Stormwater control impacts on runoff volume and peak flow: A meta-analysis of watershed modelling studies

Decades of research has concluded that the percent of impervious surface cover in a watershed is strongly linked to negative impacts on urban stream health. Recently, there has been a push by municipalities to offset these effects by installing structural stormwater control measures (SCMs), which are landscape features designed to retain and reduce runoff to mitigate the effects of urbanisation on event hydrology. The goal of this study is to build generalisable relationships between the level of SCM implementation in urban watersheds and resulting changes to hydrology. A literature review of 185 peer-reviewed studies of watershed-scale SCM implementation across the globe was used to identify 52 modelling studies suitable for a meta-analysis to build statistical relationships between SCM implementation and hydrologic change. Hydrologic change is quantified as the percent reduction in storm event runoff volume and peak flow between a watershed with SCMs relative to a (near) identical control watershed without SCMs. Results show that for each additional 1% of SCM-mitigated impervious area in a watershed, there is an additional 0.43% reduction in runoff and a 0.60% reduction in peak flow. Values of SCM implementation required to produce a change in water quantity metrics were identified at varying levels of probability. For example, there is a 90% probability (high confidence) of at least a 1% reduction in peak flow with mitigation of 33% of impervious surfaces. However, as the reduction target increases or mitigated impervious surface decreases, the probability of reaching the reduction target also decreases. These relationships can be used by managers to plan SCM implementation at the watershed scale.     

专题制图中多因素数据的Fuxxy-Grey局势决策综合分类

专题制图中，所收集到的数据经常是单因素的，而在专题地图上却往往需要把多个单因素专题数据进行综合分类来表示。本文中，采用Fuzzy-Grey局势决策（下简称F-G决策）来研究多因素专题数据的综合分类问题，把“数据的模糊性”引入到灰色局势决策之中，根据不同情况，讨论各局势上效果测度中模糊隶属度确定的建模方法，在合适的隶属函数的基础上，在计算机上对实例分类进行程序运行，获得满意的结果。研究表明应用该方法在专题制图中对多因素数据进行综合分类是一种有效的手段。     

Hydrologic processes at the urban residential scale

In the face of increasing urbanization, there is growing interest in application of microscale hydrologic solutions to minimize storm runoff and conserve water at the source. In this study, a physically based numerical model was developed to understand hydrologic processes better at the urban residential scale and the interaction of these processes among different best management practices (BMPs). This model simulates hydrologic processes using an hourly interval for over a full year or for specific storm events. The model was applied to treatment and control single‐family residential parcels in Los Angeles, California. Data collected from the control and treatment sites over 2 years were used to calibrate and validate the model. Annual storm runoff to the street was eliminated by 97% with installation of rain gutters, a driveway interceptor, and lawn retention basin. Evaluated individually, the driveway interceptor was the most effective BMP for storm runoff reduction (65%), followed by the rain gutter installation (28%), and lawn converted to retention basin (12%). An 11 m³ cistern did not substantially reduce runoff, but provided 9% of annual landscape irrigation demand. Simulated landscape irrigation water use was reduced 53% by increasing irrigation system efficiency, and adjusting application rates monthly based on plant water demand. The model showed that infiltration and surface runoff processes were particularly sensitive to the soil's physical properties and its effective depth. Replacing the existing loam soil with clay soil increased annual runoff discharge to the street by 63% when climate and landscape features remained unchanged. Copyright © 2006 John Wiley & Sons, Ltd.     

空间测边交会解析算法与迭代算法的综合应用

本文提出了一种新的三维测边交会解析算法,应用几何判别方法排除多解问题。研究了测边网最稳定解析解的交会图形选择方法,将此解析解作为迭代算法的初值进行迭代计算,不但能保证计算精度,极大加快迭代收敛速度,而且能减少计算机工作量与计算时间,避免迭代算法多值判断问题的同时,保证了迭代初值直接位于收敛域内。试验结果表明,解析算法与迭代算法综合应用算法可高效率,高稳定性求解空间测边交会问题。     

基于WRF的黄渤海海雾数值模拟参数化方案研究

对数值模拟的研究现状进行了总结梳理,分析了已有研究的不足,并根据研究目标在已有研究结论基础上有针对性地设计了敏感性实验方案。经过与实地观测的结果对比来看,与海雾模拟密切相关的边界层参数化方案中的YSU方案对我国黄渤海海区的不同强度海雾均具有良好的适用性,而长波辐射方案中的Fu-Liou-Gu方案则具有更好的普适性,在这种核心方案配置下的模拟结果均可满足一般科学研究与预报业务的需求。     

Assessing uncertainty in best management practice effectiveness under future climate scenarios

Uncertainty of best management practice (BMP) performance in future climates is an important consideration for water resources managers. The objective of this study was to quantify the level of uncertainty in performance of seven agricultural BMPs due to climate change in reducing sediment, total nitrogen, and total phosphorus loads. The Soil and Water Assessment Tool coupled with mid‐21^st century climate data from the Community Climate System Model were used to develop climate change scenarios for the Tuttle Creek Lake Watershed of Kansas and Nebraska. Uncertainty level of each BMP was determined using Latin Hypercube Sampling, a constrained Monte Carlo sampling technique. Samples were taken from distributions of several variables (monthly precipitation, temperature, CO₂, and BMP implementation parameters). Cumulative distribution functions were constructed for each BMP, pollutant, and climate scenario combination. Results demonstrated that BMP performance uncertainty is amplified in the extreme climate scenario. Among BMPs, native grass replacement generally had higher uncertainty level but also had the greatest reductions. This study highlights the importance of incorporating uncertainty analysis into mitigation strategies aiming to reduce negative impacts of climate change on water resources. Copyright © 2013 John Wiley & Sons, Ltd.     

用Hash表技术实现快速流分类

Hash表技术是流分类的常用方法之一,用Hash表技术实现快速流分类的关键问题是降低冲突率,提高冲突解决的效率。该文通过提出几个新的概念（如发散、最佳流分类比特和相似比特等）来降低冲突率,通过提出查找树方案来提高冲突解决的效率,从而得到了一种能适应进行任意域流分类工作的、高效的流分类哈希（Efficient Packet Classification Hash,EPCH）表技术方案。仿真试验证明：该方案冲突率低、效率高,值得推广。     

变形测量异常数据处理中小波变换最佳级数的确定

综合分析数据去噪效果的4个分项评价指标,即数据的均方根差变化量、互相关系数、信噪比及平滑度,将各分项评价指标归化到0,1后相加得到总体评价指标,将总体评价指标最大值所对应的级数定义为小波分解与重构的最佳级数。模拟和实测两个算例验证了此方法的有效性。     

Assimilating Best Track Minimum Sea Level Pressure Data Together with Doppler Radar Data Using an Ensemble Kalman Filter for Hurricane Ike (2008) at a Cloud-Resolving Resolution

Extending an earlier study, the best track minimum sea level pressure (MSLP) data are assimilated for landfalling Hurricane Ike (2008) using an ensemble Kalman filter (EnKF), in addition to data from two coastal ground-based Doppler radars, at a 4-km grid spacing. Treated as a sea level pressure observation, the MSLP assimilation by the EnKF enhances the hurricane warm core structure and results in a stronger and deeper analyzed vortex than that in the GFS (Global Forecast System) analysis; it also improves the subsequent 18-h hurricane intensity and track forecasts. With a 2-h total assimilation window length, the assimilation of MSLP data interpolated to 10-min intervals results in more balanced analyses with smaller subsequent forecast error growth and better intensity and track forecasts than when the data are assimilated every 60 minutes. Radar data are always assimilated at 10-min intervals. For both intensity and track forecasts, assimilating MSLP only outperforms assimilating radar reflectivity (Z) only. For intensity forecast, assimilating MSLP at 10-min intervals outperforms radar radial wind (Vr) data (assimilated at 10-min intervals), but assimilating MSLP at 60-min intervals fails to beat Vr data. For track forecast, MSLP assimilation has a slightly (noticeably) larger positive impact than Vr(Z) data. When Vr or Z is combined with MSLP, both intensity and track forecasts are improved more than the assimilation of individual observation type. When the total assimilation window length is reduced to 1h or less, the assimilation of MSLP alone even at 10-min intervals produces poorer 18-h intensity forecasts than assimilating Vr only, indicating that many assimilation cycles are needed to establish balanced analyses when MSLP data alone are assimilated; this is due to the very limited pieces of information that MSLP data provide.     

Evaluating suspended sediment and turbidity reduction projects in a glacially conditioned catchment through dynamic regression and fluvial process-based modelling

Elevated turbidity (T_n) and suspended sediment concentrations (SSC) during and following flood events can degrade water supply quality and aquatic ecosystem integrity. Streams draining glacially conditioned mountainous terrain, such as those in the Catskill Mountains of New York State, are particularly susceptible to high levels of T_n and SSC sourced from erosional contact with glacial-related sediment. This study forwards a novel approach to evaluate the effectiveness of stream restoration best management practices (BMPs) meant to reduce stream T_n and SSC, and demonstrates the approach within the Stony Clove sub-basin of the Catskills, a water supply source for New York City. The proposed approach is designed to isolate BMP effects from natural trends in T_n and SSC caused by trends in discharge and shifts in average T_n or SSC per unit discharge (Q) following large flood events. We develop Dynamic Linear Models (DLMs) to quantify how T_n-Q and SSC-Q relationships change over time at monitoring stations upstream and downstream of BMPs within the Stony Clove and in three other sub-basins without BMPs, providing observational evidence of BMP effectiveness. A process-based model, the River Erosion Model, is then developed to simulate natural, hydrology-driven SSC-Q dynamics in the Stony Clove sub-basin (absent of BMP effects). We use DLMs to compare the modelled and observed SSC-Q dynamics and isolate the influence of the BMPs. Results suggest that observed reductions in SSC and T_n in the Stony Clove sub-basin have been driven by a combination of declining streamflow and the installed BMPs, confirming the utility of the BMPs for the monitored hydrologic conditions.