scholarly journals The solution to DEM resolution effects and parameter inconsistency by using scale-invariant TOPMODEL

2012 ◽  
Vol 43 (1-2) ◽  
pp. 146-155 ◽  
Author(s):  
Jing Xu ◽  
Liliang Ren ◽  
Fei Yuan ◽  
Xiaofan Liu
Keyword(s):  
Scale Effects ◽  
Scale Invariant ◽  
Topographic Index ◽  
Topographic Complexity ◽  
Dem Resolution ◽  
Coarse Resolution ◽  
Resolution Factor ◽  
Digital Elevation ◽  
Fractal Parameters ◽  
Elevation Model

The parameter calibration of TOPMODEL is influenced by digital elevation model (DEM) resolution because of the utilization of scale-dependent topographic index representing hydrologic similarity. The downscaled DEM from the coarse-resolution DEM and the resolution factor are applied to remove the DEM scale effects on the upslope area. Meanwhile, a fractal method is introduced as an approach to account for the effect of DEM resolution on slope. A significant improvement on the estimation of slope directly from the coarse-resolution data is made by applying fractal parameters that are computed from the standard deviation of elevation and the topographic complexity index in a 3 × 3 window of the DEM to account for local variability in the surface. The method to downscale the topographic index distribution is then coupled with the TOPMODEL to develop the scale-invariant TOPMODEL and is applied to perform streamflow simulation in the context of different DEM resolutions in the Zishui catchment. Results show that the calculated hydrograph based on the DEM data at 900 and 1,800 m resolution is consistent with that based on the DEM data at 100 m resolution when the same parameter set is used.

The effects of spatial aggregation of complex topography on hydroecological process simulations within a rugged forest landscape: development and application of a satellite-based topoclimatic model

2004 ◽  
Vol 34 (3) ◽  
pp. 519-530 ◽  
Author(s):  
S Kang ◽  
D Lee ◽  
J S Kimball
Keyword(s):  
Solar Radiation ◽  
Scale Effects ◽  
Net Primary Production ◽  
Spatial Scales ◽  
Spatial Aggregation ◽  
Area Index ◽  
Topographic Complexity ◽  
Digital Elevation ◽  
Process Simulations ◽  
Elevation Model

We evaluated the effects of topographic complexity on landscape carbon and hydrologic process simulations within a rugged mixed hardwood forest by developing and applying a satellite-based hydroecological model at multiple spatial scales. The effects of topographic variability were evaluated by aggregating raster-based digital elevation model and satellite-derived leaf area index inputs across eight different spatial resolutions from 30 m (62 208 pixels) to 2160 m (12 pixels). Our modeling analysis showed that the effect of topography was the strongest on solar radiation and temperature, intermediate on soil water and evapotranspiration, and ambiguous on soil respiration. Spatial aggregation of model inputs smoothed heterogeneous spatial patterns of modeled output variables relative to fine-scale results. Model outputs varied nonlinearly with different levels of spatial aggregation, while spatial variability of model inputs and outputs were dampened at increasingly coarse aggregation levels. Biases in spatially aggregated model predictions were generally less than ±10%, except for solar radiation, which showed biases of up to +50% at coarser spatial scales. The large positive bias in the solar radiation implies that overestimation of biophysical variables that are sensitive to solar radiation (e.g., photosynthesis and net primary production) may be considerable in rugged forested landscapes unless subgrid scale effects are accounted for.

scholarly journals Reducing scale dependence in TOPMODEL using a dimensionless topographic index

2009 ◽  
Vol 13 (12) ◽  
pp. 2399-2412 ◽  
Author(s):  
A. Ducharne
Keyword(s):  
Cell Size ◽  
Scale Dependence ◽  
Contour Length ◽  
Topographic Index ◽  
Dem Resolution ◽  
Unit System ◽  
Topographic Slope ◽  
Digital Elevation ◽  
Numerical Effect ◽  
Elevation Model

Abstract. This paper stems from the fact that the topographic index used in TOPMODEL is not dimensionless. In each pixel i in a catchment, it is defined as xi=ln(ai/Si), where ai is the specific contributing area per unit contour length and Si is the topographic slope. In the SI unit system, ai/Si is in meters, and the unit of xi is problematic. We propose a simple solution in the widespread cases where the topographic index is computed from a regular raster digital elevation model (DEM). The pixel length C being constant, we can define a dimensionless topographic index yi=xi-lnC. Reformulating TOPMODEL equations to use yi instead of xi helps giving the units of all their terms and emphasizes the scale dependence of these equations via the explicit use of C outside from the topographic index, in what can be defined as the transmissivity at saturation per unit contour length T0/C. The term lnC defines the numerical effect of DEM resolution, which contributes to shift the spatial mean x of the classical topographic index when the DEM cell size C varies. A key result is that both the spatial mean y of the dimensionless index and T0/C are much more stable with respect to DEM resolution than their counterparts x and T0 in the classical framework. This shows the importance of the numerical effect in the dependence of the classical topographic index to DEM resolution, and reduces the need to recalibrate TOPMODEL when changing DEM resolution.

scholarly journals Digital terrain analysis of the Haute-Mentue catchment an scale effect for hydrological modelling with TOPMODEL

2000 ◽  
Vol 4 (2) ◽  
pp. 225-237 ◽  
Author(s):  
C. Higy ◽  
A. Musy
Keyword(s):  
Digital Elevation Model ◽  
Scale Effects ◽  
Digital Terrain Model ◽  
Hydrological Modelling ◽  
Terrain Analysis ◽  
Topographic Index ◽  
Terrain Model ◽  
Digital Terrain ◽  
Digital Elevation ◽  
Elevation Model

Abstract. It is widely recognised that topography plays an important role in the generation of runoff. The scale of a digital elevation model has been found to have some impacts on the results of hydrological modelling in several studies. In particular it has been shown that the representation of the statistical distribution of the topographic index used by TOPMODEL is sensitive to the scale of the digital terrain model. The objectives of this study are to develop an analysis of the topography and scale effects for the Haute-Mentue catchment and to test the role of different spatial resolution on parameter calibration. The major result is that the spatial scale is important for the parameter values, but not determinant for the modelling results if a pertinent methodology is adopted for the determination of digital watershed representation. Keywords: digital elevation model, topographic index, scale problems, TOPMODEL

scholarly journals Explicitation of an important scale dependence in TOPMODEL using a dimensionless topographic index

2009 ◽  
Vol 6 (2) ◽  
pp. 1621-1649 ◽  
Author(s):  
A. Ducharne
Keyword(s):  
Cell Size ◽  
Scale Dependence ◽  
Contour Length ◽  
Dimensionless Quantity ◽  
Topographic Index ◽  
Dem Resolution ◽  
Unit System ◽  
Topographic Slope ◽  
Digital Elevation ◽  
Elevation Model

Abstract. This paper stems from the fact that the topographic index used in TOPMODEL is not dimensionless. In each pixel i in a catchment, it is defined as xi=ln (ai /Si), where ai is the specific contributing area per unit contour length and Si is the topographic slope. In the SI unit system, ai /Si is in meters, and the unit of xi is problematic. Even if all the equations in TOPMODEL are homogeneous, it is confusing to use the logarithm of a non-dimensionless quantity as an index, and we propose a simple solution to this issue in the nowadays widespread cases where the topographic index is computed from a regular raster digital elevation model (DEM). The pixel length C being constant, we can define a dimensionless topographic index yi=xi−ln C. Reformulating TOPMODEL's equations to use yi instead of xi helps giving the units of all the terms in TOPMODEL's equations. Another advantage is to raise awareness about the scale dependence of these equations via the explicit use of the DEM cell size C outside from the topographic index, in what what can be defined as the transmissivity at saturation per unit contour length T0/C. We eventually demonstrate, based on various examples from the literature, that both T0/C and the spatial mean y of the proposed dimensionless topographic index are very stable with respect to DEM resolution. This markedly reduces the recalibration necessity when changing DEM resolution, thus offering an efficient rescaling framework.

scholarly journals The use of LIDAR as a data source for digital elevation models – a study of the relationship between the accuracy of digital elevation models and topographical attributes in northern peatlands

2011 ◽  
Vol 8 (3) ◽  
pp. 5497-5522 ◽  
Author(s):  
A. Hasan ◽  
P. Pilesjö ◽  
A. Persson
Keyword(s):  
High Resolution ◽  
Interpolation Method ◽  
Digital Elevation Models ◽  
Drainage Area ◽  
Absolute Deviation ◽  
Weighting Method ◽  
Dem Resolution ◽  
Coarse Resolution ◽  
Digital Elevation ◽  
Topographical Attributes

Abstract. It is important to study the factors affecting estimates of wetness since wetness is crucial in climate change studies. The availability of digital elevation models (DEMs) generated with high resolution data is increasing, and their use is expanding. LIDAR earth elevation data have been used to create several DEMs with different resolutions, using various interpolation parameters, in order to compare the models with collected surface data. The aim is to study the accuracy of DEMs in relation to topographical attributes such as slope and drainage area, which are normally used to estimate the wetness in terms of topographic wetness indices. Evaluation points were chosen from the high-resolution LIDAR dataset at a maximum distance of 10 mm from the cell center for each DEM resolution studied, 0.5, 1, 5, 10, 30 and 90 m. The interpolation method used was inverse distance weighting method with four search radii: 1, 2, 5 and 10 m. The DEM was evaluated using a quantile-quantile test and the normalized median absolute deviation. The accuracy of the estimated elevation for different slopes was tested using the DEM with 0.5 m resolution. Drainage areas were investigated at three resolutions, with coinciding evaluation points. The ability of the model to generate the drainage area at each resolution was obtained by pairwise comparison of three data subsets. The results show that the accuracy of the elevations obtained with the DEM model are the same for different resolutions, but vary with search radius. The accuracy of the values (NMAD of errors) varies from 29.7 mm to 88.9 mm, being higher for flatter areas. It was also found that the accuracy of the drainage area is highly dependent on DEM resolution. Coarse resolution yielded larger estimates of the drainage area but lower slope values. This may lead to overestimation of wetness values when using a coarse resolution DEM.

scholarly journals Evaluation of Reliable Digital Elevation Model Resolution for TOPMODEL in Two Mountainous Watersheds, South Korea

2019 ◽  
Vol 9 (18) ◽  
pp. 3690 ◽  
Author(s):  
Daeryong Park ◽  
Huan-Jung Fan ◽  
Jun-Jie Zhu ◽  
Sang-Eun Oh ◽  
Myoung-Jin Um ◽  
...  
Keyword(s):  
South Korea ◽  
Cell Size ◽  
Digital Elevation Model ◽  
River Basin ◽  
Grid Cell ◽  
Dem Resolution ◽  
Digital Elevation ◽  
Mountainous Watersheds ◽  
Elevation Model ◽  
Digital Elevation Model Resolution

This study analyzed the result of parameter optimization using the digital elevation model (DEM) resolution in the TOPography-based hydrological MODEL (TOPMODEL). Also, this study investigated the sensitivity of the TOPMODEL efficiency by applying the varying resolution of the DEM grid cell size. This work applied TOPMODEL to two mountainous watersheds in South Korea: the Dongkok watershed in the Wicheon river basin and the Ieemokjung watershed in the Pyeongchang river basin. The DEM grid cell sizes were 5, 10, 20, 40, 80, 160, and 300 m. The effect of DEM grid cell size on the runoff was investigated by using the DEM grid cell size resolution to optimize the parameter sets. As the DEM grid cell size increased, the estimated peak discharge was found to increase based on different parameter sets. In addition, this study investigated the DEM grid cell size that was most reliable for use in runoff simulations with various parameter sets in the experimental watersheds. The results demonstrated that the TOPMODEL efficiencies in both the Dongkok and Ieemokjung watersheds rarely changed up to a DEM grid-size resolution of about 40 m, but the TOPMODEL efficiencies changed with the coarse resolution as the parameter sets were changed. This study is important for understanding and quantifying the modeling behaviors of TOPMODEL under the influence of DEM resolution based on different parameter sets.

scholarly journals Effects of digital elevation model resolution on topography-based runoff simulation under uncertainty

2014 ◽  
Vol 16 (6) ◽  
pp. 1343-1358 ◽  
Author(s):  
L. Cui ◽  
Y. P. Li ◽  
G. H. Huang ◽  
Y. Huang
Keyword(s):  
Water Resources ◽  
Digital Elevation Model ◽  
Water Resources Management ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Resources Management ◽  
Dem Resolution ◽  
Analysis Technique ◽  
Digital Elevation ◽  
Elevation Model

Topography plays a critical role in controlling water dispersion and soil movement in hydrologic modeling for water resources management with raster-based digital elevation model (DEM). This study aims to model effects of DEM resolution on runoff simulation through coupling fuzzy analysis technique with a topography based rainfall–runoff model (TOPMODEL). Different levels of DEM grid sizes between 30 m and 200 m are examined, and the results indicate that 30 m DEM resolution is the best for all catchments. Results demonstrate that the DEM resolution could have significant influence on the TOPMODEL rainfall–runoff simulation. Fuzzy analysis technique is used to further examine the uncertain DEM resolution based on considering Nash, sum of squared error, and sum of absolute error values of TOPMODEL. The developed model is calibrated and validated against observed flow during the period 2010–2012, and generally performed acceptably for model Nash–Sutcliffe value. The proposed method is useful for studying hydrological processes of watershed associated with topography uncertainty and providing support for identifying proper water resources management strategy.

scholarly journals An Improved Approach for Downscaling Coarse-Resolution Thermal Data by Minimizing the Spatial Averaging Biases in Random Forest

2020 ◽  
Vol 12 (21) ◽  
pp. 3507
Author(s):  
Sammy M. Njuki ◽  
Chris M. Mannaerts ◽  
Zhongbo Su
Keyword(s):  
Random Forest ◽  
Land Surface ◽  
Spatial Averaging ◽  
Complex Environments ◽  
Spatial And Temporal Scales ◽  
Coarse Resolution ◽  
Digital Elevation ◽  
Thermal Data ◽  
Geophysical Processes ◽  
Elevation Model

Land surface temperature (LST) plays a fundamental role in various geophysical processes at varying spatial and temporal scales. Satellite-based observations of LST provide a viable option for monitoring the spatial-temporal evolution of these processes. Downscaling is a widely adopted approach for solving the spatial-temporal trade-off associated with satellite-based observations of LST. However, despite the advances made in the field of LST downscaling, issues related to spatial averaging in the downscaling methodologies greatly hamper the utility of coarse-resolution thermal data for downscaling applications in complex environments. In this study, an improved LST downscaling approach based on random forest (RF) regression is presented. The proposed approach addresses issues related to spatial averaging biases associated with the downscaling model developed at the coarse resolution. The approach was applied to downscale the coarse-resolution Satellite Application Facility on Land Surface Analysis (LSA-SAF) LST product derived from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor aboard the Meteosat Second Generation (MSG) weather satellite. The LSA-SAF product was downscaled to a spatial resolution of ~30 m, based on predictor variables derived from Sentinel 2, and the Advanced Land Observing Satellite (ALOS) digital elevation model (DEM). Quantitatively and qualitatively, better downscaling results were obtained using the proposed approach in comparison to the conventional approach of downscaling LST using RF widely adopted in LST downscaling studies. The enhanced performance indicates that the proposed approach has the ability to reduce the spatial averaging biases inherent in the LST downscaling methodology and thus is more suitable for downscaling applications in complex environments.

Impacts of coarse-resolution soil maps and high-resolution digital-elevation-model-generated attributes on modelling forest soil zinc and copper

2021 ◽  
pp. 1-16
Author(s):  
Zhengyong Zhao ◽  
Qi Yang ◽  
Xiaogang Ding ◽  
Zisheng Xing
Keyword(s):  
High Resolution ◽  
Forest Soil ◽  
Digital Elevation Model ◽  
Cross Validation ◽  
Large Area ◽  
Coarse Resolution ◽  
Digital Elevation ◽  
Ann Models ◽  
Elevation Model ◽  
Fold Cross Validation

The depth-specific zinc (Zn) and copper (Cu) maps with high resolution (i.e., ≤10 m) are important for soil and forest management and conservation. The objective of this study was to assess the effects of easily accessible model inputs, i.e., existing coarse-resolution parent material, pH, and soil texture maps with 1:1 800 000–2 800 000 scale and nine digital elevation model (DEM)-generated terrain attributes with 10 m resolution, on modelling Zn and Cu distributions of forest soil over a large area (e.g., thousands of km2). A total of 511 artificial neural network (ANN) models for each depth (20 cm increments to 100 cm) were built and evaluated by a 10-fold cross-validation with 385 soil profiles from the Yunfu forest, South China, about 4915 km2 areas. The results indicated that the optimal models for five depths engaged five to seven DEM-generated attributes together with three coarse-resolution soil attributes as inputs, respectively, and accuracies for estimating Zn and Cu varied with R2 of 0.76–0.85 and relative overall accuracy ±10% of 74%–86%. The produced maps showed that DEM-generated sediment delivery ratio, topographic position index (TPI), and aspect were the most important attributes for predicting Cu, but flow length, TPI, and slope were for Zn, which heavily affected Zn and Cu distributions in detail. Boundaries of three coarse-resolution maps were still visible in the generated maps indicated that the maps affected the distributions of Zn and Cu in large scales. Thus, the modelling method, i.e., developing ANN models with k-fold cross-validation, can be used to map high-resolution Zn and Cu over a large area.

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