Search Results (23)

Debris flows represent a significant geohydrological hazard, impacting the surrounding environment and threatening human settlements by altering ecological equilibria. The formation of temporary, often unstable, natural dams that obstruct normal river flow and create secondary flood risks poses a complex and prolonged threat to the sustainable management of water resources. Non-invasive risk assessment and analysis tools are therefore essential for addressing this challenge effectively. In this context, this study uses an end-to-end numerical modelling approach validated on an actual river obstructed in past by a debris flow. The simulation focused on sustainable risk management after the landslide dam rupture. This computational methodology is a non-invasive technology that provides a fundamental alternative to costly and environmentally invasive field techniques for assessing the risk of complex river systems. Two separate numerical simulations were carried out using the HEC-RAS code. The first simulation used the integrated sediment transport module to quantify the dynamics of solid material deposition and dilution. The second simulation modelled secondary flooding scenarios using the dam break simulation module. The aim of integrating these non-invasive simulations is to analyse the interaction between the river and debris accumulation, understand the river’s natural regeneration capacity and determine the hydraulic response to sudden dam failure. These results are essential for geohydrological risk assessment and mitigation, thereby improving the effectiveness of prevention measures and systemic resilience against landslides. Full article

Karst mining regions frequently encounter ecological and geological challenges during extraction, especially the increased water inflow into mine pits, water contamination, and karst collapse due to dewatering activities. These challenges not only threaten the safety of mineral resource extraction but also escalate operational expenses. To address these concerns, this study offers a detailed examination of the geohydrological conditions in a karst mining area. It integrates multiple data sources, such as the dynamics of groundwater, mine dewatering activities, and precipitation patterns, to identify the primary sources of water ingress into the mines. The result reveals that the primary water inflow of the mine pits is directly recharged by atmospheric precipitation through runoff zones. Additionally, the key factors leading to karst collapses are the decrease in groundwater levels due to dewatering and the stability of surrounding rock. Consequently, this paper presents a set of innovative methods for water hazard prevention and control. Utilizing the GMS (Groundwater Modeling System), the groundwater numerical model is built to estimate water consumption in mining operations, and also to validate the efficacy of these methods. The model reveals that application of these techniques can reduce groundwater inflow of the mine by 34.3%. The set of methods not only substantially lowers the risk of water inrush incidents but also avoids the contamination of groundwater. Consequently, it ensures the safety of mine production, especially in the wet season. Full article

Rainfalls are the result of complex cloud microphysical processes. Trying to estimate their intensity and duration is a key task necessary for assessing precipitation magnitude. Across mountains, extreme rainfalls may cause several side effects on the ground, triggering severe geo-hydrological issues (floods and landslides) which impact people, human activities, buildings, and infrastructure. Therefore, having a tool able to reconstruct rainfall processes easily and understandably is advisable for non-expert stakeholders and researchers who deal with rainfall management. In this work, an evolution of the LUME (Linear Upslope Model Experiment), designed to simplify the study of the rainfall process, is presented. The main novelties of the new version, called LUME 2D, regard (1) the 2D domain extension, (2) the inclusion of warm-rain and cold-rain bulk-microphysical schemes (with snow and hail categories), and (3) the simulation of convective precipitations. The model was completely rewritten using Python (version 3.11) and was tested on a heavy rainfall event that occurred in Piedmont in April 2025. Using a 2D spatial and temporal interpolation of the radiosonde data, the model was able to reconstruct a realistic rainfall field of the event, reproducing rather accurately the rainfall intensity pattern. Applying the cold microphysics schemes, the snow and hail amounts were evaluated, while the rainfall intensity amplification due to the moist convection activation was detected within the results. The LUME 2D model has revealed itself to be an easy tool for carrying out further studies on intense rainfall events, improving understanding and highlighting their peculiarity in a straightforward way suitable for non-expert users. Full article

The automated recognition of landforms holds significant importance within the framework of digital geomorphological mapping, serving as a pivotal focal point for research and practical applications alike. Over the last decade, various methods have been developed to achieve this goal, ranging from grid-based to object-based approaches, covering a range from supervised to completely unsupervised techniques. Furthermore, the vast majority of the methods mentioned depend on Digital Elevation Models (DEMs) as their primary input, highlighting the crucial significance of meticulous preparation and rigorous quality assessment of these datasets. In this study, we compare the outcomes of grid-based methods for landforms extraction and surficial process type assessment, leveraging various DEMs as input data. Initially, we employed a photogrammetric Digital Terrain Model (DTM) generated at a regional scale, along with two LiDAR datasets. The first dataset originates from an airborne survey conducted by the national government approximately a decade ago, while the second dataset was acquired by UAV as part of this study’s framework. The results highlight how the higher resolution and level of detail of the LiDAR datasets allow the recognition of a higher number of features at higher scales; but, in contrast, generally, a high level of detail corresponds with a higher risk of noise within the dataset, mostly due to unwanted natural features or anthropogenic disturbance. Utilizing these datasets for generating geomorphological maps harbors significant potential in the framework of natural hazard assessment, particularly concerning phenomena associated with geo-hydrological processes. Full article

Powerlines are strategic infrastructures for the Italian electro-energetic network, and natural threats represent a potential risk that may influence their operativity and functionality. Geo-hydrological hazards triggered by heavy rainfall, such as shallow landslides, have historically affected electrical infrastructure networks, causing pylon failures and extensive blackouts. In this work, an application of the reworked version of the model proposed by Borga et al. and Tarolli et al. for rainfall-induced shallow landslide hazard assessment is presented. The revised model is called SLEM (Shallow Landslide Express Model) and is designed to merge in a closed-from equation the infinite slope stability with a simplified hydrogeological model. SLEM was written in Python language to automatise the parameter calculations, and a new strategy for evaluating the Dynamic Contributing Area (DCA) and its dependence on the initial soil moisture condition was included. The model was tested for the case study basin of Trebbia River, in the Emilia-Romagna region (Italy) which in the recent past experienced severe episodes of geo-hydrological hazards. The critical rainfall ratio (r_crit) able to trigger slope instability prediction was validated against the available local rainfall threshold curves, showing good performance skills. The rainfall return time (TR) was calculated from r_crit identifying the most hazardous area across the Trebbia basin with respect to the position of powerlines. TR was interpreted as an index of the magnitude of the geo-hydrological events considering the hypothesis of iso-frequency with precipitation. Thanks to its fast computing, the critical rainfall conditions, the temporal recurrence and the location of the most vulnerable powerlines are identified by the model. SLEM is designed to carry out risk analysis useful for defining infrastructure resilience plans and for implementing mitigation strategies against geo-hazards. Full article

Recent water availability and scarcity problems have highlighted the importance of surface–groundwater interactions. Thus, groundwater models are coupled with surface water models. However, this solution is complex, needing code modifications and long computation times. Recently, a new groundwater module (gwflow) was developed directly inside the SWAT code to tackle these issues. This research assesses gwflow’s capabilities in representing surface–groundwater system interactions in the Dijle catchment (892.54 km²), a groundwater-driven watershed in Belgium. Additional developments were made in SWAT+gwflow to represent the interaction between the groundwater and soil (gwsoil). The model was calibrated for monthly mean streamflow at the catchment outlet (1983 to 1996) and validated for two periods (validation 1: 1975 to 1982 and validation 2: 1997 to 2002). It was found that the SWAT+gwflow model is better at representing the total flow (NSE of 0.6) than the standalone SWAT+ (NSE of 0.4). This was confirmed during two validation periods where the standalone model scored unsatisfactory monthly NSE (0.6 and 0.1), while the new model’s NSE was 0.7 and 0.5. Additionally, the SWAT+gwflow model simulations better depict the groundwater via baseflow and attain proper water balance values. Thus, in a highly groundwater-driven catchment, the simplified representation of groundwater systems by the standalone SWAT+ model has pitfalls. In addition, the modification made to the gwflow module (gwsoil) improved the model’s performance, which, without such adjustment, overestimates the streamflow via saturation excess flow. When including the gwsoil mechanism, thereby providing a more accurate representation of water storage and movement, groundwater is transferred to the soil profile, increasing the overall soil water content and thereby increasing lateral flow. This novel modification can also have implications for other distributed hydrological models to consider such exchanges in their modeling scheme. Full article

The impacts of climate change are becoming more widespread across the world, with hydro-meteorological extreme events on the rise, causing severe threats to nature and communities. Increasing trends in the frequency and intensity of floods and landslides have been projected by climate models. This necessitates the development of more effective measures such as nature-based solutions (NBS) which can complement grey infrastructures. Recent studies have identified knowledge gaps and limitations in existing research and tools that aid in spatial planning for the implementation of large-scale NBS and proposed new methodologies for the spatial allocation of large-scale NBS for flood risk reduction. This work presents a novel method for mapping the suitability of NBS addressing geo-hydrological hazards such as shallow landslides, debris flow, and rockfall, which are typically caused due to slope instability. This methodology incorporates landslide susceptibility mapping, and was used to create a toolbox ESRI ArcGIS environment to aid decision-makers in the planning and implementation of large-scale NBS. The spatial allocation toolbox was applied to the case study Portofino promontory, Liguria region, Italy, and 70% of the area was found to be highly susceptible to landslides. The produced suitability maps show that 41%, 33%, and 65% of the study area is suitable for the restoration of terraces, bio-engineering, and vegetative measures such as NBS for landslide risk reduction. Full article

Interest has grown in applying hydrologic models in managed catchments despite uncertainties around model inputs and empirical relationships to simulate complex geo-hydrological processes of streamflow and sediment variations. Unquantified interactions between geophysical, climate and management indices can also increase simulation uncertainties. Calibration of model outputs against observed values allows identification of the most influential variables and their optimised ranges by which model performance can be enhanced. A rainfall-runoff Soil and Water Assessment Tool (SWAT) model was utilised for four catchments in northern New South Wales, Australia to simulate time series of streamflow across varying rainfall regimes, from dry seasons from 2002 towards rainy 2009. Parameters causing a substantial change on model streamflow outputs were first identified using a sensitivity analysis which indicated that hydrologic factors governing the sources of water supply were critical parameters. These sensitive variables were substantially derived from groundwater modules, basic flow in the main channel, and management practices. Statistical tests of between-catchment differences showed that model simulations performed better in a catchment where the sole rain gauge was installed, while also having the narrowest variations in simulated values (r-index = 0.02). In contrast, the highest uncertainty of model simulations was found in the furthest catchment from the rain gauge where there was not a satisfactory agreement with observed data. Yearly differences between 2002 and 2009 indicated an overestimation of streamflow during low flow periods. However, the calibration process performed well in most peak flows where estimations followed the respective observed values. Long-term dry periods between 2002 and 2007 resulted in an overestimated baseflow by predicting an unrealistic recharge infiltrating aquifers. Full article

Terraced landscapes are widely applied in many mountainous regions around the world as a result of the necessity to practice subsistence agriculture. Hence, they can be regarded as one of the most diffused anthropogenic modifications of the Earth’s surface. Different techniques have been used for their implementation leading to the artificial immobilization of debris and soil along the slopes whose surface is interrupted by a sequence of sub-horizontal and sub-vertical areas often using stone walls. In some areas of the world, such interventions are thousands of years old and their resistance to the degradation caused by the morphogenetic system can be attributed to the permeability of the stone walls as well as to their regular maintenance. In some other areas, the lack of maintenance has been the main cause for degradation processes ending with their collapse. The effects of climate change manifested through higher intensities and higher frequencies of rainfall are likely to accelerate the degradation process further by causing terraces to act as a source of debris or hyperconcentrated flow. This will in turn increase the severity of geo-hydrological hazards. The measures concerning reduction of geo-hydrological hazards are sought through identification of abandoned terraces and assessment of the potential for their sudden collapse. The present paper describes a framework for identification of abandoned terraces and estimation of the potential volume of shallow landslides that can be generated. The research conducted aims to advance the existing hazard assessment practices by combining numerical modeling with processing of high-resolution LiDAR data. A new algorithm is developed to support localization of terraces. The catchment scale approach applied to eight smaller catchments enables estimation of the total volume of soil and debris trapped along the slopes. It also generated some important quantitative data which will be used in the future risk assessment work. The work has been carried out within the EU-funded H2020 project RECONECT. Full article

Flood risk in Italy is a key aspect for the administrative authorities, from the national to the local level. This is especially true in Northern Italy, where the Po River, the most important river of the peninsula, and its river basin are located. In North-Western Italy, the Po Basin is described by numerous sub-basins, among which is the Tanaro River basin: here, in the last decades, floods have produced significant damage, causing an increased concern to local and regional administrations. The main goal of this study was to identify suitable sites for the construction of dams, having the function of retention basins, aiming to mitigate the flood risk in the Upper Tanaro Valley. First, using a qualitative approach, suitable sites were identified using available public data provided by regional administrations and field data obtained from geomorphological surveys, later elaborated in a Geographic Information System (GIS) environment. Several models were then produced using conventional methods to evaluate the hydrological characteristics of the study area and to assess the efficiency of each site in terms of flood water flow rate reduction: the performance was evaluated at control sections chosen in urban areas along the Upper Tanaro Valley. The results show that it is possible to find suitable locations for risk mitigation structures. These models also allowed for a rapid cost-effectiveness evaluation, which led to the definition of the best-performing site. The Upper Tanaro Valley case study here analyzed contributes to proving the importance of an integrated approach based on geomorphological, geo-hydrological, and hydraulic evaluations when dealing with the choice of a flood risk mitigation strategy. Full article

Red mud is a strong alkaline solid waste pollutant produced in the process of aluminum smelting, which causes great pollution to the regional groundwater environment due to its high content of fluorine and aluminum and high concentration of strong alkali. In this study, fluoride ion was selected as the model contaminant, and a numerical model of the groundwater flow field and solute transport was developed using GMS software to simulate and analyze the migration patterns of fluoride contaminants caused by the red mud pit for the fractured karst geohydrological conditions. The results demonstrated that the groundwater model and flow pattern were mainly controlled by atmospheric precipitation recharge, given flow boundary conditions and leakage of rivers and drains. When the concentration of fluorine pollutants in the red mud yard was 60.0 mg/L, the maximum migration distance of F⁻ in the groundwater of the ordovician limestone aquifer was 473, 1160, 1595 and 1750 m after 1, 5, 10 and 15 years of bottom leakage, and the additional transport distances were 687, 435 and 155 m every 5 years, respectively. The range of F⁻ pollution plume was 0.37 km², 1.15 km², 1.95 km² and 2.14 km², respectively and the range of newly added pollution plume was 0.78 km², 0.80 km² and 0.19 km², respectively, every five years. Both indicated that with the extension of time, the migration and diffusion rate of pollutants slow down, and the diffusion volume increased first and then decreased. The F⁻ pollution plume spread from the red mud pit to the northeast, which was consistent with the flow of groundwater. The high-concentration pollution plume was mainly distributed in the Ordovician limestone fractured aquifer in the northeast. This study revealed the migration law of red mud pollutants, and provided a scientific decision-making basis for the prevention and control of red mud groundwater pollution in the future. Full article

The study of geo-hydrological problems in urban contexts of considerable historical importance plays an extremely interesting role in the safeguarding of architectural and artistic assets of great value. The need to guarantee the conservation of monumental heritage is an ethical and moral requirement that new generations have a duty to support. Operating in urbanised contexts is extremely difficult, due to the presence of infrastructures and underground services that prevent the execution of classical surveys and prospecting. The technologies currently available, however, allow us to also investigate the subsoil in a non-destructive way and to control the evolution of active natural phenomena in a continuous and automated way with remote-sensing techniques. The methodological approach consists of the development of a series of cognitive investigations, aimed at identifying the elements of weakness of the soil system, so as to be able to subsequently undertake the most appropriate decisions for the reduction of geo-hydrological risks. The case here analysed concerns Lanciano city (Central Italy), famous for its pre-Roman origins, that was affected by a violent storm in the summer of 2018. This event devastated the inhabited Centre with flooding of all the neighbourhoods and the collapse of parts of buildings. For this reason, direct and indirect geognostic investigations were carried out within the Historical Centre, which is of considerable architectural value, and an important monitoring system was installed. The actual geo-hydrological hazard was planned using 3D numerical modelling to define the hydraulic and deformational behaviour of the subsoil. Comparison between the modelling performed and the monitoring data acquired has allowed us to understand the complex behaviour of the subsoil and the subsidence mechanisms of the Historic Centre. Full article

Meeting long-term rural community water supply needs requires diligent geohydrological conceptualisation. Study of Malawi’s Lake Chilwa Basin, including sampling of 330 water points in Phalombe District, enabled assessment of groundwater quality influence upon supply. The control of larger Lake Chilwa paleo-environments on current Basin groundwater quality is demonstrated. Lacustrine sediment deposition forming high-level deposits under open lake conditions and terrace deposits under open and closed lake conditions significantly control the groundwater major-ion quality and salinity now observed. Paleo-lake extent marks the transition between low-TDS (total dissolved solids) groundwater suitable for water supply at higher elevations and high-TDS brackish groundwater in areas overlain by lacustrine deposits closer to the current lake level. Low-TDS groundwater is limited to mid-to-low reach influent leakage of rivers incising terraces. Permeable fluvial deposits within the deeper paleo-river channel may possibly provide low-TDS water. The conceptual model, whereby paleo-lake controls groundwater salinity, provides science-based evidence to address policy to manage the significant water point functionality concerns quantified at the district and river basin scales. Targeting of the low-TDS groundwater alongside improved use of upland low-TDS stream/river sources with fewer, but larger capacity, and better maintained gravity-fed supply schemes are recommended. This study hence shows the value of paleo-geohydrology interpretation of the lake–groundwater system conceptualisation to inform Sustainable Development Goal 6 (SDG 6.5.1)—integrated water resources management policy for rural water supply. Full article

In an arid region, flash floods (FF), as a response to climate changes, are the most hazardous causing massive destruction and losses to farms, human lives and infrastructure. A first step towards securing lives and infrastructure is the susceptibility mapping and predicting of occurrence sites of FF. Several studies have been applied using an ensemble machine learning model (EMLM) but measuring FF magnitude using a hybrid approach that integrates machine learning (MCL) and geohydrological models have not been widely applied. This study aims to modify a hybrid approach by testing three machine learning models. These are boosted regression tree (BRT), classification and regression trees (CART), and naive Bayes tree (NBT) for FF susceptibility mapping at the northern part of the United Arab Emirates (NUAE). This is followed by applying a group of accuracy metrics (precision, recall and F1 score) and the receiving operating characteristics (ROC) curve. The result demonstrated that the BRT has the highest performance for FF susceptibility mapping followed by the CART and NBT. After that, the produced FF map using the BRT was then modified by dividing it into seven basins, and a set of new FF conditioning parameters namely alluvial plain width, basin gradient and mean slope for each basin was calculated for measuring FF magnitude. The results showed that the mountainous and narrower basins (e.g., RAK, Masafi, Fujairah, and Rol Dadnah) have the highest probability occurrence of FF and FF magnitude, while the wider alluvial plains (e.g., Al Dhaid) have the lowest probability occurrence of FF and FF magnitude. The proposed approach is an effective approach to improve the susceptibility mapping of FF, landslides, land subsidence, and groundwater potentiality obtained using ensemble machine learning, which is used widely in the literature. Full article

The hydraulic and hydrogeological features of the Caposele aquifer have been investigated by using a numerical groundwater flow model. In particular, groundwater flow simulations were performed for a multilayered, unconfined aquifer in steady-state conditions for different thicknesses of the aquifer’s saturated zone. The Caposele groundwater model was carried out starting from a generic model drained by a unique spring outlet in accordance with the geo-hydrological features of the study area. The conceptual model was built considering hydrogeological features of spring catchment, and was then implemented with the MODFLOW numerical code. A combined 2D-3D approach was adopted, and the model was calibrated on borehole data available for the time period 2012–2019. Different thicknesses of the aquifer were set, and a reliable relationship was found between the hydraulic head, saturated zone and hydraulic conductivity of the aquifer. Using the MODPATH package, the mean travel time (Darcian) of groundwater was computed for five different scenarios, corresponding to the model’s depths; the analysis that was performed shows that the travel time is higher for a greater and lower for a smaller thickness of the aquifer’s saturated zone, respectively. The Caposele aquifer model was zoned in different sectors, named flow pipe areas, that play different roles in groundwater recharge-discharge processes. A vector analysis was also carried out in order to highlight the ascendant flow near the spring zone. Full article