A framework for quantifying the impacts of climate change and human activities on hydrological drought in a semiarid basin of Northern China

Climate change and human activities are two major driving forces affecting the hydrologic cycle, which further influence the stationarity of the hydrologic regime. Hydrological drought is a substantial negative deviation from the normal hydrologic conditions affected by these two phenomena. In this study, we propose a framework for quantifying the effects of climate change and human activities on hydrological drought. First, trend analysis and change‐point test are performed to determine variations of hydrological variables. After that, the fixed runoff threshold level method (TLM) and the standardized runoff index (SRI) are used to verify whether the traditional assessment methods for hydrological drought are applicable in a changing environment. Finally, two improved drought assessment methods, the variable TLM and the SRI based on parameter transplantation are employed to quantify the impacts of climate change and human activities on hydrological drought based on the reconstructed natural runoff series obtained using the variable infiltration capacity hydrologic model. The results of a case study on the typical semiarid Laohahe basin in North China show that the stationarity of the hydrological processes in the basin is destroyed by human activities (an obvious change‐point for runoff series is identified in 1979). The traditional hydrological drought assessment methods can no longer be applied to the period of 1980–2015. In contrast, the proposed separation framework is able to quantify the contributions of climate change and human activities to hydrological drought during the above period. Their ranges of contributions to hydrological drought calculated by the variable TLM method are 20.6–41.2% and 58.8–79.4%, and the results determined by the SRI based on parameter transplantation method are 15.3–45.3% and 54.7–84.7%, respectively. It is concluded that human activities have a dominant effect on hydrological drought in the study region. The novelty of the study is twofold. First, the proposed method is demonstrated to be efficient in quantifying the effects of climate change and human activities on hydrological drought. Second, the findings of this study can be used for hydrological drought assessment and water resource management in water‐stressed regions under nonstationary conditions.     

A new depression‐dominated delineation (D‐cubed) method for improved watershed modelling

Prior to hydrologic modelling, topographic features of a surface are derived, and the surface is divided into sub‐basins. Surface delineation can be described as a procedure, which leads to the quantitative rendition of surface topography. Different approaches have been developed for surface delineation, but most of them may not be applicable to depression‐dominated surfaces. The main objective of this study is to introduce a new depression‐dominated delineation (D‐cubed) method and highlight its unique features by applying it to different topographic surfaces. The D‐cubed method accounts for the hierarchical relationships of depressions and channels by introducing the concept of channel‐based unit (CBU) and its connection with the concept of puddle‐based unit (PBU). This new delineation method implements a set of new algorithms to determine flow directions and accumulations for puddle‐related flats. The D‐cubed method creates a unique cascaded channel‐puddle drainage system based on the channel segmentation algorithm. To demonstrate the capabilities of the D‐cubed method, a small laboratory‐scale surface and 2 natural surfaces in North Dakota were delineated. The results indicated that the new method delineated different surfaces with and without the presence of depressional areas. Stepwise changes in depression storage and ponding area were observed for the 3 selected surfaces. These stepwise changes highlighted the dynamic filling, spilling, and merging processes of depressions, which need to be considered in hydrologic modelling for depression‐dominated areas. Comparisons between the D‐cubed method and other methods emphasized the potential consequences of use of artificial channels through the flats created by the depression‐filling process in the traditional approaches. In contrast, in the D‐cubed method, sub‐basins were further divided into a number of smaller CBUs and PBUs, creating a channel‐puddle drainage network. The testing of the D‐cubed method also demonstrated its applicability to a wide range of digital elevation model resolutions. Consideration of CBUs, PBUs, and their connection provides the opportunity to incorporate the D‐cubed method into different hydrologic models and improve their simulation of topography‐controlled runoff processes, especially for depression‐dominated areas.     

Establishing a threshold for rainfall-induced landslides by a kinetic energy–duration relationship

Many investigators have attempted to define the threshold of landslide failure, that is, the level of the selected climatic variable above which a rainfall-induced landslide occurs. Intensity–duration (I–d) relationships are the most common type of empirical thresholds proposed in the literature for predicting landslide occurrence induced by rainfall. Recent studies propose the use of the kinetic power per unit volume of rainfall (J m⁻² mm⁻¹) to quantify the threshold of landslides induced by rainfall. In this paper, the relationship between rainfall duration and kinetic power corresponding to landslides triggered by rain was used to propose a new approach to define the threshold for predicting landslide occurrence. In particular, for the first time, a kinetic power per unit volume of rainfall–duration relationship is proposed for defining the minimum threshold needed for landslide failure. This new method can be applied using commonly used relationship for estimating the kinetic power per unit volume of rainfall and a new equation based on the measured raindrop size distribution. The applicability of this last method was tested using the data of rainfall intensity, duration and median volume diameter for 51 landslides in Taiwan. For the 51 landslides, the comparison between the measured pairs' kinetic power–duration and all selected relationships demonstrated that the equation based on the measured raindrop size distribution is the best method to define the landslide occurrence threshold, as it is both a process-oriented approach and is characterized by the best statistical performance. This last method has also the advantage to allow the forecasting of landslide hazard before the end of the rainfall event, since the rainfall kinetic power threshold value can be exceeded for a time interval less than the event duration.     

Comparison of automatic procedures for selecting flood peaks over threshold based on goodness‐of‐fit tests

In comparison with the traditional analysis of annual maximums, the peaks over threshold method provides many advantages when performing flood frequency analysis and trend analysis. However, the choice of the threshold remains an important question without definite answers and common visual diagnostic tools are difficult to reproduce on a large scale. This study investigates the behaviour of some automatic methods for threshold selection based on the generalized Pareto model for flood peak exceedances of the threshold and the Anderson–Darling test for fitting this model. In particular, the choice of a critical significance level to define an interval of acceptable values is addressed. First, automatic methods are investigated using a simulation study to assess fitting and prediction performance in a controlled environment. It is shown that P values approximated by an existing table of critical values can speed up computation without affecting the quality of the outcomes. Second, a case study compares automatically and manually selected thresholds for 285 sites across Canada by flood regime and super regions based on site characteristics. Correspondences are examined in terms of prediction of flood quantiles and trend analysis. Results show that trend detection is sensitive to the threshold selection method when studying the evolution of the number of peaks per year. Finally, a hybrid method is developed to combine automatic methods and is calibrated on the basis of super regions. The outcomes of the hybrid method are shown to more closely reproduce the estimates of the manually selected thresholds while reducing the model uncertainty.     

Identifying threshold storm events and quantifying potential impacts of climate change on sediment yield in a small upland agricultural watershed of Ontario

Agricultural zones are significant sediment sources, but it is crucial to identify critical source areas (CSAs) of sediment yield within these zones where best management practices (BMPs) can be applied to the best effect in reducing sediment delivery to receiving water bodies rather than the economically nonviable alternative of randomly or sweepingly implementing BMPs. A storm event of a specific magnitude and hyetograph profile may, at different times, generate a greater or lesser sediment yield. The widely used agricultural nonpoint source (AGNPS) model was used to identify CSAs for sediment losses in Southwestern Ontario's agriculture‐dominated 374‐ha Holtby watershed. A storm threshold approach was adopted to identify critical periods for higher sediment losses. An AGNPS model for the Holtby watershed was set up, calibrated, and validated for run‐off volume, peak flow rate, and sediment yield for several storms. The calibrated and validated model was run for storms of increasing return periods to identify threshold storm events that would generate sediment yield greater than an acceptable value for early and late spring, summer, and fall seasons. Finally, to evaluate the potential impacts of climate change, we shifted shorter duration summer storms into spring conditions and quantified the changes in sediment yield dynamics. A 6‐hr, 7.5‐year early spring storm would generate sediment losses exceeding the acceptable limit of 0.34 t ha^?1 for the season. However, summer storms (2 hr, up to 100 years) tended to generate sediment yields below those of an identifiable threshold storm. If such shorter duration summer storms occurred in spring, the sediment yield would increase by more than fivefold. A 5‐year future storm would generate an equivalent effect of a 100‐year current spring event. The high sediment delivery to be expected will have significant implications regarding the future management of water quality of receiving waters. Appropriate placement of BMPs at CSAs will thus be needed to reduce such high sediment delivery to receiving waters.     

Pipeflow response in loess‐derived soils to precipitation and groundwater table fluctuations in a temperate humid climate

Piping is a widespread phenomenon in the world and can significantly contribute to the downward movement of water, sediments, and nutrients. This study examines the hydrological functioning of soil pipes in a loess‐derived soil under pasture using hydrometric and hydrochemical analyses. It aims to investigate the relation between pipeflow, rainfall, and groundwater table fluctuations and to determine the dominant source of the water flowing through the soil pipes using both hydrometric and hydrochemical approaches. A rapid pipeflow response is observed when a threshold rainfall depth is exceeded. This threshold depth is larger in the summer (9 mm) compared with that in the winter (4 mm) which is related to the prestorm wetness of the soil. Hydrochemical analyses indicate that both groundwater and rainfall contribute to the pipeflow with a dominance of groundwater. This study shows that pipeflow can be an important hydrological pathway in loess‐derived soils with a clear seasonal pattern in pipeflow responses to rainfall events.     

经验模态分解阈值消噪方法及其在惯性导航系统数据处理中的应用

针对惯性元件误差中有色噪声影响远大于白噪声的情况,建立元件误差的分形高斯噪声模型,利用功率谱密度方法估计模型参数。基于噪声模型推导经验模分解(EMD)的各固有模态函数(IMF)分量中噪声的方差,以此估计各分量相应的阈值,建立EMD阈值消噪方法。将该方法应用于INS中,并与小波阈值法进行比较。结果表明,小波阈值法难以控制元件中有色噪声的影响,EMD阈值法与噪声模型紧密结合,能够更有效地削弱元件中的随机误差,提高INS精度。     

一种改进小波阀值算法的变形监测数据滤波方法

针对变形监测数据的去噪问题,在分析现有阀值确定方法的基础上,提出了一种新的小波阈值算法。实际算例表明,新算法能够有效地克服软阈值法存在的恒定偏差,进一步地提高了消噪的精度和可靠性。     

基于多尺度虚拟网格与坡度阈值的机载LiDAR点云滤波方法

点云滤波是机载LiDAR数据后处理的基础工作,本文提出一种基于多尺度虚拟网格与坡度阈值的机载LiDAR点云滤波方法。该方法采用类似影像金字塔的方式构建不同尺度即不同分辨率的虚拟网格,各级网格都以每个方格内最低点作为地面种子点,然后根据坡度阈值以分辨率由低到高的方式逐层对种子点进行平滑处理,最后以最高分辨率即最小尺度虚拟网格地面种子点作为基准种子点对整个数据集进行滤波处理。本文分别采用城区与郊区两块机载LiDAR数据进行了实验。实验表明,该方法能够有效地提取出地面点,运算效率也比较高,具有一定的实用价值。     

弱电机房防雷系统可靠性关键参数解析

在弱电机房防雷系统建设和工程验收过程中,需要一个全面、实用和直观的评判方法,来评价其防雷系统的防护能力是否达到设备安全的要求。以一个弱电机房防雷工程项目为例,分析并得出影响弱电机房防雷系统可靠性的关键参数是:空间屏蔽效能、传输线缆的屏蔽效能、终端最大脉冲电压设限、机房布线最大开口环的感应电压、均压和泄流能力等。在此基础上,以归纳描述或量化分析的方法,对这些关键参数进行了评估和计算,并得出弱电机房防雷设施效能判定参数表。