内蒙古中西部地区土壤水分对沙尘暴的贡献

以2001年4月至2002年6月内蒙中部地区逐时观测的土壤水分资料为基础，论证了该区日土壤水分和日平均风速的变化规律，统计分析了日平均风速与土壤水分对沙尘暴的成生综合贡献。得出的主要结论是：①该地区沙尘暴发生时日平均风速的最小值是3．5m／s。如果日平均风速大于8．0m／s，预示着有沙尘暴的发生。②在平均风速大于3.5m／s的条件下，观测样本中18．4％日数发生沙尘暴，而81．6％日数没有发生。说明大风的天气条件不应当被视其为沙尘暴的唯一重要的因子。③在同一地点、同样的风力条件下，在沙尘暴发生时，日平均风速与日平均土壤水分呈明显的反相关变化；而它们的反相关关系不明显时，沙尘暴就很少发生。     

February floods in the lower North Island, 2004: Catastrophe – causes and consequences

Abstract: The February 2004 Manawatu floods in New Zealand were the result of a naturally occurring, although unusual, storm. Up to 300 mm of rain fell on the already saturated ground of the lower North Island over two days, generating substantial and rapid runoff from catchment slopes. Rivers rose quickly, inundating unprotected farmland and properties and in places breaching stopbanks. There was widespread slope failure in the hill country of the lower North Island, affecting an area of ca. 7500 km². Slopes under scrub, plantation forest and native bush were not as badly affected as those under pasture, where slopes typically failed by shallow translational landsliding. Flooding caused catastrophic channel change in a number of small to medium sized channel systems in the upland fringes. Whilst the occurrence of landsliding and channel changes during an extreme event such as this is natural, the intensity of both landsliding and channel erosion was exacerbated by human activity within the catchments.     

兰州市2001年沙尘气溶胶质量浓度的特征分析

 分析了2001年沙尘暴期间兰州与靠近沙尘源区的武威的沙尘浓度和粒径分布特征,并运用对数正态分布规律拟合了沙尘粒径的分布。通过对比武威、皋兰和兰州沙尘暴期间沙尘浓度的变化以及武威与兰州的沙尘粒径分布特征,揭示了河西走廊沙漠对兰州市沙尘暴的影响。     

固沙林庇护区内降尘特征的初步观测

采用野外定位实测法,连续两年对科尔沁沙地24龄人工固沙杨树(Populussimonii)林庇护区内4～6月份及强沙尘暴事件中的降尘特征进行了观测研究。结果表明:(1)林地庇护区内4、5月份的降尘量较多,分别为273和437kg/hm2,6月份的降尘量较少,为171kg/hm2。(2)林地中央的滞尘效应在风蚀季节和强沙尘暴天气过程中十分显著。(3)林地庇护区内的降尘中粒径<0.02mm颗粒含量占60.7%,降尘中的全C、全N和速效P含量分别高达1.676%、0.163%和210.66mg/kg,这对风沙土表层土壤的细化和养分的积累具有重要的生态学意义。     

A new magnitude category disaggregation approach for temporal high‐resolution rainfall intensities

Simulation of quick runoff components such as surface runoff and associated soil erosion requires temporal high‐resolution rainfall intensities. However, these data are often not available because such measurements are costly and time consuming. Current rainfall disaggregation methods have shortcomings, especially in generating the distribution of storm events. The objectives of this study were to improve point rainfall disaggregation using a new magnitude category rainfall disaggregation approach. The procedure is introduced using a coupled disaggregation approach (Hyetos and cascade) for multisite rainfall disaggregation. The new procedure was tested with ten long‐term precipitation data sets of central Germany using summer and winter precipitation to determine seasonal variability. Results showed that dividing the rainfall amount into four daily rainfall magnitude categories (1–10, 11–25, 26–50, >50 mm) improves the simulation of high rainfall intensity (convective rainfall). The Hyetos model category approach (Hyetos_Cat) with seasonal variation performs representative to observed hourly rainfall compared with without categories on each month. The mean absolute percentage accuracy of standard deviation for hourly rainfall is 89.7% in winter and 95.6% in summer. The proposed magnitude category method applied with the coupled Hyetos_Cat–cascade approach reproduces successfully the statistical behaviour of local 10‐min rainfall intensities in terms of intermittency as well as variability. The root mean square error performance statistics for disaggregated 10‐min rainfall depth ranges from 0.20 to 2.38 mm for summer and from 0.12 to 2.82 mm for the winter season in all categories. The coupled stochastic approach preserves the statistical self‐similarity and intermittency at each magnitude category with a relatively low computational burden. Copyright © 2014 John Wiley & Sons, Ltd.     

An analytical approach to ascertain saturation‐excess versus infiltration‐excess overland flow in urban and reference landscapes

Uncontrolled overland flow drives flooding, erosion, and contaminant transport, with the severity of these outcomes often amplified in urban areas. In pervious media such as urban soils, overland flow is initiated via either infiltration‐excess (where precipitation rate exceeds infiltration capacity) or saturation‐excess (when precipitation volume exceeds soil profile storage) mechanisms. These processes call for different management strategies, making it important for municipalities to discern between them. In this study, we derived a generalized one‐dimensional model that distinguishes between infiltration‐excess overland flow (IEOF) and saturation‐excess overland flow (SEOF) using Green–Ampt infiltration concepts. Next, we applied this model to estimate overland flow generation from pervious areas in 11 U.S. cities. We used rainfall forcing that represented low‐ and high‐intensity events and compared responses among measured urban versus predevelopment reference soil hydraulic properties. The derivation showed that the propensity for IEOF versus SEOF is related to the equivalence between two nondimensional ratios: (a) precipitation rate to depth‐weighted hydraulic conductivity and (b) depth of soil profile restrictive layer to soil capillary potential. Across all cities, reference soil profiles were associated with greater IEOF for the high‐intensity set of storms, and urbanized soil profiles tended towards production of SEOF during the lower intensity set of storms. Urban soils produced more cumulative overland flow as a fraction of cumulative precipitation than did reference soils, particularly under conditions associated with SEOF. These results will assist cities in identifying the type and extent of interventions needed to manage storm water produced from pervious areas.     

Impact of climate indicators on continental‐scale potential groundwater recharge in Africa

In the last decades, human activity has been contributing to climate change that is closely associated with an increase in temperatures, increase in evaporation, intensification of extreme dry and wet rainfall events, and widespread melting of snow and ice. Understanding the intricate linkage between climate warming and the hydrological cycle is crucial for sustainable management of groundwater resources, especially in a vulnerable continent like Africa. This study investigates the relationship between climate‐change drivers and potential groundwater recharge (PGR) patterns across Africa for a long‐term record (1960–2010). Water‐balance components were simulated by using the PCR‐GLOBWB model and were reproduced in both gridded maps and latitudinal trends that vary in space with minima on the Tropics and maxima around the Equator. Statistical correlations between temperature, storm occurrences, drought, and PGR were examined in six climatic regions of Africa. Surprisingly, different effects of climate‐change controls on PGR were detected as a function of latitude in the last three decades (1980–2010). Temporal trends observed in the Northern Hemisphere of Africa reveal that the increase in temperature is significantly correlated to the decline of PGR, especially in the Northern Equatorial Africa. The climate indicators considered in this study were unable to explain the alarming negative trend of PGR observed in the Sahelian region, even though the Standardized Precipitation‐Evapotranspiration Index (SPEI) values report a 15% drought stress. On the other hand, increases in temperature have not been detected in the Southern Hemisphere of Africa, where increasing frequency of storm occurrences determine a rise of PGR, particularly in southern Africa. Time analysis highlights a strong seasonality effect, while PGR is in‐phase with rainfall patterns in the summer (Northern Hemisphere) and winter (Southern Hemisphere) and out‐of‐phase during the fall season. This study helps to elucidate the mechanism of the processes influencing groundwater resources in six climatic zones of Africa, even though modelling results need to be validated more extensively with direct measurements in future studies. Copyright © 2016 John Wiley & Sons, Ltd.     

Stormflow concentration–discharge dynamics of suspended sediment and dissolved phosphorus in an agricultural watershed

Concentration–discharge (C-Q) relationships are an effective tool for identifying watershed biogeochemical source and transport dynamics over short and long timescales. We examined stormflow C-Q, hysteresis, and flushing patterns of total suspended sediment (TSS) and soluble reactive phosphorus (SRP) in two stream reaches of a severely impaired agricultural watershed in northeastern Wisconsin, USA. The upper watershed reach—draining a relatively flat, row crop-dominated contributing area—showed predominantly anti-clockwise TSS hysteresis during storms, suggesting that particulate materials were mobilized more from distal upland sources than near- and in-channel areas. In contrast, the incised lower watershed reach produced strong TSS flushing responses on the rising limb of storm hydrographs and clockwise hysteresis, signalling rapid mobilization of near- and in-channel materials with increasing event flows. C-Q relationships for SRP showed complex patterns in both the upper and lower reaches, demonstrating largely non-linear chemodynamic C-Q behaviour during events. As with TSS, anti-clockwise SRP hysteresis in the upper reach suggested a delay in the hydrologic connectivity between SRP sources and the stream, with highly variable SRP concentrations during some events. A broad range of clockwise, anti-clockwise, and complex SRP hysteresis patterns occurred in the lower watershed, possibly influenced by in-channel legacy P stores and connection to tile drainage networks in the lower watershed area. Total suspended sediment and SRP responses were also strongly related to precipitation event characteristics including antecedent precipitation, recovery period, and precipitation intensity, highlighting the complexity of stormflow sediment and phosphorus responses in this severely impaired agricultural stream.     

风暴分类识别技术在人工防雹中的应用

利用新一代多普勒天气雷达资料,在风暴跟踪识别算法的基础上,发展了风暴分类技术,以提高人工防雹作业指挥的效率。首先以SCIT算法为基础,结合风暴的结构特征,综合利用雷达、探空资料,自动提取风暴结构特征指数;其次采用基于决策树模型的风暴自动分类技术,将风暴按强度分为雷雨云、单体风暴、多单体风暴和强风暴;最后根据风暴强度、高度和位置等属性,对有可能产生冰雹的单体,结合GIS,自动对下游方向或附近作业点进行预警或输出作业参数。通过对2006—2014年期间重庆、辽宁大连和河南三门峡三地发生的较为典型的31次冰雹天气过程、182站次冰雹样本的检验来看:该方法通过对风暴按强度、垂直结构等综合属性进行分类,能有效提高冰雹识别的命中率、降低空报率,其中强风暴的命中率能达到100%,空报率仅为11.4%。能有效提高人工防雹作业的自动化程度,对防雹作业的科学决策有着重要参考作用。     

Application of Linear Mean-Square Estimation in Ocean Engineering

The attempt to obtain long-term observed data around some sea areas we concern is usually very hard or even impossible in practical offshore and ocean engineering situations. In this paper, by means of linear mean-square estimation method, a new way to extend short-term data to long-term ones is developed. The long-term data about concerning sea areas can be constructed via a series of long-term data obtained from neighbor oceanographic stations, through relevance analysis of different data series. It is effective to cover the insufficiency of time series prediction method’s overdependence upon the length of data series, as well as the limitation of variable numbers adopted in multiple linear regression model. The storm surge data collected from three oceanographic stations located in Shandong Peninsula are taken as examples to analyze the number-selection effect of reference oceanographic stations (adjacent to the concerning sea area) and the correlation coefficients between sea sites which are selected for reference and for engineering projects construction respectively. By comparing the N-year return-period values which are calculated from observed raw data and processed data which are extended from finite data series by means of the linear mean-square estimation method, one can draw a conclusion that this method can give considerably good estimation in practical ocean engineering, in spite of different extreme value distributions about raw and processed data.