Flood-type trend analysis for alpine catchments

ABSTRACT

In many places, magnitudes and frequencies of floods are expected to increase due to climate change. To understand these changes better, trend analyses of historical data are helpful. However, traditional trend analyses do not address issues related to shifts in the relative contributions of rainfall versus snowmelt floods, or in the frequency of a particular flood type. We present a novel approach for quantifying such trends in time series of floods using a fuzzy decision tree for event classification and applied it to maximal annual and seasonal floods in 27 alpine catchments for the period 1980–2014. Trends in flood types were studied with Sen’s slope and double mass curves. Our results reveal a decreasing number of rain-on-snow and an increasing number of short rainfall events in all catchments, with flash floods increasing in smaller catchments. Overall, the results demonstrate the value of incorporating a fuzzy flood-type classification into flood trend analyses.     

A minimalistic approach for evapotranspiration estimation using the Prophet model

ABSTRACT

This study aimed to evaluate the potential of the recently introduced Prophet model for estimating reference evapotranspiration (ETo). A comparative study was conducted for benchmarking the model results with support vector regression (SVR) and temperature-based empirical models (Thornthwaite and Hargreaves) in southern Japan. The performance of the Prophet, SVR and temperature-based empirical models was evaluated by Nash–Sutcliffe efficiency (NSE) and coefficient of determination (R²). The results indicate that temperature-based Prophet and SVR models have greater accuracy than the empirical models. The Prophet model with sole input of relative humidity, sunshine hours or windspeed showed acceptable accuracy (NSE > 0.80; R² > 0.80), while SVR models with similar inputs showed greater errors. Accuracy improved with increasing number of input parameters, giving excellent performance (NSE > 0.95; R² > 0.95) with all input parameters. Hence, the Prophet model is a new promising approach for modelling ETo with limited input variables.     

A workflow for Sustainable Development Goals indicators assessment based on high-resolution satellite data

ABSTRACT

For evaluating the progresses towards achieving the Sustainable Development Goals (SDGs), a global indicator framework was developed by the UN Inter-Agency and Expert Group on Sustainable Development Goals Indicators. In this paper, we propose an improved methodology and a set of workflows for calculating SDGs indicators. The main improvements consist of using moderate and high spatial resolution satellite data and state-of-the-art deep learning methodology for land cover classification and for assessing land productivity. Within the European Network for Observing our Changing Planet (ERA-PLANET), three SDGs indicators are calculated. In this research, harmonized Landsat and Sentinel-2 data are analyzed and used for land productivity analysis and yield assessment, as well as Landsat 8, Sentinel-2 and Sentinel-1 time series are utilized for crop mapping. We calculate for the whole territory of Ukraine SDG indicators: 15.1.1 – ‘Forest area as proportion of total land area’; 15.3.1 – ‘Proportion of land that is degraded over total land area’; and 2.4.1 – ‘Proportion of agricultural area under productive and sustainable agriculture’. Workflows for calculating these indicators were implemented in a Virtual Laboratory Platform. We conclude that newly available high-resolution remote sensing products can significantly improve our capacity to assess several SDGs indicators through dedicated workflows.     

遥感图像人机交互判读方法研究及其应用

对于大型复杂的遥感判读任务,往往需要灵活地运用不同的判读方法,才能取得令人满意的效果,然而传统目视判读和常规计算机分类都难以满足这一要求,笔者设计了屏幕目视判读,改进型监督自动分类,分区自动分类,辅助波段分类,动态变化判读,人机混合判读和多组分工判读等遥感图像人机交互判读方法,把计算机自动分类与人工判读的优势相结合,对于提高图像判读精度,速度和高效率的遥感专题信息生成,帮助判读人员更好地完成各种遥感图像的判读任务都具有重要的意义,该文探讨了以上方法的特点,适用范围与实现方法,并给出了一些实例加以说明。     

Nonrenewable resources in economic, social, and environmental sustainability

This paper reviews the linkages among energy and mineral resources and economic, social, and environmental sustainability. Nonrenewable resources are shown to be integral components of sustainability, regardless of which paradigmatic definition of the concept is invoked. Potential measures of the degree to which nonrenewable resources contribute to or detract from sustainability are presented. We conclude that a set of such measures should be incorporated in the comprehensive framework of sustainability currently being developed by the Federal government. National scale indicators could be presented within the structure of the seven criteria from the Santiago Declaration, whereas a life cycle or materials flow approach could be used when sustainability of specific resources is at issue.     

A proposal for comparing the reliabilities of alternative seismic hazard models

Differences between statistical unertainty and modeling uncertainty are briefly discussed. It is pointed out that, when different models are proposed for the interpretation of reality, the uncertainty cannot be described in terms of mean value and coefficient of variation. The important question is: which of the proposed models is more reliable than the others? The attention, then, is concentrated on the comparison between different models proposed for the estimate of the required quantity, looking for a criterion leading to the selection of the most reliable one. A criterion for comparison of different models is suggested. In the example of application considered in this paper, it proved to be effective, so that the continuation of numerical experiments, exploring different and more complex situations, seems promising.     

Multiscale approach to geo‐composite cellular structures subjected to rock impacts

Geo‐composite cellular structures are an efficient technological solution for various applications in civil engineering. This type of structure is particularly well adapted to resisting rockfalls and can act as a defensive structure. However, the design of such structures is for the most part empirically based; this lack of research‐based design stagnates optimization and advanced development. In this paper, the mechanical behaviour of a geo‐composite cellular structure is investigated using a multi‐scale approach, from the individual cell made up of an assembly of rocky particles contained in a wire netting cage to the entire structure composed of a regular array of cells. Based on discrete modelling of both the cell and structure scales, a computational tool has been developed for design purposes. Copyright © 2007 John Wiley & Sons, Ltd.     

基于Landsat-8遥感影像和LiDAR测深数据的水深主被动遥

主被动遥感结合反演远海岛礁周边水深信息,不仅可以有效弥补传统测深方法覆盖范围小且费时费力的不足,也可为航运安全、海洋减灾、生态环境保护等领域提供基础资料。以夏威夷瓦胡岛周边水深反演为例,应用Landsat-8多光谱遥感数据和机载Li DAR测深数据,开展了不同密度Li DAR测深数据对水深多光谱遥感反演精度的影响分析、不同水深网格化处理方法对水深遥感反演结果的影响分析和基于少量Li DAR控制区块的大区域水深反演能力分析三方面的研究工作。结果表明:(1)Li DAR测深数据密度的改变对水深反演结果的影响不大,变化后的水深反演结果与原始的水深反演结果相比,平均相对误差变化在0.3%以内,平均绝对误差变化在0.03m以内;(2)采用均值格网处理方法的多光谱遥感水深反演精度要略高于采用中值格网处理方法的水深反演精度,具体体现在均值的平均绝对误差要比中值的低0.04~0.05 m,平均相对误差低1%~10%,反演结果的残差分布显示在0~2 m和20~25 m的水深段内均值统计法的残差分布更集中且其平均值接近于0 m,而在其它水深段二者的残差分布基本相同;(3)基于少量Li DAR控制区块的大区域遥感水深反演结果较为理想,两个检查区块的水深反演结果 R2、平均绝对误差和平均相对误差分别为:0.877,1.66 m,3.5%和0.941,1.62 m,28.4%。反演结果分段分析表明各水深段内反演的精度都比较理想,平均绝对误差除20~25 m水深段外,均低于2.5 m,平均相对误差除0~2 m,2~5 m外,均低于25%。