Projecting Spring Consecutive Rainfall Events in the Three Gorges Reservoir Based on Triple-Nested Dynamical Downscaling

Spring consecutive rainfall events(CREs) are key triggers of geological hazards in the Three Gorges Reservoir area(TGR), China. However, previous projections of CREs based on the direct outputs of global climate models(GCMs) are subject to considerable uncertainties, largely caused by their coarse resolution. This study applies a triple-nested WRF(Weather Research and Forecasting) model dynamical downscaling, driven by a GCM, MIROC6(Model for Interdisciplinary Research on Climate, version 6), to improve the historical simulation and reduce the uncertainties in the future projection of CREs in the TGR. Results indicate that WRF has better performances in reproducing the observed rainfall in terms of the daily probability distribution, monthly evolution and duration of rainfall events, demonstrating the ability of WRF in simulating CREs. Thus, the triple-nested WRF is applied to project the future changes of CREs under the middle-of-the-road and fossil-fueled development scenarios. It is indicated that light and moderate rainfall and the duration of continuous rainfall spells will decrease in the TGR, leading to a decrease in the frequency of CREs. Meanwhile, the duration, rainfall amount, and intensity of CREs is projected to regional increase in the central-west TGR. These results are inconsistent with the raw projection of MIROC6. Observational diagnosis implies that CREs are mainly contributed by the vertical moisture advection. Such a synoptic contribution is captured well by WRF, which is not the case in MIROC6,indicating larger uncertainties in the CREs projected by MIROC6.

The Inter-Annual Variability of Rainfall Onset and Its Implication on Crop Planting in Selected East Africa Countries

The inter-annual variability of rainfall onset and crop replanting in East Africa (EA) was assessed using daily estimated rainfall data from climate hazard group infrared precipitation (CHIRPS Ver2.0) and monthly Sea Surface Temperature (SST) indices [Indian Ocean Dipole (IOD) and El-Ni?o Southern Oscillation (ENSO) at NINO3.4 region] from the National Center for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR). The data covered a period of 40 years from1981 to 2020. The methods of cumulative of daily mean rainfall, percentage of onset date departure (PODD), Mann-Kendall (MK) trend test, student t-test, and correlation were applied in the analysis. The results showed that early onset with dry spell (WDS) consideration frequently occurs in Uganda between the first and second dekads of September, while late rainfall onset WDS occurs in the first and second dekads of December over central and Northern Kenya as well as in the Northeastern highlands, parts of the northern coast and unimodal regions in Tanzania. Rainfall onset with no dry spell (WnDS) portrayed an average of 10 days before the occurrence of true onset WDS, with maximum onset departure days (ODD) above 30 days across the Rift Valley area in Kenya and the Northeastern highlands in Tanzania. The high chance of minimum ODD is seen over entire Uganda and the area around Lake Victoria. However, few regions, such as Nakuru (Kenya) Gulu and Kibale (Uganda), and Gitega (Burundi), revealed a slight positive linear trend while others showed negative trend. Significant positive patterns for correlation between onset WDS and SST indices (IOD and NINO 3.4) were discovered in Northern and Northeastern Kenya, as well as areas along the Indian Ocean (over Tanzania’s Northern Coast). Inter-annual relationship between onset dates WDS and IOD (NINO3.4) indices exhibits a high correlation coefficient r = 0.23 (r = 0.48) in Uganda and r = 0.44 (r = 0.36) in Kenya. On the other hand, a negative correlation was revealed over Burundi and Tanzania (over a unimodal region). A high percentage of PODD was observed, ranging from 40% to 70% over the Rift Valley in Kenya and at the Northeastern highlands in Tanzania. However, a strong PODD above 70% was observed over Tanga and the Northern Pwani Region in Tanzania. These findings will help farmers to understand the appropriate time for crop planting, as well as help other socio-economic activities that strongly depend on rainfall.

Detecting Climate Change Trend, Size, and Change Point Date on Annual Maximum Time Series Rainfall Data for Warri, Nigeria

The study focused on the detection of indicators of climate change in 24-hourly annual maximum series (AMS) rainfall data collected for 36 years (1982-2017) for Warri Township, using different statistical methods yielded a statistically insignificant positive mild trend. The IMD and MCIMD downscaled model’s time series data respectively produced MK statistics varying from 1.403 to 1.4729, and 1.403 to 1.463 which were less than the critical Z-value of 1.96. Also, the slope magnitude obtained showed a mild increasing trend in variation from 0.0189 to 0.3713, and 0.0175 to 0.5426, with the rate of change in rainfall intensity at 24 hours duration as 0.4536 and 0.42 mm/hr.year (4.536 and 4.2 mm/decade) for the IMD and the MCIMD time series data, respectively. The trend change point date occurred in the year 2000 from the distribution-free CUSUM test with the trend maintaining a significant and steady increase from 2010 to 2015. Thus, this study established the existence of a trend, which is an indication of a changing climate, and satisfied the condition for rainfall Non-stationary intensity-duration-frequency (NS-IDF) modeling required for infrastructural design for combating flooding events.

Evaluation of rainfall threshold models for debris flow initiation in the Jiangjia Gully,Yunnan Province,China

Systematically determining the discriminatory power of various rainfall properties and their combinations in identifying debris flow occurrence is crucial for early warning systems.In this study,we evaluated the discriminatory power of different univariate and multivariate rainfall threshold models in identifying triggering conditions of debris flow in the Jiangjia Gully,Yunnan Province,China.The univariate models used single rainfall properties as indicators,including total rainfall(R_(tot)),rainfall duration(D),mean intensity(I_(mean)),absolute energy(Eabs),storm kinetic energy(E_(s)),antecedent rainfall(R_(a)),and maximum rainfall intensity over various durations(I_(max_dur)).The evaluation reveals that the I_(max_dur)and Eabs models have the best performance,followed by the E_(s),R_(tot),and I_(mean)models,while the D and R_(a)models have poor performances.Specifically,the I_(max_dur)model has the highest performance metrics at a 40-min duration.We used logistic regression to combine at least two rainfall properties to establish multivariate threshold models.The results show that adding D or R_(a)to the models dominated by Eabs,E_(s),R_(tot),or I_(mean)generally improve their performances,specifically when D is combined with I_(mean)or when R_(a)is combined with Eabs or E_(s).Including R_(a)in the I_(max_dur)model,it performs better than the univariate I_(max_dur)model.A power-law relationship between I_(max_dur)and R_(a)or between Eabs and R_(a)has better performance than the traditional I_(mean)–D model,while the performance of the E_(s)–R_(a)model is moderate.Our evaluation reemphasizes the important role of the maximum intensity over short durations in debris flow occurrence.It also highlights the importance of systematically investigating the role of R_(a)in establishing rainfall thresholds for triggering debris flow.Given the regional variations in rainfall patterns worldwide,it is necessary to evaluate the findings of this study across diverse watersheds.

Spatiotemporal Characteristics of Rainfall over Different Terrain Features in the Middle Reaches of the Yangtze River Basin during the Warm Seasons of 2016–20

Based on hourly rain gauge data during May–September of 2016–20,we analyze the spatiotemporal distributions of total rainfall(TR)and short-duration heavy rainfall(SDHR;hourly rainfall≥20 mm)and their diurnal variations over the middle reaches of the Yangtze River basin.For all three types of terrain(i.e.,mountain,foothill,and plain),the amount of TR and SDHR both maximize in June/July,and the contribution of SDHR to TR(CST)peaks in August(amount:23%;frequency:1.74%).Foothill rainfall is characterized by a high TR amount and a high CST(in amount);mountain rainfall is characterized by a high TR frequency but a small CST(in amount);and plain rainfall shows a low TR amount and frequency,but a high CST(in amount).Overall,stations with high TR(amount and frequency)are mainly located over the mountains and in the foothills,while those with high SDHR(amount and frequency)are mainly concentrated in the foothills and plains close to mountainous areas.For all three types of terrain,the diurnal variations of both TR and SDHR exhibit a double peak(weak early morning and strong late afternoon)and a phase shift from the early-morning peak to the late-afternoon peak from May to August.Around the late-afternoon peak,the amount of TR and SDHR in the foothills is larger than over the mountains and plains.The TR intensity in the foothills increases significantly from midnight to afternoon,suggesting that thermal instability may play an important role in this process.

Comparative Analysis of Climatic Change Trend and Change-Point Analysis for Long-Term Daily Rainfall Annual Maximum Time Series Data in Four Gauging Stations in Niger Delta

The aim of this study is to establish the prevailing conditions of changing climatic trends and change point dates in four selected meteorological stations of Uyo, Benin, Port Harcourt, and Warri in the Niger Delta region of Nigeria. Using daily or 24-hourly annual maximum series (AMS) data with the Indian Meteorological Department (IMD) and the modified Chowdury Indian Meteorological Department (MCIMD) models were adopted to downscale the time series data. Mann-Kendall (MK) trend and Sen’s Slope Estimator (SSE) test showed a statistically significant trend for Uyo and Benin, while Port Harcourt and Warri showed mild trends. The Sen’s Slope magnitude and variation rate were 21.6, 10.8, 6.00 and 4.4 mm/decade, respectively. The trend change-point analysis showed the initial rainfall change-point dates as 2002, 2005, 1988, and 2000 for Uyo, Benin, Port Harcourt, and Warri, respectively. These prove positive changing climatic conditions for rainfall in the study area. Erosion and flood control facilities analysis and design in the Niger Delta will require the application of Non-stationary IDF modelling.

Assessment of Seasonal Rainfall Prediction in Ethiopia: Evaluating a Dynamic Recurrent Neural Network to Downscale ECMWF-SEAS5 Rainfall

Seasonal rainfall plays a vital role in both environmental dynamics and decision-making for rainfed agriculture in Ethiopia, a country often impacted by extreme climate events such as drought and flooding. Predicting the onset of the rainy season and providing localized rainfall forecasts for Ethiopia is challenging due to the changing spatiotemporal patterns and the country's rugged topography. The Climate Hazards Group Infra Red Precipitation with Station Data(CHIRPS), ERA5-Land total precipitation and temperature data are used from 1981–2022 to predict spatial rainfall by applying an artificial neural network(ANN). The recurrent neural network(RNN) is a nonlinear autoregressive network with exogenous input(NARX), which includes feed-forward connections and multiple network layers, employing the Levenberg Marquart algorithm. This method is applied to downscale data from the European Centre for Medium-range Weather Forecasts fifth-generation seasonal forecast system(ECMWF-SEAS5) and the Euro-Mediterranean Centre for Climate Change(CMCC) to the specific locations of rainfall stations in Ethiopia for the period 1980–2020. Across the stations, the results of NARX exhibit strong associations and reduced errors. The statistical results indicate that, except for the southwestern Ethiopian highlands, the downscaled monthly precipitation data exhibits high skill scores compared to the station records, demonstrating the effectiveness of the NARX approach for predicting local seasonal rainfall in Ethiopia's complex terrain. In addition to this spatial ANN of the summer season precipitation, temperature, as well as the combination of these two variables, show promising results.

Comparison of Adaptive Simulation Observation Experiments of the Heavy Rainfall in South China and Sichuan Basin

This study examines the effectiveness of adaptive observation experiments using the ensemble transformation sensitivity(ETS) method to improve precipitation forecasts during heavy rainfall events in South China and the Sichuan Basin. High-resolution numerical models are employed to simulate adaptive observations. By identifying the sensitive areas of key weather system positions 42 hours before heavy rainfall events, the adaptive observations improve the prediction of jet streams, strong winds, and shear lines, which are essential for accurate heavy rainfall forecasting. This improvement is reflected in both the precipitation structure and location accuracy within the verification region. In South China, targeted observations enhance rainfall predictions by improving water vapor transport. In the Sichuan Basin, adaptive observations refine water vapor transport and adjust vortex dynamics. This research highlights the importance of accurately predicting shear lines and jet streams for forecasting heavy rainfall in these areas. Overall, this study found that adaptive observation enhances the precipitation forecast skills of the structure and location for heavy rainfall in South China and the Sichuan Basin, emphasizing their potential utility in operational numerical weather prediction.

The Influence of Variable (Monsoon) Rainfall on Sedimentation in the Roaches Grit and Other Upper Carboniferous Delta Sequences in the UK Pennine Basin

The Roaches Grit in the UK Pennine Basin was a complex deep water deltaic sequence deposited during the Late Carboniferous glacial period. The channels of the upper part of the Roaches Grit, deposited towards the end of the cyclothem after the eustatic minimum, contain evidence for very high seasonal discharges related to strong monsoon rainfall in the catchment areas. In some channels, intense turbulence near the delta front, led to knick point recession and deep incision. These channels were filled with sediments during reduced discharge, including very large sets of cross-bedding up to 16 m thick. Channels were short-lived with frequent avulsions. Over time slightly lower discharges formed laterally migrating channels dominated by bar forms. Different discharge-controlled processes operated on the reactivated delta slope. Incised channels generated turbidity currents during floods which transported sediments directly into the basin far from the delta. Migrating channels built mouth bars;resedimentation during floods formed density currents which then deposited sediment on the lower parts of the slope.

Annual variation of adult survival of a south-temperate House Wren population in Argentina

Identifying factors affecting the survival of individuals is essential for understanding the evolution of life-history traits and population dynamics.Despite numerous studies on this subject in north-temperate environments,there is a lack of equivalent studies at similar latitudes in the south.Here,we used a 14-year dataset of capture,banding,and resighting to estimate the annual variation in the apparent adult survival probability of a south-temperate population of House Wrens(Troglodytes aedon bonariae).We evaluated temporal variation in sur-vival and the effect of environmental(climatic)and demographic variables(adult abundance,total number of fledglings produced during each breeding season)on survival estimators.We found that the probability of adult survival decreased as the abundance of breeding adults increased.This density-dependent effect could be related to the resident lifestyle of southern House Wrens,which could determine an intense competition for territories and resources that ultimately would affect their survival.

Effects of Initial and Boundary Conditions on Heavy Rainfall Simulation over the Yellow Sea and the Korean Peninsula:Comparison of ECMWF and NCEP Analysis Data Effects and Verification with Dropsonde Observation

This study evaluated the simulation performance of mesoscale convective system(MCS)-induced precipitation,focusing on three selected cases that originated from the Yellow Sea and propagated toward the Korean Peninsula.The evaluation was conducted for the European Centre for Medium-Range Weather Forecasts(ECMWF)and National Centers for Environmental Prediction(NCEP)analysis data,as well as the simulation result using them as initial and lateral boundary conditions for the Weather Research and Forecasting model.Particularly,temperature and humidity profiles from 3D dropsonde observations from the National Center for Meteorological Science of the Korea Meteorological Administration served as validation data.Results showed that the ECMWF analysis consistently had smaller errors compared to the NCEP analysis,which exhibited a cold and dry bias in the lower levels below 850 hPa.The model,in terms of the precipitation simulations,particularly for high-intensity precipitation over the Yellow Sea,demonstrated higher accuracy when applying ECMWF analysis data as the initial condition.This advantage also positively influenced the simulation of rainfall events on the Korean Peninsula by reasonably inducing convective-favorable thermodynamic features(i.e.,warm and humid lower-level atmosphere)over the Yellow Sea.In conclusion,this study provides specific information about two global analysis datasets and their impacts on MCS-induced heavy rainfall simulation by employing dropsonde observation data.Furthermore,it suggests the need to enhance the initial field for MCS-induced heavy rainfall simulation and the applicability of assimilating dropsonde data for this purpose in the future.

Three-dimensional numerical analysis of plant-soil hydraulic interactions on pore water pressure of vegetated slope under different rainfall patterns

Understanding the pore water pressure distribution in unsaturated soil is crucial in predicting shallow landslides triggered by rainfall,mainly when dealing with different temporal patterns of rainfall intensity.However,the hydrological response of vegetated slopes,especially three-dimensional(3D)slopes covered with shrubs,under different rainfall patterns remains unclear and requires further investigation.To address this issue,this study adopts a novel 3D numerical model for simulating hydraulic interactions between the root system of the shrub and the surrounding soil.Three series of numerical parametric studies are conducted to investigate the influences of slope inclination,rainfall pattern and rainfall duration.Four rainfall patterns(advanced,bimodal,delayed,and uniform)and two rainfall durations(4-h intense and 168-h mild rainfall)are considered to study the hydrological response of the slope.The computed results show that 17%higher transpiration-induced suction is found for a steeper slope,which remains even after a short,intense rainfall with a 100-year return period.The extreme rainfalls with advanced(PA),bimodal(PB)and uniform(PU)rainfall patterns need to be considered for the short rainfall duration(4 h),while the delayed(PD)and uniform(PU)rainfall patterns are highly recommended for long rainfall durations(168 h).The presence of plants can improve slope stability markedly under extreme rainfall with a short duration(4 h).For the long duration(168 h),the benefit of the plant in preserving pore-water pressure(PWP)and slope stability may not be sufficient.

Occurrence of Extreme Rainfall and Flood Risks in Yopougon, Abidjan, Southeast Côte d’Ivoire from 1971 to 2022

Yopougon, located in the western part of the Autonomous District of Abidjan, is the most heavily populated municipality in Côte d’Ivoire. However, this area is prone to floods and landslides during the rainy season. The study aims to assess recent flood risks in the municipality of Yopougon of the Autonomous District of Abidjan. To achieve this objective, the study analyzed two types of data: daily rainfall from 1971 to 2022 and parameters derived from a Numerical Field and Altitude Model (NFAM). The study examined six rainfall parameters using statistical analysis and combined land use maps obtained from the NFAM of Yopougon. The results indicated that, in 67% of cases, extreme rainfall occurred mainly between week 3 of May and week 1 of July. The peak of extreme rainfall was observed in week 2 of June with 15% of cases. These are critical periods of flood risks in the Autonomous District of Abidjan, especially in Yopougon. In addition, there was variability of rainfall parameters in the Autonomous District of Abidjan. This was characterized by a drop of annual and seasonal rainfall, and an increase of numbers of rainy days. Flood risks in Yopougon are, therefore, due to the regular occurrence of rainy events. Recent floods in Yopougon were caused by normal rains ranging from 55 millimeters (mm) to 153 mm with a return period of less than five years. Abnormal heavy rains of a case study on June 20-21, 2022 in Yopougon were detected by outputs global climate models. Areas of very high risk of flood covered 18% of Yopougon, while 31% were at high risk. Climate information from this study can assist authorities to take in advance adaptation and management measures.

Local Torrential Rainfall Event within a Mei-Yu Season Mesoscale Convective System:Importance of Back-Building Processes

An extreme rainfall event occurred over Hangzhou,China,during the afternoon hours on 24 June 2013.This event occurred under suitable synoptic conditions and the maximum 4-h cumulative rainfall amount was over 150 mm.This rainfall event had two major rainbands.One was caused by a quasi-stationary convective line,and the other by a backbuilding convective line related to the interaction of the outflow boundary from the first rainband and an existing low-level mesoscale convergence line associated with a mei-yu frontal system.The rainfall event lasted 4 h,while the back-building process occurred in 2 h when the extreme rainfall center formed.So far,few studies have examined the back-building processes in the mei-yu season that are caused by the interaction of a mesoscale convergence line and a convective cold pool.The two rainbands are successfully reproduced by the Weather Research and Forecasting(WRF)model with fourlevel,two-way interactive nesting.In the model,new cells repeatedly occur at the west side of older cells,and the backbuilding process occurs in an environment with large CAPE,a low LFC,and plenty of water vapor.Outflows from older cells enhance the low-level convergence that forces new cells.High precipitation efficiency of the back-building training cells leads to accumulated precipitation of over 150 mm.Sensitivity experiments without evaporation of rainwater show that the convective cold pool plays an important role in the organization of the back-building process in the current extreme precipitation case.

Determination of the critical rainfall of runoff-initiated debris flows by the perspective of physical mechanics and Shields stress

The critical rainfall of runoff-initiated debris flows is utmost importance for local early hazard forecasting.This paper presents research on the critical rainfall of runoff-initiated debris flows through comparisons between slope gradients and three key factors,including topographic contributing area,dimensionless discharge,and Shields stress.The rainfall amount was estimated by utilizing in-situ rainfall records and a slope-dependent Shields stress model was created.The created model can predict critical Shields stress more accurately than the other two models.Furthermore,a new dimensionless discharge equation was proposed based on the corresponding discharge-gradient datasets.The new equation,along with factors such as contributing area above bed failure sites,channel width,and mean diameter of debris flow deposits,predicts a smaller rainfall amount than the in-situ measured records.Although the slope-dependent Shields stress model performs well and the estimated rainfall amount is lower than the in-situ records,the sediment initiation in the experiments falls within sheet flow regime due to a large Shields stress.Therefore,further sediment initiation experiments at a steeper slope range are expected in the future to ensure that the sediment transport belongs to mass failure regime characterized by a low level of Shields stress.Finally,a more accurate hazard forecast on the runoff-initiated debris flow holds promise when the corresponding critical slope-dependent dimensionless discharge of no motion,fluvial sediment transport,mass flow regime,and sheet flow regime are considered.

Stability analysis of loose accumulation slopes under rainfall:case study of a high‑speed railway in Southwest China

The high and steep slopes along a high-speed railway in the mountainous area of Southwest China are mostly composed of loose accumulations of debris with large internal pores and poor stability,which can easily induce adverse geological disasters under rainfall conditions.To ensure the smooth construction of the high-speed railway and the subsequent safe operation,it is necessary to master the stability evolution process of the loose accumulation slope under rainfall.This article simulates rainfall using the finite element analysis software’s hydromechanical coupling module.The slope stability under various rainfall situations is calculated and analysed based on the strength reduction method.To validate the simulation results,a field monitoring system is established to study the deformation characteristics of the slope under rainfall.The results show that rainfall duration is the key factor affecting slope stability.Given a constant amount of rainfall,the stability of the slope decreases with increasing duration of rainfall.Moreover,when the amount and duration of rainfall are constant,continuous rainfall has a greater impact on slope stability than intermittent rainfall.The setting of the field retaining structures has a significant role in improving slope stability.The field monitoring data show that the slope is in the initial deformation stage and has good stability,which verifies the rationality of the numerical simulation method.The research results can provide some references for understanding the influence of rainfall on the stability of loose accumulation slopes along high-speed railways and establishing a monitoring system.

The changes in the annual distribution of mountain runoff during the period of 1965-2018 in Hexi Corridor,Northwest China

The annual distribution characteristics of river runoff in arid regions have significant implications for water resource stability and management.Based on the mountain runoff data from 1965 to 2018,this study examines the annual change characteristics of monthly runoff of the Shiyang River Basin,Heihe River Basin,and Shule River Basin in the Hexi Corridor,Northwest China.Many indexes are used and analyzed,including the coefficient of variance,the complete regulation coefficient,the concentration degree and concentration period,the magnitude of change,the skewness coefficient,and the kurtosis coefficient of the annual distribution curves.The results reveal the following:(1)The inhomogeneity of annual runoff distribution in the Taolai River and the rivers to the west of it,except the Shiyou River,show an increasing trend.Conversely,the inhomogeneity of the rivers to the east of the Taolai River generally show a downward trend,but the coefficient of variance value is still very high.(2)In the Shiyang River Basin,the annual distribution of the concentration period is characterized by a relatively discrete pattern.Conversely,the Heihe River Basin exhibits a relatively concentrated pattern,and the distribution pattern of the Shule River Basin is quite different.Notably,all concentration periods in the three basins have shifted backward after the 2000s.(3)The Shiyang River Basin exhibits disordered annual distribution curves of runoff in different years.In contrast,the Heihe River Basin presents a typical‘single-peak’pattern with a prominent right-skewed.The Shule River Basin has regular distribution curves,with a gradually significant‘double-peak’pattern from east to west.Overall,there has been a slight change in runoff in the Shiyang River Basin,while the Heihe River Basin and Shule River Basin have experienced significant increases in runoff.The annual distribution curves of runoff in the Liyuan River and the rivers to the east of it exhibit a gentle peak pattern,and the appearance probability of extreme runoff during the year is low.Conversely,the rivers to the west of the Liyuan River,excluding the Danghe River,display a sharp peak and thick tail pattern,indicating that the appearance probability of extreme runoff during the year is high.These findings have practical implications for the planning and management of water resources in the Hexi Corridor.Moreover,they provide a solid foundation for predicting future changes in regional water resources.

Characterizing Rainfall of the Great Kei River Catchment, Eastern Cape Province, South Africa

This study seeks to understand long-term changes of rainfall for the Great Kei River catchment (GKRc) in South Africa for water resources management and planning. Monthly and annual rainfall time series data from 1950 to 2017 for 11 rainfall gauging stations are analyzed using various statistical methods. Data obtained from South African Weather Services (SAWS) was quality controlled to enable the use of Mann-Kendall (MK), Theil Sen’s method, Precipitation Concentration Index (PCI), among others to characterise rainfall. Rainfall in the catchment is seasonal (particularly wet in spring and summer) and highly variable with a PCI of 17.2. Years which received rain above and below the mean inter-annually were 46% and 54%, respectively. Seasonality trends also confirm that the GKRc has been progressively receiving less rainfall since 1950, especially in the autumn. The methods are novel in understanding historical and existing trends, variability and characteristics that control freshwater availability in this catchment.

Exploring the groundwater response to rainfall in a translational landslide using the master recession curve method and cross-correlation function

Rainfall is a common trigger for landslide reactivation,as it raises groundwater levels and reduces bedrock or soil shear resistance.This study focuses on the Kualiangzi landslide in the southern region of Sichuan Province,China.Real-time monitoring of groundwater levels and rainfall from July 2013 to September 2016 is analyzed.Groundwater table increments,considering groundwater drainage rate,were calculated using the water-table fluctuation and master recession curve method and the response time of the groundwater table to rainfall events was estimated using the cross-correlation function.Results reveal that groundwater level declines from tension troughs to landslide fronts in the rainy season,with a significant positive correlation between the groundwater level in the tension trough and landslide surface displacement.Evaluated spring elevations for groundwater discharge range from 410 m to 440 m,which is in agreement with the actual spring elevations(390-423 m).Lag times of groundwater response to rainfall decreases with cumulative rainfall of the rainy periods.In the middle part of the landslide,two responses between rainfall and groundwater levels indicate two water movement pathways:Vertical cracks or fractures resulting from the slow landslide movement,and matrix pore space in unconsolidated sediment.Variations in peak values of the cross-correlation function suggest early dominance of the uniform matrix flow and later dominance of preferential flow during the rainy period.

Rainfall Dynamics and Landslides in Urban Areas of Gabon: The Case of Libreville-Est (Gabon)

Due to its abundant rainfall, the city of Libreville, which concentrates more than half of Gabon’s population, is frequently confronted with the impacts of natural disasters such as floods and landslides. This study attempts to identify the complex relationships between the dynamics of land use and the role of rainfall in the occurrence of landslides. On the one hand, it uses statistics on landslides compiled from information taken from general news bulletins and, on the other, daily rainfall data obtained from the National Meteorological Department. The study revealed that the Libreville East sector, dominated by Mount Nkol Ogoum, one of Libreville’s most prominent landforms, is affected by a land-use dynamic in which human settlement has been progressing for some thirty years, to the detriment of the original vegetation which, among other things, helped to stabilise the soil on the hillsides and the marshy areas at the foot of the slopes. The result is not only an uncontrolled occupation of the land, but also a major landslide every two years in this part of the city, causing significant loss of life and property. However, an analysis of the time series shows little rainfall variability, marked in particular by a predominance of negative anomalies, and the occurrence of a few exceptional daily rainfall peaks. Similarly, the period from 20 October to 20 November, which receives the most rainfall, also appears to be the most conducive to landslides.