闽江河口芦苇潮汐湿地甲烷通量及主要影响因子

2007年利用静态箱-气相色谱仪法对闽江河口区最大的鳝鱼滩芦苇湿地和入侵种互花米草斑块涨潮前、涨落潮过程及落潮后甲烷通量季节动态进行了原位测定,并利用室内培养-气相色谱仪法测定了芦苇湿地不同土层土壤甲烷产生潜力.结果表明,鳝鱼滩芦苇湿地全年均属于大气甲烷的排放源,排放通量具有明显的季节变化;涨潮前、涨落潮过程和落潮后甲烷通量大小并无一致的规律,平均排放通量分别为5.13、5.06和4.74 mg·m-2·h-1,差异不显著,其中涨落潮过程排放到潮水和大气环境的甲烷通量分别为2.98和2.08 mg·m-2·h-1.互花米草入侵斑块年均甲烷排放通量(11.02mg·m-2·h-1)明显高于芦苇湿地年均甲烷排放通量(4.98mg·m-2·h-1),互花米草入侵明显增加了闽江河口区湿地的甲烷排放通量.芦苇湿地0～40 cm土壤中甲烷产生潜力范围为0.029～0.123μg·g-1·d-1,0～5 cm土层的甲烷产生潜力最大,且与其它土层差异显著(P<0.05).气温、土壤温度和地上生物量对芦苇湿地甲烷排放影响显著(P<0.05),落潮后芦苇湿地甲烷排放通量与盐度有负相关关系.     

Error Assessment for Height Above the Nearest Drainage Inundation Mapping

Real‐time flood inundation mapping is vital for emergency response to help protect life and property. Inundation mapping transforms rainfall forecasts into meaningful spatial information that can be utilized before, during, and after disasters. While inundation mapping has traditionally been conducted on a local scale, automated algorithms using topography data can be utilized to efficiently produce flood maps across the continental scale. The Height Above the Nearest Drainage method can be used in conjunction with synthetic rating curves (SRCs) to produce inundation maps, but the performance of these inundation maps needs to be assessed. Here we assess the accuracy of the SRCs and calculate statistics for comparing the SRCs to rating curves obtained from hydrodynamic models calibrated against observed stage heights. We find SRCs are accurate enough for large‐scale approximate inundation mapping while not as accurate when assessing individual reaches or cross sections. We investigate the effect of terrain and channel characteristics and observe reach length and slope predict divergence between the two types of rating curves, and SRCs perform poorly for short reaches with extreme slope values. We propose an approach to recalculate the slope in Manning’s equation as the weighted average over a minimum distance and assess accuracy for a range of moving window lengths.     

A Rapid Response Survey to Characterize the Impacts of the 2017 High Water Event on Lake Ontario

In the spring and summer of 2017, communities along the Lake Ontario shoreline suffered from the worst flood event on record. In late May, daily water levels reached their highest point in over 100 years, and flooding continued throughout much of the summer as lake levels slowly declined, with inundation and erosion significantly impacting shoreline homes and businesses. In this work, we present results from a rapid response online survey of property owners along the New York Lake Ontario shoreline to quantify the perceived flood impacts of the 2017 extended high water event. The survey focused on the degree and spatial distribution of inundation and erosion; the duration and drivers of inundation; the associated damages to different property features, with an emphasis on shoreline protection; and the degree of disruption to business and other activities and services. Photographic documentation of inundation extent and property damage also was provided by survey respondents. We demonstrate the potential utility of this dataset by characterizing key features of inundation and erosion impacts across the shoreline, and by using classification and regression trees to explore the predictability of inundation and erosion based on property characteristics. This work is part of a larger effort to develop models of inundation and erosion that can support flood impact assessments across the shoreline and help communities better prepare for future extended high water events.     

Runoff Storage Potential of Drained Upland Depressions on the Des Moines Lobe of Iowa

We present estimates of the volumetric storage capacities of currently drained upland depressions and catchment depressional specific storage and runoff storage indices for the Des Moines Lobe of Iowa (DML‐IA) subregion of the Prairie Pothole Region of North America. Storage capacities were determined using hydrologically enforced Light Detection and Ranging‐derived digital elevation models, and a unique geoprocessing algorithm. Depressional specific storage was estimated for each 12‐digit Hydrologic Unit Code (HUC12) watershed in the region from total catchment‐specific depressional storage volume and catchment area. Runoff storage indices were calculated using catchment depressional specific storage values and estimates of the amount of rainfall likely to fall within each watershed during sub‐annual and 1‐, 2‐, 5‐, and 10‐year 24‐h events. The 173,171 identified drained depressions in the DML‐IA can store up to 903.5 Mm³ of runoff. Most of this capacity is in depressions located in the north of the region. Specific storage varies from nearly 109 mm in the younger landscapes to <10 mm in older more eroded areas. For 95% of the HUC12 watersheds comprising the region, depressional storage will likely be exhausted by rainfall‐derived runoff in excess of a 1‐year 24‐h event. Rainfall amounts greater than a 5‐year 24‐h event will exceed all available depressional storage. Therefore, the capacity of drained depressions in the DML‐IA to mitigate flooding resulting from infrequent, but large, storm events is limited.     

Estimating Floodwater Depths from Flood Inundation Maps and Topography

Information on flood inundation extent is important for understanding societal exposure, water storage volumes, flood wave attenuation, future flood hazard, and other variables. A number of organizations now provide flood inundation maps based on satellite remote sensing. These data products can efficiently and accurately provide the areal extent of a flood event, but do not provide floodwater depth, an important attribute for first responders and damage assessment. Here we present a new methodology and a GIS‐based tool, the Floodwater Depth Estimation Tool (FwDET), for estimating floodwater depth based solely on an inundation map and a digital elevation model (DEM). We compare the FwDET results against water depth maps derived from hydraulic simulation of two flood events, a large‐scale event for which we use medium resolution input layer (10 m) and a small‐scale event for which we use a high‐resolution (LiDAR; 1 m) input. Further testing is performed for two inundation maps with a number of challenging features that include a narrow valley, a large reservoir, and an urban setting. The results show FwDET can accurately calculate floodwater depth for diverse flooding scenarios but also leads to considerable bias in locations where the inundation extent does not align well with the DEM. In these locations, manual adjustment or higher spatial resolution input is required.     

Challenges and Opportunities for Creating Intelligent Hazard Alerts: The “FloodHippo” Prototype

Disasters evolving from hazards are a persistent and deadly occurrence in the United States. Despite this, hazard alerts have remained spatially vague, temporally imprecise, and lack actionable information. These deficiencies indicate a divide between the status quo and what is possible given modern environmental models, geographic information systems (GIS), and smartphone capabilities. This work describes an alternative, prototype system, “FloodHippo,” which integrates operational model outputs, cloud‐based GIS, and expanded communication channels to provide personal and interactive disaster alerts for floods. The precepts and methods underpinning FloodHippo apply equally to other disasters that evolve over space and time, presenting the opportunity for a more intelligent disaster response system. The development of such a system would not only minimize current shortcomings in disaster alerts but also improve resilience through individual action, along with community, academic, and federal cooperation.     

从长江洪水看土壤环境保护的重要性

从１９９８ 年长江流域发生的特大洪水说起,分析从汉代到清末２０００ 年间及近４０ 年来长江流域水旱灾害的变化趋势,认为造成长江洪水灾害的原因主要是气候异常,但也与生态环境遭到破坏有关,其中土壤侵蚀、水土流失是最重要的因素。探讨了防治长江水患的对策;基于对土壤的吸水和贮水功能主要靠地被层和土壤有机质层,而水土流失是从植被破坏、地被层消失开始的,以及对古今治水、治土正反两个方面的认识,提出了治水的同时应治土的观点及５ 条有效的途径。     

A New Flood Index for Use in Evaluation of Local Flood Severity: A Case Study of Small Ungauged Catchments in Korea1

Ahn, Jae Hyun and Hyun Il Choi, 2013. A New Flood Index for Use in Evaluation of Local Flood Severity: A Case Study of Small Ungauged Catchments in Korea. Journal of the American Water Resources Association (JAWRA) 49(1): 1‐14. DOI: 10.1111/jawr.12025 Abstract: The aim of this article is to develop a new index measuring the severity of floods in small ungauged catchments for initial local flood information by the regression analysis between the new flooding index and rainfall patterns. Although a rapid local flood caused by heavy storm in a short period of time is now one of common natural disasters worldwide, such a sudden and violent hydrologic event is difficult to forecast. As local flooding rises rapidly with little or no advance warning, the key to local flood forecasting is to quickly identify when and where local flooding above a threshold is likely to occur. The new flooding index to characterize local floods is measured by the three normalized relative severity factors for the flood magnitude ratio, the rising curve gradient, and the flooding duration time, quantifying characteristics of flood runoff hydrographs. The new flooding index implemented for the two selected small ungauged catchments in the Korean Peninsula shows a very high correlation with logarithm of the 2‐h maximum rainfall depth. This study proposes 30 mm of rainfall in a 2‐h period as a basin‐specific guidance of precaution for the incipient local flooding in the two study catchments. It is expected that the best‐fit regression equation between the new flooding index and a certain rainfall rate can provide preliminary observations, the flood threshold, and severity information, for use in a local flood alert system in small ungauged catchments. Editor's note: This paper is part of a featured series on Korean Hydrology. The series addresses the need for a new paradigm of river and watershed management for Korea due to climate and land use changes.     

Flooding in Texas: Examination of Temporal Changes and Impacts of Tropical Cyclones

Annual maximum peak discharge measurements from 62 stations with a record of at least 70 years are used to assess extreme flooding in Texas at the regional scale. This work focuses on examination of the validity of the stationarity assumption and on the impact of tropical cyclones (TCs) on the upper tail of the flood peak distribution. We assess the validity of the stationarity assumption by testing the records for abrupt and gradual changes. The presence of abrupt changes in the first two moments of the flood peak distribution is assessed using the Lombard test. We use the Mann‐Kendall test to examine the presence of monotonic trends. Results indicate that violations of the stationarity assumption are most commonly caused by abrupt changes, which are often associated with river regulation. We fit the time series of stationary flood records with the generalized extreme value distribution to investigate whether TCs control the upper tail of the flood peak distribution. Our results indicate that TCs play a diminished role in shaping the upper tail of the flood peak distribution compared with areas of the eastern United States subject to frequent TCs.     

Examining Flood Frequency Distributions in the Midwest U.S.1

Villarini, Gabriele, James A. Smith, Mary Lynn Baeck, and Witold F. Krajewski, 2011. Examining Flood Frequency Distributions in the Midwest U.S. Journal of the American Water Resources Association (JAWRA) 47(3):447‐463. DOI: 10.1111/j.1752‐1688.2011.00540.x Abstract: Annual maximum peak discharge time series from 196 stream gage stations with a record of at least 75 years from the Midwest United States is examined to study flood peak distributions from a regional point of view. The focus of this study is to evaluate: (1) “mixtures” of flood peak distributions, (2) upper tail and scaling properties of the flood peak distributions, and (3) presence of temporal nonstationarities in the flood peak records. Warm season convective systems are responsible for some of the largest floods in the area, in particular in Nebraska, Kansas, and Iowa. Spring events associated with snowmelt and rain‐on‐snow are common in the northern part of the study domain. Nonparametric tests are used to investigate the presence of abrupt and slowly varying changes. Change‐points rather than monotonic trends are responsible for most violations of the stationarity assumption. The abrupt changes in flood peaks can be associated with anthropogenic changes, such as changes in land use/land cover, agricultural practice, and construction of dams. The trend analyses do not suggest an increase in the flood peak distribution due to anthropogenic climate change. Examination of the upper tail and scaling properties of the flood peak distributions are examined by means of the location, scale, and shape parameters of the Generalized Extreme Value distribution.