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Computing hydrological fluxes at the Earth's surface is crucial for landscape evolution models, topographic analysis, and geographic information systems. However, existing formalisms, like single or multiple flow algorithms, often rely on ad hoc rules based on local topographic slope and drainage area, neglecting the physics of water flow. While more physics-oriented solutions offer accuracy (e.g. shallow-water equations), their computational costs limit their use in terms of spatial and temporal scales. In this contribution, we introduce GraphFlood, a novel and efficient iterative method for computing river depth and water discharge in 2D with a digital elevation model (DEM). Leveraging the directed acyclic graph structure of surface water flow, GraphFlood iteratively solves the 2D shallow-water equations. This algorithm aims to find the correct hydraulic surface by balancing discharge input and output over the topography. At each iteration, we employ fast-graph-theory algorithms to calculate flow accumulation on the hydraulic surface, approximating discharge input. Discharge output is then computed using the Manning flow resistance equation, similar to the River.lab model (Davy and Lague, 2009). The divergence of discharges iteratively increments flow depth until reaching a stationary state. This algorithm can also solve for flood wave propagation by approximating the input discharge function of the immediate upstream neighbours. We validate water depths obtained with the stationary solution against analytical solutions for rectangular channels and the River.lab and CAESAR-Lisflood models for natural DEMs. GraphFlood demonstrates significant computational advantages over previous hydrodynamic models, an with approximately 10-fold speed-up compared to the River.lab model (Davy and Lague, 2009). Additionally, its computational time scales slightly more than linearly with the number of cells, making it suitable for large DEMs exceeding 106–108 cells. We demonstrate the versatility of GraphFlood by integrating realistic hydrology into various topographic and morphometric analyses, including channel width measurement, inundation pattern delineation, floodplain delineation, and the classification of hillslope, colluvial, and fluvial domains. Furthermore, we discuss its integration potential in landscape evolution models, highlighting its simplicity of implementation and computational efficiency.

The rapidly expanding Himalayan road network connects rural mountainous regions. However, the fragility of the landscape and poor road construction practices lead to frequent mass movements alongside roads. In this study, we investigate fully or partially road-blocking landslides along National Highway (NH-7) in Uttarakhand, India, between Rishikesh and Joshimath. Based on an inventory of >300 landslides along the ∼250 km long corridor following exceptionally high rainfall during September and October 2022, we identify the main controls on the spatial occurrence of mass-movement events. Our analysis and modeling approach conceptualizes landslides as a network-attached spatial point pattern. We evaluate different gridded rainfall products and infer the controls on landslide occurrence using Bayesian analysis of an inhomogeneous Poisson process model. Our results reveal that slope, rainfall amounts, lithology and road widening are the main controls on landslide occurrence. The individual effects of aggregated lithozones are consistent with previous assessments of landslide susceptibilities of rock types in the Himalayas. Our model spatially predicts landslide occurrences and can be adapted to other rainfall scenarios, thus having potential applications for efficiently allocating efforts for road maintenance. To this end, our results highlight the vulnerability of the Himalayan road network to landslides. Climate change and increasing exposure along this pilgrimage route will likely exacerbate landslide risk along the NH-7 in the future.

This special issue focuses on natural hazards and risks in the Himalayan region. Nine research articles address critical gaps in research, from compiling avalanche databases to developing early warning systems for landslides and assessing flood risk and vulnerabilities in urban areas. By fostering interdisciplinary collaboration and leveraging advanced methods, the research presented in this special issue contributes to building safer and more resilient communities in the Himalayan region.

In situ soil pH measurements with ion-selective electrodes (ISEs) are receiving increasing attention in soil mapping for precision agriculture as they can avoid time-consuming sampling and off-site laboratory work. However, unlike the standard laboratory protocol, in situ pH measurements are carried out at lower and varying soil moisture contents (SMCs), which can have a pronounced effect on the sensor readings. In addition, as the contact with the soil during in situ measurements should be relatively short, effects of soil texture could be expected because texture controls the migration of protons to the electrode interface. This may be exacerbated by the fact that the electrodes used for in situ measurements are made of less sensitive but more robust materials as compared to the standard glass electrode. Therefore, the aim of the present study was to investigate the effect of soil moisture and soil texture on pH measurements using robust antimony and epoxy-body ISEs pressed directly into the soil for 30 s. The SMC was gradually increased from dry conditions to field capacity. A wide range of soil texture classes were included, with sand, silt, and clay contents ranging from 16 % to 91 %, 5 % to 44 %, and 4 % to 65 %, respectively. An exponential model was fitted to the data to quantify the relationship between SMC and pH. The results show that an increase in SMC causes a maximum increase in pH of approximately 1.5 pH units, regardless of the type of pH ISE used. Furthermore, for sandy soil textures, a rather linear relationship between pH and SMC was observed, whereas, with decreasing mean particle diameter (MPD), the model had a pronounced exponential shape, i.e., a greater pH increase at low SMC and a plateau effect at high SMC. With increasing SMC, the pH values asymptotically approached the standard pH measured with a glass electrode in 0.01 M CaCl2 (soil : solution ratio of 1:2.5). Thus, at high SMC, subsequent calibration of the sensor pH values to the standard pH value is negligible, which may be relevant for using the sensor pH data for lime requirement estimates. The pH measurement error decreases exponentially with increasing soil moisture and increases with decreasing MPD. Using a knee point detection, reliable pH values were obtained for SMC > 11 %, irrespective of the pH ISE used. An analysis of the regression coefficients of the fitted exponential model showed that the maximum pH increase also depends on soil texture; i.e., the influence of soil moisture variation on the pH value increases with decreasing MPD. Moreover, the concavity of the exponential curve increases with decreasing MPD.

Mass movements play an important role in landscape evolution of high mountain areas such as the Himalayas. Yet, establishing numerical age control and reconstructing transport dynamics of past events is challenging. To fill this research gap, we bring luminescence dating to the test in an extremely challenging environment: the Pokhara Valley in Nepal. This is challenging for two reasons: (i) the optically stimulated luminescence (OSL) sensitivity of quartz, typically the mineral of choice for dating sediments younger than 100 ka, is poor, and (ii) highly rapid and turbid conditions during mass movement transport hamper sufficient OSL signal resetting prior to deposition, which eventually results in age overestimation. Here, we first assess the applicability of single-grain feldspar dating of medieval mass movement deposits catastrophically emplaced in the Pokhara Valley. Second, we exploit the poor bleaching mechanisms to get insight into the sediment dynamics of this paleo-mass movement through bleaching proxies. The Pokhara Valley is a unique setting for our case study, considering the availability of an extensive independent radiocarbon dataset as a geochronological benchmark. Single-grain infrared stimulated luminescence (IRSL) signals were measured at 50 ∘C (IRSL-50) and post-infrared infrared stimulated luminescence signals at 150 ∘C (pIRIR-150). Our results show that the IRSL-50 signal is better bleached than the pIRIR-150 signal. A bootstrapped minimum age model (bMAM) is applied to retrieve the youngest subpopulation to estimate the paleodose. However, burial ages calculated with this paleodose overestimate the radiocarbon ages by an average factor of ∼23 (IRSL-50) and ∼72 (pIRIR-150), showing that dating of the Pokhara Formation with a single-grain approach was not successful for most samples. Some samples, however, only slightly overestimate the true emplacement age and thus could be used for a rough age estimation. Large inheritances in combination with the scatter in the single-grain dose distributions show that the sediments have been transported under extremely limited light exposure prior to deposition, which is consistent with the highly turbid nature of the sediment-laden flood and debris flows depositing the Pokhara gravels. To investigate the sediment transport dynamics in more detail, we studied three bleaching proxies: the percentage of grains in saturation 2D0 criteria, the percentage of best-bleached grains (2σ range of bMAM-De) and the overdispersion (OD). None of the three bleaching proxies indicate a spatial relationship with runout distance of the mass movement deposits. We interpret this as evidence for the lack of bleaching during transport, which reflects the catastrophic nature of the event. While not providing reliable burial ages of the Pokhara mass movement deposits, single-grain feldspar dating can potentially be used as an age range finder method. Our approach shows the potential of luminescence techniques to provide insights in sediment transport dynamics of extreme and rare mass movement events in mountainous regions.

Sediment burial dating using optically stimulated luminescence (OSL) is a well-established tool in geochronology. An important but often inapplicable requirement for its successful use is that the OSL signal is sufficiently reset prior to deposition. However, subaqueous bleaching conditions during fluvial transport are vastly understudied; for example the effect of turbidity and sediment mixing on luminescence bleaching rates is only poorly established. The possibility that slow bleaching rates may dominate under certain transport conditions led to the concept that OSL could be used to derive sediment transport histories. The feasibility of this concept is still to be demonstrated, and experimental set-ups are still to be tested. Our contribution to this scientific challenge involves subaquatic bleaching experiments, in which we suspend saturated coastal sand of Miocene age in a circular flume and illuminate it for discrete time intervals with natural light. We record the in situ energy flux density received by the suspended grains in the UV-NIR frequency range by using a broadband spectrometer with a submersible probe. Our analysis includes pre-profiling of each sample following a polymineral multiple signal (PMS) protocol. Using the PMS, the quartz-dominated, blue-stimulated luminescence signal at 125 ∘C (BSL-125) decays slower than the K-feldspar-dominated, infrared-stimulated luminescence signal at 25 ∘C (IR-25) even under subaerial conditions. The BSL-125 from purified quartz shows the opposite behaviour, which renders the PMS unreliable in our case. We find a negative correlation between suspended-sediment concentration and bleaching rate for all the measured signals. For outdoor bleaching experiments we propose to relate the measured luminescence dose to the cumulative received irradiance rather than to the bleaching time. Increases in the sediment concentration lead to a stronger attenuation of the UV–blue compared to the red–NIR wavelength. This attenuation thereby follows an exponential decay that is controlled by the sediment concentration and a wavelength-dependent decay constant, λ. As such λ could potentially be used in numerical models of luminescence signal resetting in turbid suspensions.

Increased rates of glacier retreat and thinning need accurate local estimates of glacier elevation change to predict future changes in glacier runoff and their contribution to sea level rise. Glacier elevation change is typically derived from digital elevation models (DEMs) tied to surface change analysis from satellite imagery. Yet, the rugged topography in mountain regions can cast shadows onto glacier surfaces, making it difficult to detect local glacier elevation changes in remote areas. A rather untapped resource comprises precise, time-stamped metadata on the solar position and angle in satellite images. These data are useful for simulating shadows from a given DEM. Accordingly, any differences in shadow length between simulated and mapped shadows in satellite images could indicate a change in glacier elevation relative to the acquisition date of the DEM. We tested this hypothesis at five selected glaciers with long-term monitoring programmes. For each glacier, we projected cast shadows onto the glacier surface from freely available DEMs and compared simulated shadows to cast shadows mapped from ∼40 years of Landsat images. We validated the relative differences with geodetic measurements of glacier elevation change where these shadows occurred. We find that shadow-derived glacier elevation changes are consistent with independent photogrammetric and geodetic surveys in shaded areas. Accordingly, a shadow cast on Baltoro Glacier (the Karakoram, Pakistan) suggests no changes in elevation between 1987 and 2020, while shadows on Great Aletsch Glacier (Switzerland) point to negative thinning rates of about 1 m yr−1 in our sample. Our estimates of glacier elevation change are tied to occurrence of mountain shadows and may help complement field campaigns in regions that are difficult to access. This information can be vital to quantify possibly varying elevation-dependent changes in the accumulation or ablation zone of a given glacier. Shadow-based retrieval of glacier elevation changes hinges on the precision of the DEM as the geometry of ridges and peaks constrains the shadow that we cast on the glacier surface. Future generations of DEMs with higher resolution and accuracy will improve our method, enriching the toolbox for tracking historical glacier mass balances from satellite and aerial images.

Landscape evolution models can be used to assess the impact of rainfall variability on bedrock river incision over millennial timescales. However, isolating the role of rainfall variability remains difficult in natural environments, in part because environmental controls on river incision such as lithological heterogeneity are poorly constrained. In this study, we explore spatial differences in the rate of bedrock river incision in the Ecuadorian Andes using three different stream power models. A pronounced rainfall gradient due to orographic precipitation and high lithological heterogeneity enable us to explore the relative roles of these controls. First, we use an area-based stream power model to scrutinize the role of lithological heterogeneity in river incision rates. We show that lithological heterogeneity is key to predicting the spatial patterns of incision rates. Accounting for lithological heterogeneity reveals a nonlinear relationship between river steepness, a proxy for river incision, and denudation rates derived from cosmogenic radionuclide (CRNs). Second, we explore this nonlinearity using runoff-based and stochastic-threshold stream power models, combined with a hydrological dataset, to calculate spatial and temporal runoff variability. Statistical modeling suggests that the nonlinear relationship between river steepness and denudation rates can be attributed to a spatial runoff gradient and incision thresholds. Our findings have two main implications for the overall interpretation of CRN-derived denudation rates and the use of river incision models: (i) applying sophisticated stream power models to explain denudation rates at the landscape scale is only relevant when accounting for the confounding role of environmental factors such as lithology, and (ii) spatial patterns in runoff due to orographic precipitation in combination with incision thresholds explain part of the nonlinearity between river steepness and CRN-derived denudation rates. Our methodology can be used as a framework to study the coupling between river incision, lithological heterogeneity and climate at regional to continental scales.

Drainage divides are organized into tree-like networks that may record information about drainage divide mobility. However, views diverge about how to best assess divide mobility. Here, we apply a new approach of automatically extracting and ordering drainage divide networks from digital elevation models to results from landscape evolution model experiments. We compared landscapes perturbed by strike-slip faulting and spatiotemporal variations in erodibility to a reference model to assess which topographic metrics (hillslope relief, flow distance, and χ) are diagnostic of divide mobility. Results show that divide segments that are a minimum distance of ∼5 km from river confluences strive to attain constant values of hillslope relief and flow distance to the nearest stream. Disruptions of such patterns can be related to mobile divides that are lower than stable divides, closer to streams, and often asymmetric in shape. In general, we observe that drainage divides high up in the network, i.e., at great distances from river confluences, are more susceptible to disruptions than divides closer to these confluences and are thus more likely to record disturbance for a longer time period. We found that across-divide differences in hillslope relief proved more useful for assessing divide migration than other tested metrics. However, even stable drainage divide networks exhibit across-divide differences in any of the studied topographic metrics. Finally, we propose a new metric to quantify the connectivity of divide junctions.

We propose a novel way to measure and analyze networks of drainage divides from digital elevation models. We developed an algorithm that extracts drainage divides based on the drainage basin boundaries defined by a stream network. In contrast to streams, there is no straightforward approach to order and classify divides, although it is intuitive that some divides are more important than others. A meaningful way of ordering divides is the average distance one would have to travel down on either side of a divide to reach a common stream location. However, because measuring these distances is computationally expensive and prone to edge effects, we instead sort divide segments based on their tree-like network structure, starting from endpoints at river confluences. The sorted nature of the network allows for assigning distances to points along the divides, which can be shown to scale with the average distance downslope to the common stream location. Furthermore, because divide segments tend to have characteristic lengths, an ordering scheme in which divide orders increase by 1 at junctions mimics these distances. We applied our new algorithm to the Big Tujunga catchment in the San Gabriel Mountains of southern California and studied the morphology of the drainage divide network. Our results show that topographic metrics, like the downstream flow distance to a stream and hillslope relief, attain characteristic values that depend on the drainage area threshold used to derive the stream network. Portions along the divide network that have lower than average relief or are closer than average to streams are often distinctly asymmetric in shape, suggesting that these divides are unstable. Our new and automated approach thus helps to objectively extract and analyze divide networks from digital elevation models.

The evaluation and verification of landscape evolution models (LEMs) has long been limited by a lack of suitable observational data and statistical measures which can fully capture the complexity of landscape changes. This lack of data limits the use of objective function based evaluation prolific in other modelling fields, and restricts the application of sensitivity analyses in the models and the consequent assessment of model uncertainties. To overcome this deficiency, a novel model function approach has been developed, with each model function representing an aspect of model behaviour, which allows for the application of sensitivity analyses. The model function approach is used to assess the relative sensitivity of the CAESAR-Lisflood LEM to a set of model parameters by applying the Morris method sensitivity analysis for two contrasting catchments. The test revealed that the model was most sensitive to the choice of the sediment transport formula for both catchments, and that each parameter influenced model behaviours differently, with model functions relating to internal geomorphic changes responding in a different way to those relating to the sediment yields from the catchment outlet. The model functions proved useful for providing a way of evaluating the sensitivity of LEMs in the absence of data and methods for an objective function approach.

The analysis of longitudinal river profiles is an important tool for studying landscape evolution. However, characterizing river profiles based on digital elevation models (DEMs) suffers from errors and artifacts that particularly prevail along valley bottoms. The aim of this study is to characterize uncertainties that arise from the analysis of river profiles derived from different, near-globally available DEMs. We devised new algorithms – quantile carving and the CRS algorithm – that rely on quantile regression to enable hydrological correction and the uncertainty quantification of river profiles. We find that globally available DEMs commonly overestimate river elevations in steep topography. The distributions of elevation errors become increasingly wider and right skewed if adjacent hillslope gradients are steep. Our analysis indicates that the AW3D DEM has the highest precision and lowest bias for the analysis of river profiles in mountainous topography. The new 12 m resolution TanDEM-X DEM has a very low precision, most likely due to the combined effect of steep valley walls and the presence of water surfaces in valley bottoms. Compared to the conventional approaches of carving and filling, we find that our new approach is able to reduce the elevation bias and errors in longitudinal river profiles.

Landscape evolution models (LEMs) allow the study of earth surface responses to changing climatic and tectonic forcings. While much effort has been devoted to the development of LEMs that simulate a wide range of processes, the numerical accuracy of these models has received less attention. Most LEMs use first-order accurate numerical methods that suffer from substantial numerical diffusion. Numerical diffusion particularly affects the solution of the advection equation and thus the simulation of retreating landforms such as cliffs and river knickpoints. This has potential consequences for the integrated response of the simulated landscape. Here we test a higher-order flux-limiting finite volume method that is total variation diminishing (TVD-FVM) to solve the partial differential equations of river incision and tectonic displacement. We show that using the TVD-FVM to simulate river incision significantly influences the evolution of simulated landscapes and the spatial and temporal variability of catchment-wide erosion rates. Furthermore, a two-dimensional TVD-FVM accurately simulates the evolution of landscapes affected by lateral tectonic displacement, a process whose simulation was hitherto largely limited to LEMs with flexible spatial discretization. We implement the scheme in TTLEM (TopoToolbox Landscape Evolution Model), a spatially explicit, raster-based LEM for the study of fluvially eroding landscapes in TopoToolbox 2.

Globalisation and interregional exchange of people, goods, and services has boosted the importance of and reliance on all kinds of transport networks. The linear structure of road networks is especially sensitive to natural hazards. In southern Norway, steep topography and extreme weather events promote frequent traffic disruption caused by debris flows. Topographic susceptibility and trigger frequency maps serve as input into a hazard appraisal at the scale of first-order catchments to quantify the impact of debris flows on the road network in terms of a failure likelihood of each link connecting two network vertices, e.g. road junctions. We compute total additional traffic loads as a function of traffic volume and excess distance, i.e. the extra length of an alternative path connecting two previously disrupted network vertices using a shortest-path algorithm. Our risk metric of link failure is the total additional annual traffic load, expressed as vehicle kilometres, because of debris-flow-related road closures. We present two scenarios demonstrating the impact of debris flows on the road network and quantify the associated path-failure likelihood between major cities in southern Norway. The scenarios indicate that major routes crossing the central and north-western part of the study area are associated with high link-failure risk. Yet options for detours on major routes are manifold and incur only little additional costs provided that drivers are sufficiently well informed about road closures. Our risk estimates may be of importance to road network managers and transport companies relying on speedy delivery of services and goods.

Meltwater delivered to the bed of the Greenland Ice Sheet is a driver of variable ice-motion through changes in effective pressure and enhanced basal lubrication. Ice surface velocities have been shown to respond rapidly both to meltwater production at the surface and to drainage of supraglacial lakes, suggesting efficient transfer of meltwater from the supraglacial to subglacial hydrological systems. Although considerable effort is currently being directed towards improved modelling of the controlling surface and basal processes, modelling the temporal and spatial evolution of the transfer of melt to the bed has received less attention. Here we present the results of spatially distributed modelling for prediction of moulins and lake drainages on the Leverett Glacier in Southwest Greenland. The model is run for the 2009 and 2010 ablation seasons, and for future increased melt scenarios. The temporal pattern of modelled lake drainages are qualitatively comparable with those documented from analyses of repeat satellite imagery. The modelled timings and locations of delivery of meltwater to the bed also match well with observed temporal and spatial patterns of ice surface speed-ups. This is particularly true for the lower catchment (

TopoToolbox is a MATLAB program for the analysis of digital elevation models (DEMs). With the release of version 2, the software adopts an object-oriented programming (OOP) approach to work with gridded DEMs and derived data such as flow directions and stream networks. The introduction of a novel technique to store flow directions as topologically ordered vectors of indices enables calculation of flow-related attributes such as flow accumulation ∼20 times faster than conventional algorithms while at the same time reducing memory overhead to 33% of that required by the previous version. Graphical user interfaces (GUIs) enable visual exploration and interaction with DEMs and derivatives and provide access to tools targeted at fluvial and tectonic geomorphologists. With its new release, TopoToolbox has become a more memory-efficient and faster tool for basic and advanced digital terrain analysis that can be used as a framework for building hydrological and geomorphological models in MATLAB.

Along the southeastern margin of the Tibetan Plateau, the onset of rapid fluvial incision during the Miocene is commonly attributed to growth of high topography. Recent recognition of lacustrine strata preserved atop interfluves, however, suggest that headward expansion of river networks drove migration of the topographic divide. Here, we explore the impact of this process on fluvial incision along the Yangtze River. Landscape evolution simulations demonstrate that expansion of the Yangtze watershed since the Late Miocene could be responsible for 1 to 2 kilometers of fluvial incision. The distribution of modern knickpoints and river profiles is consistent with this hypothesis. We suggest that increased erosive power associated with capture and basin integration drove accelerated incision during the Late Miocene. Our results imply that eastern Tibet was elevated before middle Cenozoic time and that the tempo of fluvial incision may be out of phase with uplift of plateau topography.

On 7 February 2021, a catastrophic mass flow descended the Ronti Gad, Rishiganga, and Dhauliganga valleys in Chamoli, Uttarakhand, India, causing widespread devastation and severely damaging two hydropower projects. More than 200 people were killed or are missing. Our analysis of satellite imagery, seismic records, numerical model results, and eyewitness videos reveals that ~27 × 10 6 cubic meters of rock and glacier ice collapsed from the steep north face of Ronti Peak. The rock and ice avalanche rapidly transformed into an extraordinarily large and mobile debris flow that transported boulders greater than 20 meters in diameter and scoured the valley walls up to 220 meters above the valley floor. The intersection of the hazard cascade with downvalley infrastructure resulted in a disaster, which highlights key questions about adequate monitoring and sustainable development in the Himalaya as well as other remote, high-mountain environments., (Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Geomorphic footprints of past large Himalayan earthquakes are elusive, although they are urgently needed for gauging and predicting recovery times of seismically perturbed mountain landscapes. We present evidence of catastrophic valley infill following at least three medieval earthquakes in the Nepal Himalaya. Radiocarbon dates from peat beds, plant macrofossils, and humic silts in fine-grained tributary sediments near Pokhara, Nepal's second-largest city, match the timing of nearby M > 8 earthquakes in ~1100, 1255, and 1344 C.E. The upstream dip of tributary valley fills and x-ray fluorescence spectrometry of their provenance rule out local sources. Instead, geomorphic and sedimentary evidence is consistent with catastrophic fluvial aggradation and debris flows that had plugged several tributaries with tens of meters of calcareous sediment from a Higher Himalayan source >60 kilometers away., (Copyright © 2016, American Association for the Advancement of Science.)