Reconstruction of a realistic rainfall field for extreme events happened in mountain area

<p>In the field of hydrogeological risk, rainfalls represent the most important triggering factor for superficial terrain failures such as shallow landslides, soil slips and debris flow. The availability of local rain gauges measurements is fundamental for defining the cause-effect relationship for predicting failure scenarios. Unfortunately, these hydrogeological phenomena are typical triggered over mountains regions where the density of the ground-based meteorological network is poor, and the local effects caused by mountains topography can change dramatically the spatial and temporal distribution of rainfall. Therefore, trying to reconstruct a representative rainfall field across mountain areas is a challenge but is a mandatory task for the interpretation of triggering causes. We present a reanalysis of an ensemble of extreme rainfall events happened across central Alps and Pre-Alps, in the northern part of Lombardy Region, Italy. We have investigated around some critical aspects such as their intensity and persistency also proposing a modelling of their meteorological evolution, using the Linear Upslope-Rainfall Model (LUM). We have considered this model because it is designed for describing the mechanism of orographic precipitation intensification that was identified as the main cause of that extreme events. To test and calibrate the LUM model we have considered local rain gauges data because they represent the effective rainfall poured on the ground. These punctual data are generally considered for landslide assessment, in particular for rainfall induced phenomena such as shallow landslides and debris flows. Considering our test cases, the results obtained have shown that the LUM has been able to reproduce accurately the rainfall field. In this regard, LUM model can help to address further information around those ungauged area where rainfall estimation could be critical for evaluating the hazard. We are conscious that our and other studies around this topic would be propaedeutic in the next future for the adoption of an integrated framework among the real-time meteorological modelling and the hydrogeological induced risk assessment and prevision.</p>

Enhancing Flood Hazard Assessments in Coastal Louisiana Through Coupled Hydrologic and Surge Processes

Traditional coastal flood hazard studies do not typically account for rainfall-runoff processes in quantifying flood hazard and related cascading risks. This study addresses the potential impacts of antecedent rainfall-runoff, tropical cyclone (TC)-driven rainfall, and TC-driven surge on total water levels and its influence in delineating a coastal flood transition zone for two distinct coastal basins in southeastern Louisiana (Barataria and Lake Maurepas watersheds). Rainfall-runoff from antecedent and TC-driven rainfall along with storm surge was simulated using a new rain-on-mesh module incorporated into the ADCIRC code. Antecedent rainfall conditions were obtained for 21 landfalling TC events spanning 1948–2008 via rain stations. A parametric, TC-driven, rainfall model was used for precipitation associated with the TC. Twelve synthetic storms of varying meteorological intensity (low, medium, and high) and total rainfall were utilized for each watershed and provided model forcing for coastal inundation simulations. First, it was found that antecedent rainfall (pre-TC landfall) is influential up to 3 days pre-landfall. Second, results show that antecedent and TC-driven rainfall increase simulated peak water levels within each basin, with antecedent rainfall dominating inundation across the basin's upper portions. Third, the delineated flood zones of coastal, transition, and hydrologic show stark differences between the two basins.

On the Rainfall Triggering of Phlegraean Fields Volcanic Tremors

We study whether the shallow volcanic seismic tremors related to the bradyseism observed at the Phlegraean Fields (Campi Flegrei, Pozzuoli, and Naples) from 2008 to 2020 by the Osservatorio Vesuviano could be partially triggered by local rainfall events. We use the daily rainfall record measured at the nearby Meteorological Observatory of San Marcellino in Naples and develop two empirical models to simulate the local seismicity starting from the hypothesized rainfall-water effect under different scenarios. We found statistically significant correlations between the volcanic tremors at the Phlegraean Fields and our rainfall model during years of low bradyseism. More specifically, we observe that large amounts and continuous periods of rainfall could trigger, from a few days to 1 or 2 weeks, seismic swarms with magnitudes up to M = 3. The results indicate that, on long timescales, the seismicity at the Phlegraean Fields is very sensitive to the endogenous pressure from the deep magmatic system causing the bradyseism, but meteoric water infiltration could play an important triggering effect on short timescales of days or weeks. Rainfall water likely penetrates deeply into the highly fractured and hot shallow-water-saturated subsurface that characterizes the region, reduces the strength and stiffness of the soil and, finally, boils when it mixes with the hot hydrothermal magmatic fluids migrating upward. The structural collapse of the saturated fractured soil and the mixing of the meteoric fluid with the hot deep fluids triggers the local seismic activity.

Statistical modelling of extreme rainfall in Peninsular Malaysia

Flash floods are known as one of the common natural disasters that cost over billions of Ringgit Malaysia throughout history. Academically, an extreme rainfall model is effective in modelling to predict and prevent the occurrence of flash floods. This paper compares four probability distributions, namely, exponential distribution, generalized extreme value distribution, gamma distribution, and Weibull distribution, with the rainfall data of 10 stations in peninsular Malaysia. The period of the data is from 1975 to 2008. The comparison is based on the descriptive and predictive analytics of the models. The determination of the most effective model is through Kolmogorov-Smirnov, Anderson-Darling, and chi-square test. The result shows that generalized extreme value is the most preferred extreme rainfall model for the rainfall cases in Peninsular Malaysia.

Stability analysis of Baishuihe landslide under the combined effect of reservoir and rainfall

Reservoir drawdown and rainfall have important influence on bank landslides, but existing research on these two factors is too idealistic. A new reservoir drawdown model was proposed for the rapid drawdown stage based on the consideration of reduction, navigation and power generation. A rainfall model was proposed considering actural rainfall and rainfall time based on fifty years of daily rainfall data. At last, taking Baishuihe landslide as an example, the landslide stability was analyzed under the combined influenced of rainfall and reservoir drawdown. Results show that the Baishuihe landslide is mainly influenced by reservoir drawdown. The terminal reservoir drawdown model can reduce the effect of continuous decline of reservoir on landslide and the stability decreases about 0.7%~1.2% compared with normal scenario. The reservoir drawdown model proposed in this paper is of significance to the reservoir operation in the Three Gorges Reservoir.

Simulating Heavy Meiyu Rainfall: A Note on the Choice of the Model Microphysics Scheme

Better simulations and predictions of heavy rainfall associated with Meiyu fronts are critical for flood management in the Yangtze River Valley, China. This work systematically evaluates and compares the performances of three microphysics schemes in Weather Research and Forecasting (WRF) Model with regard to simulating properties of a classic Meiyu rainstorm in central China which occurred during a 30-hour period in July 2016, including spatial distribution, rain rate PDF, and lifecycle behavior of local rainfall. Model simulations are validated using both in situ and remote sensing observations. It is found that all three schemes capture the overall spatial distribution of precipitation and the average rainfall intensity changes more rapidly with time in the simulation than in the observation. Further insights are gained through an examination of the budget terms of raindrop and ice-phase hydrometeors in the model. Accretion of cloud droplets by raindrops and melting of ice-phase hydrometeors are the major source of rainwater. Bergeron and riming processes are found to play a prevailing role in the growth of ice-phase hydrometeors in Meiyu rainfall. Large differences in the parameterization of riming process in different schemes lead to significant differences in the simulated growth of ice-phase hydrometeors.