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Unstable surface‐layer velocity and temperature spectra, scaled using inertial subrange properties and Monin–Obukhov similarity theory, have been known to show a notable spread in low frequencies. Here, a large ensemble of 14 datasets, over relatively simple (from flat and homogeneous terrain to gentle slopes or valley floor) and very complex mountainous terrain (steep slopes, crater rim, mountain tops), is used to assess the reasons for this low‐frequency behaviour. Turbulence anisotropy is shown to be the primary factor accounting for the spread in the spectral density at the largest scales and the spectral peak position of streamwise and spanwise velocity spectra. On the other hand, the low‐frequency behaviour of surface‐normal spectra is dominated by stability effects, whereas for temperature spectra turbulence anisotropy and stability play a similar role. Using a combination of scaling relations for temperature and velocity variances as well as dissipation of turbulence kinetic energy and half the temperature variance, and of a semi‐empirical model provided in the literature, we are able to describe the behaviour of the velocity and temperature spectra with only turbulence anisotropy and stability as input parameters. These observations are valid over both simple and complex mountainous terrain, although variability of the largest scales of complex‐terrain datasets highlights the effect of processes other than turbulence anisotropy or stability. Finally, we provide some insights into the scalewise nature of anisotropic eddies under different stabilities. [ABSTRACT FROM AUTHOR]

This article presents an analytical model for calculating representative daily‐periodic cycles of net surface radiation on a slope with any angle α$$ \alpha $$ (0∘≤α≤90∘$$ {0}^{\circ}\le \alpha \le 9{0}^{\circ } $$) and orientation, at any latitude and elevation (up to 2500 m), and for all seasons. Starting from the basic equations for estimating the daytime direct and diffuse components of the incoming solar radiation at the Earth's surface under clear‐sky conditions, a Fourier series expansion is derived to get an overall daily‐periodic expression, that is, covering both daytime and nighttime, which does not require data from observations, differently from most models available in the literature. Among various possible applications, this formulation is preliminary to evaluating the radiation and energy budgets driving daily‐periodic wind systems on a simple slope, as reproduced by the model presented in Part 2. [ABSTRACT FROM AUTHOR]

For optimizing the operational efficiency of a wind farm in complex terrain, the wake study of wind turbines and the detailed analysis of the wind data are essential. In this research, The Manjil wind farm located in the Alborz Mountains with special topography and distinct wind regimes has been studied. OpenFOAM has been applied for computational fluid dynamics simulations of two wind speeds at different reference heights as case studies. Then, a comparison between the simulation results and the available supervisory control and data acquisition dataset was made. The result assumed that the velocity of the wake is recovered up to 85% after ten times the diameter of the turbine. In this distance, there is a 14.5% and 15.5% speed reduction on average for two simulations, with velocity on the hub height of 9 and 17 m/s respectively. The analysis of raw wind data shows that a high potential of wind energy is available in summer and there is almost no wind in wintertime, which causes some challenges for developing the wind farms under these conditions. [ABSTRACT FROM AUTHOR]

According to traffic accident statistics, the main causes are violations of traffic rules. Based on scientific research, it is clear that the main reason for these events is the drivers' incorrect assessment of the road situation and their inadequate response. Assessing road conditions depends on drivers' qualifications, skills, work experience, reaction time, and other physiological factors. The functional state of drivers is important to consider. It reflects their ability to work reliably and affects both fatigue levels and how fatigue builds up. Factors that impact decision-making speed and quality are crucial when evaluating the risks of the transportation process, particularly those associated with human behavior. This study investigates the safety of freight transportation for drivers, road users, third parties, and the environment. The study focuses on road traffic characteristics in mountainous conditions at high altitudes. The study aims to analyze how drivers' performance is affected while navigating challenging sections of mountain roads in the Ukrainian Carpathians. Four different routes will be examined. The research will provide graphic analysis of the results. It will show the main patterns of changes in drivers' functional state based on the route's complexity. The research aims to analyze indicators of drivers' functional state and their impact on their performance reliability. It allows for a more detailed evaluation of transport routes and planning of truck drivers' work and rest schedules on suburban routes.

Copyright of Architectural Journal / Jian Zhu Xue Bao is the property of Architectural Journal Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The rapid urbanization of Abha and its surrounding cities in Saudi Arabia's mountainous regions poses challenges for sustainable and secure development. This study aimed to identify suitable sites for eco-friendly and safe building complexes amidst complex geophysical, geoecological, and socio-economic factors, integrating natural hazards assessment and risk management. Employing the Fuzzy Analytic Hierarchy Process (Fuzzy-AHP), the study constructed a suitability model incorporating sixteen parameters. Additionally, a Deep Neural Network (DNN) based on eXplainable Artificial Intelligence (XAI) conducted sensitivity analyses to assess the parameters' influence on optimal location decision making. The results reveal slope as the most crucial parameter (22.90%), followed by altitude and land use/land cover (13.24%), emphasizing topography and environmental considerations. Drainage density (11.36%) and rainfall patterns (9.15%) are also significant for flood defense and water management. Only 12.21% of the study area is deemed "highly suitable", with "no-build zones" designated for safety and environmental protection. DNN-based XAI demonstrates the positive impact of variables like the NDVI and municipal solid waste generation on site selection, informing waste management and ecological preservation strategies. This integrated methodology provides actionable insights for sustainable and safe residential development in Abha, aiding informed decision making and balancing urban expansion with environmental conservation and hazard risk reduction. [ABSTRACT FROM AUTHOR]

To estimate catchment-scale hydrogeological parameters such as hydraulic conductivity (k) and specific yield (Sy), the streamflow recession analysis method proposed by Brutsaert and Nieber (1977) was used. The analysis employed the technique of fitting a theoretical recession curve to the observed data in which three points of transition between the short- and long-term flow regimes were determined. This method is a simple, fast, and cheap alternative to standard point-based hydrogeological methods using investigations carried out in hydrogeological boreholes. The study area covered the mountainous catchment of the Biała Lądecka River, located in south-western Poland and composed of metamorphic rocks. The hydrogeological environments drained by the Biała Lądecka are two zones, i.e. the zone of weathered covers and rock debris and the zone of fractured rock mass. The k values determined based on the recession analysis were in the boundary zone of the range from 10-4 to 10-5 m/s and they represented the upper range of the values reported in the literature (from 10-4 to 10-7 m/s). The Sy values at a level of 0.38-1.02%, in turn, entirely fitted the literature data. The results confirm the thesis that the recession method, despite certain limitations in terms of its applicability, can be well adapted to the conditions of a mountainous catchment composed of crystalline rocks where a cool temperate climate prevails. [ABSTRACT FROM AUTHOR]

Purpose: to develop a water intake structure for land reclamation purpose under the conditions of water withdrawal from mountainous natural water sources. Materials and methods. The paper is based on the theoretical analysis of the river hydrological and geological characteristics, which made it possible to calculate the minimum flow required for the stable operation of water intake structure and guaranteed water withdrawal during the growing seasons. The design parameters of the water intake structure were developed using the method of expert assessment with non-parametric statistics by comparing several dependent variables. Having determined the required qualities for a water intake structure, the design of a reclamation facility adapted for the conditions of the mountain and foothill zones of the North Caucasus was developed. Results. To achieve this goal, a static method for analyzing water intake structures was adapted, and statements with a factorial rating scale for expert assessment were developed. Kendall's concordance coefficient was 0.726, the data were consistent, the significance level P was less than 0.05, the differences between the factors were significant. The layer-by-layer latticed type of water intake structure has maximum efficiency. The design of a bottom-type water intake structure has been developed on the basis of the river hydrological regime and the method of water supply to the system. This type of structure demonstrates high efficiency in conditions of difficult terrain and unstable water source regimes during the growing seasons, ensuring stable water intake with minimal impact on the ecosystem. Conclusions. The proposed design of a water intake structure can be adapted to different types of water resources and their fluctuations, which makes it acceptable for mountainous areas with variable water levels in natural water sources. Minimal impact on the ecosystem is ensured by a high degree of water purification without significant changes in river channels.

Climate change is a major concern for freshwater allocation and management, but there is a lack of attention regarding how water impoundment impacts boreal climate at the intersection of mountain topography. We explore how the local climate was affected by the construction of one of North America's largest reservoirs, the Williston Hydropower Reservoir, in British Columbia's Rocky Mountain Trench. High-resolution simulations of the Weather Research and Forecasting model over a 10-year period were used to analyze differences in mean meteorological states with and without the reservoir represented in the landscape. Relative to terrain without the Williston Reservoir, autumn precipitation increased by up to 30 mm (11.5%); however, a substantial precipitation decrease in summer results in a 15% reduction of mean annual precipitation over ridges east of the reservoir. The presence of the reservoir with high thermal inertia in place of vegetated soil reduced convection in the warm season so that heavy precipitation events (> 20 mm) become fewer. An increase in mean annual air temperature within 10 km of the reservoir by 0.2–0.5 °C due mainly to significant warming in autumn was also detected. Overland wind increased by 0.5 m s−1 up to 13 km from the reservoir. We highlight the social importance of these results on the perception of environmental change. [ABSTRACT FROM AUTHOR]

The current high rate of urbanization in developing countries and its consequences, like traffic congestion, slum development, scarcity of resources, and urban heat islands, raise a need for better Land Use Land Cover (LULC) classification mapping for improved planning. This study mainly deals with two objectives: 1) to explore the applicability of machine learning-based techniques, especially the Random forest (RF) algorithm and Support Vector Machine (SVM) algorithm as the potential classifiers for LULC mapping under different scenarios, and 2) to prepare a better LULC classification model for mountain terrain by using different indices with combination of spectral bands. Due to differences in topography, shadows, spectral confusion from overlapping spectral signatures of different land cover types, and a lack of access for ground verification, classification in mountainous terrain is difficult task compared to plain terrain classification. An enhanced LULC classification model has been designed using two popular machine learning (ML) classifier algorithms, SVM and RF, explicitly for mountainous terrains by taking into consideration of a study area of Gopeshwer town in the Chamoli district of Uttarakhand state, India. Online-based cloud platform Google Earth Engine (GEE) was used for overall processing. Four classification models were built using Sentinel 2B satellite imagery with 20m and 10m resolutions. Two of these models (Model 'i' based on RF algorithm and Model 'ii' based on SVM algorithm) were designed using spectral bands of visible and infrared wavelengths, and the other two (Model 'iii' based on RF algorithm and Model 'iv' based on SVM algorithm) with the addition of indices with spectral bands. The accuracy assessment was done using the confusion matrix based on the output results. Obtained result highlights that the overall accuracy for model 'i' and model 'ii' were 82% and 86% respectively, whereas these were 87.17% and 87.2% for model 'iii' and model 'iv' respectively. Finally, the study compared the performance of each model based on different accuracy metrics for better LULC mapping. It proposes an improved LULC classification model for mountainous terrains, which can contribute to better land management and planning in the study area. [ABSTRACT FROM AUTHOR]

A mass‐conserving method to downscale precipitation from global climate models (GCMs) using sub‐grid‐scale topography and modeled 700‐mb wind direction is presented. Runoff is simulated using a stand‐alone hydrological model, with this and several other methods as inputs, and compared to runoff simulated using historical observations over the western contiguous United States. Results suggest the mitigation of grid‐scale biases is more critical than downscaling for some regions with large wet biases (e.g., the Great Basin and Upper Colorado). In other regions (e.g., the Pacific Northwest) the new method produces more realistic sub‐grid‐scale variability in runoff compared to unadjusted GCM output and a simpler downscaling method. The presented method also brings the runoff centroid timing closer to that simulated with observations for all subregions examined. Plain Language Summary: Due to limitations in computing power which necessitates coarse spatial resolution, climate models do not include many details on mountains and their impact on precipitation. For this reason, it is difficult to estimate the impact of climate change on the availability of water for human consumption in places like the western United States, where mountain snowpack is an important source of water. This paper presents a way to adjust precipitation estimates from climate models by using some simple statistics about nearby mountains and valleys. The adjusted precipitation is then used in a hydrologic model to calculate the runoff that is simulated with different precipitation inputs. Results show that in most cases, the precipitation adjustment improves estimates of the resultant runoff relative to simulations with observed precipitation. The main exceptions are in very dry areas where the climate model produces far too much precipitation. With further work, the proposed adjustment may be integrated into the climate model itself to make it easier for those managing water resources (e.g., controlling reservoir levels) to use the model output to plan and adapt to climate change. Key Points: A mass‐conserving method for downscaling orographic precipitation improves modeled runoff from the CESM2Considering upwind topography further improves modeled runoff compared to simpler adjustmentsNot tuning to individual model grid points makes this method more generalizable than many existing statistical downscaling methods [ABSTRACT FROM AUTHOR]

Multiscale numerical weather prediction models transition from mesoscale, where turbulence is fully parameterized, to microscale, where the majority of highly energetic scales of turbulence are resolved. The turbulence gray-zone is situated between these two regimes and multiscale models must downscale through these resolutions. Here, we compare three multiscale simulations which vary by the parameterization used for turbulence and mixing within the gray-zone. The three parameterizations analyzed are the Mellor-Yamada Nakanishi and Niino (MYNN) Level 2.5 planetary boundary layer scheme, the TKE-1.5 large eddy simulation (LES) closure scheme, and a recently developed three-dimensional planetary boundary layer scheme based on the Mellor-Yamada model. The simulation domain includes complex (i.e., mountainous) terrain in Nevada that was instrumented with meteorological towers, profiling and scanning lidars, a tethered balloon, and a surface flux tower. Simulations are compared to each other and to observations, with assessment of model skill at predicting wind speed, wind direction and TKE, and qualitative evaluations of transport and dispersion of smoke from controlled releases. This analysis demonstrates that microscale predictions of transport and dispersion can be significantly influenced by the choice of turbulence and mixing parameterization in the terra incognita, particularly over regions of complex terrain and with strong local forcing. This influence may not be apparent in the analysis of model skill, and motivates future field campaigns involving controlled tracer releases and corresponding modeling studies of the turbulence gray-zone.

Abstract A mass‐conserving method to downscale precipitation from global climate models (GCMs) using sub‐grid‐scale topography and modeled 700‐mb wind direction is presented. Runoff is simulated using a stand‐alone hydrological model, with this and several other methods as inputs, and compared to runoff simulated using historical observations over the western contiguous United States. Results suggest the mitigation of grid‐scale biases is more critical than downscaling for some regions with large wet biases (e.g., the Great Basin and Upper Colorado). In other regions (e.g., the Pacific Northwest) the new method produces more realistic sub‐grid‐scale variability in runoff compared to unadjusted GCM output and a simpler downscaling method. The presented method also brings the runoff centroid timing closer to that simulated with observations for all subregions examined.

In parts of the world characterised by high precipitation and steep topography, hydroelectric dams often play the dual role of power generation and flood control. Improper and uncoordinated management of such dams during extreme and unexpected precipitation events can have disastrous consequences. As such, there exists a growing need for a reliable, transparent, and publicly available reservoir assessment and information system that can help water managers better prepare for such natural events. A fully satellite sensor-based framework offers a potentially viable approach towards this goal. The Reservoir Assessment Tool (RAT 3.0), which utilises high frequency remote sensing-based surface area and reservoir storage estimation alongside hydrological modelled inflow is tested and analysed for the 2018 Kerala floods in India. The effectiveness of RAT 3.0 was gauged by considering how well a fully satellite sensor-based framework was able to capture the rapidly evolving dynamics of the flood and reservoir state. Application of RAT 3.0 in monitoring the state of 19 reservoirs in Kerala during the flood event showed very promising results. In general, RAT 3.0 was found to be able to capture the temporal trend of the reservoir storage and pinpoint the sudden shift in filling or release decisions made by the dam operator. This translated to reliable updating of downstream flood risk in near real-time for improving flood preparedness, even though the absolute magnitudes were sometimes found to be in need of bias correction. A customised form of RAT 3.0 tailored for hydropower dams operating during high precipitation events in mountainous regions is proposed as an outcome of this study. [ABSTRACT FROM AUTHOR]

In order to effectively utilize the ground electric field data of approaching thunderstorms to realize accurate lightning warning in the plateau mountainous area, a typical thunderstorm cloud model and a basic mountain model were built, and the elevation data was combined to simulate real plateau mountainous terrain. Then, the finite element method (FEM) was used to study the influence of the plateau mountainous terrain on the distribution characteristics and evolution trend of the ground electric field by thunderstorm cloud. The results show that the electric field of thunderstorm cloud on surface of the basic mountain is distorted, and the degree of distortion is related to the mountain shape and the observation location. The electric field distribution of thunderstorm cloud on real terrain fluctuates due to the uneven surface but the overall trend is basically consistent with that on the flat ground. The evolution of the near-earth electric field presents the law of a large increase and then a small decrease when thunderstorm cloud approaches the observation point. However, the terrain surrounding the observation point can affect the amplitude of electric field change. [ABSTRACT FROM AUTHOR]

The conventional methods of estimating soil water content (SWC) are mainly based on in situ measurements at sampling points and remote sensing measurements over an entire region. In view of these methods, cosmic-ray neutron sensing (CRNS) has received increasing attention in recent years as a mesoscale, noncontact SWC estimation technology that can provide more accurate and timely estimates of SWC over a larger area. In this study, we estimated SWC using both CRNS and soil-mounted detectors in farmland and mountainous areas, and evaluated the accuracy of the estimations at two experimental sites. Ultra-rapid adaptable neutron-only simulation (URANOS) was used to simulate the detection radius and depth of the two experimental sites and to obtain the spatial weights of the CRNS footprint. The results show that the theoretical range of detection was reduced in farmland compared to mountainous areas during the experimental period, suggesting that farmland retained more SWC even with less precipitation. Spatial weights were simulated to calculate the SWC of sampling points, and the weighted and averaged SWC were then correlated with CRNS. The weighting calculation improves the accuracy of CRNS estimations, with a determination coefficient (R2) of 0.645 and a root mean square error (RMSE) of 0.046 cm3·cm−3 for farmland, and reproduces the daily dynamics of SWC. The R2 and RMSE in mountainous areas are 0.773 and 0.049 cm3·cm−3, respectively, and the estimation accuracy of CRNS cannot be improved by the weighting calculation. The estimation accuracy of CRNS is acceptable in both regions, but the mountainous terrain obstructs neutron transmission, causing a deviation between the actual and theoretical neutron footprints in mountainous areas. Thus, the accuracy of SWC estimation is limited in mountainous terrain. In conclusion, this study demonstrates that CRNS is suitable for use in farmland and mountainous areas and that further attention should be given to the effects of topography and vegetation when it is applied in mountainous environments. [ABSTRACT FROM AUTHOR]

The construction of sponge cities in mountainous areas is crucial to achieving high-quality development in these regions. Owing to rugged terrain, significant changes in elevation, and uneven distribution of cities, the construction of sponge cities in mountainous areas faces challenges such as difficulties in clearing mountains and roads, high cost, and varying regional development requirements. However, there is currently limited research focusing on the impact of terrain on sponge city construction plans. In this study, we developed an optimal low impact development (LID) system layout method based on the annual runoff control rate. This study suggests implementing LID plans in stages to balance cost-effectiveness and enhance resilience. The optimized case1_100 scheme, which takes regional differences into account, can effectively achieve a runoff control coefficient of less than 0.25 in 98.86% of the area. Remarkably, this achievement comes at a significantly lower total cost of only 1.22 billion RMB compared to the unoptimized case2_100 scheme (which does not consider regional differences) with a cost of 3.03 billion RMB. Interestingly, the optimized case1_100 plan, selected using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, has an LID layout that is closely related to the surface terrain. Structural equation modeling analysis indicates that terrain affects land types, which in turn impacts the surface impermeability and runoff coefficients, ultimately influencing the corresponding LID deployment plan. The coefficients of relative elevation and slope on the final plan are determined as −0.13 and −0.77, respectively, with a high overall explanatory power of 0.84. This indicates that terrain characteristics have a significant impact on the spatial patterns and surface features of typical mountainous cities in China and the optimal LID strategy largely depends on the initial terrain conditions. This study provides valuable insights for optimizing LID construction in sponge cities, particularly in the context of new mountainous urban planning. [Display omitted] • Mountainous terrain shapes urban sponge construction and runoff management. • Cost-effectiveness and resilience guide phased low-impact development (LID) deployment in mountains. • Terrain factors drive optimal LID strategy placement. [ABSTRACT FROM AUTHOR]

Copyright of Mountain Research (10082786) is the property of Mountain Research Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• We identified the contributing factors of rollover crashes on mountainous interstates. • Crash, roadway, driver and weather variables were considered in the analysis. • The analysis was conducted via a random parameter logit model. • Weather, road surface conditions and speeding were found to have a significant impact on rollover crash risk. • The study shows the importance of accounting for unobserved heterogeneity effects of the key factors when understanding the rollover event. Introduction: The risk of rollover crashes on mountainous roads is a major concern for transportation authorities due to adverse weather conditions and complex topography. Such crashes incur hazardous consequences on road users' lives. Therefore, it is crucial to identify the contributing factors that give rise to these severe crashes in order to identify preventive measures. Furthermore, exploring the potential sources of heterogeneity of rollover crash contributing factors is equally important. Method: By having a dataset of single-vehicle crashes that occurred on mountainous curved sections in Wyoming, we applied a random parameters, otherwise known as mixed, logit model to identify the factors contributing to the increased risk of rollovers. Vehicle, driver, roadway, environmental, and crash attributes variables were considered as potential predictors in the model. Then, random parameters were identified to uncover the unobserved effects. Results: Weather, road surface conditions, and speeding were found to have a significant impact on rollover crash risk. These factors were also found to exhibit unobserved heterogeneity effects, which could be attributed to the drivers' responses and conditions. Furthermore, it was found that the propensity of rollovers was higher for sports utility vehicles (SUVs) and pick-up trucks among other vehicle types. Conclusions: The results indicated that investigating the impact of these factors on the risk of rollovers while taking into account unobserved heterogeneity effects is an essential step for implementing countermeasures to reduce the frequency and severity of rollover crashes. Practical applications: This study uncovered insights into the factors that lead vehicles to overturn. This aids in suggesting appropriate safety countermeasures that mitigate the occurrences of rollover crashes to transportation agencies. [ABSTRACT FROM AUTHOR]

Coplanar scans from three Doppler lidars are used to retrieve the horizontal wind field in a horizontal plane of about 5 km × 5 km in size above the city of Stuttgart in south-western Germany. Stuttgart is located in moderate mountainous terrain that is characterized by a basin-shaped valley (Stuttgart basin) which opens into the larger Neckar Valley. Using the retrieved horizontal wind field, which is available on 22 days with a temporal resolution of 1 min and a horizontal resolution of 100 m, we investigate the mesoscale structure of the horizontal flow in the valleys with respect to time of the day, stratification and wind above the mean ridge height, and determine how fast the cells in the convective boundary layer move downstream, i.e. we estimate the convection velocity. The measurements reveal a large spatial and temporal variability of the flow. During stable conditions, the flow below the mean ridge height is decoupled from the flow aloft and downvalley wind dominates in the valleys. At the opening of the Stuttgart basin into the Neckar Valley outflow dominates during nighttime, whereas inflow into the basin prevails in the early morning. During thermally unstable conditions the flow in the valleys is mainly coupled to the flow aloft with a preference for upvalley wind direction. Convective cells moving downstream are detected in the horizontal wind field and a method to estimate the convection velocity from the horizontal wind field measurements is presented. The mean convection velocity is found to be higher by 24 % than the mean horizontal wind speed at the same height and about similar to the wind speed 100 m further up.

Two heavy rainfall events are analyzed based on the hourly rainfall data at Shennongjia airport meteorological station from 11:00 BT on 23 June to 08:00 BT on 24 June 2016 and Xianning meteorological station from 04:00 on July 3 to 01:00 on July 4, 2016, vertical profiles of water vapor density, liquid water, relative humidity and temperature with high resolution from ground to 10 km, and integrated water vapor, path-integrated cloud liquid water and cloud base data, . The differences of atmospheric vertical structure between Shennongjia in mountainous area and Xianning in plain before and after the rainstorm are obvious. The precipitable water and path-integrated cloud liquid water in Shennongjia are lower than those in Xiannin. The water vapor density, liquid water content and temperature at all altitudes above Shennongjia airport meteorological station are also lower than thoae at the corresponding altitudes above Xianning. The relative humidity in the mixing layer at Shennongjia is slightly higher than that at Xianning. Shennongjia is located in the mountainous area, where the external water vapor supply is not sufficient, and the formation of precipitation mainly depends on the condensation of local water vapor. Due to the high elevation of the mountainous area, the atmospheric temperature in Shennongjia is relatively low, and the temperature and humidity conditions are better for ice nucleation and growth than those in Xianning, which makes Shennongjia produce rainstorm even when the water vapor supply is insufficient. Xianning has sufficient water vapor supply, which can be replenished in time after condensation. Although the humidity condition in the mixing layer in Xianning is not as good as that in Shennongjia, and the growth of ice crystals is relatively weak, the process of riming process in the mixing layer and the coagulation of cloud and rain drops in the melting layer play important roles in the precipitation process. Before the onset of precipitation, because of the topographic effect, air lifting at Shennongjia is stronger than that in Xianning, while the atmospheric uplift in Xianning was more significant after the precipitation begans, showing obvious convective characteristics.

Abstract Background Understanding the spatial pattern and driving factors of forest carbon density in mountainous terrain is of great importance for monitoring forest carbon in support of sustainable forest management for mitigating climate change. Methods We collected the forest inventory data in 2015 in Shanxi Province, eastern Loess Plateau of China, to explore the spatial pattern and driving factors of biomass carbon density (BCD) for natural and planted coniferous forests using Anselin Local Moran’s I, Local Getis-Ord G* and semivariogram analyses, and multi-group structural equation modeling, respectively. Results The result of spatial pattern of BCDs for natural forests showed that the BCD was generally higher in the north but lower in the south of Shanxi. The spatial pattern for planted forests was substantially different from that for natural forests. The results of multi-group SEM suggested that elevation (or temperature as the alternative factor of elevation) and stand age were important driving factors of BCD for these two forest types. Compared with other factors, the effects of latitude and elevation on BCD showed much greater difference between these two forest types. The difference in indirect effect of latitude (mainly through affecting elevation and stand age) between natural and planted forests was to some extent a reflection of the difference between the spatial patterns of BCDs for natural and planted forests in Shanxi. Conclusions The natural coniferous forests had a higher biomass carbon density, a stronger spatial dependency of biomass carbon density relative to planted coniferous forests in Shanxi. Elevation was the most important driving factor, and the effect on biomass carbon density was stronger for natural than planted coniferous forests. Besides, latitude presented only indirect effect on it for the two forest types.

Investigation of the atmospheric boundary-layer structure in urban areas can be challenged by landscape complexity and the heterogenous conditions this instills. Stuttgart, Germany, is a city situated in a bowl-shaped basin and troubled by the accumulation of pollutants during weak-wind conditions. The center of Stuttgart is surrounded by steep slopes up to 250 m above the basin floor, except for an opening to the northeast that allows runoff towards the Neckar river. Urban planning and regulation of air quality require advanced monitoring and forecasting skills, which in turn require knowledge about the structure of the atmospheric boundary layer (ABL), down to the surface. Three-dimensional observations of the ABL were collected in the City Centre of Stuttgart in 2017. A laser ceilometer and a concerted network of Doppler lidar systems were deployed on roof-tops, providing continuous observations of the cloud base, the mixing-layer height and the three-dimensional wind field. The impact of weak-wind conditions, the presence of shear layers, properties of convective cells and the impact of nocturnal low-levels jets were studied for representative days in winter and summer. The observations revealed the development of distinctive layers with high directional deviation from the flow aloft, reoccurring as a dominant diurnal pattern. Our findings highlight the influence of topography and surface heterogeneity on the structure of the ABL and development of flow regimes near the surface that are relevant for the transport of heat and pollutants.

Building thermal climate (BTC) zoning is important for building energy efficiency. However, previous BTC zoning has been mainly performed at national and regional scales, without sufficient attention to small-scale regions and even less so for terrain-complex regions. Typically, the complex terrain in mountainous areas causes the spatial heterogeneity of city and local climates, which can reduce BTC zoning accuracy if city and local climate variability is not considered. Therefore, this study aims to refine BTC zoning scheme for mountainous areas, by examining the accuracy of refined BTC zoning scheme and analyzing its benefit for building energy efficiency. Chongqing, a mountainous China municipality consisting of 38 districts and towns, was chosen as a representative case to perform BTC zoning scheme refinement. The results indicate that the refined zoning scheme is conducive to improving zoning resolution, coverage, accuracy, and reliability. First, the BTC zones based on China National Standard GB50176-2016 only cover four districts and towns while the zoning types of all other 34 districts and towns are assumed based on spatial proximity. The refined one can determine the zoning types of all 38 districts and towns based on robust quantitative analysis. Second, Chongqing was refined into three BTC zone types, while there were only two BTC zone types in Chongqing Standard DBJ50-102–2010. The zoning types of 21 districts and towns changed, two of which were reclassified to Mild Zone A (MZ_A) from the original Hot Summer and Cold Winter Zone A (HSCWZ_A). The refined zoning scheme can help improve building energy efficiency potential. Based on the refined zoning scheme, the annual heating energy use reduction ranged between 14.0 %–21.7 % over 2011–2020, the annual cooling energy use increase ranged between 4.3 %–7.6 %, and the reduction of energy use for heating and cooling was ∼ 2 %. Overall, this study provides a theoretical and methodological reference to understand BTC zoning refinement in mountainous areas. Based on the refined zoning scheme, all districts and towns in Chongqing can practically adjust their building energy efficiency strategies for better climate adaptation. [ABSTRACT FROM AUTHOR]

Uncoordinated management of hydropower dams during extreme and unexpected precipitation events in mountainous terrain can have disastrous consequences due to the competing nature of flood control and hydropower generation. Numerous cases of flooding events that have been exacerbated due to insufficient storage conditions in hydropower dams have been reported worldwide. There is a need for a scalable and publicly-accessible monitoring framework that is capable of providing reliable, near-real time, and transparent reservoir operations data. A fully satellite-based framework is the most viable solution to build such capability. The Reservoir Assessment Tool (RAT 3.0), which utilises high frequency remote sensing-based surface area and reservoir storage estimation alongside hydrological modelled inflow was applied here for the 2018 Kerala floods in India as a globally representative case for a mountainous river basin with high precipitation and hydropower dams. Application of satellite-based RAT 3.0 in monitoring the state of 19 reservoirs in Kerala during the flood event showed very promising results. In general, RAT 3.0, using satellite remote sensing, was found to be able to capture the temporal trend of the reservoir storage and pinpoint the sudden shift in filling or release decisions made by the dam operator. Inflow modelling in such regions was found to require careful calibration with identification of reservoirs that are heavily regulated being a critical aspect. The perennial high cloud cover in such regions necessitate and highlights the central role played by microwave and radar-based satellite sensors, such as the Surface Water and Ocean Topography (SWOT) mission, in tracking reservoir state. An operational version of RAT 3.0 for stakeholder agencies tailored for hydropower dams operating in high precipitation and mountainous environments is a real-world outcome of this study. • A satellite-based reservoir framework can monitor reservoirs effectively during extreme weather events. • Temporal trend of reservoir inflows and releases are captured accurately by satellite framework. • Uncertainties associated with satellite-based framework has to be addressed diligently. [ABSTRACT FROM AUTHOR]

• The POT approach performs reasonably well for the mountainous terrains. • ROR traffic events happen more frequently on two-lane undivided highways. • Yaw Rate does not influence ROR crash risk of HCVs in mountainous terrain. • Horizontal Curve Radius is the most influencing variable for ROR crash risk of HCVs in mountainous terrain. Heavy commercial vehicles (HCVs) face elevated crash risks in mountainous terrains due to the challenging topography and intricate geometry, posing a significant challenge for transportation agencies in mitigating these risks. While safety studies in such terrains traditionally rely on historical crash data, the inherent issues associated with crash data have led to a shift towards proactive safety studies using surrogate safety measures (SSM) in recent years. However, the scarcity of accurate microscopic data related to HCV drivers has limited the application of proactive safety studies in mountainous terrains. This study addresses this gap by employing an SSM known as anticipated collision time (ACT) to explore the impact of horizontal curves on the crash risk of HCVs in mountainous terrain. To perform the crash risk analysis, a collection of videos was gathered from horizontal curves in the mountainous terrain along the Guwahati-Shillong bypass in the Northeastern region of India. Subsequently, trajectories were extracted from these videos using semi-automated image processing software. Traffic conflicts were identified using ACT, and the crash risk was estimated through the Peak-Over Threshold (POT) approach of the Extreme Value Theory (EVT). The findings indicate that Run-Off-Road (ROR) traffic events happen more frequently on or near the horizontal curves falling in mountainous terrain. However, the frequency of severe ROR traffic events is lower, indicating the lower propensity for such collisions on the selected curves. The threshold for the safety margin of ROR traffic events involving HCVs was 2 s. The study revealed that stationary models exhibit an overestimation of crash frequency (0, 6) compared to the observed crash frequency (0, 2). Consequently, non-stationary crash risk models were developed, incorporating road geometry and the braking and yaw rates of HCVs as covariates. The results demonstrate that the estimated confidence bounds (1, 2) align with the observed crash frequency (0, 2), emphasizing the applicability of POT models for safety analysis in mountainous terrains in India. The study identified curve radius, length of the approach tangent, and the distance between the center points of horizontal and vertical curves as influential factors affecting the Run-Off-Road (ROR) crash risk of HCVs. Notably, sharp curves with radii less than 200 m or more are associated with a significantly higher crash risk. Additionally, an increased distance between the midpoints of horizontal and vertical curves beyond 1 m was found to escalate the ROR crash risk of HCVs. To mitigate these risks, it is recommended to reduce the length of the approach tangent to prevent high-speed travel on sharp curves. Furthermore, proper signage should be strategically placed to warn drivers and avert potential hazards. [ABSTRACT FROM AUTHOR]

In the morning, the nocturnal stable boundary layer, SBL, transitions into its daytime convective counterpart substantially impacting the distribution of temperature, humidity, and pollutants. Applying distributed temperature sensing (DTS) below a tethered balloon (2–200 m) and along a tower (0–11 m), for the first time we observed three morning transitions (MTs) in a mountain boundary layer with high temporal (<10 s) and spatial (<0.25 m) resolutions. We show that MTs are best derived from a change in static stability from synchronous DTS observations. Our findings confirm that the MT occurs at the SBL top and bottom simultaneously, and identify horizontal heat advection as a main driver aiding solar surface heating in this midrange mountain valley. We conclude that heterogenous land use and mountainous topography cause complex interactions between valley‐scale and local airflows leading to thermal signatures characterized by strong, small‐scale variability. Our study highlights DTS as a crucial tool for investigating complex thermodynamic processes. Plain Language Summary: On calm nights, a nocturnal stable boundary layer forms near the Earth's surface characterized by increasing temperatures with height and very little mixing. Its counterpart is the daytime convective boundary layer, CBL, which has the opposite characteristics. Both the stable and convective boundary layers have received much attention; however, the in‐between morning transition (MT) has received less attention, which can degrade weather and air quality forecasts. To better understand the morning transition, we measured air temperature below a tethered balloon and on a tower during the MT with a technique called distributed temperature sensing (DTS) using thin fiber‐optic cables. Our unique design enabled an unprecedented view of the MT revealing its detailed and fast‐changing structure. The morning transition is a highly variable process whose theoretical description and experimental investigation had previously been simplified due to observational limitations. We found that it starts simultaneously at the top and bottom of the stable layer, and can take an hour to complete. It is strongly influenced by the surrounding land. While more work using DTS is necessary to understand why the air takes so long to respond to the rising sun, we demonstrate how critical this technique is for future research. Key Points: A novel technique, distributed temperature sensing (DTS) below a tethered balloon, reveals unknown details of the morning transitionThe morning transition, despite its strong spatiotemporal variability, is robustly determined by changes in static stabilityDTS provides first evidence that the transition occurs simultaneously at the stable boundary bottom and top, and is subject to advection and counter‐gradient flux [ABSTRACT FROM AUTHOR]

This study aims to capture groundwater potential zones integrating deep neural network and groundwater influencing factors. The present work was carried out for Gopi khola watershed, mountainous terrain in Nepal Himalaya as the watershed mainly relies upon the groundwater assets; it is a need to explore groundwater potential for better management of the aquifer framework. Ten groundwater influencing factors were collected such as elevation, slope, curvature, topographic positioning index, topographic roughness index, drainage density, topographic wetness index, geology, lineament density, and land use thematic layers. Among those influencing factors, topographic roughness index was removed because of multicollinearity issue to reduce the dimension of the dataset. A spring inventory map of 145 spring locations was prepared using field survey method and an equal number of spring absence points were randomly generated. The 70% of spring and spring absence pixels were used as training dataset and remaining as test dataset. The final map was created based on predicted probabilities ranging from 0 to 1. The validation was done using the receiver operating characteristic curve, which shows that the area under the curve is 76.1% for the training dataset and 82.1% for the test dataset. The sensitivity analysis was performed using Jackknife test which shows that the lineament density is the most important factor. The experimental results demonstrated that deep neural network is highly capable to capture groundwater potential zone in mountainous terrain. The present study might be useful and preliminary work to exploit the groundwater. The consequences of the current study may be valuable to water administrators to settle on appropriate choices on the ideal utilization of groundwater assets for future arranging in the basic investigation zone. [ABSTRACT FROM AUTHOR]

We compare the processing of Persistent Scatterer Interferometry data in map geometry versus their processing in slant-range/azimuth radar coordinates. In mountainous areas, using the map geometry significantly reduces the geometric distortion of radar coordinates that places scatterers that are actually widely separated in altitude in very close proximity in terms of slant-range. Processing in slant-range coordinates over mountainous regions introduces distortion in the distances used for estimation and filtering of tropospheric phase and phase unwrapping. Spatial filtering, interpolation of missing values, and phase unwrapping have better performance in map geometry because the distances between points are closer to reality. Performing these steps in a map geometry results in a more robust and more reliable processing chain. [ABSTRACT FROM AUTHOR]

A concept of a new energy management system synthesizing meteorological and orographic influences on airplane safety envelope was developed and implemented at the ZHAW Centre for Aviation. A corresponding flight simulation environment was built in a Research and Didactics Simulator (ReDSim) to test the first implementation of the cockpit display system. A series of pilot-in-the-loop flight simulations were carried out with a group of pilots. A general aviation airplane model Piper PA-28 was modified for the study. The environment model in the ReDSim was modified to include a new ad hoc subsystem simulating atmospheric disturbance. In order to generate highly resolved wind fields in the ReDsim, a well-established large-eddy simulation model, the Parallelized Large-Eddy Simulation (PALM) framework, was used in the concept study, focusing on a small mountainous region in Switzerland, not far from Samedan. For a more realistic representation of specific meteorological situations, PALM was driven with boundary conditions extracted from the COSMO-1 reanalysis of MeteoSwiss. The essential variables (wind components, temperature, and pressure) were extracted from the PALM output and fed into the subsystem after interpolation to obtain the values at any instant and any aircraft position. Within this subsystem, it is also possible to generate statistical atmospheric turbulence based on the widely used Dryden turbulence model. The paper compares two ways of generating atmospheric turbulence, by combining the numerical method with the statistical model and introduces the flight test procedure with an emphasis on turbulence realism; it then presents the experiment results including a statistical assessment achieved by collecting pilot feedback on turbulence characteristics and turbulence/task combination.

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Background: Understanding the spatial pattern and driving factors of forest carbon density in mountainous terrain is of great importance for monitoring forest carbon in support of sustainable forest management for mitigating climate change. Methods: We collected the forest inventory data in 2015 in Shanxi Province, eastern Loess Plateau of China, to explore the spatial pattern and driving factors of biomass carbon density (BCD) for natural and planted coniferous forests using Anselin Local Moran's I, Local Getis-Ord G* and semivariogram analyses, and multi-group structural equation modeling, respectively. Results: The result of spatial pattern of BCDs for natural forests showed that the BCD was generally higher in the north but lower in the south of Shanxi. The spatial pattern for planted forests was substantially different from that for natural forests. The results of multi-group SEM suggested that elevation (or temperature as the alternative factor of elevation) and stand age were important driving factors of BCD for these two forest types. Compared with other factors, the effects of latitude and elevation on BCD showed much greater difference between these two forest types. The difference in indirect effect of latitude (mainly through affecting elevation and stand age) between natural and planted forests was to some extent a reflection of the difference between the spatial patterns of BCDs for natural and planted forests in Shanxi. Conclusions: The natural coniferous forests had a higher biomass carbon density, a stronger spatial dependency of biomass carbon density relative to planted coniferous forests in Shanxi. Elevation was the most important driving factor, and the effect on biomass carbon density was stronger for natural than planted coniferous forests. Besides, latitude presented only indirect effect on it for the two forest types. [ABSTRACT FROM AUTHOR]

Based on a theological approach, we consider the architectural and compositional symbolism of Christian church complexes in rough geomorphological conditions. We have studied differences in the architecture of monastic complexes in mountainous terrains pertaining to the traditions of eastern and western Christian churches. The basis for the formation of Christian churches in mountainous terrains is determined to be symbolic representation of spiritual growth. Architecture is considered as supporting the symbolism of the spiritual content of Christian churches depending on their location on the terrain. We have developed a system of principles for designing churches in complex geomorphological conditions. An experience in designing the restoration and expansion of St. George's Katerlez Monastery in Kerch located on a mountainous terrain is described.

The various types of electron-optical supervisory control systems (SCS) have been used in Armed Forces of many advanced countries. The mission of these SCS is to supervise day and night enemy troops, technics and weapon systems, frontier intruders with high precision a great and middle distance. The SCS optimal deployment in mountainous terrain makes possibility to use rationally SCS number, because SCS has very much costs. Using the rationally SCS number we can reduce a necessity of the specialist number. Also, it accelerates comander’s correct decision making. The optimal deployment of SCS on a terrain is one of important task of military reconnaissance. The specific character of such task is that the necessary for continuing surveillance and control military objects can be located in specific zones of terrain (for examples, in canyons, along of river etc.). Accessible places of SCS set are situated on some distance from these zones. The number of SCS is limited; therefore, it is impossible to distribute theirs on the all set points. It is necessary to select such SCS set points that the zone observation range would be the largest. In present paper the mathematical model of the rationally deployment of technical observing systems in mountainous terrain has been developed and offered. The determination method of visibility level between selected terrain points has been developed. The assesment criterion of rationally deployment and the algorithm of fast solution have been offered.

In this paper, a full‐wave two‐dimensional Finite‐Difference‐Time‐Domain model is developed to evaluate the propagation effects of lightning electromagnetic fields over mountainous terrain in the Earth‐ionosphere waveguide. In the model, we investigate the effect of the Earth‐ionosphere waveguide structure and medium parameters, including the effect of the ionospheric cold plasma characteristics, the effect of the Earth curvature, and the propagation effects over mountainous terrain. For the first time, the obtained results are validated against simultaneous experimental data consisting of lightning currents measured at the Säntis Tower and electric fields measured in Neudorf, Austria, located at 380‐km distance from the tower. It is shown that both the time delays and amplitudes of the lightning electromagnetic fields at 380‐km distance can be strongly affected by the ionospheric electron density profile, the mountainous terrain, and the Earth curvature. After taking into account the effect of the irregular terrain between the Säntis Tower and the field measurement station, the vertical electric fields calculated by using our model are found to be in good agreement with the corresponding measured cases occurred in both daytime and nighttime. The ideal approximation used in either the classical solutions or the simplified models might lead to inaccuracies in the estimated reflection height. Furthermore, we discuss the sensitivity of our results by considering different return stroke models, as well as different typical values of the return stroke speed and of the ground conductivity. Key Points: A new model is developed to analyze the effect of the medium parameters in the Earth‐ionosphere waveguide and tested with measured dataThe time delays and amplitudes of the fields are affected by the electron density profile, the earth curvature and mountainous terrainThe numerical simulations agree well with the observations after taking into account the effect of the medium parameters in the ionosphere [ABSTRACT FROM AUTHOR]

Although the number of weather stations in the Republic of Korea that are located in mountainous regions has been increasing to provide better information of the weather in the mountains and aid effective predictions of disasters such as fires, landslides, and the dispersion of pollutants or airborne viruses, there is no standard method to aid the location of weather stations in mountainous regions. This study aims to develop a computational fluid dynamics (CFD) model to suggest a method for the proper installation of a wind monitoring system in a forested mountainous region. The inertial resistance coefficients of the canopy of coniferous and deciduous trees were measured through field experiments to simulate the wind environment in a mountainous region by considering the air resistance of trees. The averaged coefficients of the inertial resistance of coniferous and deciduous trees were 0.768 and 0.712 m-1, respectively. The developed open-source CFD model was validated using the measured field experiment data. The economic mesh size and a proper turbulence model were a 6.25 m and a standard k–ε turbulence model to simulate the wind environment in the selected forested mountainous region. Using the validated CFD model, the wind environments were analysed according to various environmental conditions, such as air resistance of trees, tree height, and diameter of the clear-cut, and a proper installation method for the mountain meteorological observation system to observe the wind was proposed based on the simulated results. • 3D open-source CFD model was developed considering topography and canopy of trees. • Wind environment on mountain area according to clear-cut size and height of trees. • Proper size of clear-cut to observe wind environment on mountain area. • Proper height of weather station to observe wind environment on mountain area. [ABSTRACT FROM AUTHOR]

Rugged terrain, as a large percentage of the Earth's terrestrial surface, is frequently reported to cause directionality of land surface thermal radiation (LSTR), and seriously affects the retrieval accuracy of land surface temperature (LST) and surface longwave radiation from satellite measurements. Therefore, modeling topographic effects on surface thermal anisotropy is essential to understand surface radiative processes. The directional brightness temperature (DBT) and equivalent brightness temperature (EBT) models at the pixel scale are proposed to indicate thermal anisotropy, considering viewing geometry, topographic effects, and subpixel variations based on the thermal infrared radiative transfer equation. A simulated data set of DBT and EBT at the 1-km resolution was obtained based on LST, emissivity, and terrain data with 30-m resolution. The terrain, coupled with solar and viewing geometries and subgrid variation, significantly affects the directionality of LSTR, and results in a remarkable bias between DBT and EBT. For the nadir observation, the bias is from −0.8 to 1 K, and reaches −5 to 2 K when viewing zenith angle becomes 50°. The maximal deviation is about 9 K over the most rugged mountains, which causes ${\text{57.6}}\;{\text{W/m}}^{2}$ bias of longwave radiation based on a 300 K blackbody. Furthermore, when LST is retrieved from DBT, the uncertainty of broadband emissivity of 0.01 causes LST bias of ∼0.35 K. The models are considered to be very helpful in exploring terrain-induced thermal anisotropy, and enlightening in reducing estimation bias of remote sensing products over complex terrain. [ABSTRACT FROM AUTHOR]

The influence of offshore wind farms in the northern South China Sea on a tropical depression far away (over the Beibu Gulf) is investigated through a fully coupled atmosphere-ocean model. Results show that in the experimental run with the offshore wind farms, the tropical depression located downstream of the wind farm are maintained for longer periods of time. This is mainly due to the stronger convection on the western side of the tropical depression. The stronger convergence in the lower level and divergence in the upper level caused by low-level gravity waves become the key dynamic condition. The primary factor influencing such gravity waves is the rapid decrease of the low-level vertical wind shear. The diagnostic analysis shows that wind-farm wakes affect the local low-level vertical velocity through the downstream mountainous terrain, which makes the vertical momentum term as the main contributing term affecting the variation of the horizontal momentum and subsequently the low-level vertical wind shear. This amplified impact of wind farms through the mountainous terrain may also occur in other regions. • The evolution of a tropical depression is modified significantly by upstream offshore wind farms. • The enhancement of convergence in the western side of the tropical depression is associated with gravity waves. • Wind-farm wakes affect the low-level vertical wind shear through the downstream mountainous terrain. [ABSTRACT FROM AUTHOR]

The current high rate of urbanization in developing countries and its consequences, like traffic congestion, slum development, scarcity of resources, and urban heat islands, raise a need for better Land Use Land Cover (LULC) classification mapping for improved planning. This study mainly deals with two objectives: 1) to explore the applicability of machine learning-based techniques, especially the Random forest (RF) algorithm and Support Vector Machine (SVM) algorithm as the potential classifiers for LULC mapping under different scenarios, and 2) to prepare a better LULC classification model for mountain terrain by using different indices with combination of spectral bands. Due to differences in topography, shadows, spectral confusion from overlapping spectral signatures of different land cover types, and a lack of access for ground verification, classification in mountainous terrain is difficult task compared to plain terrain classification. An enhanced LULC classification model has been designed using two popular machine learning (ML) classifier algorithms, SVM and RF, explicitly for mountainous terrains by taking into consideration of a study area of Gopeshwer town in the Chamoli district of Uttarakhand state, India. Online-based cloud platform Google Earth Engine (GEE) was used for overall processing. Four classification models were built using Sentinel 2B satellite imagery with 20m and 10m resolutions. Two of these models (Model 'i' based on RF algorithm and Model 'ii' based on SVM algorithm) were designed using spectral bands of visible and infrared wavelengths, and the other two (Model 'iii' based on RF algorithm and Model 'iv' based on SVM algorithm) with the addition of indices with spectral bands. The accuracy assessment was done using the confusion matrix based on the output results. Obtained result highlights that the overall accuracy for model 'i' and model 'ii' were 82% and 86% respectively, whereas these were 87.17% and 87.2% for model 'iii' and model 'iv' respectively. Finally, the study compared the performance of each model based on different accuracy metrics for better LULC mapping. It proposes an improved LULC classification model for mountainous terrains, which can contribute to better land management and planning in the study area., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)