The influence of the calibration metric on design flood estimation using continuous simulation

© 2016 International Association for Hydro-Environment Engineering and Research. Estimation of design flood flow has been and remains a concern for both hydrologic research and hydrologic practice. Knowledge of design flood flows provides a basis for sustainable flood management, which has the aim of reducing flood risk, thereby protecting people’s lives and property. Design floods for a given location can be estimated by a number of approaches including analysis of past flood statistics and the use of catchment modelling. When catchment modelling approaches are applied estimation of design flood flows, there is a need to calibrate the model parameters. As part of this calibration process, a calibration metric, or fitness measure, is needed to enable assessment of alternative sets of parameter values. Presented herein is an investigation into design flood quantiles derived from predictions obtained from a continuous catchment modelling system when alternative calibration metrics are used to assess the suitability of parameter values. Two alternative calibration metrics are considered with one calibration metric aimed at ensuring replication of recorded hydrographs and the second calibration metric aimed at ensuring replication of the statistical characteristics of the annual maxima series. It was found that use of the later calibration metric resulted in better reproduction of the flood probability model estimated from the historical data while reproduction of the recorded hydrographs (i.e. the first calibration metric) did not ensure reproduction of the flood probability model

The hydrological performance of a permeable pavement

Urban stormwater runoff is a transport medium for many contaminants from anthropogenic sources. There are many alternative management strategies available to treat these contaminants. One of the technologies suggested for this purpose is the use of permeable pavements to minimise the quantity of surface runoff generated by impervious surfaces within an urban catchment. Reported herein are the results of a monitoring program undertaken to assess the effectiveness of permeable road surface for managing the quantity and quality of stormwater runoff. It was found that the catchment, where the permeable road surface was installed, had the effective imperviousness reduced from 45% prior to reconstruction of the road surface to less than 5% after reconstruction of the road. Furthermore, it was found that the generation of surface runoff from the permeable road surface required a rainfall intensity in excess of 20 mm/h. Finally, the quality of the surface runoff was found to be at the lower levels of runoff from road surfaces. © 2010 Taylor & Francis

Estimating design flood magnitude for a Vietnamese catchment

© 2015, Engineers Australia. All rights reserved. Flood is a common phenomenon in many tropical countries. Estimation of design flood flow has been a concern for many years in both hydrologic research and in hydrologic practice. Design flood magnitudes provide a basis for sustainable flood management which has the aims of reducing flood risk, and protecting people's lives and property. Design flood magnitudes for a given location can be estimated by a number of approaches including analysis of past flood statistics or the use of catchment modelling approaches like design storm methods or continuous simulation. The aim of this paper is to apply Annual Maximum Series fitting method for design flood estimation in continuous simulation with particular reference to a monsoon catchment. In this aspect, the annual maximum series was used as a performance measure rather than reproduction of individual hydrographs. This approach was used as the focus was on reproducing the observed frequency curve. For this purpose, a case study is performed for a large catchment, namely the Ba River, located in central Vietnam. This catchment is subject to a monsoonal climate and also to tropical cyclones

A Comparison and Strategy of Semantic Segmentation on Remote Sensing Images

In recent years, with the development of aerospace technology, we use more and more images captured by satellites to obtain information. But a large number of useless raw images, limited data storage resource and poor transmission capability on satellites hinder our use of valuable images. Therefore, it is necessary to deploy an on-orbit semantic segmentation model to filter out useless images before data transmission. In this paper, we present a detailed comparison on the recent deep learning models. Considering the computing environment of satellites, we compare methods from accuracy, parameters and resource consumption on the same public dataset. And we also analyze the relation between them. Based on experimental results, we further propose a viable on-orbit semantic segmentation strategy. It will be deployed on the TianZhi-2 satellite which supports deep learning methods and will be lunched soon.Comment: 8 pages, 3 figures, ICNC-FSKD 201

Scour at partially blocked box-culverts under steady flow

© 2016, Thomas Telford Services Ltd. All rights reserved. Culverts are built at locations where a waterway crosses a road or railway and creates a limitation to flow passage. Furthermore, blockage commonly occurs during flood events with accumulation of debris at the culvert inlet. The inlet blockage changes the flow structure at the outlet and may result in culvert failure. Despite this, the impacts of blockage on culvert hydraulics and downstream waterways have not received consideration in the literature. The purpose of this paper is to mitigate this deficiency by reporting on an investigation into scouring at the outlet of partially blocked culverts. Experimental tests were conducted under steady flow to investigate a relationship between the maximum scour depth, blockage ratio of the culvert and the flow characteristics. Both non-blocked and partially blocked conditions were considered. Consideration of the results obtained showed that the scoured area and maximum scour depth increased with partially blocked culverts conditions compared with equivalent non-blocked culverts

Detecting long-term occupancy changes in Californian odonates from natural history and citizen science records

In a world of rapid environmental change, effective biodiversity conservation and management relies on our ability to detect changes in species occurrence. While long-term, standardized monitoring is ideal for detecting change, such monitoring is costly and rare. An alternative approach is to use historical records from natural history collections as a baseline to compare with recent observations. Here, we combine natural history collection data with citizen science observations within a hierarchical Bayesian occupancy modeling framework to identify changes in the occupancy of Californian dragonflies and damselflies (Odonata) over the past century. We model changes in the probability of occupancy of 34 odonate species across years and as a function of climate, after correcting for likely variation in detection probability using proxies for recorder effort and seasonal variation. We then examine whether biological traits can help explain variation in temporal trends. Models built using only opportunistic records identify significant changes in occupancy across years for 14 species, with eight of those showing significant declines and six showing significant increases in occupancy in the period 1900–2013. These changes are consistent with estimates obtained using more standardized resurvey data, regardless of whether resurvey data are used individually or in conjunction with the opportunistic dataset. We find that species increasing in occupancy over time are also those whose occupancy tends to increase with higher minimum temperatures, which suggests that these species may be benefiting from increasing temperatures across California. Furthermore, these species are also mostly habitat generalists, whilst a number of habitat specialists display some of the largest declines in occupancy across years. Our approach enables more robust estimates of temporal trends from opportunistic specimen and observation data, thus facilitating the use of these data in biodiversity conservation and management

de Branges-Rovnyak spaces: basics and theory

For $S$ a contractive analytic operator-valued function on the unit disk ${\mathbb D}$, de Branges and Rovnyak associate a Hilbert space of analytic functions ${\mathcal H}(S)$ and related extension space ${\mathcal D(S)}$ consisting of pairs of analytic functions on the unit disk ${\mathbb D}$. This survey describes three equivalent formulations (the original geometric de Branges-Rovnyak definition, the Toeplitz operator characterization, and the characterization as a reproducing kernel Hilbert space) of the de Branges-Rovnyak space ${\mathcal H}(S)$, as well as its role as the underlying Hilbert space for the modeling of completely non-isometric Hilbert-space contraction operators. Also examined is the extension of these ideas to handle the modeling of the more general class of completely nonunitary contraction operators, where the more general two-component de Branges-Rovnyak model space ${\mathcal D}(S)$ and associated overlapping spaces play key roles. Connections with other function theory problems and applications are also discussed. More recent applications to a variety of subsequent applications are given in a companion survey article