Soil pipe flow tracer experiments: 1. Connectivity and transport characteristics

Much debate has occurred in catchment hydrology regarding the connectivity of flow paths from upslope areas to catchment outlets. This study was conducted in two catchments, one with three upper branches, in a loess soil with a fragipan that fosters lateral flow and exhibits an extensive distribution of soil pipe collapse features. The study aimed to determine the connectivity of multiple soil pipe networks as well as determine pipe flow velocities during storm events. Fluorescein dye was injected directly into soil pipes at the upper most pipe collapse feature of four different hillslopes. Breakthrough curves (BTC) were determined by sampling multiple pipe collapse features downslope. The BTCs were used to determine the ‘average’ (centre of mass) and ‘maximum’ (first arrival) flow velocities. This study confirmed that these catchments contain individual continuous soil pipe networks that extend over 190 m and connect the upper most hillslopes areas with the catchment outlet. While the flow paths are continuous, the individual pipe networks consist of alternating reaches of subsurface flow through soil pipes and reaches of surface flow through gullies formed by pipe collapses. In addition, flow can be occurring both through the subsurface soil pipes simultaneous with surface flow generated by artesian flow from the soil pipes. The pipe flow velocities were as high as 0.3 m/s, which was in the range of streamflow velocities. These pipe flow velocities were also in the range of velocities observed in pinhole erosion tests suggesting that these large, mature soil pipes are still actively eroding. Copyright © 2015 John Wiley & Sons, Ltd.     

New graphical methods for estimating aquifer hydraulic parameters using pumping tests with exponentially decreasing rates

Actual pumping tests may involve continuously decreasing rates over a certain period of time, and the hydraulic conductivity (K) and specific storage (S_s) of the tested confined aquifer cannot be interpreted from the classical constant‐rate test model. In this study, we revisit the aquifer drawdown characteristics of a pumping test with an exponentially decreasing rate using the dimensionless analytical solution for such a variable‐rate model. The drawdown may decrease with time for a short period of time at intermediate pumping times for such pumping tests. A larger ratio of initial to final pumping rate and a smaller radial distance of the observation well will enhance the decreasing feature. A larger decay constant results in an earlier decrease, but it weakens the extent of such a decrease. Based on the proposed dimensionless transformation, we have proposed two graphical methods for estimating K and S_s of the tested aquifer. The first is a new type curve method that does not employ the well function as commonly done in standard type curve analysis. Another is a new analytic method that takes advantage of the decreasing features of aquifer drawdown during the intermediate pumping stage. We have demonstrated the applicability and robustness of the two new graphical methods for aquifer characterization through a synthetic pumping test.     

Revised runoff curve number for runoff prediction in the Loess Plateau of China

The soil conservation service (now Natural Resources Conservation Service) Curve Number (SCS-CN), one of the most commonly used methods for surface runoff prediction. The runoff calculated by this method was very sensitive to CN values. In this study, CN values were calculated by both arithmetic mean (CN_C) and least square fit method (CN_F) using observed rainfall-runoff data from 43 sites in the Loess Plateau region, which are considerably different from the CN₂ values obtained from the USDA-SCS handbook table (CN_T). The results showed that using CN_C instead of CN_T for each watershed produce little improvement, while replacing CN_T with CN_F improves the performance of the original SCS-CN method, but still performs poorly in most study sites. This is mainly due to the SCS-CN method using a constant CN value and discounting of the temporal variation in rainfall-runoff process. Therefore, three factors—soil moisture, rainfall depth and intensity—affecting the surface runoff variability are considered to reflect the variation of CN in each watershed, and a new CN value was developed. The reliability of the proposed method was tested with data from 38 watersheds, and then applied to the remaining five typical watersheds using the optimized parameters. The results indicated that the proposed method, which boosted the model efficiencies to 81.83% and 74.23% during calibration and validation cases, respectively, performed better than the original SCS-CN and the Shi and Wang (2020b) method, a modified SCS-CN method based on tabulated CN value. Thus, the proposed method incorporating the influence of the temporal variability of soil moisture, rainfall depth, and intensity factors suggests an accurate runoff prediction for general applications under different hydrological and climatic conditions on the Loess Plateau region.     

Predicting the dependency of a degree of saturation on void ratio and suction using effective stress principle for unsaturated soils

The paper presents an approach to predicting variation of a degree of saturation in unsaturated soils with void ratio and suction. The approach is based on the effective stress principle for unsaturated soils and several underlying assumptions. It focuses on the main drying and wetting processes and does not incorporate the effects of hydraulic hysteresis. It leads to the dependency of water retention curve (WRC) on void ratio, which does not require any material parameters apart from the parameters specifying WRC for the reference void ratio. Its validity is demonstrated by comparing predictions with the experimental data on four different soils taken over from the literature. Good correlation between the measured and predicted behaviour indirectly supports applicability of the effective stress principle for unsaturated soils. Copyright © 2009 John Wiley & Sons, Ltd.     

Cracking risk of partially saturated porous media—Part I: Microporoelasticity model

Drying of deformable porous media results in their shrinkage, and it may cause cracking provided that shrinkage deformations are hindered by kinematic constraints. This is the motivation to develop a thermodynamics‐based microporoelasticity model for the assessment of cracking risk in partially saturated porous geomaterials. The study refers to 3D representative volume elements of porous media, including a two‐scale double‐porosity material with a pore network comprising (at the mesoscale) 3D mesocracks in the form of oblate spheroids, and (at the microscale) spherical micropores of different sizes. Surface tensions prevailing in all interfaces between solid, liquid, and gaseous matters are taken into account. To establish a thermodynamics‐based crack propagation criterion for a two‐scale double‐porosity material, the potential energy of the solid is derived, accounting—in particular—for mesocrack geometry changes (main original contribution) and for effective micropore pressures, which depend (due to surface tensions) on the pore radius. Differentiating the potential energy with respect to crack density parameter yields the thermodynamical driving force for crack propagation, which is shown to be governed by an effective macrostrain. It is found that drying‐related stresses in partially saturated mesocracks reduce the cracking risk. The drying‐related effective underpressures in spherical micropores, in turn, result in a tensile eigenstress of the matrix in which the mesocracks are embedded. This way, micropores increase the mesocracking risk. Model application to the assessment of cracking risk during drying of argillite is the topic of the companion paper (Part II). Copyright © 2009 John Wiley & Sons, Ltd.     

基于Logistic和Gompertz曲线模型拟合的建筑物沉降分析

重大工程建设一般会有定期的沉降和变形监测,本研究利用具有规律变化的Logistic和Gompertz曲线模型进行拟合,并以某大型发电厂为研究对象,利用近15年的监测数据,建立预测模型并进行精度评估。研究结果表明,若监测数据具有一定程度的稳定性,并对计算时监测数据进行合理取舍,对采取的全区、分区平均值或单一点高度值的检测数据,运用Logistic和Gompertz曲线模型来预测大型建筑物的沉降情况是可行的。     

采用弯曲进行道路化简冲突避免的方法

针对道路化简后可能导致要素间空间关系前后不一致的问题,提出了一种采用弯曲进行道路化简冲突避免的方法。首先,以弯曲为单元分析道路化简前后弯曲的形态变化规律,对化简过程产生的要素间空间冲突类型进行了归纳和总结;其次,基于道路弯曲与要素之间的空间关系,提出了相应的冲突判别规则;最后,利用弯曲化简的可控性和弯曲组的间接化简策略实现对化简冲突的避免。试验表明,该方法能有效地识别和避免道路化简产生的空间冲突,确保化简前后道路与其他要素空间关系的一致性。     

一种迭代法的圆曲线拟合方法

针对在实际测量工作中量测圆心坐标及半径时存在的问题,该文基于迭代法的思想,推导了一种圆曲线拟合的方法,并用实例数据进行了检验。结果显示,该方法在离散点均匀采集或非均匀采集的情况下均具有良好的拟合效果,与目前在圆曲线拟合方法中普遍采用的最小二乘法相比,具有同样高的拟合精度,验证了该拟合方法的正确性与可行性。     

一种曲线拟合圆心坐标算法及精度分析

针对在工程应用中,经常需要根据某些圆形物体上的离散点求取其圆心坐标,而采用何种算法简单易行,其精度又与哪些因素有关的相关研究较少的问题,该文提出一种利用曲线拟合求取圆心坐标的简洁算法,并编程实现。然后采用模拟仿真结合统计分析的方法评估了该算法在不同条件下的拟合精度,得出测点误差越大,拟合精度越低;测点个数越多,分布越均匀,拟合精度越高;圆半径对拟合精度影响甚小等结论。在某工程项目中使用该算法得到的结果精度较高,验证了其有效可行,且与采用其他方法得到的坐标值较为接近,说明了该算法的可靠性高。     

Curve matching approaches to waveform classification: a case study using ICESat data

Light Detection and Ranging (LiDAR) waveforms are being increasingly used in many forest and urban applications, especially for ground feature classification. However, most studies relied on either discretizing waveforms to multiple returns or extracting shape metrics from waveforms. The direct use of the full waveform, which contains the most comprehensive and accurate information has been scarcely explored. We proposed to utilize the complete waveform to test its ability to differentiate between objects having distinct vertical structures using curve matching approaches. Two groups of curve matching approaches were developed by extending methods originally designed for pixel-based hyperspectral image classification and object-based high spatial image classification. The first group is based on measuring the curve similarity between an unknown waveform and a reference waveform, including curve root sum squared differential area (CRSSDA), curve angle mapper (CAM), and Kullback–Leibler (KL) divergence. The second group assesses the curve similarity between an unknown and reference cumulative distribution functions (CDFs) of their waveforms, including cumulative curve root sum squared differential area (CCRSSDA), cumulative curve angle mapper (CCAM), and Kolmogorov–Smirnov (KS) distance. When employed to classify open space, trees, and buildings using ICESat waveform data, KL provided the highest average classification accuracy (87%), closely followed by CCRSSDA and CCAM, and they all significantly outperformed KS, CRSSDA, and CAM based on 15 randomized sample sets.