This study presents a methodological framework to investigate the impacts of climate change on rainfall-triggered landslides at the subregional scale. Focusing on a ∼170 km² area in the Partenio Mountains in southern Italy, we employed regional rainfall projections (CORDEX) under moderate (RCP4.5) and high (RCP8.5) emission scenarios for 2006–2070. Rainfall data were bias corrected with observations from 2006–2023 and benchmarked against a synthetic dataset generated through stochastic reproduction of currently observed conditions. Physically based simulations of hydrological processes, coupled with slope stability analyses that account for unsaturated soil conditions, enabled event-by-event identification of landslides throughout the period. Statistical comparisons between scenarios were conducted across three rainfall homogeneous subregions. Results show a general tendency toward drier soil conditions, consistent with regional-scale climate studies, but with increasing rainfall variability across subregions. Despite this drying trend, projections indicate a significant rise in landslide occurrence, with a faster increase under RCP4.5 when compared to RCP8.5. This counterintuitive outcome reflects shifts in rainfall dynamics: under RCP8.5, landslides are mainly linked to more intense triggering rainfall, while under RCP4.5 they result from a combination of wetter antecedent conditions and more intense early-peak rainfall events. These findings emphasize the critical role of antecedent soil moisture in landslide initiation by showing its stable influence on landslide occurrence despite the rapid evolution of climate change. Overall, the methodology provides a transferable framework to assess local climate change impacts on geohazards by integrating bias-corrected climate projections with physically based hydrological–geomechanical modeling.

This chapter examines the variety of flow-like landslides that may involve fine-grained soils. Five case studies are presented: two of them concern earthflows in softened stiff clays or marls, which are characterised by lower displacement rates than all other types of flows; one describes slope movements in sensitive clay that occurred in the debris of a large, older landslide; a coastal landslide and a huge submarine event are the topics of the last two case studies.

Understanding the hydrology in the upstream mountainous part of the Karnali basin in Nepal is vital, considering the importance of streamflow for downstream nature conservation and water supply. We use a fully distributed hydrological model to understand the current hydrology, the associated vulnerability of the basin, and the importance of the different hydrological components in regulating flow. Downscaled ERA5 meteorological data is used to force the model for the period 1991–2022 at a high spatial resolution (500 meters). We calibrate our model using observed discharges, and the model performance is considered good with a reported Kling-Gupta efficiency of 0.84 and a bias of −3.33%. Our results show that 40% of the overall discharge generated in the Karnali basin originates from rain runoff, 35% from baseflow, 24% from snowmelt, and a negligible 0.8% from glaciers. The water balance components vary spatially in magnitude, but the overall monthly patterns are comparable. On average, the basin receives 1,485 mm/year of precipitation, peaking in July, and is a pronounced southwest region. The annual average evapotranspiration in the basin is 574 mm/year, and discharge is 914 mm/year. Analysis of anomalies reveals that the discharge has become increasingly more variable over the last decades and, therefore, less predictable. Our results also reveal that the basin is frequently experiencing meteorological droughts, often translating into a hydrological drought with a lag time of a month. The average duration of a hydrological drought period in the basin was about 6 months. Snow storage plays an important role in modulating these droughts, and variability in initial snow storage impacts basin streamflow for up to 6 months. A climate change-induced shift from snow to rain may therefore impact the climate resilience of the Karnali considerably.

Landslide dams, created when rapid mass movements block river channels, are strongly influenced by hydrological conditions of the upstream catchment. The formation and long-term stability of landslide dams are closely linked to hydrological factors such as streamflow, lake area, water level and precipitation. Conversely, the formation of these dams changes upstream and downstream hydrological regimes such as water storage, sediment transport and flooding risk. Since the previous reviews by Costa and Schuster, (1988) and Korup, (2002), several review articles have focused on the formation and failure mechanism of landslide dams (e.g., Fan et al. 2020; Zheng et al. 2021). These reviews have mainly focused on geomorphological factors of dams and their formation. However, the hydrological processes around and within the landslide dam are crucial for the behavior of landslide dams, the downstream hydrology and potential flash flood risks. Therefore, there is an urgent need to study hydrological processes upstream and within landslide dams in order to better predict landslide dam stability, up- and downstream consequences. Streamflow (inflow and outflow), precipitation and snowmelt, water level, dammed lake area, lake volume, water balance, surface runoff, erosion, sedimentation, and water storage capacity are key factors for assessing the behavior of landslide dams. This review analyzes the current state of knowledge on hydrological processes influencing the evolution, and failure of landslide dams. It further examines the role of remote sensing and modelling techniques in assessing hydrological factors where field data are scarce.

Sand rivers — ephemeral rivers with water stored in their sandy alluvial beds — offer a decentralized, low-cost, and underutilized source of water in many arid to semi-arid regions in Africa. This study explores a novel approach to remotely estimate the water storage potential in these systems using satellite-derived dry season total evaporation from the riparian vegetation and sand channels. Sentinel-2 imagery was used to delineate sandy channels and riparian zones across three sub-catchments in southern Zimbabwe, and total evaporation was estimated using WaPOR v3 data. Abstractable water storage was estimated at the locations of 34 in-situ sand depth measurements from literature assuming a specific yield of 0.15 and a rectangular channel shape. Total evaporation was found to be below abstractable channel storage for 27 (79%) of the in-situ observations suggesting remaining unconsumed water in sand river channels. A linear regression was used to estimate abstractable water storage in reaches without depth measurements based on total evaporation. Two methods were used to obtain the slope of the regression and total unconsumed water storage was estimated to be sufficient to irrigate between 3 700 and 6 200 ha across the study area. While field studies are recommended to validate the results, our approach provides a spatially distributed indicator of nature-based water storage potential in sand rivers based on remote sensing. The method presented enables the rapid low-cost identification of priority areas for water access and smallholder irrigation and provides a first approximation for regional planning, in particular for farmer-led irrigation and decentralized water access.

Satellite-derived surface soil moisture (SSM) data are rarely applied in landslide modelling due to their shallow sensing depth (< 5 cm) and large spatial footprint, limiting their perceived relevance for subsurface hydrological processes. This study presents an integrated approach combining SMAP-Sentinel L2 SSM with high-resolution gridded radar rainfall data for coupled subsurface flow–stability landslide modelling. The 2020 landslide in Khao Yai National Park, Thailand, was used as a case study, supported by two years (2022–2024) of slope monitoring, including soil moisture, rainfall, and tiltmeter-based deformation data. Monthly averaged SSM showed reasonable agreement with in-situ soil moisture (R² = 0.63) and was applied as an initial boundary condition in flow models to estimate soil moisture variation with depth and time. The SSM-based model produced comparable results to in-situ soil moisture-based model (R² = 0.96) but generally underpredicted the factor of safety (F_S) by 9% especially during the onset of rain events. Two-dimensional flow and stability analyses revealed that rainfall-induced subsurface flow parallel to the slope reduced F_S to near unity prior to 2020 landslide. A moderate correlation (R² = 0.62) between soil moisture change and tiltmeter deformation indicated slope contraction during dry periods and downslope movement during wet conditions. These findings support the use of SSM and radar rainfall for improving landslide prediction and early warning systems.

Preferential flow and soil strength degradation induced by desiccation cracks are important causes for expansive clay slope instability. The cyclic opening and closing of desiccation cracks during drying-wetting processes incessantly alters preferential flow paths and soil strength. Quantify the impact of desiccation crack dynamics on slope hydrology and stability remains a major unresolved challenge. To bridge this gap, we developed the first slope-scale hydro-mechanical model that couples weather-driven crack evolution with preferential flow while incorporating the deterioration effect on soil strength. This unified approach is a major contribution to our capacity to model the integration of hydrological processes and mechanical degradation of soil strength induced by dynamic cracks. The hydrological part adopted a dynamic dual-permeability model (dynamic DPM) and was validated by a physical slope model test. The dynamic DPM was then integrated into a set of numerical slope stability analyses under one-year atmospheric conditions. The groundwater level, water balance, pore water distribution, crack evolution and slope stability were investigated in the case of dynamic cracks and fixed cracks. The hydrological results showed that the slope model with dynamic cracks retained more water and higher groundwater level than that with fixed cracks. The narrowing of desiccation cracks slows down slope drainage process, resulting in a rapid build-up of pore water pressure due to preferential flow, which emerges as an often overlooked and significant factor contributing to slope instability. Conversely, fixed and well-connected cracks in soils enhance water drainage and thus benefit slope stability. The mechanical results revealed that the irreversible deterioration effect induced by crack dynamics on soil strength persistently degrades long-term slope stability. These findings provide new insights into failure mechanisms in cracked soil slopes, and show the importance of the integration of dynamic crack properties into climate-resilient slope design. Also, our results underscore the importance of understanding and quantifying the physical behavior of soil structures for soil hydrological response and slope stability assessment.

Organisms perpetually release genetic material in their surroundings, referred to as environmental DNA (eDNA), which can be captured and subsequently analyzed to detect biodiversity across the tree of life. In lotic, dynamic environments, little is known about the specific factors that affect the concentration of eDNA between release by the host and its dissemination into the environment. This gap in knowledge introduces significant uncertainty when applying eDNA as a monitoring tool. Our objective is to provide insight on the factors that affect the eDNA concentrations in ecosystems representative of rivers and streams. To this end, we conducted a series of laboratory experiments in a rotating circular (annular) flume, which allows for extended degradation experiments under conditions of flow. Here, we show that flow velocity impacts the observed eDNA concentration over time. Our results suggest that flow-induced transport keeps eDNA in suspension, reducing eDNA removal from the water column, which increased the observed concentration of eDNA. We observed a temporary increase in eDNA concentration over the early phase of the flume experiment with the highest flow velocity. This increase in eDNA concentration seems to be due to a combination of low eDNA degradation rates and high shear stress, which fragment and subsequently homogenize eDNA particles over the water column. The results of our study show the importance of better understanding and assessing the detection probability of eDNA, both in controlled laboratory and larger-scale environmental conditions.

Intensity-duration (ID) thresholds are used to identify rainfall conditions likely to initiate landslides. They consider the average rain intensity observed over the entire length (called duration) of user-defined wet periods that lead to the triggering. Intensity-duration-frequency (IDF) curves assign a probability to the intensity of precipitation observed over fixed-length temporal windows (also called durations). As the term duration refers to different concepts, ID thresholds and IDF curves cannot be compared directly, and should better not be plotted in one figure, and IDF curves should not be used to quantify the exceedance probability of ID thresholds.

With the availability of an increased number of ground-based weather radars, the development of composite radar rainfall estimates has become common practice. In mountainous terrain, weather radar measurements often encounter beam blockage effects, resulting in erroneous estimates of rainfall. This study introduces a novel relative radar quality index based on the radar reflectivity fraction to enhance the radar composite product. Additionally, we develop an improved mean field bias adjustment technique by including the spatial variability of the bias adjustment factors associated with the quality of radar observations. Radar reflectivity data from a network of single-polarization S-band radars, the Sattahip and Phimai radar stations in Thailand, and automatic rain gauges within the composite area, were used for the analysis. Three independent datasets were employed: (1) 51 storm events (2016–2022) for evaluating radar composite performance and QI-based bias adjustment; (2) hourly data from August–October 2020 to assess bias factor uncertainty; and (3) three heavy storms (2016, 2017, and 2020) to examine the QI method's effectiveness in beam-blocked basins. Our analysis explored seven combinations of hourly radar composite products. Subsequently, the performance of radar rainfall estimates obtained from applying the proposed mean field bias was evaluated by comparing them with the conventional technique. Results show the potential of integrating combined multiple quality indices to improve rainfall estimates, particularly for heavy rainfall events in mountainous regions.

Vegetation plays a critical role in regulating the catchment water balance and enhancing soil stability through root reinforcement. The dynamic nature of vegetation, particularly its seasonal change, significantly affects the magnitude of this influence. However, quantifying the long-term impacts of dynamic vegetation on both flood and landslide occurrences at the catchment scale remains challenging due to the complexity of root structures and the varying dimensions of landslides. In this study, we improved the coupled hydrological-geotechnical model iHydroSlide3D v1.0 by incorporating key vegetation components, such as Leaf Area Index (LAI), root characteristics, and their seasonal dynamics. The improved model was validated using historical observations and applied to a 100-years simulation driven by a weather generator. Three computational scenarios were employed to assess the influence of vegetation on key hydrological and slope-stability variables. Results show that vegetation reduces soil moisture and runoff during low to moderate rainfall events but has a limited impact during larger rainfall events. Additionally, slope stability is found to be more influenced by root reinforcement than soil water uptake. The dynamic nature of vegetation plays a decisive role in modulating its effects on hydrological processes and soil stability, depending on the growth or decay trend of vegetation. This modeling framework offers a robust tool for assessing long-term flood and landslide risks in vegetated catchments.

Enhanced and effective hydrological monitoring plays a crucial role in understanding water-related processes in a rapidly changing world. Within this context, image-based river monitoring has been shown to significantly enhance data collection, improve analysis and accuracy, and support effective and timely decision making. The integration of remote and proximal sensing technologies with citizen science and artificial intelligence may revolutionize monitoring practices. Therefore, it is crucial to evaluate the quality of current research and ongoing initiatives to envision the potential trajectories for research activities within this specific field. The evolution of monitoring strategies is progressing in multiple directions that should converge to build a critical mass around relevant challenges to find innovative solutions that overcome limitations of traditional approaches. The present study reviews examples and good practices of enhanced hydrological monitoring in different applications, reflecting on the strengths and limitations of new approaches.

The new scientific decade (2023-2032) of the International Association of Hydrological Sciences (IAHS) aims at searching for sustainable solutions to undesired water conditions–whether it be too little, too much or too polluted. Many of the current issues originate from global change, while solutions to problems must embrace local understanding and context. The decade will explore the current water crises by searching for actionable knowledge within three themes: global and local interactions, sustainable solutions and innovative cross-cutting methods. We capitalise on previous IAHS Scientific Decades shaping a trilogy; from Hydrological Predictions (PUB) to Change and Interdisciplinarity (Panta Rhei) to Solutions (HELPING). The vision is to solve fundamental water-related environmental and societal problems by engaging with other disciplines and local stakeholders. The decade endorses mutual learning and co-creation to progress towards UN sustainable development goals. Hence, HELPING is a vehicle for putting science in action, driven by scientists working on local hydrology in coordination with local, regional, and global processes.

Sand filtration systems (SF) are a well-established approach in ensuring the availability of clean water. Understanding the transport properties of colloidal particles within SF systems is of paramount importance for optimizing their performance. This study investigated the potential utilization of silica-encapsulated DNA particles, equipped with a magnetic core to enhance particle separation and quantification efficiency (SiDNAMag). These particles were evaluated as tracers for delineating complex pathways and conducting source tracking within sand filtration (SF) systems for particulate substances. The study focused on exploring the sensitivity of SiDNAMag to solution chemistry, while elucidating the underlying mechanisms governing their transport and retention in sand filtration systems. Laboratory columns and HYDRUS-1D modeling were employed to analyze a range of water chemistry solutions, encompassing NaCl, NaHCO₃, CaCl₂, and MgCl₂, with ionic strengths ranging from 0.1 mM to 20 mM. The results revealed that the transport of DNA-tagged silica particles could be described by a first-order kinetic attachment and detachment rate coefficient. Elevated ionic strengths consistently led to increased particle adhesion and decreased rates of detachment. The sticking efficiencies of SiDNAMag particles exhibited a range of 0.7 to 1. The remarkable adhesive effectiveness can be ascribed to the comparatively low negative charge exhibited by SiDNAMag particles. This leads to the creation of unstable colloids and encourages the aggregation of these colloidal particles, thereby limiting the potential application of these particles as a tracer. In conclusion, this work underlines the potential of SiDNAMag particles as a potential subsurface tracer. However, further research is warranted to investigate strategies for reducing the interaction between these particles and sand, particularly in response to the chemistry of the infiltrated water.

In the terrestrial environment, interactions between natural organic matter (NOM) and colloids can lead to the formation of an environmental corona around colloids, influencing their transport behaviour and, ultimately, their ecotoxicity. We used a synthetically designed colloid tagged with DNA (DNAcol) as a surrogate for natural colloids and investigated its transport in saturated sand columns. We varied the concentrations of NOM and ionic strength (CaCl₂), to better understand the transport and release of DNAcol in porous media under both steady and transient porewater chemistry conditions. In addition, we aimed to understand the main factors that control deposition and release of DNAcol under tested conditions. To induce transient chemistry, we replaced the injection solution containing NOM and/or CaCl₂ with Milli-Q water. The results showed that the deposition rate of DNAcol was inversely proportional to the concentration of NOM. The deposition rate increased significantly even under low ionic strength (CaCl₂) conditions of tested conditions. Notably, the influence of NOM on the transport of DNAcol was most pronounced at the lowest range of [Ca²⁺]/DOC ratios, and the attachment of DNAcol to the sand grains was negligible. Moreover, the results showed while the DLVO theory captured the general trend of experimental results, it significantly underestimated the deposition of DNAcol in the presence of CaCl₂. Under transient porewater chemistry conditions, colloid remobilization was observed upon flushing the column with Milli-Q water, leading to a secondary peak in the breakthrough curves. We observed that under transient porewater chemistry conditions, when the ionic strength of the solution was 10 mM, the magnitude of the remobilization peak was more significant compared to conditions with 1 mM ionic strength. Our work emphasized the complex interplay between water quality on the one hand and deposition and release of colloidal matter in saturated porous media on the other hand.

Occurrence of rainfall-induced landslides is increasing worldwide, owing to land use and climate changes. Although the connection between hydrology and rainfall-induced landslides might seem obvious, hydrological processes have been only marginally considered in landslide research for decades. In 2016, an advanced review paper published in WIREs Water [Bogaard and Greco (2016), WIREs Water, 3(3), 439–459] pointed out several challenging issues for landslide hydrology research: considering large-scale hydrological processes in the assessment of slope water balance; including antecedent hydrological information in landslide hazard assessment; understanding and quantifying the feedbacks between deformation and infiltration/drainage processes; overcoming the conceptual mismatch of soil mechanics models and hydrological models. While little progress has been made on the latter two issues, a variety of studies have been published, focusing on the role of hydrological processes in landslide initiation and prediction. The importance of the identification of the origin of water to understand the processes leading to landslide activation is largely acknowledged. Techniques and methodologies for the definition of landslide catchments and for the assessment of landslide water balance are progressing fast, often considering the hydraulic effect of vegetation. The use of hydrological information in landslide prediction models has also progressed enormously. Empirical predictive tools, to be implemented in early warning systems for shallow landslides, benefit from the inclusion of antecedent soil moisture, extracted from different sources depending on the scale of the prediction, leading to significant improvement of their predictive skill. However, this kind of information is generally still missing in operational LEWS. This article is categorized under: Science of Water > Hydrological Processes.

The growing coincidence of occurrence of natural hazards and vulnerable societies, leading to economic damages and fatalities, has triggered more studies on benefits of prevention measures. This chapter describes a study that aims to demonstrate benefits of risk-prevention measures by applying the KULTURisk methodology (see Chapter 6). The demonstration was implemented in the Ubaye Valley (Barcelonnette town), France. Our findings show that the methodology is an adaptable decision-making tool that may be used to support the analysis of alternative scenarios for flood-risk reduction.