THE CHARACTERISTICS OF RAINFALL AND DISASTERS OF DEBRIS FLOW IN BEIJING AREA

LINTRODUCTIONDisastersofdebrisflotvoccurfrequentlyinChina.Mostofthemareinrainstormtype.TherainStormdebrisflowiscausedbyStormrainfallthatinducesastrongStreamflowsonloosematerialsinwatershed.Theeffectsofprecipitationonthedebrisflowareasfollows(ChengduResearchInstituteC;DisasterandEnvironment,1989)f(l)Precipitationacceleratesthematerialsofloosedebristogather,(2)PrecipitationsuPPlywatercomponentofdebrisflow,(3)Precipitationprovidesdynamicconditionsfordebrisflow,(4)Precipitationisatrigg…     

Predicting post-fire debris flow grain sizes and depositional volumes in the Intermountain West,United States

Post-fire debris flows represent one of the most erosive consequences associated with increasing wildfire severity and investigations into their downstream impacts have been limited. Recent advances have linked existing hydrogeomorphic models to predict potential impacts of post-fire erosion at watershed scales on downstream water resources. Here we address two key limitations in current models: (1) accurate predictions of post-fire debris flow volumes in the absence of triggering storm rainfall intensities and (2) understanding controls on grain sizes produced by post-fire debris flows. We compiled and analysed a novel dataset of depositional volumes and grain size distributions (GSDs) for 59 post-fire debris flows across the Intermountain West (IMW) collected via fieldwork and from the literature. We first evaluated the utility of existing models for post-fire debris flow volume prediction, which were largely developed for Southern California. We then constructed a new post-fire debris flow volume prediction model for the IMW using a combination of Random Forest modelling and regression analysis. We found topography and burn severity to be important variables, and that the percentage of pre-fire soil organic matter was an essential predictor variable. Our model was also capable of predicting debris flow volumes without data for the triggering storm, suggesting that rainfall may be more important as a presence/absence predictor, rather than a scaling variable. We also constructed the first models that predict the median, 16th percentile, and 84th percentile grain sizes, as well as boulder size, produced by post-fire debris flows. These models demonstrate consistent landscape controls on debris flow GSDs that are related to land cover, physical and chemical weathering, and hillslope sediment transport processes. This work advances our ability to predict how post-fire sediment pulses are transported through watersheds. Our models allow for improved pre- and post-fire risk assessments across diverse ranges of watersheds in the IMW.     

GIS-based risk analysis of debris flow： an application in Sichuan, southwest China

Debris flow is a serious geologic hazard in China. It is estimated that nationally debris flows cause up to 2 billion RMB （250 million US$） in damages and 300-600 deaths and injuries annually. To mitigate debris flow hazards, it is necessary to map, model, and identify zones of debris flow hazards and vulnerability as to inform the local people about the potential risk with a geographic information system. This research presents a regional scale case study modeling debris flow risk （hazard and vulnerability） in Sichuan Province, Southwestern China. In this area, 3,290 debris flows have been identified and the spatial-temporal distribution and activity characteristics of them have been documented. Based on the available meteorological data, a Digital Elevation Model with the rate of 1：250,000 and a regional geological map, the 24-hr rainfall threshold （y） for debris flow occurrence is closely related （significant at 99% confidence level） to the index （x） defined using a geology factor （rock hardness： a） and a topographical factor （channel gradient： d） where y = 21 ＋ 10200 / x, in which x = 2.7 × e^a ＋ 1000 × d. The discipline is constructive in developing the rainfall threshold for debris flow activity in remote mountainous areas that lack data. For a given watershed, a four-level debris flow hazard map is developed by comparing the rainfall threshold to the design rainfall intensities with 50-, 20-, and 5-year average recurrence intervals, respectively. The degree of debris flow vulnerability is determined by the watershed socio-economic conditions. A four-class debris flow risk map, at the final phase of the research, is generated by combining debris flow hazards and vulnerability. With the debris flow risk assessment, the Sichuan Province is classified into the slight, moderate, severe and very severe regions, which accounts for 36%, 19%, 20% and 25% of total area respectively.     

Single-grain quartz OSL dating of debris flow deposits from Men Tou Gou,south west Beijing,China

Debris flows in the mountainous regions south west of Beijing, China occur frequently and often result in considerable mass movements with disastrous consequences for human life, infrastructure and agriculture. Obtaining chronological information on such events is important for the prediction of the return frequency of these debris flows, risk assessment and climate change research. In this project, we use quartz single-grain optically stimulated luminescence (OSL) methods to determine the burial ages of five debris flow samples from the Zhai Tang region ∼60 km west of Beijing. OSL characteristics were found to be acceptable despite the low inherent brightness of quartz extracted from these samples. Single-grain thermal transfer was determined to be negligible and beta dose recovery experiments were satisfactory. The quartz single-grain dose distributions strongly indicate that the samples were poorly bleached prior to deposition; relative over-dispersions are larger than 60%. Minimum age modelling indicates that all five samples were deposited within the past few hundred years, indicating that catastrophic debris flows are occurring under the historically-recent land-use pattern.     

Spatial and temporal diversity for debris‐flow meteorological control in subarctic oceanic periglacial environments in Iceland

Slopes in fjord environments of Iceland are prone to debris‐flow initiation, responding to a wide variety of meteorological triggering factors, such as rain on snow, rapid snowmelt, long‐lasting rainfall or intense rainfall. If all fjord regions have similar debris flows with regards to their magnitude, their meteorological control is diverse both in space and in time. Debris flows in Northwest Iceland are triggered mostly by rain‐on‐snow and long‐lasting rainfall, while snowmelt is more characteristic in North Iceland, and rainfall has a clear impact in East Iceland. Most debris‐flow events occur on a single slope, and only a few are recorded at the same time in different regions. Observations of the threshold values underline the diversity of debris‐flow initiation, occurring with huge amounts of sudden water supply as well as with very moderate ones. Copyright © 2007 John Wiley & Sons, Ltd.     

Applying Probability Determination to Refine Landslide-triggering Rainfall Thresholds Using an Empirical “Antecedent Daily Rainfall Model”

—Rainfall-triggered landslides constitute a serious hazard and an important geomorphic process in many parts of the world. Attempts have been made at various scales in a number of countries to investigate triggering conditions in order to identify patterns in behaviour and, ultimately, to define or calculate landslide-triggering rainfall thresholds. This study was carried out in three landslide-prone regions in the North Island of New Zealand. Regional landslide-triggering rainfall thresholds were calculated using an empirical “Antecedent Daily Rainfall Model.” In this model, first introduced by, triggering rainfall conditions are represented by a combination of rainfall occurring in a period before the event (antecedent rainfall) and rainfall on the day of the event. A physically-based decay coefficient is derived for each region from the recessional behaviour of storm hydrographs and is used to produce an index for antecedent rainfall. Statistical techniques are employed to obtain the thresholds which best separate the rainfall conditions associated with landslide occurrence from those of non-occurrence or a given probability of occurrence.The resultant regional models are able to represent the probability of occurrence of landsliding events on the basis of rainfall conditions. The calculated thresholds show regional differences in susceptibility of a given landscape to landslide-triggering rainfall. These differences relate to both the landslide database and the difference of existing physical conditions between the regions.     

Analysing the relation between rainfall characteristics and lahar activity at Mount Pinatubo,Philippines

The eruption of Mount Pinatubo in June 1991 altered the conditions of the surrounding river catchments. Pyroclastic flows and tephra fall were deposited over extensive areas, stripping off the forest cover and burying drainage divides. These recent deposits are very loosely consolidated and generally consist of sand‐sized particles, which commonly mobilize into lahars in response to rainfall of a certain magnitude. Several devastating lahar occurrences have buried settlements covering tens to several hundred square kilometres in a single event. Correlation of storm rainfall intensities and durations with lahar activity as recorded by acoustic flow monitors is used to investigate trends in the initiation conditions for lahar activity. This research confirms that the relationships of rainfall intensity and duration with lahar initiation threshold values are not linear but rather approximate a power relation. Different relations were found for lahar initiation in different years, from 1991 to 1997, as a result of the dynamic changes in hydrologic and geomorphic conditions of the affected catchments. Data from acoustic flow monitors are used to distinguish debris flow and hyperconcentrated flow activity from that of muddy water. Copyright © 2005 John Wiley & Sons, Ltd.     

北京地区泥石流灾害的发育特征及预报方法探讨

通过认真研究北京地区泥石流的发育特征,深入分析了泥石流的形成条件和影响因素,并在此基础上对北京地区泥石流预报方法进行了初步探讨．建立了综合考虑地形地貌、地质条件、土壤类型以及降雨情况等因素的判断公式,并就北京地区泥石流预报方法提出了建议。     

Variability in rainfall threshold for debris flow after the Chi-Chi earthquake in central Taiwan, China

The purpose of this study is to analyze variability in rainfall threshold for debris flow （critical rainfall for debris flow triggering） after the ML 7.3 Chi-Chi earthquake in central Taiwan in 1999. Two study sites with different geological conditions were surveyed in the earthquake area. Streambed surveys were conducted to continuously monitor debris flows between 1999 and 2006. During the 7-year study period, every debris flow event was identified, and the streambed characterized. Results show that the rainfall threshold for debris flow was remarkably lower just after the Chi-Chi Earthquake, but gradually recovered. To date, this rainfall threshold is still lower than the original level prior to the earthquake. This variability in rainfall threshold is closely related to the mount of sediment material in the initiation area of debris flow, which increased rapidly due to landslides resulting from the earthquake. With the increase in sediment material, the rainfall threshold was lowered severely during the first year following the Chi-Chi earthquake. However, heavy rainfalls mobilized the sediment material, causing debris flows and transporting sediment downstream. With the decrease in sediment material, the rainfall threshold recovered gradually over time. Furthermore, debris flows occurred only in the subbasins that had sufficient sediment material to cause significant movement. Hence, these results confirm that the sediment material in the initiation area of debris flow is a crucial component of the rainfall threshold for debris flow.     

Hydrometeorological controls and erosive response of an extreme alpine debris flow

On 29 August, 2003, an intense convective storm system affected the Fella River basin, in the eastern Italian Alps, producing rainfall peaks of approximately 390 mm in 12 h. The storm triggered an unusually large debris flow in the ungauged Rio Cucco basin (0·65 km²), with a volume of approximately 78 000 m³. The analysis of the time evolution of the rainstorm over the basin has been based on rainfall estimates from radar observations and data recorded by a raingauge network. Detailed geomorphological field surveys, carried out both before and after the flood of August 2003, and the application of a distributed hydrological model have enabled assessment of flood response, estimation of erosion volumes and sediment supply to the channel network. The accounts of two eyewitnesses have provided useful elements for reconstructing the time evolution and the flow processes involved in the event. Liquid peak discharge estimates cluster around 20 m³ s^?1 km^?2, placing this event on the flood envelope curve for the eastern Italian Alps. The hydrological analysis has shown that the major controls of the flood response were the exceptional cumulated rainfall amount, required to exceed the large initial losses, and the large rainfall intensities at hourly temporal scales, required to generate high flood response at the considered basin scale. Observations on the deposits accumulated on the alluvial fan indicate that, although the dominant flow process was a debris flow, sheetflood also contributed to fan aggradation and fluvial reworking had an important role in winnowing debris‐flow lobes and redistributing sediment on the fan surface. This points out to the large discharge values during the recession phase of the flood, implying an important role for subsurface flow on runoff generation of this extreme flash flood event. Copyright © 2009 John Wiley & Sons, Ltd.     

Radar rainfall estimation for flash flood forecasting in small urban watersheds

Radar rainfall estimation for flash flood forecasting in small, urban catchments is examined through analyses of radar, rain gage and discharge observations from the 14.3 km² Dead Run drainage basin in Baltimore County, Maryland. The flash flood forecasting problem pushes the envelope of rainfall estimation to time and space scales that are commensurate with the scales at which the fundamental governing laws of land surface processes are derived. Analyses of radar rainfall estimates are based on volume scan WSR-88D reflectivity observations for 36 storms during the period 2003–2005. Gage-radar analyses show large spatial variability of storm total rainfall over the 14.3 km² basin for flash flood producing storms. The ability to capture the detailed spatial variation of rainfall for flash flood producing storms by WSR-88D rainfall estimates varies markedly from event to event. As spatial scale decreases from the 14.3 km² scale of the Dead Run watershed to 1 km² (and the characteristic time scale of flash flood producing rainfall decreases from 1 h to 15 min) the predictability of flash flood response from WSR-88D rainfall estimates decreases sharply. Storm to storm variability of multiplicative bias in storm total rainfall estimates is a dominant element of the error structure of radar rainfall estimates, and it varies systematically over the warm season and with flood magnitude. Analyses of the 7 July 2004 and 28 June 2005 storms illustrate microphysical and dynamical controls on radar estimation error for extreme flash flood producing storms.     

Thresholds for post-wildfire debris flows: Insights from the Pinal Fire,Arizona, USA

Wildfire significantly alters the hydrologic properties of a burned area, leading to increases in overland flow, erosion, and the potential for runoff-generated debris flows. The initiation of debris flows in recently burned areas is well characterized by rainfall intensity-duration (ID) thresholds. However, there is currently a paucity of data quantifying the rainfall intensities required to trigger post-wildfire debris flows, which limits our understanding of how and why rainfall ID thresholds vary in different climatic and geologic settings. In this study, we monitored debris-flow activity following the Pinal Fire in central Arizona, which differs from both a climatic and hydrogeomorphic perspective from other regions in the western United States where ID thresholds for post-wildfire debris flows are well established, namely the Transverse Ranges of southern California. Since the peak rainfall intensity within a rainstorm may exceed the rainfall intensity required to trigger a debris flow, the development of robust rainfall ID thresholds requires knowledge of the timing of debris flows within rainstorms. Existing post-wildfire debris-flow studies in Arizona only constrain the peak rainfall intensity within debris-flow-producing storms, which may far exceed the intensity that actually triggered the observed debris flow. In this study, we used pressure transducers within five burned drainage basins to constrain the timing of debris flows within rainstorms. Rainfall ID thresholds derived here from triggering rainfall intensities are, on average, 22 mm h⁻¹ lower than ID thresholds derived under the assumption that the triggering intensity is equal to the maximum rainfall intensity recorded during a rainstorm. We then use a hydrologic model to demonstrate that the magnitude of the 15-min rainfall ID threshold at the Pinal Fire site is associated with the rainfall intensity required to exceed a recently proposed dimensionless discharge threshold for debris-flow initiation. Model results further suggest that previously observed differences in regional ID thresholds between Arizona and the San Gabriel Mountains of southern California may be attributed, in large part, to differences in the hydraulic properties of burned soils. © 2019 John Wiley & Sons, Ltd.     

Estimation of discharges of water flows and debris floods in a small watershed

Floods in small mountainous watersheds cover a wide spectrum of flow. They can range from clear water flows and hyperconcentrated flows to debris floods and debris flows, and calculation of the peak discharge is crucial for predicting and mitigating such hazards. To determine the optimal approach for discharge estimation, this study compared water flow monitoring hydrographs to investigate the performance of five hydrological models that incorporate different runoff yields and influx calculation methods. Two of the models performed well in simulating the peak discharge, peak time, and total flow volume of the water flood. The ratio (γ) of the monitored debris flood discharge (Q_d) to the simulated water flow discharge (Q_w) was investigated. Qualitatively, γ initially increased with Q_w but then decreased when Q_w exceeded a certain threshold, which corresponded to rainfall of 95 and 120 mm in a 6- and 24-h event with a normal distribution of precipitation, respectively. The decrease might be attributable to a threshold of sediment availability being reached, beyond which increased flow rate is not matched by increased sediment input in the large watershed. Uncertainty of hydrological calculation was evaluated by dividing the catchment into sub-basins and adopting different rainfall time steps as input. The efficiency of using a distributed simulation exhibited marginal improvement potential compared with a lumped simulation. Conversely, the rainfall time step input significantly affected the simulation results by delaying the peak time and decreasing the peak discharge. This research demonstrates the applicability of a discharge estimation method that combines a hydrological water flow simulation and an estimation of γ. The results were verified on the basis of monitored flow densities and videos obtained in two watersheds with areas of 2.34 and 32.4 km².     

Large wood inhibits debris flow runout in forested southeast Alaska

Due to their potentially long runout, debris flows are a major hazard and an important geomorphic process in mountainous environments. Understanding runout is therefore essential to minimize risk in the near-term and interpret the pace and pattern of debris flow erosion and deposition over geomorphic timescales. Many debris flows occur in forested landscapes where they mobilize large volumes of large woody debris (LWD) in addition to sediment, but few studies have quantitatively documented the effects of LWD on runout. Here, we analyze recent and historic debris flows in southeast Alaska, a mountainous, forested system with minimal human alteration. Sixteen debris flows near Sitka triggered on August 18, 2015 or more recently had volumes of 80 to 25 000 m³ and limited mobility compared to a global compilation of similarly-sized debris flows. Their deposits inundated 31% of the planimetric area, and their runout lengths were 48% of that predicted by the global dataset. Depositional slopes were 6°–26°, and mobility index, defined as the ratio of horizontal runout to vertical elevation change, ranged from 1.2 to 3, further indicating low mobility. In the broader southeast Alaskan region consisting of Chichagof and Baranof Islands, remote sensing-based analysis of 1061 historic debris flows showed that mobility index decreased from 2.3–2.5 to 1.4–1.8 as average forest age increased from 0 to 416 years. We therefore interpret that the presence of LWD within a debris flow and standing trees, stumps, and logs in the deposition zone inhibit runout, primarily through granular phenomena such as jamming due to force chains. Calibration of debris flow runout models should therefore incorporate the ecologic as well as geologic setting, and feedbacks between debris flows and vegetation likely control the transport of sediment and organic material through steep, forested catchments over geomorphic time. © 2020 John Wiley & Sons, Ltd.     

Use of the Connectivity of Runoff Model (CRUM) to investigate the influence of storm characteristics on runoff generation and connectivity in semi‐arid areas

Much attention has been given to the surface controls on the generation and transmission of runoff in semi‐arid areas. However, the surface controls form only one part of the system; hence, it is important to consider the effect that the characteristics of the storm event have on the generation of runoff and the transmission of flow across the slope. The impact of storm characteristics has been investigated using the Connectivity of Runoff Model (CRUM). This is a distributed, dynamic hydrology model that considers the hydrological processes relevant to semi‐arid environments at the temporal scale of a single storm event. The key storm characteristics that have been investigated are the storm duration, rainfall intensity, rainfall variability and temporal structure. This has been achieved through the use of a series of defined storm hydrographs and stochastic rainfall. Results show that the temporal fragmentation of high‐intensity rainfall is important for determining the travel distances of overland flow and, hence, the amount of runoff that leaves the slope as discharge. If the high‐intensity rainfall is fragmented, then the runoff infiltrates a short distance downslope. Longer periods of high‐intensity rainfall allow the runoff to travel further and, hence, become discharge. Therefore, storms with similar amounts of high‐intensity rainfall can produce very different amounts of discharge depending on the storm characteristics. The response of the hydrological system to changes in the rainfall characteristics can be explained using a four‐stage model of the runoff generation process. These stages are: (1) all water infiltrating, (2) the surface depression store filling or emptying without runoff occurring, (3) the generation and transmission of runoff and (4) the transmission of runoff without new runoff being generated. The storm event will move the system between the four stages and the nature of the rainfall required to move between the stages is determined by the surface characteristics. This research shows the importance of the variable‐intensity rainfall when modelling semi‐arid runoff generation. The amount of discharge may be greater or less than the amount that would have been produced if constant rainfall intensity is used in the model. Copyright © 2006 John Wiley & Sons, Ltd.     

Exploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north‐eastern Sicily,Italy)

This study aims at evaluating the performance of the Maximum Entropy method in assessing landslide susceptibility, exploiting topographic and multispectral remote sensing predictors. We selected the catchment of the Giampilieri stream, which is located in the north‐eastern sector of Sicily (southern Italy), as test site. On 1 October 2009, a storm rainfall triggered in this area hundreds of debris flow/avalanche phenomena causing extensive economical damage and loss of life. Within this area a presence‐only‐based statistical method was applied to obtain susceptibility models capable of distinguishing future activation sites of debris flow and debris slide, which where the main source of failure mechanisms for flow or avalanche type propagation. The set of predictors used in this experiment comprised primary and secondary topographic attributes, derived by processing a high resolution digital elevation model, CORINE land cover data and a set of vegetation and mineral indices obtained by processing multispectral ASTER images. All the selected data sources are dated before the disaster. A spatially random partition technique was adopted for validation, generating 50 replicates for each of the two considered movement typologies in order to assess accuracy, precision and reliability of the models. The debris slide and debris flow susceptibility models produced high performances with the first type being the best fit. The evaluation of the probability estimates around the mean value for each mapped pixel shows an inverted relation, with the most robust models corresponding to the debris flows. With respect to the role of each predictor within the modelling phase, debris flows appeared to be primarily controlled by topographic attributes whilst the debris slides were better explained by remotely sensed derived indices, particularly by the occurrence of previous wildfires across the slope. The overall excellent performances of the two models suggest promising perspectives for the application of presence‐only methods and remote sensing derived predictors. Copyright © 2016 John Wiley & Sons, Ltd.     

Investigating the impact of the Chi‐Chi earthquake on the occurrence of debris flows using artificial neural networks

Debris flows have caused enormous losses of property and human life in Taiwan during the last two decades. An efficient and reliable method for predicting the occurrence of debris flows is required. The major goal of this study is to explore the impact of the Chi‐Chi earthquake on the occurrence of debris flows by applying the artificial neural network (ANN) that takes both hydrological and geomorphologic influences into account. The Chen‐Yu‐Lan River watershed, which is located in central Taiwan, is chosen for evaluating the critical rainfall triggering debris flows. A total of 1151 data sets were collected for calibrating model parameters with two training strategies. Significant differences before and after the earthquake have been found: (1) The size of landslide area is proportioned to the occurrence of debris flows; (2) the amount of critical rainfall required for triggering debris flows has reduced significantly, about half of the original critical rainfall in the study case; and (3) the frequency of the occurrence of debris flows is largely increased. The overall accuracy of model prediction in testing phase has reached 96·5%; moreover, the accuracy of occurrence prediction is largely increased from 24 to 80% as the network trained with data from before the Chi‐Chi earthquake sets and with data from the lumped before and after the earthquake sets. The results demonstrated that the ANN is capable of learning the complex mechanism of debris flows and producing satisfactory predictions. Copyright © 2009 John Wiley & Sons, Ltd.     

A comparison of gauge and radar precipitation data for simulating an extreme hydrological event in the Severn Uplands,UK

This paper provides a comparison of gauge and radar precipitation data sources during an extreme hydrological event. November–December 2006 was selected as a time period of intense rainfall and large river flows for the Severn Uplands, an upland catchment in the United Kingdom. A comparison between gauge and radar precipitation time‐series records for the event indicated discrepancies between data sources, particularly in areas of higher elevation. The HEC‐HMS rainfall‐runoff model was selected to assess the accuracy of the precipitation to simulate river flows for the extreme event. Gauge, radar and gauge‐corrected radar rainfall were used as model inputs. Universal cokriging was used to geostatistically interpolate gauge data with radar and elevation data as covariates. This interpolated layer was used to calculate the mean‐field bias and correct the radar composites. Results indicated that gauge‐ and gauge‐corrected radar‐driven models replicated flows adequately for the extreme event. Gauge‐corrected flow predictions produced an increase in flow prediction accuracy when compared with the raw radar, yet predictions were comparative in accuracy to those using the interpolated gauge network. Subsequent investigations suggested this was due to an adequate spatial and temporal resolution of the precipitation gauge network within the Severn Uplands. Results suggested that the six rain gauges could adequately represent precipitation variability of the Severn Uplands to predict flows at an approximately equal accuracy to that obtained by radar. Temporally, radar produced an increase in flow prediction accuracy in mountainous reaches once the gauge time step was in excessive of an hourly interval. Copyright © 2010 John Wiley & Sons, Ltd.     

Sensitivity of the Weather Research and Forecasting (WRF) model to downscaling ratios and storm types in rainfall simulation

Accurate information of rainfall is needed for sustainable water management and more reliable flood forecasting. The advances in mesoscale numerical weather modelling and modern computing technologies make it possible to provide rainfall simulations and forecasts at increasingly higher resolutions in space and time. However, being one of the most difficult variables to be modelled, the quality of the rainfall products from the numerical weather model remains unsatisfactory for hydrological applications. In this study, the sensitivity of the Weather Research and Forecasting (WRF) model is investigated using different domain settings and various storm types to improve the model performance of rainfall simulation. Eight 24‐h storm events are selected from the Brue catchment, southwest England, with different spatial and temporal distributions of the rainfall intensity. Five domain configuration scenarios designed with gradually changing downscaling ratios are used to run the WRF model with the ECMWF 40‐year reanalysis data for the periods of the eight events. A two‐dimensional verification scheme is proposed to evaluate the amounts and distributions of simulated rainfall in both spatial and temporal dimensions. The verification scheme consists of both categorical and continuous indices for a first‐level assessment and a more quantitative evaluation of the simulated rainfall. The results reveal a general improvement of the model performance as we downscale from the outermost to the innermost domain. Moderate downscaling ratios of 1:7, 1:5 and 1:3 are found to perform better with the WRF model in giving more reasonable results than smaller ratios. For the sensitivity study on different storm types, the model shows the best performance in reproducing the storm events with spatial and temporal evenness of the observed rainfall, whereas the type of events with highly concentrated rainfall in space and time are found to be the trickiest case for WRF to handle. Finally, the efficiencies of several variability indices are verified in categorising the storm events on the basis of the two‐dimensional rainfall evenness, which could provide a more quantitative way for the event classification that facilitates further studies. It is important that similar studies with various storm events are carried out in other catchments with different geographic and climatic conditions, so that more general error patterns can be found and further improvements can be made to the rainfall products from mesoscale numerical weather models. Copyright © 2011 John Wiley & Sons, Ltd.     

Multi-decadal changes in the relationships between rainfall characteristics and debris-flow occurrences in response to gully evolution after the 1990–1995 Mount Unzen eruptions

Explosive volcanic eruptions can cause long-term landscape change, leading to increased sediment discharge that continues after the cessation of the eruptions. During the period 1990–1995, eruptions of Mount Unzen, Japan, generated large amounts of pyroclastic material, resulting in 57 debris-flow events during 1991–2018. To investigate changes in the relationships between rainfall characteristics and debris-flow occurrence, we conducted the following: geometric analysis of two gullies (i.e., debris-flow initiation zones) using LiDAR (light detection and ranging)-generated 1 m DEMs (digital elevation models); rainfall analysis, based on the relationship between rainfall duration and mean intensity (i.e., considering the intensity–duration, or ID, threshold); and debris-flow monitoring during 2016–2018. Since 1991, rainfall runoff has caused erosion of the supplied pyroclastic material, generating a channel network consisting of incised gullies. With sufficient rainfall, debris flows formed, accompanied by further gully erosion; this resulted in both vertical and lateral adjustments of the cross-sectional geometry. In the two decades since the eruptions ceased, readily mobilized pyroclastic material has become scarce as the gullies have adjusted to local hydrographic conditions. At the same time, the infiltration capacity of the volcanic flank has increased, reducing the capacity for overland flow. As a result, since 2000, rainfall events with intensities above the ID threshold have occurred; however, the lack of sediment supplied by the gullies appears to have hindered the occurrence and development of debris flows. This suggests that debris flows in volcanically perturbed landscapes may occur at lower rainfall thresholds as long as the corresponding upland channels are evolving as a result of intense overland flow. However, as such channels evolve towards equilibrium geometries, the frequency of debris flows decreases in response to the reduction in sediment availability.