Quantifying rainfall controls on catchment‐scale landslide erosion in Taiwan

Landslide erosion is a dominant hillslope process and the main source of stream sediment in tropical, tectonically active mountain belts. In this study, we quantified landslide erosion triggered by 24 rainfall events from 2001 to 2009 in three mountainous watersheds in Taiwan and investigated relationships between landslide erosion and rainfall variables. The results show positive power‐law relations between landslide erosion and rainfall intensity and cumulative rainfall, with scaling exponents ranging from 2·94 to 5·03. Additionally, landslide erosion caused by Typhoon Morakot is of comparable magnitude to landslide erosion caused by the Chi‐Chi Earthquake (M_W = 7·6) or 22–24 years of basin‐averaged erosion. Comparison of the three watersheds indicates that deeper landslides that mobilize soil and bedrock are triggered by long‐duration rainfall, whereas shallow landslides are triggered by short‐duration rainfall. These results suggest that rainfall intensity and watershed characteristics are important controls on rainfall‐triggered landslide erosion and that severe typhoons, like high‐magnitude earthquakes, can generate high rates of landslide erosion in Taiwan. Copyright © 2012 John Wiley & Sons, Ltd.     

Modelling catchment‐scale shallow landslide occurrence and sediment yield as a function of rainfall return period

A model‐based method is proposed for improving upon existing threshold relationships which define the rainfall conditions for triggering shallow landslides but do not allow the magnitude of landsliding (i.e. the number of landslides) to be determined. The SHETRAN catchment‐scale shallow landslide model is used to quantify the magnitude of landsliding as a function of rainfall return period, for focus sites of 180 and 45 km² in the Italian Southern Alps and the central Spanish Pyrenees. Rainfall events with intensities of different return period are generated for a range of durations (1‐day to 5‐day) and applied to the model to give the number of landslides triggered and the resulting sediment yield for each event. For a given event duration, simulated numbers of landslides become progressively less sensitive to return period as return period increases. Similarly, for an event of given return period, landslide magnitude becomes less sensitive to event duration as duration increases. The temporal distribution of rainfall within an event is shown to have a significant impact on the number of landslides and the timing of their occurrence. The contribution of shallow landsliding to catchment sediment yield is similarly quantified as a function of the rainfall characteristics. Rainfall intensity–duration curves are presented which define different levels of landsliding magnitude and which advance our predictive capability beyond, but are generally consistent with, published threshold curves. The magnitude curves are relevant to the development of guidelines for landslide hazard assessment and forecasting. Copyright © 2011 John Wiley & Sons, Ltd.     

基于高分卫星遥感影像的地震应急滑坡编目与分布特征探讨——以2017年8月8日九寨沟7.0级地震为例

地震应急是减轻地震灾害的重要途径之一。地震应急工作具有时间紧迫、事关重大的特点。2017年8月8日四川九寨沟M_S7.0级地震发生后,为快速、准确地提供地震引发的滑坡灾害分布,本研究基于震后第一天获取到的高分辨率遥感影像（高分二号卫星影像、北京二号卫星影像）,通过人工目视解译的方法初步建立了四川九寨沟地震滑坡编目。结果表明,该地震至少触发了622处同震滑坡,分布在沿使用影像边界框定的面积为3919km2的区域内。本研究还利用这个地震滑坡编目,统计了九寨沟地震滑坡数量和滑坡点密度（LND）与地形（坡度、坡向）、地震（地震烈度、震中距）等因素的关系。结果表明九寨沟地震滑坡多发生在坡度为20°—50°的区域内,滑坡的易发性随着坡度的增加而增加。受地震波传播方向的影响,E、SE向是地震滑坡较易发生的坡向。滑坡的易发程度和地震烈度呈正相关,即随着烈度的增大,滑坡易发性增大。滑坡易发性还随着震中距增加而降低,这是由于地震波能量随震中距的增加而衰减导致的。     

Application of a multi‐temporal,LiDAR‐derived,digital terrain model in a landslide‐volume estimation

Sediments produced by landslides are crucial in the sediment yield of a catchment, debris flow forecasting, and related hazard assessment. On a regional scale, however, it is difficult and time consuming to measure the volumes of such sediment. This paper uses a LiDAR‐derived digital terrain model (DTM) taken in 2005 and 2010 (at 2 m resolution) to accurately obtain landslide‐induced sediment volumes that resulted from a single catastrophic typhoon event in a heavily forested mountainous area of Taiwan. The landslides induced by Typhoon Morakot are mapped by comparison of 25 cm resolution aerial photographs taken before and after the typhoon in an 83.6 km² study area. Each landslide volume is calculated by subtraction of the 2005 DTM from the 2010 DTM, and the scaling relationship between landslide area and its volume are further regressed. The relationship between volume and area are also determined for all the disturbed areas (V_L = 0.452A_L^1.242) and for the crown areas of the landslides (V_L = 2.510A_L^1.206). The uncertainty in estimated volume caused by use of the LiDAR DTMs is discussed, and the error in absolute volume estimation for landslides with an area >10⁵ m² is within 20%. The volume–area relationship obtained in this study is also validated in 11 small to medium‐sized catchments located outside the study area, and there is good agreement between the calculation from DTMs and the regression formula. By comparison of debris volumes estimated in this study with previous work, it is found that a wider volume variation exists that is directly proportional to the landslide area, especially under a higher scaling exponent. Copyright © 2013 John Wiley & Sons, Ltd.     

Analysis of historical landslide time series in the Emilia‐Romagna region,northern Italy

A catalogue of historical landslides, 1951–2002, for three provinces in the Emilia‐Romagna region of northern Italy is presented and its statistical properties studied. The catalogue consists of 2255 reported landslides and is based on historical archives and chronicles. We use two measures for the intensity of landsliding over time: (i) the number of reported landslides in a day (D_L) and (ii) the number of reported landslides in an event (S_event), where an event is one or more consecutive days with landsliding. From 1951–2002 in our study area there were 1057 days with 1 ≤ D_L ≤?45 landslides per day, and 596 events with 1 ≤ S_event ≤ 129 landslides per event. In the first set of analyses, we find that the probability density of landslide intensities in the time series are power‐law distributed over at least two‐orders of magnitude, with exponent of about ?2·0. Although our data is a proxy for landsliding built from newspaper reports, it is the first tentative evidence that the frequency‐size of triggered landslide events over time (not just the landslides in a given triggered event), like earthquakes, scale as a power‐law or other heavy‐tailed distributions. If confirmed, this could have important implications for risk assessment and erosion modelling in a given area. In our second set of analyses, we find that for short antecedent rainfall periods, the minimum amount of rainfall necessary to trigger landslides varies considerably with the intensity of the landsliding (D_L and S_event); whereas for long antecedent periods the magnitude is largely independent of the cumulative amount of rainfall, and the largest values of landslide intensity are always preceded by abundant rainfall. Further, the analysis of the rainfall trend suggests that the trigger of landslides in the study area is related to seasonal rainfall. Copyright © 2010 John Wiley & Sons, Ltd.     

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.     

Comparison of the return period for landslide-triggering rainfall events in Japan based on standardization of the rainfall period

The intensity of rainfall events with potential to cause landslides has varying temporal characteristics. In this study, the time at which the 72-h accumulated rainfall reached its maximum was used to standardize the period of rainfall measurement. The proposed standardization of the rainfall period was used in conjunction with the return level of rainfall intensity, obtained from intensity–duration–frequency curves, to investigate rainfall intensity anomalies associated with 10 hazardous rainfall events that triggered numerous landslides at the regional scale in Japan. These landslides included shallow landslides in volcanic and non-volcanic areas, as well as deep-seated landslides. The rainfall events that triggered the shallow landslides were divided into two types: downpours that repeatedly reached close to the 100-year return level within approximately 3–4 h, and accumulated rainfall that reached close to 200–400 mm over longer time intervals but within 72 h. Lithological differences seemed unrelated to the differences between the two types of shallow-landslide-triggering rainfall; however, precipitation >1000 mm was necessary to trigger deep-seated landslides. Although the characteristics of the hyetographs differed markedly among the landslide-triggering rainfall events, all the landslides could have been triggered when the mean rainfall intensity reached the 100-year rainfall level during the standardized period. Thus, the landslide trigger can be evaluated indirectly based on the increase in the return level of the mean rainfall intensity, which could provide a means for estimating the time of landslide occurrence.     

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.     

The Spatial Distribution and Attribute Parameter Statistics of Landslides Triggered by the May 12th, 2008, MW7.9 Wenchuan Earthquake

A complete landslide inventory and attribute database is the importantly fundamental for the study of the earthquake-induced landslide. Substantial landslides were triggered by the M_W7.9 Wenchuan earthquake on May 12^th, 2008. Google Earth images of pre- and post-earthquakes show that 52 194 co-seismic landslides were recognized and mapped, with a total landslides area of 1 021 km².Based on the statistics,we assigned all landslide parameters and established the co-seismic landslides database, which includes area, length, and width of landslides, elevation of the scarp top and foot edge, and the top and bottom elevations of each located slope. Finally, the spatial distribution and the above attribute parameters of landslides were analyzed. The results show that the spatial distribution of the co-seismic landslides is extremely uneven. The landslides that mainly occur in a rectangular area (a width of 30 km of the hanging wall of the Yingxiu-Beichuan fault and a length of 120 km between Yingxiu and Beichuan) are obviously controlled by surface rupture, terrain, and peak ground acceleration. Meanwhile, a large number of small landslides (individual landslide area less than 10 000 m²)contribute less to the total landslides area. The number of landslides larger than 10 000 m² accounts for 38.7% of the total number of co-seismic landslides, while the area of those landslides account for 88% of the total landslides area. The 52 194 co-seismic landslides are caused by bedrock collapse that usually consists of three parts:source area, transport area, and accumulation area. However, based on the area-volume power-law relationship, the resulting regional landslide volume may be much larger than the true landslide volume if the landslide volume is calculated using the influenced area from each landslide.     

Analysing the Relationship Between Typhoon‐Triggered Landslides and Critical Rainfall Conditions

Many landslides are triggered by rainfall. Previous studies of the relationship between landslides and rainfall have concentrated on deriving minimum rainfall thresholds that are likely to trigger landslides. Though useful, these minimum thresholds derived from a log–log plot do not offer any measure of confidence in a landslide monitoring or warning system. This study presents a new and innovative method for incorporating rainfall into landslide modelling and prediction. The method involves three steps: compiling radar reflectivity data in a QPESUMS (quantitative precipitation estimation and segregation using multiple sensors) system during a typhoon (tropical hurricane) event, estimating rainfall from radar data and using rainfall intensity and rainfall duration as explanatory variables to develop a landslide logit model. Given the logit model, this paper discusses ways in which the model can be used for computing probabilities of landslide occurrence for a real‐time monitoring system or a warning system, and for delineating and mapping landslides. Copyright © 2007 John Wiley & Sons, Ltd.     

Unique landslides (loess slide-flows) induced by an extreme rainstorm in 2018 on the Loess Plateau: A new geological hazard and erosion process

Currently, the vegetation has recovered well in most areas of the Loess Plateau in China, and soil erosion has significantly decreased. However, the heavy rainfall event in July 2018 triggered many instances of a unique type of loess landslides(i.e., slide-flows) on the gully-slopes with vegetation recovery in the Nanxiaohegou Basin on the Loess Plateau. This rainfall event was unusual and was a persistent heavy rainfall. The accumulated rainfall from 24 June to 10 July was 232.2 mm, which compr...     

山西大宁县典型滑坡体地貌特征与降雨和强震关系

山西大宁县位于山西省吕梁山南端，境内沟壑纵横，具有独特的黄土高原地形地貌特征。在该地区进行地质灾害调查，以查明灾害分布、形成原因和隐患情况。应用地貌学的有关原理，结合遥感影像解译，在义亭河的支流河谷两岸0.3 km²（575 m×526 m）范围内发现并确认了2个大型和2个中型滑坡体。滑坡体均为基岩与上方的黄土沉积层整体滑下，滑坡体沿河流流动的方向发生一定程度的扭转，滑面近于直立，滑动方向与河流流向一致，没有形成堰塞湖。对滑坡体与周围地貌特征，以及河道被改动的方向特征研究认为：①4个滑坡体是在不同的地质时期形成；②其中1个滑坡体明显受到一条断裂的影响；③其它3个滑坡体，可能是在河流侵蚀搬运作用加强，导致的"重力塌陷"，及河流流向作用牵引的动力学作用下，经过较漫长的时间形成；④在距离该地区约60 km的洪洞地震、临汾地震，以及距离该地区230余公里的华县地震，这三次8级地震过程中，地震应力可能加剧了滑坡体的发生或滑动；⑤未来该滑坡体，仍然可能在非常规的外界条件下，如强降雨或地震应力等的影响下，出现加速滑动的可能。     

An updated method for estimating landslide‐event magnitude

Summary statistics derived from the frequency–area distribution (FAD) of inventories of triggered landslides allows for direct comparison of landslides triggered by one event (e.g. earthquake, rainstorm) with another. Such comparisons are vital to understand links between the landslide‐event and the environmental characteristics of the area affected. This could lead to methods for rapid estimation of landslide‐event magnitude, which in turn could lead to estimates of the total triggered landslide area. Previous studies proposed that the FAD of landslides follows an inverse power‐law, which provides the basis to model the size distribution of landslides and to estimate landslide‐event magnitude (mLS), which quantifies the severity of the event. In this study, we use a much larger collection of earthquake‐induced landslide (EQIL) inventories (n=45) than previous studies to show that size distributions are much more variable than previously assumed. We present an updated model and propose a method for estimating mLS and its uncertainty that better fits the observations and is more reproducible, robust, and consistent than existing methods. We validate our model by computing mLS for all of the inventories in our dataset and comparing that with the total landslide areas of the inventories. We show that our method is able to estimate the total landslide area of the events in this larger inventory dataset more successfully than the existing methods. © 2018 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.     

Temporal and spatial variation of infilling processes in a landslide scar in a steep mountainous region,Japan

The duration of the soil‐depth recovery needed for reoccurrence of shallow colluvial landslides at a given site in humid regions is much longer than the return period of rainfall needed to generate sufficient pore water pressure to initiate a landslide. Knowledge of the rate of change in soil depth in landslide scars is therefore necessary to evaluate return intervals of landslides. Spatial variation in sediment transport at the Kumanodaira landslide scar in central Japan was investigated by field observations. Spatial distribution of the rate of change in soil depth was estimated using sediment transport data and geographic information system (GIS) analysis. Observations revealed that the timing of sediment transport differed for shallow and deep soil layers. Near‐surface sediment transport (mostly dry ravel and some shallow soil creep at depths ≤0·05 m) measured in sediment traps was active in winter and early spring and was affected by freezing–thawing; soil creep of subsoil (i.e. >0·05 m), monitored by strain probes, was active in summer and autumn when precipitation was abundant. Near‐surface sediment flux was estimated by a power law function of slope gradient. Deeper soil creep was more affected by relative location to the landslide scar, which influences soil depth, than by slope gradient. Our study indicated that the rate of soil‐depth recovery is high just below the head scarp of the landslide. Abrupt changes in the longitudinal slope topography immediately above, within and just below the head scarp became smoother with time due to degradation proximate to the landslide head scarp and flanks, as well as aggradation just below the head scarp. Copyright © 2014 John Wiley & Sons, Ltd.     

Application of the SHETRAN basin‐scale,landslide sediment yield model to the Llobregat basin,Spanish Pyrenees

The first application of the SHETRAN basin‐scale, landslide erosion and sediment yield model is carried out for a major landsliding event in the upper 505 km² of the Llobregat basin, in the eastern Spanish Pyrenees, in November 1982. The model simulates the spatial distribution of shallow landslides and their sediment yield. Acknowledging uncertainty in the model parameter evaluation, the aim of the application was not to reproduce the observed occurrence of landslides as accurately as possible with one simulation, but to bracket the observed pattern with several simulations representing uncertainty in the key input conditions. Bounds on the landslide simulations were thus determined as a function of uncertainty in the vegetation root cohesion (used in the model factor of safety calculations). The resulting upper bound considerably overestimates the observed pattern (17 000 landslides compared with an observation of around 700), but it reproduces several of the principal clusters in the observed pattern. The lower bound contains around 500 landslides. The sediment yield estimates (2670–14 630 t km^?2) are comparable to measurements elsewhere in the Pyrenees for extreme events. The results demonstrate an ability to simulate the basin‐scale landslide response to a rainfall event and the resulting sediment yield. They also highlight the need for further research in setting the uncertainty bounds and in avoiding large overestimates of landslide occurrence arising in part from a current inability to model small‐scale controls for a basin of the given size. Copyright © 2006 John Wiley & Sons, Ltd.     

1920年海原地震滑坡密集区的地震动场地效应研究

地震动作为引起地震灾害的原动力,常常通过造成建筑物倒塌、山体滑坡等形式引起大量人员伤亡和财产损失。1920年海原8½级地震,在震中距80 km远的西吉—静宁交界的黄土丘陵区引发了大量的山体滑坡,并造成重大人员伤亡和财产损失。在分析海原地震高烈度区滑坡分布特征的基础上,通过场地调查和数值计算等方法,研究典型滑坡密集场地的地质条件及地震反应特征。研究表明起伏地形和黄土厚度不均等因素造成丘陵山体两侧地震反应的差异,从而导致地震滑坡在斜坡土体较厚的一侧成群连片发育。海原地震造成的滑坡密集区的地形地貌、岩土性质、土层结构等条件决定了该地区地震动随局部场地条件变化非常迅速,地层场地效应和地形场地效应联合作用加剧了斜坡地表的地震动放大作用,增加了触发地震滑坡的动力。     

宝兰客专天水市王家墩滑坡地震稳定性分析

天水市秦安县王家墩滑坡为宝兰客专沿线巨型古滑坡群,宝兰客运专线秦安隧道穿其而过。以王家墩滑坡为研究对象,围绕工程中静、动力抗滑稳定性问题,通过室内试验、现场调查对影响王家墩古滑坡稳定性的地质构造、场地工程条件等内在因素进行分析评价,在此基础上通过有限元动力分析,对王家墩古滑坡在地震载荷下的动力响应进行分析,明确地震荷载作用下,王家墩古滑坡失稳影响因素、地震荷载与滑坡失稳破坏间的关系。采用动力有限元法和强度折减法相结合的方法,开展动力抗滑稳定性分析方法研究;采用位移突变的方法来确定边坡动力失稳及动力安全系数,分析结果表明：地震作用时的水平推力对王家墩古滑坡的稳定性有很大影响,表现为上部坡体的整体滑移和隧道入口段黄土堆积层局部失稳滑塌;在天然状态下坡体处于稳定状态,在遭遇未来该区域中强地震作用时,该斜坡会发生失稳,黄土斜坡的整体滑动最容易出现在第三阶坡体,沿着塑性应变最大的滑移面整体滑移;给出了坡体动力稳定性安全系数F_s=0.92。     

Rainfall characteristics for shallow landsliding in Seattle,Washington, USA

Shallow landsliding in the Seattle, Washington, area, has caused the occasional loss of human life and millions of dollars in damage to property. The effective management of the hazard requires an understanding of the rainfall conditions that result in landslides. We present an empirical approach to quantify the antecedent moisture conditions and rainstorm intensity and duration that have triggered shallow landsliding using 25 years of hourly rainfall data and a complementary record of landslide occurrence. Our approach combines a simple water balance to estimate the antecedent moisture conditions of hillslope materials and a rainfall intensity–duration threshold to identify periods when shallow landsliding can be expected. The water balance is calibrated with field‐monitoring data and combined with the rainfall intensity–duration threshold using a decision tree. Results are cast in terms of a hypothetical landslide warning system. Two widespread landslide events are correctly identified by the warning scheme; however, it is less accurate for more isolated landsliding. Copyright © 2005 John Wiley & Sons, Ltd.     

Slope control on the frequency distribution of shallow landslides and associated soil properties,North Island,New Zealand

The extrapolation of results from field trials to larger areas of land for purposes of regional impact assessment is an important issue in geomorphology, particularly for landform properties that show high stochastic variability in space and time, such as shallow landslide erosion. It is shown in this study, that by identifying the main driver for spatial variability in shallow landslide erosion at field scales, namely slope angle, it is possible to develop a set of generic functions for assessing the impact of landslides on selected soil properties at larger spatial scales and over longer time periods. Research was conducted within an area of pastoral soft‐rock Tertiary hill country in the North Island of New Zealand that is subject to infrequent high intensity rainfall events, producing numerous landslides, most of which are smaller than several hundred square metres in size and remove soil to shallow depths. All landslides were mapped within a 0·6 km² area and registered to a high resolution (2 m) slope map to show that few landslides occur on slopes < 20° and 95% were on slopes > 24°. The areal density of landslides from all historical events showed an approximately linear increase with slope above 24°. Integrating landslide densities with soil recovery data demonstrates that the average value of a soil property fluctuates in a ‘saw‐tooth’ fashion through time with the overall shape of the curve controlled by the frequency of landslide inducing storm events and recovery rate of the soil property between events. Despite such fluctuations, there are gradual declines of 7·5% in average total carbon content of topsoil and 9·5% in average soil depth to bedrock, since the time of forest clearance. Results have application to large‐scale sediment budget and water quality models and to the New Zealand Soil Carbon Monitoring System (CMS). Copyright © 2012 John Wiley & Sons, Ltd.