Research and realization of large-scale complex terrain generation

2002 ◽  
Author(s):  
Jian-yu Wang ◽  
Xiao-xia Zhong ◽  
Hui-zhong Wu
Keyword(s):  
Complex Terrain ◽  
Large Scale ◽  
Terrain Generation

scholarly journals Probabilistic downscaling of precipitation data in a subtropical mountain area: a two-step approach

2011 ◽  
Vol 18 (2) ◽  
pp. 223-234 ◽  
Author(s):  
R. Haas ◽  
K. Born
Keyword(s):  
Complex Terrain ◽  
Large Scale ◽  
Distribution Functions ◽  
Data Availability ◽  
Cumulative Distribution ◽  
Second Step ◽  
Mountain Area ◽  
Investigation Area ◽  
Distribution Parameters ◽  
Mountain Environment

Abstract. In this study, a two-step probabilistic downscaling approach is introduced and evaluated. The method is exemplarily applied on precipitation observations in the subtropical mountain environment of the High Atlas in Morocco. The challenge is to deal with a complex terrain, heavily skewed precipitation distributions and a sparse amount of data, both spatial and temporal. In the first step of the approach, a transfer function between distributions of large-scale predictors and of local observations is derived. The aim is to forecast cumulative distribution functions with parameters from known data. In order to interpolate between sites, the second step applies multiple linear regression on distribution parameters of observed data using local topographic information. By combining both steps, a prediction at every point of the investigation area is achieved. Both steps and their combination are assessed by cross-validation and by splitting the available dataset into a trainings- and a validation-subset. Due to the estimated quantiles and probabilities of zero daily precipitation, this approach is found to be adequate for application even in areas with difficult topographic circumstances and low data availability.

scholarly journals Multi-Scale Evaluation of the TSEB Model over a Complex Agricultural Landscape in Morocco

2020 ◽  
Vol 12 (7) ◽  
pp. 1181
Author(s):  
Jamal Elfarkh ◽  
Jamal Ezzahar ◽  
Salah Er-Raki ◽  
Vincent Simonneaux ◽  
Bouchra Ait Hssaine ◽  
...  
Keyword(s):  
Latent Heat ◽  
Complex Terrain ◽  
Large Scale ◽  
Agricultural Landscape ◽  
Local Scale ◽  
Heat Fluxes ◽  
Balance Model ◽  
Modis Data ◽  
Multi Scale ◽  
Basin Scale

An accurate assessment of evapotranspiration (ET) is crucially needed at the basin scale for studying the hydrological processes and water balance especially from upstream to downstream. In the mountains, this term is poorly understood because of various challenges, including the vegetation complexity, plant diversity, lack of available data and because the in situ direct measurement of ET is difficult in complex terrain. The main objective of this work was to investigate the potential of a Two-Source-Energy-Balance model (TSEB) driven by the Landsat and MODIS data for estimating ET over a complex mountain region. The complexity is associated with the type of the vegetation canopy as well as the changes in topography. For validating purposes, a large-aperture scintillometer (LAS) was set up over a heterogeneous transect of about 1.4 km to measure sensible (H) and latent heat (LE) fluxes. Additionally, two towers of eddy covariance (EC) systems were installed along the LAS transect. First, the model was tested at the local scale against the EC measurements using multi-scale remote sensing (MODIS and Landsat) inputs at the satellite overpasses. The obtained averaged values of the root mean square error (RMSE) and correlation coefficient (R) were about 72.4 Wm−2 and 0.79 and 82.0 Wm−2 and 0.52 for Landsat and MODIS data, respectively. Secondly, the potential of the TSEB model for evaluating the latent heat fluxes at large scale was investigated by aggregating the derived parameters from both satellites based on the LAS footprint. As for the local scale, the comparison of the latent heat fluxes simulated by TSEB driven by Landsat data performed well against those measured by the LAS (R = 0.69, RMSE = 68.0 Wm−2), while slightly more scattering was observed when MODIS products were used (R = 0.38, RMSE = 99.8 Wm−2). Based on the obtained results, it can be concluded that (1) the TSEB model can be fairly used to estimate the evapotranspiration over the mountain regions; and (2) medium- to high-resolution inputs are a better option than coarse-resolution products for describing this kind of complex terrain.

scholarly journals Gully Erosion Susceptibility Mapping in Highly Complex Terrain Using Machine Learning Models

2021 ◽  
Vol 10 (10) ◽  
pp. 680
Author(s):  
Annan Yang ◽  
Chunmei Wang ◽  
Guowei Pang ◽  
Yongqing Long ◽  
Lei Wang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Complex Terrain ◽  
Large Scale ◽  
Area Under The Curve ◽  
Gully Erosion ◽  
Susceptibility Mapping ◽  
Weight Of Evidence ◽  
Gradient Boosting ◽  
Machine Learning Classification ◽  
Extreme Gradient Boosting

Gully erosion is the most severe type of water erosion and is a major land degradation process. Gully erosion susceptibility mapping (GESM)’s efficiency and interpretability remains a challenge, especially in complex terrain areas. In this study, a WoE-MLC model was used to solve the above problem, which combines machine learning classification algorithms and the statistical weight of evidence (WoE) model in the Loess Plateau. The three machine learning (ML) algorithms utilized in this research were random forest (RF), gradient boosted decision trees (GBDT), and extreme gradient boosting (XGBoost). The results showed that: (1) GESM were well predicted by combining both machine learning regression models and WoE-MLC models, with the area under the curve (AUC) values both greater than 0.92, and the latter was more computationally efficient and interpretable; (2) The XGBoost algorithm was more efficient in GESM than the other two algorithms, with the strongest generalization ability and best performance in avoiding overfitting (averaged AUC = 0.947), followed by the RF algorithm (averaged AUC = 0.944), and GBDT algorithm (averaged AUC = 0.938); and (3) slope gradient, land use, and altitude were the main factors for GESM. This study may provide a possible method for gully erosion susceptibility mapping at large scale.

Catastrophic landslide affected by topography: a case study in Guizhou, China

2021 ◽  
Author(s):  
Jian Guo
Keyword(s):  
Complex Terrain ◽  
Large Scale ◽  
Shallow Water Equation ◽  
Maximum Velocity ◽  
Field Investigation ◽  
Guizhou Province ◽  
Future Research ◽  
Low Velocity ◽  
Runout Distance ◽  
Rainfall Analysis

<p>In mountainous areas, large-scale landslides usually cause serious disasters. A large number of studies have found that complex terrain may affect the landslides dynamic, which may be one of the significant factors in catastrophic events. However, the mechanism is rarely explored. On July 23, 2019, a large-scale landslide occurred in Jichang town, Shuicheng County, Liupanshui City, Guizhou Province in China. The landslide, which moved along two gullies, resulted in strong punching-shear, induced scarping on vegetation and large destruction of houses and finally formed a deposit with a volume of 2×106 m3. This research aims to understand the effect of topography on landslide kinematics. To achieve this aim, a detailed field investigation was first carried out with an unmanned aerial vehicle (UAV) aerial photography survey, resident interviews, and field sampling. The rainfall analysis indicate the effective rainfall within seven days before landslides was 70.14 mm which exceeded the rainfall threshold of 54.3 mm in this region, which finally triggered the landslide. Traditional soil mechanics tests were then performed to identify the soil properties of the source material. Combined with numerical simulation using the nonlinear shallow water equation, the whole process of landslides was divided into four stages: instability stage, acceleration stage, transformation stage and impact and accumulation stage. The simulations results show the landslide block slid with a low velocity of 8 m/s for about 100 m. Then, Froude number of landslide increase from 2 to 3 when passing the high and steep terrain, indicating that landslide change to inertial dominated with potential same Froude behavior of classic debris flow. The rupture mass slid with the peak velocity of 23 m/s and diverged in two gullies and ran out for about 600 m. The maximum velocity is 23 m/s in east gully while only 15 m/s in west gully. Compared with deep and incised valleys in west, shallow and straight valley in east decrease the deposit depth, further increase the velocity of landslide material with increased runout distance. This research may provide a fast flow path of back analyzing geo-hazards on complex terrain and serve as a basis for future research on long runout landslides. </p>

scholarly journals Multiscale Characteristics of Surface Winds in an Area of Complex Terrain in Northwest Utah

2016 ◽  
Vol 55 (7) ◽  
pp. 1549-1563 ◽  
Author(s):  
Matthew E. Jeglum ◽  
Sebastian W. Hoch
Keyword(s):  
Sierra Nevada ◽  
Complex Terrain ◽  
Large Scale ◽  
Surface Wind ◽  
Surface Winds ◽  
Thermally Driven ◽  
Primary Direction ◽  
Monthly Changes ◽  
Large Scale Flow ◽  
Baroclinic Zone

AbstractClimatological features of the surface wind on diurnal and seasonal time scales over a 17-yr period in an area of complex terrain at Dugway Proving Ground in northwestern Utah are analyzed, and potential synoptic-scale, mesoscale, and microscale forcings on the surface wind are identified. Analysis of the wind climatology at 26 automated weather stations revealed a bimodal wind direction distribution at times when thermally driven circulations were expected to produce a single primary direction. The two modes of this distribution are referred to as the “northerly” and “southerly” regimes. The northerly regime is most frequent in May, and the southerly regime is most frequent in August. January, May, and August constitute a “tripole seasonality” of the wind evolution. Although both regimes occur in all months, the monthly changes in regime frequency are related to changes in synoptic and mesoscale phenomena including the climatological position of the primary synoptic baroclinic zone in the western United States, interaction of the large-scale flow with the Sierra Nevada, and thermal low pressure systems that form in the Intermountain West in summer. Numerous applications require accurate forecasts of surface winds in complex terrain, yet mesoscale models perform relatively poorly in these areas, contributing to poor operational forecast skill. Knowledge of the climatologically persistent wind flows and their potential forcings will enable relevant model deficiencies to be addressed.

scholarly journals Scale Interactions in Turbulence for Mountain Blowing Snow

2018 ◽  
Vol 19 (2) ◽  
pp. 305-320 ◽  
Author(s):  
N. O. Aksamit ◽  
J. W. Pomeroy
Keyword(s):  
High Frequency ◽  
Complex Terrain ◽  
Large Scale ◽  
Quadrant Analysis ◽  
Blowing Snow ◽  
Near Surface ◽  
Atmospheric Flows ◽  
Surface Turbulence ◽  
Frequency Coherence ◽  
Snow Transport

Abstract Blowing snow particle transport responds to wind motions across many length and time scales. This coupling is nonlinear by nature and complicated in atmospheric flows where eddies of many sizes are superimposed. In mountainous terrain, wind flow descriptions are further complicated by topographically influenced or enhanced flows. To improve the current understanding and modeling of blowing snow transport in complex terrain, statistically significant timing and frequencies of wind–snow coupling were identified in high-frequency observations of surface blowing snow and near-surface turbulence from a mountain field site in the Canadian Rockies. Investigation of the mechanisms influencing near-surface, high-frequency turbulence and snow concentration fluctuations provided strong evidence for amplitude modulation from large-scale motions. The large-scale atmospheric motions modulating near-surface turbulence and snow transport were then compared to specific quadrant analysis structures recently identified as relevant for outdoor blowing snow transport. The results suggest that large atmospheric structures modulate the amplitude of high-frequency turbulence and modify turbulence statistics typically used to model blowing snow. Additionally, blowing snow was preferentially redistributed under the footprint of these same sweep motions, with both low- and high-frequency coherence increasing in their presence.

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