An integrated hydrological model for rain‐induced landslide prediction

This paper describes an extension to the Combined Hydrology And Stability Model (CHASM) to fully include the effects of vegetation and slope plan topography on slope stability. The resultant physically based numerical model is designed to be applied to site‐specific slopes in which a detailed assessment of unsaturated and saturated hydrology is required in relation to vegetation, topography and slope stability. Applications are made to the Hawke's Bay region in New Zealand where shallow‐seated instability is strongly associated with spatial and temporal trends in vegetation cover types, and the Mid‐Levels region in Hong Kong, an area subject to a variety of landslide mechanisms, some of which may be subject to strong topographic control. An improved understanding of process mechanism, afforded by the model, is critical for reliable and appropriate design of slope stabilization and remedial measures. Copyright © 2002 John Wiley & Sons, Ltd.     

Spatial and temporal variability of pore‐water pressures in residual soil slopes in a tropical climate

It is critical to understand and quantify the temporal and spatial variability in hillslope hydrological data in order to advance hillslope hydrological studies, evaluate distributed parameter hydrological models, analyse variability in hydrological response of slopes and design efficient field data sampling networks. The spatial and temporal variability of field‐measured pore‐water pressures in three residual soil slopes in Singapore was investigated using geostatistical methods. Parameters of the semivariograms, namely the range, sill and nugget effect, revealed interesting insights into the spatial structure of the temporal situation of pore‐water pressures in the slopes. While informative, mean estimates have been shown to be inadequate for modelling purposes, indicator semivariograms together with mean prediction by kriging provide a better form of model input. Results also indicate that significant temporal and spatial variability in pore‐water pressures exists in the slope profile and thereby induces variability in hydrological response of the slope. Spatial and temporal variability in pore‐water pressure decreases with increasing soil depth. The variability decreases during wet conditions as the slope approaches near saturation and the variability increases with high matric suction development following rainfall periods. Variability in pore‐water pressures is greatest at shallow depths and near the slope crest and is strongly influenced by the combined action of microclimate, vegetation and soil properties. Copyright © 2002 John Wiley & Sons, Ltd.     

基于DEM的分布式水文模型构建方法

基于 DEM的分布式水文模型是现代水文学同高科技 (如计算机技术、 3S技术等 )相结合的产物 ,是研究变化环境下水文循环与水资源演化规律的理想工具 ,代表了水文模型的最新发展方向。从 DEM的特性出发 ,本文探讨并总结了分布式水文模型的特点、建模思路和模型基本结构框图。在流域离散化方面 ,重点介绍了分布式水文模型常用的三种单元划分方法 ;最后 ,针对分布式水文模型构建问题 ,从“输入模块”、“单元水文模型”、“河网汇流模型”三方面 ,阐述了分布式水文模型微结构构建方法。     

现代水文与空间数据采集技术

从基本定义、研究对象、研究领域、研究手段、研究方法、研究目的以及数据采集、服务等多个不同层面，对传统水文(学)和现代水文(学)进行了比较，分析了二者的特征和区别，论述了从传统水文向现代水文转变是现代水利的必然要求，而空间数据采集技术是实现这一转变极其重要的途径和手段。     

河道沿岸芦苇带对氨氮的削减特性研究

氨氮污染已成为我国江河湖库水质下降和水生态系统退化的重要因素之一.借助现场对比观测试验和理论分析的方法,研究不同季节氨氮对河流水质的影响规律,得到了雨洪初期汇流河流水质污染最为严重的结论.系统地研究了沿河岸芦苇带对氨氮的削减净化效应,得到了芦苇带吸附氨氮的主要影响因素为:芦苇生长期、水体污染物浓度、河道流速及气象条件.运用数值模拟和参数优化估算技术,确定氨氮在河道两岸有、无芦苇等植物条件下的衰减系数和削减量,分析了衰减系数的变化规律和削减量大小的影响因素,为河流水生态系统修复和水质预测预报提供科学依据.     

Scaling effects on modeled surface energy-balance components using the NOAH-OSU land surface model

As surface exchange processes are highly non-linear and heterogeneous in space and time, it is important to know the appropriate scale for the reasonable prediction of these exchange processes. For example, the explicit representation of surface variability has been vital in predicting mesoscale weather events such as late-afternoon thunderstorms initiated by latent heat exchanges in mid-latitude regions of the continental United States. This study was undertaken to examine the effects of different spatial scales of input data on modeled fluxes, so as to better understand the resolution needed for accurate modeling. A statistical procedure was followed to select two cells from the Southern Great Plains 1997 hydrology experiment region, each 20 km×20 km, representing the most homogeneous and the most heterogeneous surface conditions (based on soil and vegetation) within the study region. The NOAH-OSU (Oregon State University) Land Surface Model (LSM) was employed to estimate surface energy fluxes. Three scales of study (200 m, 2 and 20 km) were considered in order to investigate the impacts of the aggregation of input data, especially soil and vegetation inputs, on the model output. Model results of net radiation and latent, sensible and ground heat fluxes were compared for the three scales. For the heterogeneous area, the model output at the 20-km resolution showed some differences when compared with the 200-m and 2-km resolutions. This was more pronounced in latent heat (12% decrease), sensible heat (22% increase), and ground heat flux (44% increase) estimation than in net radiation. The scaling effects were much less for the relatively homogeneous land area with 5% increase in sensible heat and 4% decrease in ground heat flux estimation. All of the model outputs for the 2- and 20-km resolutions were in close agreement. The results suggested that, for this study region, soils and vegetation input resolution of about 2 km should be chosen for realistic modeling of surface exchange processes. This resolution was sufficient to capture the effects of sub-grid scale heterogeneity, while avoiding the data and computational difficulties associated with higher spatial resolutions.     

Testing a model for predicting the timing and location of shallow landslide initiation in soil‐mantled landscapes

The growing availability of digital topographic data and the increased reliability of precipitation forecasts invite modelling efforts to predict the timing and location of shallow landslides in hilly and mountainous areas in order to reduce risk to an ever‐expanding human population. Here, we exploit a rare data set to develop and test such a model. In a 1·7 km² catchment a near‐annual aerial photographic coverage records just three single storm events over a 45 year period that produced multiple landslides. Such data enable us to test model performance by running the entire rainfall time series and determine whether just those three storms are correctly detected. To do this, we link a dynamic and spatially distributed shallow subsurface runoff model (similar to TOPMODEL) to an in?nite slope model to predict the spatial distribution of shallow landsliding. The spatial distribution of soil depth, a strong control on local landsliding, is predicted from a process‐based model. Because of its common availability, daily rainfall data were used to drive the model. Topographic data were derived from digitized 1 : 24 000 US Geological Survey contour maps. Analysis of the landslides shows that 97 occurred in 1955, 37 in 1982 and ?ve in 1998, although the heaviest rainfall was in 1982. Furthermore, intensity–duration analysis of available daily and hourly rainfall from the closest raingauges does not discriminate those three storms from others that did not generate failures. We explore the question of whether a mechanistic modelling approach is better able to identify landslide‐producing storms. Landslide and soil production parameters were ?xed from studies elsewhere. Four hydrologic parameters characterizing the saturated hydraulic conductivity of the soil and underlying bedrock and its decline with depth were ?rst calibrated on the 1955 landslide record. Success was characterized as the most number of actual landslides predicted with the least amount of total area predicted to be unstable. Because landslide area was consistently overpredicted, a threshold catchment area of predicted slope instability was used to de?ne whether a rainstorm was a signi?cant landslide producer. Many combinations of the four hydrological parameters performed equally well for the 1955 event, but only one combination successfully identi?ed the 1982 storm as the only landslide‐producing storm during the period 1980–86. Application of this parameter combination to the entire 45 year record successfully identi?ed the three events, but also predicted that two other landslide‐producing events should have occurred. This performance is signi?cantly better than the empirical intensity–duration threshold approach, but requires considerable calibration effort. Overprediction of instability, both for storms that produced landslides and for non‐producing storms, appears to arise from at least four causes: (1) coarse rainfall data time scale and inability to document short rainfall bursts and predict pressure wave response; (2) absence of local rainfall data; (3) legacy effect of previous landslides; and (4) inaccurate topographic and soil property data. Greater resolution of spatial and rainfall data, as well as topographic data, coupled with systematic documentation of landslides to create time series to test models, should lead to signi?cant improvements in shallow landslides forecasting. Copyright © 2003 John Wiley & Sons, Ltd.     

The design of post‐mining landscapes using geomorphic principles

Nature can provide analogues for post‐mining landscapes in terms of landscape stability and also in terms of the rehabilitated structure ‘blending in’ with the surrounding undisturbed landscape. In soil‐mantled landscapes, hillslopes typically have a characteristic pro?le that has a convex upper hillslope pro?le with a concave pro?le lower down the slope. In this paper hillslope characteristic form is derived using the area–slope relationship from pre‐mining topography at two sites in Western Australia. Using this relationship, concave hillslope pro?les are constructed and compared to linear hillslopes in terms of sediment loss using the SIBERIA erosion model. It is found that concave hillslopes can reduce sediment loss by up to ?ve times that of linear slopes. Concave slopes can therefore provide an alternative method for the construction of post‐mining landscapes. An understanding of landscape geomorphological properties and the use of erosion models can greatly assist in the design of post‐mining landscapes. Copyright © 2003 John Wiley & Sons, Ltd.     

Hydrological connectivity of soil pipes determined by ground‐penetrating radar tracer detection

Soil pipes are common and important features of many catchments, particularly in semi‐arid and humid areas, and can contribute a large proportion of runoff to river systems. They may also signi?cantly in?uence catchment sediment and solute yield. However, there are often problems in ?nding and de?ning soil pipe networks which are located deep below the surface. Ground‐penetrating radar (GPR) has been used for non‐destructive identi?cation and mapping of soil pipes in blanket peat catchments. While GPR can identify subsurface cavities, it cannot alone determine hydrological connectivity between one cavity and another. This paper presents results from an experiment to test the ability of GPR to establish hydrological connectivity between pipes through use of a tracer solution. Sodium chloride was injected into pipe cavities previously detected by the radar. The GPR was placed downslope of the injection points and positioned on the ground directly above detected soil pipes. The resultant radargrams showed signi?cant changes in re?ectance from some cavities and no change from others. Pipe waters were sampled in order to check the radar results. Changes in electrical conductivity of the pipe water could be detected by the GPR, without data post‐processing, when background levels were increased by more than approximately twofold. It was thus possible to rapidly determine hydrological connectivity of soil pipes within dense pipe networks across hillslopes without ground disturbance. It was also possible to remotely measure travel times through pipe systems; the passing of the salt wave below the GPR produced an easily detectable signal on the radargram which required no post‐processing. The technique should allow remote sensing of water sources and sinks for soil pipes below the surface. The improved understanding of ?owpath connectivity will be important for understanding water delivery, solutional and particulate denudation, and hydrological and geomorphological model development. Copyright © 2004 John Wiley & Sons, Ltd.     

贡嘎山东坡海螺沟的河川径流特征

对贡嘎山高山水文观测试验系统进行了简要介绍，并对海螺沟冰川河以及黄崩溜沟的径流特征进行了初步探讨。由于大气降水同是冰川河及黄崩溜沟径流的重要补给来源，故其径流量的季节变化明显带有大气降水过程的烙印，显得丰、枯分明。在冰川河，冰雪融水和地下水在枯水季节的稳定补给改变了大气降水对冰川河径流的年内分配过程；在黄崩溜沟，由于冰雪融水和地下水对其径流的补给非常有限，大气降水过程对其径流过程的影响便明显大过冰川河。