA) was compared with binary snow cover maps derived from moderate‐resolution imaging spectroradiometer (MODIS) and Landsat satellite imagery. Sensitivity analyses were used to assess the effect of different model parameterizations on model performance at both scales and the effect of different thresholds of simulated snow depth on the agreement with MODIS data. Our results at point scale indicated that modifying only the “snow correction factor” resulted in substantial improvements of the snow model and effectively compensated inaccurate winter precipitation by enhancing snow accumulation. SCA inaccuracies at catchment scale during accumulation and melt period were affected little by different snow depth thresholds when using calibrated winter precipitation from point scale. However, inaccuracies were strongly controlled by topographic characteristics and model parameterizations driving snow albedo (“snow ageing coefficient” and “extinction of snow albedo”) during accumulation and melt period. Although highest accuracies (overall accuracy = 1 in 86% of the catchment area) were observed during winter, lower accuracies (overall accuracy < 0.7) occurred during the early accumulation and melt period (in 29% and 23%, respectively), mostly present in areas with grassland and forest, slopes of 20–40°, areas exposed NW or areas with a topographic roughness index of ?0.25 to 0 m. These findings may give recommendations for defining more effective model parameterization strategies and guide future work, in which simulated and MODIS SCA may be combined to generate improved products for SCA monitoring in Alpine catchments.     

Elastic lateral dynamic impedance functions for a rigid cylindrical shell type foundation

Elastic lateral dynamic impedance functions are defined as the ratio of the lateral dynamic force/moment to the corresponding lateral displacement/rotation at the top ending of a foundation at very small strains. Elastic lateral dynamic impedance functions have a defining influence on the natural frequencies of offshore wind turbines supported on cylindrical shell type foundations, such as suction caissons, bucket foundations, and monopiles. This paper considers the coupled horizontal and rocking vibration of a cylindrical shell type foundation embedded in a fully saturated poroelastic seabed in contact with a seawater half‐space. The formulation of the coupled seawater–shell–seabed vibration problem is simplified by treating the shell as a rigid one. The rigid shell vibration problem is approached by the integral equation method using ring‐load Green's functions for a layered seawater‐seabed half‐space. By considering the boundary conditions at the shell–soil interface, the shell vibration problem is reduced to Fredholm integral equations. Through an analysis of the corresponding Cauchy singular equations, the intrinsic singular characteristics of the problem are rendered explicit. With the singularities incorporated into the solution representation, an effective numerical method involving Gauss–Chebyshev method is developed for the governing Fredholm equations. Selected numerical results for the dynamic contact load distributions, displacements of the shell, and lateral dynamic impedance functions are examined for different shell length–radius ratio, poroelastic materials, and frequencies of excitation. Copyright © 2016 John Wiley & Sons, Ltd.     

Sensitivity of a hydraulic model to channel erosion uncertainty during extreme flooding

Recent research into flood modelling has primarily concentrated on the simulation of inundation flow without considering the influences of channel morphology. River channels are often represented by a simplified geometry that is implicitly assumed to remain unchanged during flood simulations. However, field evidence demonstrates that significant morphological changes can occur during floods to mobilize the boundary sediments. Despite this, the effect of channel morphology on model results has been largely unexplored. To address this issue, the impact of channel cross‐section geometry and channel long‐profile variability on flood dynamics is examined using an ensemble of a 1D–2D hydraulic model (LISFLOOD‐FP) of the ~1 : 2000 year recurrence interval floods in Cockermouth, UK, within an uncertainty framework. A series of simulated scenarios of channel erosional changes were constructed on the basis of a simple velocity‐based model of critical entrainment. A Monte‐Carlo simulation framework was used to quantify the effects of this channel morphology together with variations in the channel and floodplain roughness coefficients, grain size characteristics and critical shear stress on measures of flood inundation. The results showed that the bed elevation modifications generated by the simplistic equations reflected an approximation of the observed patterns of spatial erosion that enveloped observed erosion depths. The effect of uncertainty on channel long‐profile variability only affected the local flood dynamics and did not significantly affect the friction sensitivity and flood inundation mapping. The results imply that hydraulic models generally do not need to account for within event morphodynamic changes of the type and magnitude of event modelled, as these have a negligible impact that is smaller than other uncertainties, e.g. boundary conditions. Instead, morphodynamic change needs to happen over a series of events to become large enough to change the hydrodynamics of floods in supply limited gravel‐bed rivers such as the one used in this research. Copyright © 2014 John Wiley & Sons, Ltd.     

Integrating isolated and riparian wetland modules in the PHYSITEL/HYDROTEL modelling platform: model performance and diagnosis

Mathematical modelling is a well‐accepted framework to evaluate the effects of wetlands on stream flow and watershed hydrology in general. Although the integration of wetland modules into a distributed hydrological model represents a cost‐effective way to make this assessment, the added value brought by landscape‐specific modules to a model's ability to replicate basic hydrograph characteristics remains unclear. The objectives of this paper were the following: (i) to present the adaptation of PHYSITEL (a geographic information system) to parameterize isolated and riparian wetlands; (ii) to describe the integration of specific isolated wetland and riparian wetland modules into HYDROTEL, a distributed hydrological model; and (iii) to evaluate the performance of the updated modelling platform with respect to the capacity of replicating various hydrograph characteristics. To achieve this, two sets of simulations were performed (with and without wetland modules), and the added value was assessed at three river segments of the Becancour River watershed, Quebec, Canada, using six general goodness‐of‐fit indicators and 14 water flow criteria. A sensitivity analysis of the wetland module parameters was performed to characterize their impact on stream flows of the modelled watershed. Results of this study indicate the following: (i) integration of specific wetland modules can slightly increase the capacity of HYDROTEL to replicate basic hydrograph characteristics; and (ii) the updated modelling platform allows for the explicit assessment of the impact of wetlands (e.g. typology and location) on watershed hydrology. Copyright © 2015 John Wiley & Sons, Ltd.     

Sensitivity of soil parameters in unsaturated zone modelling and the relation between effective,laboratory and in situ estimates

Simulation of soil moisture content requires effective soil hydraulic parameters that are valid at the modelling scale. This study investigates how these parameters can be estimated by inverse modelling using soil moisture measurements at 25 locations at three different depths (at the surface, at 30 and 60 cm depth) on an 80 by 20 m hillslope. The study presents two global sensitivity analyses to investigate the sensitivity in simulated soil moisture content of the different hydraulic parameters used in a one‐dimensional unsaturated zone model based on Richards' equation. For estimation of the effective parameters the shuffled complex evolution algorithm is applied. These estimated parameters are compared to their measured laboratory and in situ equivalents. Soil hydraulic functions were estimated in the laboratory on 100 cm³ undisturbed soil cores collected at 115 locations situated in two horizons in three profile pits along the hillslope. Furthermore, in situ field saturated hydraulic conductivity was estimated at 120 locations using single‐ring pressure infiltrometer measurements. The sensitivity analysis of 13 soil physical parameters (saturated hydraulic conductivity (K_s), saturated moisture content (θ_s), residual moisture content (θ_r), inverse of the air‐entry value (α), van Genuchten shape parameter (n), Averjanov shape parameter (N) for both horizons, and depth (d) from surface to B horizon) in a two‐layer single column model showed that the parameter N is the least sensitive parameter. K_s of both horizons, θ_s of the A horizon and d were found to be the most sensitive parameters. Distributions over all locations of the effective parameters and the distributions of the estimated soil physical parameters from the undisturbed soil samples and the single‐ring pressure infiltrometer estimates were found significantly different at a 5% level for all parameters except for α of the A horizon and K_s and θ_s of the B horizon. Different reasons are discussed to explain these large differences. Copyright © 2004 John Wiley & Sons, Ltd.     

Fourier-based multi-scale representation and progressive transmission of cartographic curves on the internet

ABSTRACT

Automatic generation of multi-scale representations from the same spatial data source has been the research focus in map generalization for a long time. Based on the Fourier technique, this paper proposes a continuous, multi-scale representation model for progressive transformation of cartographic curves on the Internet. In our method, all the curves, whether closed or open, are depicted as periodical functions which are further expressed as Fourier series. The convergence degrees of the Fourier series are explored for different kinds of curves, and truncating frequencies are derived based on the similarity between the original and reconstructed curves. Using information theory and the Radical Law in cartography, the relationship between map scales and Fourier frequencies is established. Based on the proposed multi-scale model, we also introduce the principles and implementation of a progressive transmission method. Our method is evaluated using the contours from a topographic map. The results show that our model is a valid approach to multi-scale representation of cartographic curves.     

Effect of sensor modelling methods on computation of 3-D coordinates from Cartosat-1 stereo data

The orbital and the rational polynomial coefficients (RPC) models are the two most commonly used models to compute a three-dimensional coordinates from an image stereo-pair. But it is still confusing that with the identical user provided inputs, which one of these two models provides more accurate digital elevation model (DEM), especially for mountainous terrain. This study aimed to find out the answer by evaluating the impact of used models on the vertical accuracy of DEM extracted from Cartosat-1 stereo data. We used high-accuracy photogrammetric DEM as the reference DEM. Apart from general variations in statistics, surprisingly in a few instances, both the DEMs provided contrasting results, thus proving the significance of this study. The computed root mean square errors and linear error at 90% (LE90) were lower in case of RPC DEM for various classes of slope, aspect and land cover, thus suggesting its better relative accuracy.     

基于灵敏度分析的海洋油气资源BP神经网络预测模型的优化

作者针对BP神经网络结构设计中存在的问题,提出利用灵敏度分析方法对BP神经网络预测模型进行优化。通过BP算法与参数灵敏度分析的结合,寻找网络输入属性与输出属性之间的影响因子;在保证精度的前提下优选网络输入属性,简化网络结构,以增强网络的泛化能力,减少人为主观因素对网络设计的影响。最后以海洋油气资源预测为例,结合实测资料建立BP神经网络预测模型并进行了优化及预测精度评价,表明优化后的模型既能有效提高油气资源预测结果的稳定性,又不损失预测精度。     

6600 years of earthquake record in the Julian Alps (Lake Bohinj,Slovenia)

Sequences of lake sediments often form long and continuous records that may be sensitive recorders of seismic shaking. A multi‐proxy analysis of Lake Bohinj sediments associated with a well‐constrained chronology was conducted to reconstruct Holocene seismic activity in the Julian Alps (Slovenia). A seismic reflection survey and sedimentological analyses identified 29 homogenite‐type deposits related to mass‐wasting deposits. The most recent homogenites can be linked to historical regional earthquakes (i.e. 1348 ad , 1511 ad and 1690 ad ) with strong epicentral intensity [greater than ‘damaging’ (VIII ) on the Medvedev–Sponheuer–Karnik scale]. The correlation between the historical earthquake data set and the homogenites identified in a core isolated from local stream inputs, allows interpretation of all similar deposits as earthquake related. This work extends the earthquake chronicle of the last 6600 years in this area with a total of 29 events recorded. The early Holocene sedimentary record is disturbed by a seismic event (6617 ± 94 cal yr bp ) that reworked previously deposited sediment and led to a thick sediment deposit identified in the seismic survey. The period between 3500 cal yr bp and 2000 cal yr bp is characterized by a major destabilization in the watershed by human activities that led to increases in erosion and sedimentation rates. This change increased the lake's sensitivity to recording an earthquake (earthquake‐sensitivity threshold index) with the occurrence of 72 turbidite‐type deposits over this period. The high turbidite frequency identified could be the consequence of this change in lake earthquake sensitivity and thus these turbidites could be triggered by earthquake shaking, as other origins are discarded. This study illustrates why it is not acceptable to propose a return period for seismic activity recorded in lake sediment if the sedimentation rate varies significantly.     

A geometric-based approach for road matching on multi-scale datasets using a genetic algorithm

Object matching is used in various applications including conflation, data quality assessment, updating, and multi-scale analysis. The objective of matching is to identify objects referring to the same entity. This article aims to present an optimization-based linear object-matching approach in multi-scale, multi-source datasets. By taking into account geometric criteria, the proposed approach uses real coded genetic algorithm (RCGA) and sensitivity analysis to identify corresponding objects. Moreover, in this approach, any initial dependency on empirical parameters such as buffer distance, threshold of spatial similarity degree, and weights of criteria is eliminated and, instead, the optimal values for these parameters are calculated for each dataset. Volunteered geographical information (VGI) and authoritative data with different scales and sources were used to assess the efficiency of the proposed approach. According to the results, in addition to an efficient performance in various datasets, the proposed approach was able to appropriately identify the corresponding objects in these datasets by achieving higher F-Score.