Assessment of Spatial Interpolation Methods to Map the Bathymetry of an Amazonian Hydroelectric Reservoir to Aid in Decision Making for Water Management

Curtarelli, Marcelo; Leão, Joaquim Antônio Dionísio; Ogashawara, Igor; Lorenzzetti, João A.; Stech, José

doi:10.3390/ijgi4010220

Cited by 75 publications

(58 citation statements)

References 14 publications

(31 reference statements)

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“…In fact, both the IDW and OK methods performed quite similarly, thus one of the methods could be adopted in this study. Our result was also similar in comparison to other studies found in the literature: (i) Curtarelli et al [35] observed RMSE value of 0.92 m using OK (isotropy) geostatistical method to map the bathymetry of an Amazonian hydroelectric reservoir over Brazil; (ii) Panhalkar and Jarag [20] found the IDW method performed better (i.e., RMSE value of 7.63 m) in generating the bathymetry of Panchganga River over India; (iii) Merwade [15] observed that the OK anisotropic method achieved RMSE values in the range of 0.20 m to 0.80 m in six river reaches in the United States; and (iv) Moskalik et al [36] investigated the bathymetry and geographical regionalization using OK method and found good relationship with the observed data (i.e., r 2 value of 0.98) over Hornsund, Norway. Furthermore, we calculated the deviation for each section of interest using both IDW and OK methods.…”

Section: Comparison Of Spatial Interpolation Methodssupporting

confidence: 50%

Use of Bathymetric and LiDAR Data in Generating Digital Elevation Model over the Lower Athabasca River Watershed in Alberta, Canada

Chowdhury

Hassan

Achari

et al. 2017

Water

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Abstract:The lower Athabasca River watershed is one of the most important regions for Alberta and elsewhere due to fact that it counts for the third largest oil reserve in the world. In order to support the oil and gas extraction, Athabasca River provides most of the required water supply. Thus, it is critical to understand the characteristics of the river and its watershed in order to develop sustainable water management strategies. Here, our main objective was to develop a digital elevation model (DEM) over the lower Athabasca River watershed including the main river channel of Athabasca River (i.e., approximately 128 km from Fort McMurray to Firebag River confluence). In this study, the primary data were obtained from the Alberta Environmental Monitoring, Evaluation and Reporting Agency. Those were: (i) Geoswath bathymetry at 5-10 m spatial resolution; (ii) point cloud LiDAR data; and (iii) river cross-section survey data. Here, we applied spatial interpolation methods like inverse distance weighting (IDW) and ordinary kriging (OK) to generate the bathymetric surface at 5 m × 5 m spatial resolution using the Geoswath bathymetry data points. We artificially created data gaps in 24 sections each in the range of 100 to 400 m along the river and further investigated the performance of the methods based on statistical analysis. We observed that the DEM generated using the both IDW and OK methods were quite similar, i.e., r 2 , relative error, and root mean square error were approximately 0.99, 0.002, and 0.104 m, respectively. We also evaluated the performance of both methods over individual sections of interest; and overall deviation was found to be within ±2.0 m while approximately 96.5% of the data fell within ±0.25 m. Finally, we combined the Geoswath-derived DEM and LiDAR-derived DEM in generating the final DEM over the lower Athabasca River watershed at 5 m × 5 m resolution.

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Section: Comparison Of Spatial Interpolation Methodssupporting

confidence: 50%

Use of Bathymetric and LiDAR Data in Generating Digital Elevation Model over the Lower Athabasca River Watershed in Alberta, Canada

Chowdhury

Hassan

Achari

et al. 2017

Water

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“…Conversely, Bello-Pineda and Hernández-Stefanoni (2007) showed that the kriging method was better than IDW for mapping the bathymetry of the Yucatan submerged platform (Curtarelli et al 2015).…”

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confidence: 99%

In Bathymetric Surfaces: Idw or Kriging?

et al. 2017

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Abstract:The representation of the submerged relief is very importance in diverse areas of knowledge such as Projects to build or reassess port dimensions, installation of moles, ducts, marinas, bridges, tunnels, mineral prospecting, waterways, dredging, silting control of river and lakes, and others. The depths of the aquatic bodies, indispensable for the representation of those, are obtained through the bathymetric surveys. However, the result of a bathymetric sampling is a grid of points that, for itself, it is not capable of generating directly the Digital Model of Depth (DMD), being necessary the use of interpolators. Currently, there are more than 40 available scientific methods of interpolation, each one with its particularities and characteristics. This study has the objective to analise, comparing, the efficiency of Universal Kriging (UK) and of the Inverse Distance Weighted (IDW) in the computational representation of bathymetric surfaces, varying in a decreasing way the quantity of sample points. Through the results, we can be stated the superiority of the interpolator Universal Kriging in efficiency in creating DMD with basis in the bathymetric surveys data.Keywords: Bathymetric surveys; Interpolators; Kriging; Inverse squared distance weighted; universal kriging. Resumo:A representação do relevo submerso é de essencial importância em diversas áreas do conhecimento como em projetos para construção ou reavaliação de dimensões portuárias, instalação de moles, dutos, marinas, pontes, túneis, prospecção mineral, cursos de água, dragagem, controle de sedimentos de rios e lagos e outros. As profundidades dos corpos aquáticos, indispensáveis para a representação destes, são obtidas através dos levantamentos batimétricos. No entanto, o produto resultante de uma batimetria é uma malha de pontos amostrais que, por si só, não é capaz de gerar diretamente o Modelo Digital de Profundidade (MDP), sendo necessário o uso de interpoladores. Até o momento existem mais de 40 métodos de interpolação disponíveis na literatura, cada um com suas particularidades e características. Este estudo teve como objetivo analisar,

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“…To treat missing data, two common approaches are available. One is to exclude periods with missing values from data analysis, and the other is to ignore the missing data based on the tacit assumption that the data represent one continuous series [3,4]. However, these approaches may disregard useful information and bias the analysis results [2].…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Method for Interpolating Missing Data in Heterogeneous Spatio-Temporal Datasets

Deng

Zide

Liu

et al. 2016

IJGI

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Space-time interpolation is widely used to estimate missing or unobserved values in a dataset integrating both spatial and temporal records. Although space-time interpolation plays a key role in space-time modeling, existing methods were mainly developed for space-time processes that exhibit stationarity in space and time. It is still challenging to model heterogeneity of space-time data in the interpolation model. To overcome this limitation, in this study, a novel space-time interpolation method considering both spatial and temporal heterogeneity is developed for estimating missing data in space-time datasets. The interpolation operation is first implemented in spatial and temporal dimensions. Heterogeneous covariance functions are constructed to obtain the best linear unbiased estimates in spatial and temporal dimensions. Spatial and temporal correlations are then considered to combine the interpolation results in spatial and temporal dimensions to estimate the missing data. The proposed method is tested on annual average temperature and precipitation data in China (1984China ( -2009. Experimental results show that, for these datasets, the proposed method outperforms three state-of-the-art methods-e.g., spatio-temporal kriging, spatio-temporal inverse distance weighting, and point estimation model of biased hospitals-based area disease estimation methods.

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Assessment of Spatial Interpolation Methods to Map the Bathymetry of an Amazonian Hydroelectric Reservoir to Aid in Decision Making for Water Management

Cited by 75 publications

References 14 publications

Use of Bathymetric and LiDAR Data in Generating Digital Elevation Model over the Lower Athabasca River Watershed in Alberta, Canada

Use of Bathymetric and LiDAR Data in Generating Digital Elevation Model over the Lower Athabasca River Watershed in Alberta, Canada

In Bathymetric Surfaces: Idw or Kriging?

A Hybrid Method for Interpolating Missing Data in Heterogeneous Spatio-Temporal Datasets

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