Statistical and Hybrid Methods Implemented in a Web Application for Predicting Reservoir Inflows during Flood Events

Reservoir management is a critical component of flood management, and information on reservoir inflows is particularly essential for reservoir managers to make real‐time decisions given that flood conditions change rapidly. This study's objective is to build real‐time data‐driven services that enable managers to rapidly estimate reservoir inflows from available data and models. We have tested the services using a case study of the Texas flooding events in the Lower Colorado River Basin in November 2014 and May 2015, which involved a sudden switch from drought to flooding. We have constructed two prediction models: a statistical model for flow prediction and a hybrid statistical and physics‐based model that estimates errors in the flow predictions from a physics‐based model. The study demonstrates that the statistical flow prediction model can be automated and provides acceptably accurate short‐term forecasts. However, for longer term prediction (2 h or more), the hybrid model fits the observations more closely than the purely statistical or physics‐based prediction models alone. Both the flow and hybrid prediction models have been published as Web services through Microsoft's Azure Machine Learning (AzureML) service and are accessible through a browser‐based Web application, enabling ease of use by both technical and nontechnical personnel.     

River Channel Geometry and Rating Curve Estimation Using Height above the Nearest Drainage

River channel geometry is an important input to hydraulic and hydrologic models. Traditional approaches to quantify river geometry have involved surveyed river cross sections, which cannot be extended to ungaged basins. In this paper, we describe a method for developing a synthetic rating curve to relate flow to water level in a stream reach based on reach‐averaged channel geometry properties developed using the Height above Nearest Drainage (HAND) method. HAND uses a digital elevation model (DEM) of the terrain and computes the elevation difference between each land surface cell and the stream bed cell to which it drains. Taking increments in water level in the stream, HAND defines the inundation zone and a water depth grid within this zone, and the channel characteristics are defined from this water depth grid. We apply our method to the Blanco River (Texas) and the Tar River (North Carolina) using 10‐m terrain data from the United States Geological Survey (USGS) 3D Elevation Program (3DEP) dataset. We evaluate the method's performance by comparing the reach‐average stage‐river geometry relationships and rating curves to those from calibrated Hydrologic Engineering Center's River Analysis System (HEC‐RAS) models and USGS gage observations. The results demonstrate that after some adjustment, the river geometry information and rating curves derived from HAND using national‐coverage datasets are comparable to those obtained from hydraulic models or gage measurements. We evaluate the inundation extent and show our approach is able to capture the majority of the Federal Emergency Management Agency (FEMA) 100‐year floodplain.     

Seasonal and Flood‐Induced Variations in Groundwater–Surface Water Exchange in a Northern Coldwater Fishery

Groundwater upwelling is important to coldwater fisheries survival. This study used stable isotopes to identify upwelling zones within a watershed, then combined isotope analyses with reach‐scale monitoring to measure surface water–groundwater exchange over time. Research focused on Amity Creek, Minnesota, a basin that exemplifies conditions limiting coldwater species survival along Lake Superior's North Shore where shallow bedrock limits groundwater capacity, lowering baseflows and increasing temperatures. Groundwater‐fed reaches were identified through synoptic isotope sampling, with results highlighting the importance of isolated shallow surficial aquifers (glacially derived sands and gravels) for providing cold baseflow waters. In an alluvial reach, monitoring well results show groundwater was stored in two reservoirs: one that reacts quickly to changes in stream levels, and one that remained isotopically isolated under most flow conditions, but which helps sustain summer baseflows for weeks to months. A 500‐year flood demonstrated the capacity of high‐flow events to alter surface water–groundwater connectivity. The previously isolated reservoir was exchanged or mixed during the flood pulse, while incision lowered the water table for years. The results here provide insight for streams that lack substantial groundwater inputs yet maintain coldwater species at risk in a warming climate and an approach for managers seeking to protect cold baseflow sources.     

Social Dimensions of Urban Flood Experience,Exposure, and Concern

With growing urban populations and climate change, urban flooding is an important global issue, even in dryland regions. Flood risk assessments are usually used to identify vulnerable locations and populations, flooding experience patterns, or levels of concern about flooding, but rarely are all of these approaches combined. Furthermore, the social dynamics of flood concerns, exposure, and experience are underexplored. We combined geographic and survey data on household‐level measures of flood experience, concern, and exposure in Utah's urbanizing Wasatch Front. We asked: (1) Are socially vulnerable groups more likely to be exposed to flood risk? (2) How common are flooding experiences among urban residents, and how are these experiences related to sociodemographic characteristics and exposure? and (3) How concerned are urban residents about flooding, and does concern vary by exposure, flood experience, and sociodemographic characteristics? Although floodplain residents were more likely to be White and have higher incomes, respondents who were of a racial/ethnic minority, were older, had less education, and were living in floodplains were more likely to report flood experiences and concern about flooding. Flood risk management approaches need to address social as well as physical sources of vulnerability to floods and recognize social sources of variation in flood experiences and concern.     

From disaster management to adaptive governance? Governance challenges to achieving resilient food systems in Australia

Building resilient food systems in the context of climate change and increased natural disasters depends on governance being more ‘adaptive’. Through a case study of events surrounding the extensive flooding that occurred in Queensland, Australia, in 2011, this paper examines how governance settings and processes affected food system actors’ engagement with three aspects of adaptive governance – responsibility, participation and collaboration – as those actors sought to ensure food availability and access during the crisis. We found that, despite the existence of formal governance instruments committed to disaster management, food security and resilience at local, state and national levels, responsibilities for ensuring food supply during a disaster were not clearly articulated. Responsibility was largely assumed by supermarkets, who in turn increased the influence of retailer–government coalitions. The participation of non-supermarket food system actors in governance was low, and there was limited collaboration between local, and other, levels of governance. The policy challenge is to ensure that responsibility, participation and collaboration become a stronger foci for adaptive governance during and after a disaster such as flooding.     

Biogeographic distribution patterns of algal community in different urban lakes in China: Insights into the dynamics and co-existence

Urban lake ecosystems are significant for social development, but currently we know little about the geographical distribution of algal community in urban lakes at a large-scale. In this study, we investigated the algal community structure in different areas of urban lakes in China and evaluated the influence of water quality parameters and geographical location on the algal community. The results showed that obvious differences in water quality and algal communities were observed among urban lakes in different geographical areas. Chlorophyta was the dominant phylum, followed by cyanobacteria in all areas. The network analysis indicated that algal community composition in urban lakes of the western and southern area showed more variations than the eastern and northern areas, respectively. Redundancy analysis and structural equation model revealed that nutrients and pH were dominant environmental factors that affected the algal community, and they showed higher influence than that of iron, manganese and COD _Mn concentration. Importantly, algal community and density exhibited longitude and latitude relationship. In general, these results provided an ecological insight into large-scale geographical distributions of algal community in urban lakes, thereby having potential applications for management of the lakes.     

城市垃圾能源化初探

简要介绍了城市垃圾能源化的可行性及利用城市垃圾制取气态、液态、固态燃料方法     

城市土地资产运作的七大对策

城市土地资产经营，关系到城市化进程乃至整个宏观经济的运行，必须实行战略思想的转变和战略对策的落实。本文借鉴国内外研究成果．提出了深化城市土地资产经营的对策与建议。     

滇中城市群产业结构与用地结构关联研究

城市群产业结构与用地结构的协调发展有利于提高滇中城市群用地的空间绩效,优化城市群产业结构,提升城市群的整体功能.运用比例变化指数和Granger因果关系方法研究了滇中城市群产业结构和土地利用之间的变化关系：滇中城市群产业结构变化滞后于城市土地结构变化,城市土地结构变化和产业结构变化的差距呈先增加后减少的趋势,即滇中城市群产业结构和土地利用结构由非同步变化逐渐进入同步变化轨迹;短期内,滇中城市群产业结构变化促进了优化土地利用,土地利用变化又反作用于产业结构,但滇中产业结构和用地结构未出现同步变化规律,说明滇中产业结构和土地的因果关系结构要在长期发展才可能实现.     

Arc StormSurge: Integrating Hurricane Storm Surge Modeling and GIS

Arc StormSurge is a data model that integrates geographic information systems and the hurricane wave and surge model SWAN+ADCIRC, which is the coupling of the Simulating WAves Nearshore (SWAN) wave model and the Advanced Circulation (ADCIRC) hydrodynamic model. The Arc StormSurge data model is a geodatabase, which is a relational database that can contain georeferenced information. It includes feature classes in feature datasets and tables, all related among them through relationship classes, and raster catalogs and grids. In addition to the data model schema, Arc StormSurge includes a number of pre‐ and post‐processing tools that help integrate spatial data and numerical modeling. As an illustration, Arc StormSurge was used to support the modeling of Hurricane Bret, which made landfall in the Corpus Christi area in Texas in 1999. By using Arc StormSurge, it was possible to take advantage of already available geo‐referenced information (e.g., base maps, land cover datasets, and monitoring station locations) for the model setup, and for identifying spatial patterns in the model results by presenting them in map format.