Exploring the causes of an extreme flood event in Central New York,USA

This study examined the causes of an extreme flood event on 28 June 2013 in Central New York, USA by comparing its hydrological, hydrometeorological, and rainfall-runoff transformation characteristics with those of a typical flood event. Flood frequency analyses showed that the maximum rainfall intensity and the peak discharge of the extreme event had recurrence intervals (RIs) of 8 and 86 years, respectively, while RIs for the typical event were 42 and 11 years, respectively. Their severity diagrams and quantification of their rainfall spatial variations illustrated that the extreme event was spatially localized with high intensities, whereas the typical event was spatially uniform and prolonged. Watershed modeling indicated that the rainfall-runoff transformation was dominated by the infiltration excess process for the extreme flood, while controlled by both infiltration and saturation excess processes for the typical event. These analyses revealed that the upgrade-magnitude conversion pattern of the extreme flood event was induced by the spatial pattern of the rainfall and the “lubricant” effect of the watershed, and emphasized the need for better understanding of such type of extreme events.     

An analysis of non-normal Markovian extremal droughts

In many arid and semi-arid environments of the world, years of extended droughts are not uncommon. The occurrence of a drought can be reflected by the deficiency of the rainfall or stream flow sequences below the long-term mean value, which is generally taken as the truncation level for the identification of the droughts. The commonly available statistics for the above processes are mean, coefficient of variation and the lag-one serial correlation coefficient, and at times some indication of the probability distribution function (pdf) of the sequences. The important elements of a drought phenomenon are the longest duration and the largest severity for a desired return period, which form a basis for designing facilities to meet exigencies arising as a result of droughts. The sequences of drought variable, such as annual rainfall or stream flow, may follow normal, log-normal or gamma distributions, and may evolve in a Markovian fashion and are bound to influence extremal values of the duration and severity. The effect of the aforesaid statistical parameters on the extremal drought durations and severity have been analysed in the present paper. A formula in terms of the extremal severity and the return period ‘T’ in years has been suggested in parallel to the flood frequency formula, commonly cited in the hydrological texts. © 1998 John Wiley & Sons, Ltd.     

The use of geometric and gamma-related distributions for frequency analysis of water deficit

This paper presents an approach to perform statistical frequency analysis of water deficit duration and severity using respectively the geometric and exponential distributions. Monthly mean water discharges are compared to a given threshold and classified in two mutually exclusive ways. This leads to a two state random variable such that: a success represents the absence of a water deficit event (mean monthly discharge exceeds threshold), and a failure, a water deficit event (mean monthly discharge is below threshold). If we suppose that this random variable gives rise to a Markov process of order 1, then the duration of a water deficit event X (consecutive months in deficit) will have a geometric distribution. In turn, the summation of discharges in deficit will give the severity of a water deficit event which can be represented by a one-parameter exponential distribution. The threshold or base level is taken as a percentile of the observed mean discharges of a given month. This base level, which varies from month to month, can be viewed as the limit of an acceptable deficit (or energetic failure) associated to a given empirical probability of being in deficit. The second step of the approach is to estimate the value of the parameter for each distribution using the maximum likelihood method. Expressions for the estimator of a given percentile, , as well as its variance are deduced. Finally, the presented models are applied to observed data.     

Using hyperspectral imagery to predict post-wildfire soil water repellency

A principal task of evaluating large wildfires is to assess fire's effect on the soil in order to predict the potential watershed response. Two types of soil water repellency tests, the water drop penetration time (WDPT) test and the mini-disk infiltrometer (MDI) test, were performed after the Hayman Fire in Colorado, in the summer of 2002 to assess the infiltration potential of the soil. Remotely sensed hyperspectral imagery was also collected to map post-wildfire ground cover and soil condition. Detailed ground cover measurements were collected to validate the remotely sensed imagery and to examine the relationship between ground cover and soil water repellency. Percent ash cover measured on the ground was significantly correlated to WDPT (r = 0.42; p-value < 0.0001), and the MDI test (r = − 0.37; p-value < 0.0001). A Mixture Tuned Matched Filter (MTMF) spectral unmixing algorithm was applied to the hyperspectral imagery, which produced fractional cover maps of ash, soil, and scorched and green vegetation. The remotely sensed ash image had significant correlations to the water repellency tests, WDPT (r = 0.24; p-value = 0.001), and the MDI test (r = − 0.21; p-value = 0.005). An iterative threshold analysis was also applied to the ash and water repellency data to evaluate the relationship at increasingly higher levels of ash cover. Regression analysis between the means of grouped data: MDI time vs. ash cover data (R² =0.75) and vs. Ash MTMF scores (R² = 0.63) yielded significantly stronger relationships. From these results we found on-the-ground ash cover greater than 49% and remotely sensed ash cover greater than 33% to be indicative of strongly water repellent soils. Combining these results with geostatistical analyses indicated a spatial autocorrelation range of 15 to 40 m. Image pixels with high ash cover (> 33%), including pixels within 15 m of these pixel patches, were used to create a likelihood map of soil water repellency. This map is a good indicator of areas where soil experienced severe fire effects—areas that likely have strong water repellent soil conditions and higher potential for post-fire erosion.     

黄河断流严重程度分级与判别方法

根据1972年以来有关黄河断流的观测数据，选择与断流特点有关的特征因子组合，给出了能够反映断流状况的综合指标，并据此结合聚类分析得出了关于黄河断流严重程度的分类结果，指出了相应的分级原则。基于断流级别与河流径流量及其年内径流变差系数之间可能存在的密切关系，建立了反映三者关系的人工神经网络模型，用以判别已知河流来水特性条件下的黄河下游断流严重程度。此方法为定量描述和预测黄河断流的程度奠定了基础，其可行性通过与实际观测结果的比较得到了较为满意的论证。     

Semi-automated mapping of burned areas in semi-arid ecosystems using MODIS time-series imagery

Understanding spatial and temporal patterns of burned areas at regional scales, provides a long-term perspective of fire processes and its effects on ecosystems and vegetation recovery patterns, and it is a key factor to design prevention and post-fire restoration plans and strategies. Remote sensing has become the most widely used tool to detect fire affected areas over large tracts of land (e.g., ecosystem, regional and global levels). Standard satellite burned area and active fire products derived from the 500-m Moderate Resolution Imaging Spectroradiometer (MODIS) and the Satellite Pour l’Observation de la Terre (SPOT) are available to this end. However, prior research caution on the use of these global-scale products for regional and sub-regional applications. Consequently, we propose a novel semi-automated algorithm for identification and mapping of burned areas at regional scale. The semi-arid Monte shrublands, a biome covering 240,000 km² in the western part of Argentina, and exposed to seasonal bushfires was selected as the test area. The algorithm uses a set of the normalized burned ratio index products derived from MODIS time series; using a two-phased cycle, it firstly detects potentially burned pixels while keeping a low commission error (false detection of burned areas), and subsequently labels them as seed patches. Region growing image segmentation algorithms are applied to the seed patches in the second-phase, to define the perimeter of fire affected areas while decreasing omission errors (missing real burned areas). Independently-derived Landsat ETM+ burned-area reference data was used for validation purposes. Additionally, the performance of the adaptive algorithm was assessed against standard global fire products derived from MODIS Aqua and Terra satellites, total burned area (MCD45A1), the active fire algorithm (MOD14); and the L3JRC SPOT VEGETATION 1 km GLOBCARBON products. The correlation between the size of burned areas detected by the global fire products and independently-derived Landsat reference data ranged from R² = 0.01–0.28, while our algorithm performed showed a stronger correlation coefficient (R² = 0.96). Our findings confirm prior research calling for caution when using the global fire products locally or regionally.     

Relative suitability of indices derived from Landsat ETM+ and SPOT 5 for detecting fire severity in sagebrush steppe

Remote sensing indices of burn area and fire severity have been developed and tested for forest ecosystems, but not sparsely vegetated, desert shrub-steppe in which large wildfires are a common occurrence and a major issue for land management. We compared the performance of remote sensing indices for detecting burn area and fire severity with extensive ground-based cover assessments made before and after the prescribed burning of a 3 km² shrub-steppe area. The remote sensing indices were based on either Landsat 7 ETM+ or SPOT 5 data, using either single or multiple dates of imagery. The indices delineating burned versus unburned areas had better overall, User, and Producer's accuracies than indices delineating levels of fire severity. The Soil Adjusted Vegetation Index (SAVI) calculated from SPOT had the greatest overall accuracy (100%) in delineating burned versus unburned areas. The relative differenced Normalized Burn Ratio (RdNBR) using Landsat ETM+ provided the highest accuracies (73% overall accuracy) for delineating fire severity. Though SPOT's spatial resolution likely conferred advantages for determining burn boundaries, the higher spectral resolution (particularly band 7, 2.21 μm) of Landsat ETM+ may be necessary for detecting differences in fire severity in sparsely vegetated shrub-steppe.     

Effects of prescribed burnings on soil hydrological parameters

Prescribed burning is a forest management tool to reduce forest fire hazards. It is largely applied in the USA and is gaining importance worldwide, particularly in Europe. However, its effects on soils still have to be better understood. This study analyses the effects of two types of prescribed burnings (i.e. low and high burn severities of up to 200 °C and at or above 400 °C) on soil hydrophobicity, infiltration, and water storage capacity of top soils. Prescribed burnings were performed on four different plots in southern and western Catalonia, Spain. Soil samples were collected before and after burning to assess water repellency with the water drop penetration time (WDPT). Three rainfall simulations before burning and three after burning were executed on areas of 1 m², and soil water contents at four to five depths were measured every 4 min during and after rainfall simulations using time domain reflectometry equipment (TDR). Following burning at both severities, water storage capacity of the top soil decreased between 1·7 and 5·4%vol on all four plots. No significant changes in volume flux density and velocity of the wetting fronts were discernible. Water drop penetration times increased moderately at the soil surface of the plots that were exposed to the high burn severity, and decreased slightly when burn severity was low. On two of the four plots the presence of partially moist organic litter prevented the underlying soil from excessive heating. Changes in hydrophobicity and water storage capacity of the top soil did not affect infiltration. Copyright © 2008 John Wiley & Sons, Ltd.     

河南省2005-06-21强对流天气分析

利用天气图和FY-2C的卫星云图及其反演产品,分析了2005年6月21日凌晨到上午河南省中部的雷雨大风和冰雹天气过程,结果表明:高空冷平流、地面辐合线和前期贮存的较高不稳定能量,为此次强对流天气过程提供了极为有利的不稳定能量和动力条件;在灾害性天气发生的前期,FY-2C卫星云图及其反演产品有很好的指示性,云顶亮温梯度大的区域是灾害性天气的易发区,对流性降水易发生在高层急流南侧的低层高湿区。     

CHIMEHERB人工皮在烧伤治疗中的应用

应用CHIMEHERB人工皮治疗烧伤病人125例.疗效观察表明,该人工皮具有与创面粘附牢固,减少创面水、电解质和蛋白质的丢失,减轻疼痛,促进上皮生长等功能.无排斥反应,存用方便和成本低廉.临床与生化检验证实,CHIMEHERB人工皮对肝肾功能无不良影响.适用于浅度烧伤创面、供皮区创面,及中、小面积深度烧伤的切、削痂创面.