典型喀斯特流域地表产流输出特征

由于喀斯特区域表层岩溶带的结构和构造表现为高度的异质性,以及大量缺失定位观测资料,使得该区域目前还没有较为完善的产汇流模型。对特定小流域地表产流输出过程的分析,有利于对流域内部各种水文过程的认识。本研究正是基于这一背景,通过对一完整自然年的地表产流输出进行分析发现,流域地表径流输出主要发生在5~10月份;受雨强和壤中流向地表径流转化过程的影响,5月份的地表径流产流输出为突发衰弱型伴有明显的迟滞效应,其他月份主要为渐进增强衰弱型,迟滞效应较5月份明显减弱;如去除5月份的影响,6~10月份流域地表径流输出量与降雨量呈显著正相关关系(p0.05,r=0.99);壤中流向地表径流径流转化具有明显的季节性差异;就全年而言,经由卡口站地表径流输出的量占全年降雨总量的23.1%。     

Long‐Term Trends in Streamflow and Precipitation in Northwest California and Southwest Oregon, 1953‐2012

Using nonparametric Mann‐Kendall tests, we assessed long‐term (1953‐2012) trends in streamflow and precipitation in Northern California and Southern Oregon at 26 sites regulated by dams and 41 “unregulated” sites. Few (9%) sites had significant decreasing trends in annual precipitation, but September precipitation declined at 70% of sites. Site characteristics such as runoff type (groundwater, snow, or rain) and dam regulation influenced streamflow trends. Decreasing streamflow trends outnumbered increasing trends for most months except at regulated sites for May‐September. Summer (July‐September) streamflow declined at many sites, including 73% of unregulated sites in September. Applying a LOESS regression model of antecedent precipitation vs. average monthly streamflow, we evaluated the underlying streamflow trend caused by factors other than precipitation. Decreasing trends in precipitation‐adjusted streamflow substantially outnumbered increasing trends for most months. As with streamflow, groundwater‐dominated sites had a greater percent of declining trends in precipitation‐adjusted streamflow than other runoff types. The most pristine surface‐runoff‐dominated watersheds within the study area showed no decreases in precipitation‐adjusted streamflow during the summer months. These results suggest that streamflow decreases at other sites were likely due to more increased human withdrawals and vegetation changes than to climate factors other than precipitation quantity.     

合流制排水系统降雨径流初期冲刷效应

通过对昆明主城区3个集水区合流制排水系统10次降雨径流过程水质水量的监测,计算了污染物的次降雨平均浓度(EMC),并采用无因次累积负荷体积分数曲线(M(V)曲线)和初期冲刷系数方法对初期冲刷现象进行了探讨。结果表明:(1)对于同一个常规污染指标,不同集水区的EMC平均值没有较明显差异,但都表现出较高浓度的污染特征。不同集水区总悬浮颗粒物(TSS)、COD、TN和TP的EMC平均值分别为140.18~174.11、144.65~161.78、21.44~23.18、1.80~2.35mg/L。(2)3个集水区所有观测降雨事件中,TP、TN、COD和TSS的初期30%径流量所对应的污染物累积负荷量(FF30)平均值分别为38.7%、37.1%、40.7%、44.6%;TSS和COD的初期冲刷强度明显较TP和TN变化更剧烈,不同污染物初期冲刷强度依次为TSSCODTPTN。(3)对于合流制排水系统,在区域特征相近情况下,汇水面积越小则初期冲刷效应越显著。而当汇水面积大到一定程度时,不同集水区之间初期冲刷强度没有显著差异。(4)降雨量、平均雨强和最大雨强与合流制排水系统的初期冲刷强度呈显著的正相关性,是影响其初期冲刷的重要水文参数;降雨历时和前期晴天与其初期冲刷强度没有显著相关性,两者对初期冲刷无明显影响。     

Sustaining food self-sufficiency of a nation: The case of Sri Lankan rice production and related water and fertilizer demands

Rising human demand and climatic variability have created greater uncertainty regarding global food trade and its effects on the food security of nations. To reduce reliance on imported food, many countries have focused on increasing their domestic food production in recent years. With clear goals for the complete self-sufficiency of rice production, Sri Lanka provides an ideal case study for examining the projected growth in domestic rice supply, how this compares to future national demand, and what the associated impacts from water and fertilizer demands may be. Using national rice statistics and estimates of intensification, this study finds that improvements in rice production can feed 25.3 million Sri Lankans (compared to a projected population of 23.8 million people) by 2050. However, to achieve this growth, consumptive water use and nitrogen fertilizer application may need to increase by as much as 69 and 23 %, respectively. This assessment demonstrates that targets for maintaining self-sufficiency should better incorporate avenues for improving resource use efficiency.

Electronic supplementary material

The online version of this article (doi:10.1007/s13280-015-0720-2) contains supplementary material, which is available to authorized users.     

Effects of Spatial Distribution of Prairie Vegetation in an Agricultural Landscape on Curve Number Values

The curve number (CN) method is used to calculate runoff in many hydrologic models, including the Soil and Water Assessment Tool (SWAT). The CN method does not account for the spatial distribution of land cover types, an important factor controlling runoff patterns. The objective of this study was to empirically derive CN values that reflect the strategic placement of native prairie vegetation (NPV) within row crop agricultural landscapes. CNs were derived using precipitation and runoff data from a seven‐year period for 14 small watersheds in Iowa. The watersheds were planted with varying amounts of NPV located in different watershed positions. The least squares and asymptotic least squares methods (LSM) were used to derive CNs using an initial abstraction coefficient (λ) of 0.2 and 0.05. The CNs were verified using leave‐one‐out cross‐validation and adjustment for antecedent moisture conditions (AMC) was tested. The asymptotic method produced CN values for watersheds with NPV treatment that were 8.9 and 14.7% lower than watersheds with 100% row crop at λ = 0.2 and λ = 0.05, respectively. The derived CNs produced Nash‐Sutcliffe efficiency values ranging from 0.4 to 0.7 during validation. Our analyses show the CNs verified best for the asymptotic LSM, when using λ of 0.05 and adjusting for AMC. Further, comparison of derived CNs against an area weighted CN indicated that the placement of vegetation does impact the CN value. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Estimation of daily sunshine duration using support vector machines

Although sunshine duration (SD) is one of the most frequently measured meteorological parameters, there is a lack of measurements in some parts of the world. Hence, it should be estimated accurately for areas where no reliable measurement is possible. The main objective of this study is to evaluate the potential of support vector machine (SVM) approach for estimating daily SD. For this purpose, three different kernels of SVM, such as linear, polynomial, and radial basis function (RBF), were used. Different combinations of five related meteorological parameters, namely cloud cover, maximum temperature (T_max), minimum temperature (T_min), relative humidity (RH), and wind speed (WS), and one astronomic parameter, day length, were considered as the inputs of the models, and the output was obtained as daily SD. Simulated values of the models were compared with ground measured values, and concluded that the usage of the SVM-RBF estimator with combination of all input attributes produced the best results. The coefficient of determination, root mean square error, and mean absolute error were found to be 0.8435, 1.5105 h, and 1.0771 h, respectively, for the pooled four-year daily data set of 14 stations in Turkey. It was also deduced that accuracy increased as the number of attributes increased and the major contribution to this came from RH as compared with T_max, T_min, and WS. This study has shown that the SVM methodology can be a good alternative for conventional and artificial neural network methods for estimating daily SD.     

Age-related differences in effects of non-driving related tasks on takeover performance in automated driving

Introduction: During SAE level 3 automated driving, the driver’s role changes from active driver to fallback-ready driver. Drowsiness is one of the factors that may degrade driver’s takeover performance. This study aimed to investigate effects of non-driving related tasks (NDRTs) to counter driver’s drowsiness with a Level 3 system activated and to improve successive takeover performance in a critical situation. A special focus was placed on age-related differences in the effects. Method: Participants of three age groups (younger, middle-aged, older) drove the Level 3 system implemented in a high-fidelity motion-based driving simulator for about 30 min under three experiment conditions: without NDRT, while watching a video clip, and while switching between watching a video clip and playing a game. The Karolinska Sleepiness Scale and eyeblink duration measured driver drowsiness. At the end of the drive, the drivers had to take over control of the vehicle and manually change the lane to avoid a collision. Reaction time and steering angle variability were measured to evaluate the two aspects of driving performance. Results: For younger drivers, both single and multiple NDRT engagements countered the development of driver drowsiness during automated driving, and their takeover performance was equivalent to or better than their performance without NDRT engagement. For older drivers, NDRT engagement did not affect the development of drowsiness but degraded takeover performance especially under the multiple NDRT engagement condition. The results for middle-aged drivers fell at an intermediate level between those for younger and older drivers. Practical Applications: The present findings do not support general recommendations of NDRT engagement to counter drowsiness during automated driving. This study is especially relevant to the automotive industry’s search for options that will ensure the safest interfaces between human drivers and automation systems.     

不同地表雨水径流冲刷特性分析

选择北京市某城区典型地表(校园、自行车道、商业街和高架桥)的雨水径流作为研究对象,系统分析了不同地表雨水径流的冲刷特性。分析结果表明:不同地表初期冲刷现象都比较明显,控制不同地表20%的初期雨水可以削减污染物总量的40%～60%,高架桥初期雨水径流中COD、SS和TP浓度最高,校园初期雨水径流中TN浓度最高。不同地表雨水径流的水质优劣顺序为:校园>商业街>自行车道>高架桥。校园和自行车道在整个降雨过程中D50和D90粒径大小相近,分别为30μm和50μm左右,且变化幅度都较小。高架桥和商业街在雨水径流初期D50和D90粒径有明显减小,但后期均出现较大幅度的波动,其粒径明显大于校园和自行车道。上述研究成果对于城市不同地表雨水径流污染控制和场地开发具有重要意义。     

Impact of Temporal Resolution of Flow‐Duration Curve on Sediment Load Estimation1

Chen, Li, Rina Schumer, Anna Knust, and William Forsee, 2011. Impact of Temporal Resolution of Flow‐Duration Curve on Sediment Load Estimation. Journal of the American Water Resources Association (JAWRA) 48(1): 145‐155. DOI: 10.1111/j.1752‐1688.2011.00602.x Abstract: Estimates of a channel’s annual sediment transport capacity typically incorporate annualized flow‐duration curves. Average daily flow data, commonly used to develop flow‐duration curves, may not adequately describe sediment‐transporting flows in arid and semiarid ephemeral streams. In this study, we examined impacts of varied temporal resolution flow data on annual sediment load estimation. We derived flow‐duration curves for eight sites in the Southwestern United States based on both 15‐min and daily‐averaged flow data. We then estimated sediment loads for both flow‐duration curves using the Sediment Impact Analysis Method, implemented in HEC‐RAS. When average daily flow is used to generate flow‐duration curves, sediment load estimation is lower by up to an order of magnitude. This trend is generally unaffected by uncertainty associated with sediment particle size or hydraulic roughness. The ratio of sediment loads estimated by 15‐min versus daily‐averaged flow‐duration curves is strongly correlated with channel slope, being greater on steep‐slope channels. Sediment loads estimated by the two types of flow‐duration curves are closely correlated, suggesting possible relationships for improving predictions when high‐temporal resolution data are unavailable. Results also suggest that the largest flow contributes significantly to total sediment load, and thus will greatly impact ephemeral stream geomorphology in arid and semiarid regions.