Complex Mountain Research Articles

Mountain Segmentation Based on Global Optimization with the Cloth Simulation Constraint

Mountains are an important research object for surveying, mapping, cartography, space science, and ecological remote sensing. Automatic mountain segmentation is one of the most critical techniques in large-scale mountain analyses. However, several factors limit the segmentation accuracy, such as the complexity of mountains, the noise of geospatial data, and the confusion in distinguishing non-mountainous objects with similar features. In order to improve the accuracy of mountain segmentation against these limiting factors, we impose the cloth constraint over the digital elevation model (DEM) with the underlying assumption that the mountain has a sizeable relative elevation and slope. We propose a robust mountain segmentation method with the cloth simulation constraint. The core algorithm extracts the relative elevation of the region using a cloth simulation filtering algorithm by transforming the mountain segmentation problem into an optimization problem based on the global energy function consisting of the relative elevation and slope. Experiments on a wide range of Earth and lunar elevation datasets with some of the aforementioned limitations show that the proposed method can extract complex mountain baselines, avoid the misclassification of lunar craters, and significantly improve the robustness and accuracy of mountain segmentation. Compared to three state-of-the-art methods (the Lunar Mountain Detection Method, the Landform Mask Method in SNAP™ from European Space Agency (located in Paris, France), and the Multiscale Segmentation Method in eCognition™ from Definiens Imaging (located in Munich, Germany), the F1 and IoU improved by 14.70% and 20.46% on average and 29.07% and 38.94% at most, respectively, which validates that the proposed method has a better all-around performance.

Evolution of global snow drought characteristics from 1850 to 2100

Seasonal snow is an integral part of the global water supply and storage system. Snow droughts impact ecological, agricultural, and urban systems by altering the amount and timing of meltwater delivery. These droughts are characterized by a lack of on-the-ground snow (snow water equivalent, SWE) that can be caused by low total precipitation (dry drought) or low proportion of precipitation falling as snowfall (warm drought), often combined with an early melt. The standardized SWE index (SWEI) ranks the current status of SWE for a given location compared to a baseline condition and identifies the existence, but not the cause, of snow drought. In this work, we use estimates of SWE, temperature, and precipitation from nine coupled model intercomparison project phase 6 (CMIP6) models to quantify the frequency, severity, and type of snow droughts globally for historical and future scenarios. Compared to a historical baseline (1850–1900) total snow drought frequency more than doubles under socio-economic pathway (SSP)2-4.5 and SSP5-8.5; all of the increase in snow drought frequency comes from an increase in warm droughts. The probability distribution of future SWEI in major snowy basins around the world are likely to be centered on more negative values, which corresponds to more severe drought and, with only moderate changes in distribution spread, more frequent drought. CMIP6 simulations pinpoint snow drought as an emerging global threat to water resources and highlight the need to explore higher resolution future models that better capture complex mountain topography, wildland fires, and snow-forest interactions.

Modelling of the Solar-Light Climate of Mountain Terrain is a Prerequisite for Assessing the Insolation and Illumination of Premises

The article analyses the current documents regulating the requirements of the insolation of premises and urban areas, as well as the solar-light regime of territories depending on the boundaries of zones along geographical latitudes for the conditions of complex mountainous terrain in order to identify their degree of study. In this regard, it is determined that in the above maps, the zoning of territories, countries on mountainous terrain are highlighted as an unexplored or poorly studied zone in terms of climatic and solar-light factors. The indicators of the solar-light climate of mountain territories characterized by a special insolation-light-climatic condition are highlighted. The algorithm for solving the problem is defined, which includes the assessment and analysis of the solar-light climate of a characteristic mountainous complex relief, revealing the influence of complex relief on light-climatic characteristics. A methodology for assessing qualitative and quantitative indicators of solar radiation, the state of the atmosphere, the probability and duration of sunshine, the magnitude and nature of changes in time of direct, scattered, reflected, and total radiation coming to horizontal and variously oriented inclined, vertical surfaces, the ratio of the latter on complex mountainous terrain potentially construction, causing the solar-light environment of buildings are considered. It is established that the information material obtained on the basis of research on the amount of radiation coming from the solar dome on inclined surfaces of various orientations allows us to more accurately take into account its effect on the indoor light-climatic regime and, along with it, determines the direction of further research when assessing also the factors of indoor microclimate and thermo-physical characteristics of enclosing structures. A method for modelling characteristic landforms with determining their typology has been developed and a regularity has been established for the flow of direct, scattered, reflected and total solar radiation to differently oriented slopes, which determine the light climate of building premises, which can serve to assess its insolation-light-climatic regime, as well as to correct the calculation method of illuminance levels.

The Contribution of Microrefugia to Landscape Thermal Inertia for Climate‐Adaptive Conservation Strategies

AbstractCurrent temperatures in microrefugia may persist longer than in nearby areas as temperatures warm. However, locating and measuring the contribution of microrefugia to thermal inertia in a landscape is challenging. We measured the thermal buffering capacity of microrefugia across a 40,000 km2 region of complex mountain topography by quantifying environmental lapse rate and solar radiation effects on air temperature in 0.1 km2 hexagons, a resource management‐relevant scale for climate adaptation. The greatest buffering capacity is −1.62°C, and only 2.8% of the region can buffer 1°C or greater. Historical loss of local cooling capacity is low, but by 2069 only 6.9%–11% of the region retains baseline temperature conditions. This thermal buffer index can find the most climate change‐buffered areas in lands identified as high priority for habitat conservation, wildlife corridors, and forest preservation. Other processes such as cold air pooling can complement our approach but depend on additional factors.

Characteristics of Coastal Low-Level Jets in the Boundary Layer of the Pearl River Estuary

It is well-known that coastal low-level jets (CLLJs) play an essential role in transporting heat, water vapor and pollutants. However, the CLLJ characteristics in the Pearl River Estuary have not been deeply revealed due to the lack of long-term observations. Based on the long-term observations from a wind lidar, we analyze the primary climatic characteristics of the CLLJs in the Pearl River Estuary and investigate their relationships with large-scale and local-scale synoptic systems. The results show that the CLLJs mainly appear during the flood season, with the most occurrence in May. The CLLJ occurrence during the flood season is mainly influenced by the large-scale north–south pressure gradient driven by the western Pacific subtropical high and terrestrial low-pressure systems. The occurrence of the CLLJs exhibits a distinct diurnal cycle with two different peaks in different seasons. One peak appears at nighttime, mainly during non-flood seasons. The other appears in the afternoon, mainly during the flood season. In the non-flood seasons, under the influence of cold air, the inertial oscillations triggered by the land–sea thermal contrast lead to CLLJ onset at nighttime in the Pearl River Estuary. During the flood season, the strong near-surface pressure gradient contributes to CLLJ onset in the afternoon, while the topography (blocking and passing) is more conducive to the occurrence of the CLLJs in the Pearl River Estuary. These findings reveal the formation mechanisms of the CLLJs over the Pearl River Estuary, thus providing a basis for further understanding the precipitation in the Pearl River Estuary and the occurrence of the CLLJs in other coastal areas with complex mountain ranges.

First Passage Dynamic Reliability Analysis of Non-Stationary and Non-Gaussian Buffeting Random Dynamic Responses of Long-Span Suspension Bridge

In the complex mountain wind environment, especially in the strong wind, fluctuating wind speed is a non-stationary and non-Gaussian random process. With the increase of suspension bridges’ span, they are more sensitive to wind-induced vibration response. In this paper, a non-stationary and non-Gaussian buffeting reliability analysis method for long-span bridges is presented. Firstly, the non-stationary wind speed is simulated by the modulation function based on the stationary wind speed model. Secondly, the load is obtained by simulated wind speed, the obtained loads are loaded on the finite element model by ANSYS and the whole bridge time-domain analysis is performed, the time history of displacement response is obtained. Thirdly, based on the first excursion failure criterion of random vibration, the samples of the non-stationary and non-Gaussian displacement time history are transformed into a standard Gaussian process through a modified Fleishman approximation method, and then the non-stationary Poisson distribution method is used for structural reliability analysis. Finally, a mountainous long-span suspension bridge is used as the engineering background, and the proposed reliability analysis method is applied to analyze the reliability of the bridge. The influence of different wind attack angles and modulation functions on the dynamic reliability of the bridge is further studied. The results indicate that the displacement response obtained by the transformation of non-stationary and non-Gaussian random process is less reliable than that obtained by traditional analysis method. Its dynamic reliability is maximum at 1[Formula: see text] wind attack angle, the reliability of negative wind attack angle is lower than that of positive wind attack angle, and decreases with the increase of wind attack angle. The reliability obtained by using different modulation functions is lower than that of traditional method. If the traditional analysis method is still used for reliability analysis, it will produce unsafe consequences and reduce the engineering safety reserve.

Comparative Study on Remote Sensing Methods for Forest Height Mapping in Complex Mountainous Environments

Forest canopy height is one of the critical parameters for carbon sink estimation. Although spaceborne lidar data can obtain relatively high precision canopy height on discrete light spots, to obtain continuous canopy height, the integration of optical remote sensing image data is required to achieve “from discrete to continuous” extrapolation based on different prediction models (parametric model and non-parametric model). This study focuses on the Shangri-La area and seeks to assess the practical applicability of two predictive models under complex mountainous conditions, using a combination of active and passive remote sensing data from ICESat-2 and Sentinel-2. The research aims to enhance our understanding of the effectiveness of these models in addressing the unique challenges presented by mountainous terrain, including rugged topography, variable vegetation cover, and extreme weather conditions. Through this work, we hope to contribute to the development of improved geospatial prediction algorithms for mountainous regions worldwide. The results show the following: (1) the fitting effect of the selected parametric model (empirical function regression) is poor in the area of Quercus acutissima and Pinus yunnanensis; (2) evaluation of the importance of each explanatory variable in the non-parametric model (random forest regression) shows that topographic and meteorological factors play a dominant role in canopy height inversion; (3) when random forest regression is applied to the inversion of canopy height, there is often a problem of error accumulation, which is of particular concern to the Quercus acutissima and Pinus yunnanensis; (4) the random forest regression with the optimal features has relatively higher precision by comparing the inversion accuracy of canopy height data of the empirical function regression, random forest regression with all features, and random forest regression with the optimal features in the study area, i.e., R2 (coefficient of determination) = 0.865 and RMSE (root mean square error) = 3.184 m. In contrast, the poor estimation results reflected by the empirical function regression, mainly resulting from the lack of consideration of topographic and meteorological factors, are not applicable to the inversion of canopy height under complex topographic conditions.

Ediacaran‐Ordovician Magmatism and REE Mineralization in the Wet Mountains, Colorado, USA: Implications for Failed Continental Rifting

AbstractStructures associated with Ediacaran‐Ordovician alkaline magmatism and the timing of rare earth element (REE) mineralization in the Wet Mountains, CO, were analyzed using field, geophysical, and U‐Th‐Pb isotope methods to interpret their tectonic setting in the context of previously proposed rift models. The Wet Mountains are known for thorium and REE mineralization associated with failed rift‐related, Ediacaran‐Ordovician alkaline intrusions and veins. Structural field data indicate that alkaline dikes and mineralized veins are controlled by a system of northwest‐striking, high‐angle faults and tension fractures formed in a 040°‐directed extensional regime. Magnetic and surface expressions of Democrat Creek and McClure Mountain complexes show tectonic elongation toward ∼045°, consistent with NE‐directed extension. Magnetic data also suggest the existence of a fourth, previously unrecognized mafic‐ultramafic complex of inferred Cambrian age with a similar elongated orientation. Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA‐ICP‐MS) 208Pb/232Th analysis of low‐uranium zircon from carbonatite dikes and in situ 206Pb/238U LA‐ICP‐MS analysis of monazite in mineralized dikes yielded 465 ± 18 Ma and 489 ± 33 Ma ages, respectively. These ages are consistent with the expected age based on slightly older, cross‐cut syenite dikes and the hypothesized Ordovician end to failed rift‐related magmatism. The Ediacaran‐Ordovician age of alkaline magmatic rocks and the associated northeast‐directed extension direction are similar to those of the along‐strike, Ediacaran‐Cambrian Southern Oklahoma Aulacogen. Therefore, the failed rift system in the Wet Mountains is interpreted to be a northwestern continuation of the Southern Oklahoma Aulacogen with carbonatite magmatism and thorium/REE mineralization representing late intrusive phases.

Spaceborne LiDAR for characterizing forest structure across scales in the European Alps

AbstractThe launch of NASA's Global Ecosystem Dynamics Investigation (GEDI) mission in 2018 opens new opportunities to quantitatively describe forest ecosystems across large scales. While GEDI's height‐related metrics have already been extensively evaluated, the utility of GEDI for assessing the full spectrum of structural variability—particularly in topographically complex terrain—remains incompletely understood. Here, we quantified GEDI's potential to estimate forest structure in mountain landscapes at the plot and landscape level, with a focus on variables of high relevance in ecological applications. We compared five GEDI metrics including relative height percentiles, plant area index, cover and understory cover to airborne laser scanning (ALS) data in two contrasting mountain landscapes in the European Alps. At the plot level, we investigated the impact of leaf phenology and topography on GEDI's accuracy. At the landscape‐scale, we evaluated the ability of GEDIs sample‐based approach to characterize complex mountain landscapes by comparing it to wall‐to‐wall ALS estimates and evaluated the capacity of GEDI to quantify important indicators of ecosystem functions and services (i.e., avalanche protection, habitat provision, carbon storage). Our results revealed only weak to moderate agreement between GEDI and ALS at the plot level (R2 from 0.03 to 0.61), with GEDI uncertainties increasing with slope. At the landscape‐level, however, the agreement between GEDI and ALS was generally high, with R2 values ranging between 0.51 and 0.79. Both GEDI and ALS agreed in identifying areas of high avalanche protection, habitat provision, and carbon storage, highlighting the potential of GEDI for landscape‐scale analyses in the context of ecosystem dynamics and management.

Evolutionary origin and establishment of a dioecious diploid-tetraploid complex.

Polyploids recurrently emerge in angiosperms, but most polyploids are likely to go extinct before establishment due to minority cytotype exclusion, which may be specifically a constraint for dioecious plants. Here we test the hypothesis that a stable sex-determination system and spatial/ecological isolation facilitate the establishment of dioecious polyploids. We determined the ploidy levels of 351 individuals from 28 populations of the dioecious species Salix polyclona, and resequenced 190 individuals of S.polyclona and related taxa for genomic diversity analyses. The ploidy survey revealed a frequency 52% of tetraploids in S.polyclona, and genomic k-mer spectra analyses suggested an autopolyploid origin for them. Comparisons of diploid male and female genomes identified a female heterogametic sex-determining factor on chromosome 15, which probably also acts in the dioecious tetraploids. Phylogenetic analyses revealed two diploid clades and a separate clade/grade of tetraploids with a distinct geographic distribution confined to western and central China, where complex mountain systems create higher levels of environmental heterogeneity. Fossil-calibrated phylogenies showed that the polyploids emerged during 7.6-2.3million years ago, and population demographic histories largely matched the geological and climatic history of the region. Our results suggest that inheritance of the sex-determining system from the diploid progenitor as intrinsic factor and spatial isolation as extrinsic factor may have facilitated the preservation and establishment of polyploid dioecious populations.

Newly recognized blueschist-facies metamorphism (glaucophane-omphacite-garnet), Belvidere Mountain Complex, northern Appalachians

Abstract An occurrence of blueschistfacies metamorphism in the Appalachian orogen is newly recognized in northwestern New England, United States. Inclusions of glaucophane and omphacite occur in a relict garnet core from a retrogressed garnetbarroisite amphibolite of the Belvidere Mountain Complex in Vermont. Pressuretemperature pseudosection and mineral composition isopleth calculations demonstrate that the Belvidere Mountain Complex blueschistfacies mineral assemblage of glaucophane–magnesio-hornblende–omphacite–chlorite–rutile–quartz–clinozoisite–garnet was stable at ~1.65–2.0 GPa and ~450–480 °C. Garnetabsent amphibolite with barroisite and chlorite inclusions in clinozoisite records highpressure epidote-amphibolite–facies metamorphism at ~1.0–1.4 GPa and ~515–550 °C. These new findings quantify deep subduction of the Belvidere Mountain Complex during the Cambrian to Ordovician Taconic orogenic cycle and suggest that more blueschistfacies mineral assemblages could be revealed in the Appalachians with detailed analysis of retrogressed rocks.

Validation of FABDEM, a global bare-earth elevation model, against UAV-lidar derived elevation in a complex forested mountain catchment

Space-based, global-extent digital elevation models (DEMs) are key inputs to many Earth sciences applications. However, many of these applications require the use of a ‘bare-Earth’ DEM versus a digital surface model (DSM), the latter of which may include systematic positive biases due to tree canopies in forested areas. Critical topographic features may be obscured by these biases. Vegetation-free datasets have been created by using statistical relationships and machine learning to train on local-scale datasets (e.g., lidar) to de-bias the global-extent datasets. Recent advances in satellite platforms coupled with increased availability of computational resources and lidar reference products has allowed for a new generation of vegetation- and urban-canopy removals. One of these is the Forest And Buildings removed Copernicus DEM (FABDEM), based on the most recent and most accurate global DSM Copernicus-30. Among the more challenging landscapes to quantify surface elevations are densely forested mountain catchments, where even airborne lidar applications struggle to capture surface returns. The increasing affordability and availability of UAV-based lidar platforms have resulted in new capacity to fly modest spatial extents with unrivalled point densities. These data allow an unprecedented ability to validate global sub-canopy DEMs against representative UAV-based lidar data. In this work, the FABDEM is validated against up-scaled lidar data in a steep and forested mountain catchment considering elevation, slope, and Terrain Position Index (TPI) metrics. Comparisons of FABDEM with SRTM, MERIT, and the Copernicus-30 dataset are made. It was found that the FABDEM had a 24% reduction in elevation RMSE and a 135% reduction in bias compared to the Copernicus-30 dataset. Overall, the FABDEM provides a clear improvement over existing deforested DEM products in complex mountain topography such as the MERIT DEM. This study supports the use of FABDEM in forested mountain catchments as the current best-in-class data product.

Sentinel-2 time series analysis for monitoring multi-taxon biodiversity in mountain beech forests

Biodiversity monitoring represents a major challenge to supporting proper forest ecosystem management and biodiversity conservation. The latter is indeed shifting in recent years from single-species to multi-taxon approaches. However, multi-taxonomic studies are quite rare due to the effort required for performing field surveys. In this context, remote sensing is a powerful tool, continuously providing consistent and open access data at a different range of spatial and temporal scales. In particular, the Sentinel-2 (S2) mission has great potential to produce reliable proxies for biological diversity. In beech forests of two Italian National Parks, we sampled the beetle fauna, breeding birds, and epiphytic lichens. First, we calculated Shannon’s entropy and Simpson’s diversity. Then, to produce variables for biodiversity assessment, we exploited S2 data acquired in the 4 years 2017–2021. S2 images were used to construct spectral bands and photosynthetic indices time series, from which 91 harmonic metrics were derived. For each taxon and multi-taxon community, we assessed the correlation with S2 harmonic metrics, biodiversity indices, and forest structural variables. Then, to assess the potential of the harmonic metrics in predicting species diversity in terms of Shannon’s and Simpson’s biodiversity indices, we also fit a random forests model between each diversity index and the best 10 harmonic metrics (in terms of absolute correlation, that is, the magnitude of the correlation) for each taxon. The models’ performance was evaluated via the relative root mean squared error (RMSE%). Overall, 241 beetle, 27 bird, and 59 lichen species were recorded. The diversity indices were higher for the multi-taxon community than for the single taxa. They were generally higher in the CVDA site than in GSML, except for the bird community. The highest correlation values between S2 data and biodiversity indices were recorded in CVDA for multi-taxon and beetle communities (| r| = 0.52 and 0.38, respectively), and in GSML for lichen and beetle communities (| r| = 0.34 and 0.26, respectively). RMSE% ranged between 2.53 and 9.99, and between 8.1 and 16.8 for the Simpson and Shannon index, respectively. The most important variables are phase and RMSE of red-Edge bands for bird and lichen communities, while RMSE and time of tassel cap and from EVI indices for beetles and multi-taxon diversity. Our results demonstrate that S2 data can be used for identifying potential biodiversity hotspots, showing that the herein presented harmonic metrics are informative for several taxa inhabiting wood, giving concrete support to cost-effective biodiversity monitoring and nature-based forest management in complex mountain systems.

Chusquea calderoniae (Poaceae: Bambusoideae), a new species of C. subg. Chusquea endemic to the Espinhaço Range, Brazil

Chusquea is the richest genus of Neotropical bamboos, occurring from Mexico to Argentina and Brazil, with 198 accepted species. In Brazil, 49 members of this genus have been recorded, with the Eastern region being its main center of diversity, especially in the states of Bahia, Minas Gerais, and Rio de Janeiro. The Espinhaço Range, found within this region, is considered the largest mountain complex in Brazil, including campo rupestre, caatinga, and cerrado vegetation types and transitional types among these, which explains the particular plant diversity of this region. Our recent taxonomic studies on Brazilian Chusquea subg. Chusquea indicated the presence of a new species herein described and illustrated, named C. calderoniae. It is morphologically related to the C. meyeriana informal group, being most similar to C. attenuata, but differing by the shape of the central bud and the length of the spikelet structures. The new species is endemic to the Espinhaço Range, occurring in riparian forest on the flanks of Pico das Almas, Chapada Diamantina, Bahia, and the Diamantina Plateau in Minas Gerais state, associated to campo rupestre vegetation, in contrast to C. attenuata, which occurs in the Atlantic rainforest in the states of Minas Gerais and Rio de Janeiro.

Numerical Simulation of Wind Characteristics in Complex Mountains with Focus on Terrain Boundary Transition Curve

In recent years, an increasing number of projects have been developed in complex mountainous areas. The wind environment in mountainous areas, extremely complex due to the undulating terrain and diverse landscapes, is a key factor threatening the structural safety of buildings and their appurtenances in mountainous areas. Therefore, it is important to study the wind environment in complex terrain to clarify the wind resistance of structures in mountainous areas. Computational fluid dynamics (CFD) approaches are commonly used to examine wind fields in complex terrain; however, due to the limited range of terrain considered, direct modeling using terrain elevation data can result in truncated elevation differences, affecting the accuracy of numerical simulations. To address the problem of truncated elevation differences at terrain boundaries, the parameters of the wind tunnel contraction curve are optimized regarding the wind tunnel contraction section design principle. Moreover, several transition curves are analyzed and evaluated by numerical simulation methods, and a transition curve applicable to the terrain boundary transition form is proposed. The proposed terrain transition curves are applied to model the terrain of complex mountainous ski resort areas to be used in CFD numerical simulations. Furthermore, the accuracy of the numerical simulation is verified through a comparison with the field-measured data. Results indicate that the proposed method can accurately and effectively reflect the wind environment characteristics of a ski resort area. The proposed terrain transition curve provides a theoretical basis and case support for designing the terrain model boundary transition section, which can be used as a reference for wind tunnel and numerical simulation studies in complex mountainous areas.

Proximal to distal geochemical variations of the Ruwai polymetallic skarn deposit, Central Borneo, Indonesia: Insights from sulfides chemistry and implications to exploration

The Ruwai deposit is the largest polymetallic skarn deposit in Borneo and is located within the Schwaner Mountains Complex. The mineralization is hosted by metalimestone of the Jurassic Ketapang Complex and the causative intrusions belong to the Cretaceous Sukadana Granitoids. Despite its large resources, the geochemical characteristics of the Ruwai skarn are still not well known. Thus, this study provides the whole-rock geochemistry of the skarn, metalimestone and intrusions, as well as the chemical compositions of sulfides (i.e., pyrite, sphalerite, galena, and chalcopyrite). The occurrence of skarn mineralization can be divided into proximal (Gojo-Karim) and distal (Central Gossan-Southwest Gossan) zones. Furthermore, the mineralization stage can be divided into prograde, retrograde and supergene stages. The whole-rock geochemical analyses clearly show that the skarn is enriched in several metals such as Ag, Nb, Co, La, Cu, V, Zr and Ti, which are higher in intrusions compared to metalimestone, which implies that these metals are mostly derived from magma. On the other hand, the skarn is also enriched in As, Pb, and Se, elements that are higher in metalimestone than in the intrusions. Thus, it can be inferred that metalimestone provided significant amounts of these metals to the mineralizing fluid. The pyrite analyses show that Cu, Zn, Bi and Ag increase towards the distal zone, while Fe, Mn and Bi in sphalerite also increase towards the distal zones Copper and Sb in galena and Ag in chalcopyrite collected from the distal zone increase from Central Gossan to Southwest Gossan zones while Bi in both minerals decrease. These trends of trace metal contents in sulfides can be utilized as a vectoring tool to delineate the center of the hydrothermal system.

Groundwater conceptual pollution model and related human health hazards, the main dilemma of a desert aquifer near ophiolite complex.

Groundwater is a finite resource in Davarzan region which is located between the ophiolite complex mountain in the north and salty playa at the south. The water samples were analyzed to assess the origin of groundwater pollution and explain links between the disturbed heavy metals composition of the earth's surface and the human health risks. The main heavy metal pollutants in the groundwater are Cr, Fe, As and Pb ions. In general, the groundwater salinity and some elements such as Cr and As are increased along with surface topography and groundwater flow directions from the northern ophiolite highlands recharge area to the adjacent desert discharging zone in the south. Despite the ophiolite complexes being the most enriched in Cr element, the lowest Cr concentration in the groundwater was measured near the ophiolite area, which is in the range of its discharged springs. Based on the groundwater conceptual pollution model, bedrock geochemistry controls the composition of soil and hence that of groundwater. The Cr samples show a direct relation with the EC value indicating that intrusion of salinity from the salt pan is probably another reason for the increased Cr concentration. The results of health risk assessment indicated that the groundwater suffered from significant contamination and if used for long-term without pre-treatment may pose serious health risks to human population via drinking water and irrigation of agricultural fields. This is the first attempt to apply hydrogeological setting along with the source of pollution and its health risk in a desert-ophiolitic area.

Impact of distributed meteorological forcing on simulated snow cover and hydrological fluxes over a mid-elevation alpine micro-scale catchment

Abstract. From the micro- to the mesoscale, water and energy budgets of mountainous catchments are largely driven by topographic features such as terrain orientation, slope, steepness, and elevation, together with associated meteorological forcings such as precipitation, solar radiation, and wind speed. Those topographic features govern the snow deposition, melting, and transport, which further impacts the overall water cycle. However, this microscale variability is not well represented in Earth system models due to coarse resolutions. This study explores the impact of precipitation, shortwave radiation, and wind speed on the water budget distribution over a 15.28 ha small, mid-elevation (2000–2200 m) alpine catchment at Col du Lautaret (France). The grass-dominated catchment remains covered with snow for 5 to 6 months per year. The surface–subsurface coupled distributed hydrological model ParFlow-CLM is used at a very high resolution (10 m) to simulate the impacts on the water cycle of meteorological variability at very small spatial and temporal scales. These include 3D simulations of hydrological fluxes with spatially distributed forcing of precipitation, shortwave radiation, and wind speed compared to 3D simulations of hydrological fluxes with non-distributed forcing. Our precipitation distribution method encapsulates the spatial snow distribution along with snow transport. The model simulates the dynamics and spatial variability of snow cover using the Common Land Model (CLM) energy balance module and under different combinations of distributed forcing. The resulting subsurface and surface water transfers are computed by the ParFlow module. Distributed forcing leads to spatially heterogeneous snow cover simulation, which becomes patchy at the end of the melt season and shows a good agreement with the remote sensing images (mean bias error (MBE) = 0.22). This asynchronous melting results in a longer melting period compared to the non-distributed forcing, which does not generate any patchiness. Among the distributed meteorological forcings tested, precipitation distribution, including snow transport, has the greatest impact on spatial snow cover (MBE = 0.06) and runoff. Shortwave radiation distribution has an important impact, reducing evapotranspiration as a function of the slope orientation (decreasing the slope between observed and simulated evapotranspiration from 1.55 to 1.18). For the primarily east-facing catchment studied here, distributing shortwave radiation helps generate realistic timing and spatial heterogeneity in the snowmelt at the expense of an increase in the mean bias error (from 0.06 to 0.22) for all distributed forcing simulations compared to the simulation with only distributed precipitation. Distributing wind speed in the energy balance calculation has a more complex impact on our catchment, as it accelerates snowmelt when meteorological conditions are favorable but does not generate snow patches at the end of our test case. This shows that slope- and aspect-based meteorological distribution can improve the spatio-temporal representation of snow cover and evapotranspiration in complex mountain terrain.

Surface-based temperature inversion characteristics and impact on surface air temperatures in northwestern Canada from radiosonde data between 1990 and 2016

Assumptions of linear lapse rates in regions prone to surface-based inversions (SBIs) can generate biases in the prediction of surface air temperature. Although studies of Arctic inversions are common, few regional studies of their characteristics exist in high-latitude regions with mountainous topography. To address this gap, vertical atmospheric temperature profiles for five sites in northwestern Canada were analysed using archived radiosonde data from 1990 to 2016. We present monthly, seasonal, and annual SBI characteristics including the occurrence of transient and persistent SBIs. A novel metric, surface-based inversion impact (SBIimp), was developed by combining the traditional inversion characteristics of depth, strength, and frequency, and was used to quantify the impact of SBIs on cooling the surface air temperature. SBIimp values of >5 °C yr−1 and ∼10 °C winter−1 occur locally. A weak linear relationship between sea ice coverage in the Beaufort Sea and SBIimp manifests across parts of the study area, though this relationship does not persist after detrending the datasets. Topographic analysis of areas surrounding each radiosonde location reveals highly variable SBIimp in complex mountain areas and more consistent SBIimp across areas of low relief. Our results can help interpret the role of inversions in climatic conditions maintaining cryospheric elements such as permafrost.

Multi-View Analysis of High-Resolution Geomorphic Features in Complex Mountains Based on UAV–LiDAR and SfM–MVS: A Case Study of the Northern Pit Rim Structure of the Mountains of Lufeng, China

Unmanned aerial vehicles (UAVs) and light detection and ranging (LiDAR) can be used to analyze the geomorphic features in complex plateau mountains. Accordingly, a UAV–LiDAR system was adopted in this study to acquire images and lidar point-cloud dataset in the annular structure of Lufeng, Yunnan. A three-dimensional (3D) model was constructed based on structure from motion and multi-view stereo (SfM–MVS) in combination with a high-resolution digital elevation model (DEM). Geomorphic identification, measurement, and analysis were conducted using integrated visual interpretation, DEM visualization, and geographic information system (GIS) topographic feature extraction. The results indicated that the 3D geomorphological visualization and mapping were based on DEM, which was employed to identify the dividing lines and ridges that were delineated of the pit rim structure. The high-resolution DEM retained more geomorphic detail information, and the topography and the variation between ridges were analyzed in depth. The catchment and ponding areas were analyzed using accurate morphological parameters through a multi-angle 3D visualization. The slope, aspect, and topographic wetness index (TWI) parameters were analyzed through mathematical statistics to qualitatively and accurately analyze the differences between different ridges. This study highlighted the significance of the UAV–LiDAR high-resolution topographic measurements and the SfM–MVS 3D scene modelling in accurately identifying geomorphological features and conducting refined analysis. An effective framework was established to acquire high-precision topographic datasets and to analyze geomorphological features in complex mountain areas, which was beneficial in deepening the research on numerical simulation analysis of geomorphological features and reveal the process evolution mechanism.