Evaluation of interpolation methods of bathymetric data at the Poxim-Açu river dam – SE
DOI:
https://doi.org/10.33448/rsd-v9i9.7755Keywords:
Geostatistics; Interpolators; Reservoirs; Bathymetry; kriging.Abstract
The depth of natural water reservoirs is usually estimated through bathymetry spot data. Once bathymetric data are collected, data values are spatially distributed using interpolation methods. This study aimed to evaluate the performance of three different types of interpolators across a range of bathymetric data collected at the Poxim river dam, in the state of Sergipe. In September 2016, 882 bathymetric measurements were performed in the water reservoir. The bathymetric data were spatialized using three methods: inverse distance square interpolation, spline and kriging. The resulting estimates were evaluated and the best method was chosen based on cross-validation statistics (RMSE). The Poxim river dam presents an average depth of approximately 8.6 m, with maximum and minimum values of 19.3 and 0.5 m, respectively. Kriging was pointed out as the best interpolation model, along with the spherical semivariogram adjustment, with RMSE values of 1.64 m in cross-validation, followed by the inverse distance square (RMSE = 1,69 m) and spline (RMSE = 1,72 m). Therefore, kriging is the recommended model for the spatialization of bathymetric data in the evaluated water reservoir.
References
Antoine, G., Pretet, T., Secher, M., & Clutier, A. (2018). Temporal variability of partially-contaminated sediments in a strongly regulated reservoir of the upper Rhine River. In E3S Web of Conferences (Vol. 40, p. 04025). EDP Sciences.
ARAÚJO, H. M. D. (2007). Hélio Mário de. Relações Socioambientais na Bacia Costeira do Rio Sergipe. Núcleo de Pós-Graduação em Geografia–NPGEO. Universidade Federal de Sergipe–UFS. Tese (Doutorado em Geografia), São Cristovão.
Babak, O., & Deutsch, C. V. (2009). Statistical approach to inverse distance interpolation. Stochastic Environmental Research and Risk Assessment, 23(5), 543-553.
Bandini, F., Olesen, D. H., Jakobsen, J., Kittel, C. M. M., Wang, S., Garcia, M., & Bauer-Gottwein, P. (2018). Bathymetry observations of inland water bodies using a tethered single-beam sonar controlled by an unmanned aerial vehicle. Hydrology and Earth System Sciences, 22(8), 4165-4181.
Brighenti, L. S. (2009). Avaliação limnológica da lagoa central (Município de Lagoa Santa-MG): uma abordagem espacial.
Camargo, E. C. G. (1998). Geoestatística: fundamentos e aplicações. Geoprocessamento para projetos ambientais. São José dos Campos: INPE.
Cambardella, C. A., Moorman, T. B., Novak, J. M., Parkin, T. B., Karlen, D. L., Turco, R. F., & Konopka, A. E. (1994). Field‐scale variability of soil properties in central Iowa soils. Soil science society of America journal, 58(5), 1501-1511.
CARVALHO, J. R. D., & ASSAD, E. D. (2005). Análise espacial da precipitação pluviométrica no Estado de São Paulo: comparação de métodos de interpolação. Eng. Agríc, 377-384.
Castro, F. D. S., Pezzopane, J. E., Cecílio, R. A., Pezzopane, J. R., & Xavier, A. C. (2010). Avaliação do desempenho dos diferentes métodos de interpoladores para parâmetros do balanço hídrico climatológico. Revista brasileira de engenharia agrícola e ambiental, 14(8), 871-880.
Chen, M., Qin, X., Zeng, G., & Li, J. (2016). Impacts of human activity modes and climate on heavy metal “spread” in groundwater are biased. Chemosphere, 152, 439-445.
COMPANHIA DE SANEAMENTO DE SERGIPE – DESO. (2013). Recuperado de https://www.deso-se.com.br/v2/.
Diaconu, D. C., Bretcan, P., Peptenatu, D., Tanislav, D., & Mailat, E. (2019). The importance of the number of points, transect location and interpolation techniques in the analysis of bathymetric measurements. Journal of Hydrology, 570, 774-785.
dos Santos, G. R., de Oliveira, M. S., Louzada, J. M., & Santos, A. M. R. T. (2011). Krigagem simples versus krigagem universal: qual o preditor mais preciso?. Energia na Agricultura, 26(2), 49-55.
Ferreira, I. O., Rodrigues, D. D., Santos, G. R. D., & Rosa, L. M. F. (2017). In bathymetric surfaces: IDW or Kriging?. Boletim de Ciências Geodésicas, 23(3), 493-508.
Gabriel-Martin, I., Sordo-Ward, A., Garrote, L., & Granados, I. (2019). Hydrological Risk Analysis of Dams: The Influence of Initial Reservoir Level Conditions. Water, 11(3), 461.
Geisser, S. (1975). The predictive sample reuse method with applications. Journal of the American statistical Association, 70(350), 320-328.
Groeneveld, D. P., & Barz, D. D. (2014). Dixie Valley, Nevada playa bathymetry constructed from Landsat TM data. Journal of Hydrology, 512, 435-441.
Guarneri, J. C., & Weih Jr, R. C. (2012). Comparing methods for interpolation to improve raster digital elevation models. Journal of the Arkansas Academy of Science, 66(1), 77-81.
Hilton, J. E., Grimaldi, S., Cohen, R. C., Garg, N., Li, Y., Marvanek, S., ... & Walker, J. P. (2019). River reconstruction using a conformal mapping method. Environmental Modelling & Software, 119, 197-213.
Lang, J., Alho, P., Kasvi, E., Goseberg, N., & Winsemann, J. (2019). Impact of Middle Pleistocene (Saalian) glacial lake-outburst floods on the meltwater-drainage pathways in northern central Europe: Insights from 2D numerical flood simulation. Quaternary Science Reviews, 209, 82-99.
Mello, C. R. D., Silva, A. M. D., Lima, J. M. D., Ferreira, D. F., & Oliveira, M. S. D. (2003). Modelos matemáticos para predição da chuva de projeto para regiões do Estado de Minas Gerais. Revista Brasileira de Engenharia Agrícola e Ambiental, 7(1), 121-128.
Müller, C. A. (1996). Hidrelétricas, meio ambiente e desenvolvimento.
Nychka, D., Furrer, R., & Sain, S. (2017). Fields: Tools for Spatial Data (R Package).
Pereira, A. S., Shitsuka, D. M., Parreira, F. J., & Shitsuka, R. (2018). Metodologia da pesquisa científica.[e-book]. Santa Maria. Ed. UAB/NTE/UFSM. Disponível em: https://repositorio. ufsm. br/bitstream/handle/1/15824/Lic_Computacao_Metodologia-Pesquisa-Cientifica. pdf.
Ribeiro Jr, P. J., & Diggle, P. J. (2015). geoR: Analysis of Geostatistical Data. R package version 1.7-5.1.
Semwal, P., Khobragade, S. D., & Nainwal, H. C. (2017). Modelling of recent Erosion rates in a Lake catchment in the North-Western Siwalik Himalayas. Environmental Processes, 4(2), 355-374.
SILVA, S. F. da; FERRARI, J. L. (2011). Avaliação de interpoladores estatísticos e determinísticos na descrição batimétricas de ambientes aquáticos. II Simpósio de Geoestatística em Ciências Agrárias.
Solos, E. (2013). Sistema brasileiro de classificação de solos. Centro Nacional de Pesquisa de Solos: Rio de Janeiro.
Stähly, S., Franca, M. J., Robinson, C. T., & Schleiss, A. J. (2019). Sediment replenishment combined with an artificial flood improves river habitats downstream of a dam. Scientific Reports, 9(1), 1-8.
Team, R. C. (2010). R Development Core Team, 2014. R: a language and environment for statistical computing.
Teh, S. Y., Koh, H. L., Lim, Y. H., & Tan, W. K. (2017, November). Integrating bathymetric and topographic data. In AIP Conference Proceedings (Vol. 1905, No. 1, p. 030039). AIP Publishing LLC.
Vieira, S. R., Carvalho, J. R. P. D., & González, A. P. (2010). Jack knifing for semivariogram validation. Bragantia, 69, 97-105.
Warrick, A. W. (1980). Spatial variability of soil physical properties in the field. Application of soil physics., 319-344.
Watson, D. F., & Philip, G. M. (1985). A refinement of inverse distance weighted interpolation. Geo-processing, 2(4), 315-327.
Wilson, D. C., & Mair, B. A. (2004). Thin-plate spline interpolation. In Sampling, Wavelets, and Tomography (pp. 311-340). Birkhäuser, Boston, MA.
Yamamoto, J. K., & Landim, P. M. B. (2015). Geoestatística: conceitos e aplicações. Oficina de textos.
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Copyright (c) 2020 Igor Vieira Leite; André Quintão de Almeida; Diego Campana Loureiro; Rodolfo Marcondes Silva Souza; Maria Isidória Silva Gonzaga; Donizete dos Reis Pereira; Anderson de Almeida Santos
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