Three-Dimensional Tetrahedron Network (3D TEN) and Volumetric Geo-Objects (VGO) Data Model for Groundwater Simulation in Bida Basin, Nigeria

Izham Mohamad Yusoff, Ishaku Bashir Yakubu

Abstract


The presence of complex ground soil structures limits the attempt for groundwater extraction for alternate water supply usage. Hydrologists and engineers have made many attempts to Model 3D groundwater flow and storage using digital elevation model (DEM) data structures but have resulted in limited success in terms of actual 3D subsurface geology representation. This study attempts to construct resistivity data in an actual 3D environment using volumetric geo-objects (VGOs) and 3D tetrahedron network (3D TEN) data structures. Subsurface data were collected using the vertical electrical sounding (VES) approach to analyse the geological structure of the study area. To determine the course and movement of groundwater, the 3D constant was applied from Darcy's law in the Lagrangian technique. A time frame of one hour, two hours, four hours and eight-hour intervals was tested to simulate the porosity and permeability of various soil types with complex geological structures. The findings validated the use of 3D visualisation to model resistivity data. The implemented volumetric geo-object (VGO) data model and the 3D TEN model show the volume of water over the topsoil to be 17,461,228.07 in an hour; clay soil was 870,614.04; clayey sand was 435,307.02; and sandy clays was 348,245.61 per kilometre cube (km3). The use of 3D TEN and VGO for groundwater simulation in this research offers an improved perspective in groundwater visualisation that will promote sustainable groundwater exploration for societal developments. The findings of this study will be beneficial to stakeholders, water resource managers and government agencies such as Ministry of Water Resources.

 

Keywords: Data model, Groundwater simulation, Three-dimensional tetrahedron network (3D TEN), Vertical electrical sounding (VES), Visualisation, Volumetric geo-objects (VGOs)


Keywords


Data model, Groundwater simulation, Three-dimensional tetrahedron network (3D TEN), Vertical electrical sounding (VES), Visualisation, Volumetric geo-objects (VGOs)

Full Text:

PDF

References


Abdul-Rahman, A., & Pilouk, M. (2007). Spatial data modelling for 3D GIS. New York, Springer Berlin Heidelberg

Abijith, D., Saravanan, S., Singh, L., Jennifer, J. J., Saranya, T., & Parthasarathy, K. S. S. (2020). GIS-based multi-criteria analysis for identification of potential groundwater recharge zones - a case study from Ponnaniyaru watershed, Tamil Nadu, India. HydroResearch, 3, 1-14. doi:https://doi.org/10.1016/j.hydres.2020.02.002

Ahmad, I., Khan, M. N., Inc, M., Ahmad, H., & Nisar, K. S. (2020). Numerical simulation of simulate an anomalous solute transport model via local meshless method. Alexandria Engineering Journal, 59(4), 2827-2838. doi:https://doi.org/10.1016/j.aej.2020.06.029

Ahmed, A., Alrajhi, A., & Alquwaizany, A. S. (2021). Identification of Groundwater Potential Recharge Zones in Flinders Ranges, South Australia Using Remote Sensing, GIS, and MIF Techniques. Water, 13(18), 2571.

Akinyemi, O. D. (2022). Multivariate interrelatedness of geotechnical and petrophysical properties towards developing near-surface lithology clusters in a sedimentary terrain. Bulletin of Engineering Geology and the

Environment, 81(7), 258. doi:10.1007/s10064-022-02755-3

Andriani, G. F., Pastore, N., Giasi, C. I., & Parise, M. (2021). Hydraulic properties of unsaturated calcarenites by means of a new integrated approach. Journal of Hydrology, 602, 126730. doi:https://doi.org/10.1016/j.jhydrol.2021.126730

Anh, N. G. T. (2011). Overview of Three-Dimensional GIS Data Models. Paper presented at the International Conference on Technological Advancements in Civil Engineering ICTACE India- Chennai, India-Chennai.

Arowoogun, K. I., & Osinowo, O. O. (2022). 3D resistivity model of 1D vertical electrical sounding (VES) data for groundwater potential and aquifer protective capacity assessment: a case study. Modeling Earth Systems and Environment, 8(2), 2615-2626. doi:10.1007/s40808-021-01254-w

Beni, H., Leila Mostafavi, Mir Abolfazl Pouliot, & Jacynthe Gavrilova, M. (2011). Toward 3D spatial dynamic field simulation within GIS using kinetic Voronoi diagram and Delaunay tetrahedralization. International Journal of Geographical Information Science, 25(1), 25-50. doi:https://doi.org/10.1080/13658811003601430

Bhattacharya, S., Das, S., Das, S., Kalashetty, M., & Warghat, S. R. (2021). An integrated approach for mapping groundwater potential applying geospatial and MIF techniques in the semiarid region. Environment, Development and Sustainability, 23(1), 495-510.

Binda, G., Frascoli, F., Spanu, D., Ferrario, M. F., Terrana, S., Gambillara, R., Trotta, S., Noble, P. J., Livio, F. A., Pozzi, A., & Michetti, A. M. (2022). Geochemical Markers as a Tool for the Characterization of a Multi-Layer Urban Aquifer: The Case Study of Como (Northern Italy). Water, 14(1), 124. doi: https://doi.org/10.3390/w14010124

Breunig, M., Bradley, P. E., Jahn, M., Kuper, P., Mazroob, N., Rösch, N., Al-Doori, M., Stefanakis, E., & Jadidi, M. (2020). Geospatial Data Management Research: Progress and Future Directions. ISPRS International Journal of Geo-Information, 9(2), 95.

Cedrick, M. M., Alexander, A., Nobert, J., & Mbudi, C. N. U. D. (2021). Modeling groundwater flow under chaotic urbanization constraints in Kinshasa Capital Region (D.R. Congo). Physics and Chemistry of the Earth, Parts A/B/C, 124, 102985. doi:https://doi.org/10.1016/j.pce.2021.102985

Ciullo, V., Rossi, L., & Pieri, A. (2020). Experimental Fire Measurement with UAV Multimodal Stereovision. Remote Sensing, 12(21), 3546.

Di Salvo, C., Mancini, M., Cavinato, G. P., Moscatelli, M., Simionato, M., Stigliano, F., Rea, R., & Rodi, A. (2020). A 3D Geological Model as a Base for the Development of a Conceptual Groundwater Scheme in the Area of the Colosseum (Rome, Italy). Geosciences, 10(7), 266.

Ekanem, A. M. (2020). Georesistivity modelling and appraisal of soil water retention capacity in Akwa Ibom State University main campus and its environs, Southern Nigeria. Modeling Earth Systems and Environment, 6(4), 2597-2608. doi:10.1007/s40808-020-00850-6

Fanos, A. M., Pradhan, B., Alamri, A., & Lee, C.-W. (2020). Machine learning-based and 3d kinematic models for rockfall hazard assessment using LiDAR data and GIS. Remote Sensing, 12(11), 1755.

Gaikwad, S., Pawar, N. J., Bedse, P., Wagh, V., & Kadam, A. (2022). Delineation of groundwater potential zones using vertical electrical sounding (VES) in a complex bedrock geological setting of the West Coast of India. Modeling Earth Systems and Environment, 8(2), 2233-2247. doi:10.1007/s40808-021-01223-3

Gong, J.Y., Cheng, P.G. & Wang, Y. D. (2004). Three‐dimensional modelling and application in geological exploration engineering. Computers & Geosciences, 30, 391–404.

Havenith, H.-B. (2021). 3D Landslide Models in VR. In B. Tiwari, K. Sassa, P. T. Bobrowsky, & K. Takara (Eds.), Understanding and Reducing Landslide Disaster Risk: Volume 4 Testing, Modeling and Risk Assessment (pp. 195-204). Cham: Springer International Publishing.

Huang, X., Li, H., Li, X., & Zhang, L. (2019). Fire numerical simulation analysis for large-scale public building in 3D GIS. Paper presented at the IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.

Izham, M. Y., Uznir, U. M., Alias, A. R., Ayob, K., & Ruslan, I. W. (2011). Influence of georeference for saturated excess overland flow modelling using 3D volumetric soft geo-objects. Computers & geosciences, 37(4), 598-609. doi:10.1016/j.cageo.2010.05.013

Izham, Y. M., & Rindam, M. (2012). 3D GIS urban runoff mechanism: A new perspective using volumetric soft geo-object. Geografia: Malaysia Journal of Society and Space 8(5), 124-139.

Jaxa-Rozen, M., Kwakkel, J. H., & Bloemendal, M. (2019). A coupled simulation architecture for agent-based/geohydrological modelling with NetLogo and MODFLOW. Environmental Modelling & Software, 115, 19-37. doi:https://doi.org/10.1016/j.envsoft.2019.01.020

Joy, J., Kanga, S., & Singh, S. K. (2020). 3D GIS retrospective flood visualisation. Acta. Tech. Corvin. Bull. Eng, 13(2), 13-18.

Lamontagne‐Hallé, P., McKenzie, J. M., Kurylyk, B. L., Molson, J., & Lyon, L. N. (2020). Guidelines for cold‐regions groundwater numerical modeling. Wiley Interdisciplinary Reviews: Water, 7(6), e1467. doi: 10.1002/wat2.1467

Langevin, C.D., Hughes, J.D., Provost, A.M., Banta, E.R., Niswonger, R.G., Panday, S. (2017). Documentation for the MODFLOW 6 Groundwater Flow (GWF) Model. U.S. Geological Survey Techniques and Methods, Book 6, A55, 197, 10.3133/tm6A55.

Lemmon, C. J. (2010). Boundary mapping and its application to geographic routing (PhD dissertation). Retrieved from James Cook University.

Li, L., Xia, F., Liu, J., Zang, K., Liu, C., Wei, J., & Liu, L. (2022). 3D Quantitative Prediction of the Groundwater Potential Area─A Case Study of a Simple Geological Structure Aquifer. ACS Omega, 7(21), 18004-18016. doi:10.1021/acsomega.2c01387

Li, W., Zhu, J., Fu, L., Zhu, Q., Xie, Y., & Hu, Y. (2021). An augmented representation method of debris flow scenes to improve public perception. International Journal of Geographical Information Science, 35(8), 1521-1544. doi:10.1080/13658816.2020.1833016

Li, X., Ke, T., Wang, Y., Zhou, T., Li, D., Tong, F., & Wen, J. (2020). Hydraulic conductivity behaviors of karst aquifer with conduit-fissure geomaterials. Frontiers in Earth Science, 8, 30.

Liu, Z., Zhang, Z., Zhou, C., Ming, W., & Du, Z. (2021). An Adaptive Inverse-Distance Weighting Interpolation Method Considering Spatial Differentiation in 3D Geological Modeling. Geosciences, 11(2), 51.

Luo, P., Luo, M., Li, F., Qi, X., Huo, A., Wang, Z., He, B., Takara, K., Nover, D., & Wang, Y. (2022). Urban flood numerical simulation: Research, methods and future perspectives. Environmental Modelling & Software, 156, 105478. doi:https://doi.org/10.1016/j.envsoft.2022.105478

Maiti, A., & Chakravarty, D. (2021). 3D reconstruction–based numerical modeling of irregular-shaped geo-objects using digital images: a novel approach. Bulletin of Engineering Geology and the Environment, 80(8), 6145-6160. doi:10.1007/s10064-021-02322-2

Morosini, R., Zucaro, F. (2019). Land use and urban sustainability assessment: A 3D GIS application to a case study in Gozo. City Territ Architecture, 6(7), https://doi.org/10.1186/s40410-019-0106-z.

Munyati, C., & Sinthumule, N. I. (2021). Comparative suitability of ordinary kriging and Inverse Distance Weighted interpolation for indicating intactness gradients on threatened savannah woodland and forest stands. Environmental and Sustainability Indicators, 12, 100151. doi:https://doi.org/10.1016/j.indic.2021.100151

Nasir, A. A. M., Azri, S., & Ujang, U. (2021). Modelling immovable asset in 3d using citygml 3.0 concept to support smart city initiatives. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W5-2021, 391-396. doi:10.5194/isprs-archives-XLVI-4-W5-2021-391-2021

Omar, P. J., Gaur, S., Dwivedi, S., & Dikshit, P. (2020). A modular three-dimensional scenario-based numerical modelling of groundwater flow. Water Resources Management, 34(6), 1913-1932. doi:https://doi.org/10.1007/s11269-020-02538-z

Omolaiye, G. E., Oladapo, I. M., Ayolabi, A. E., Akinwale, R. P., Akinola, A. A., Omolaye, K. L., & Sanuade, O. A. (2020). Integration of remote sensing, GIS and 2D resistivity methods in groundwater development. Applied Water Science, 10(6), 129. doi:10.1007/s13201-020-01219-x

Rydvanskiy, R., & Hedley, N. (2020). 3d geovisualization interfaces as flood risk management platforms: capability, potential, and implications for practice. Cartographica: The International Journal for Geographic Information and Geovisualization, 55(4), 281-290.

Schwartz, F. W., & Zhang, H. (2002). Basic Principle of Groundwater Flow. In R. Flahive, D. Powell, & N. M. Pigliucci (Eds.), Fundamentals of ground water (pp. 42-65): John Wiley & Sons.

Tuan, A. N. G. (2013). Overview of three-dimensional GIS data models. International Journal of Future Computer and Communication, 2(3), 270.

Webb, J.R., Santos, I.R., Maher, D.T., Tait, D.R., Cyronak, T., Sadat-Noori, M., Macklin, P., Jeffrey, L.C. (2019). Groundwater as a source of dissolved organic matter to coastal waters: Insights from radon and CDOM observations in 12 shallow coastal systems. Limnology and Oceanography, 64(1), 182-196.

Xiang, Z., Bailey, R. T., Nozari, S., Husain, Z., Kisekka, I., Sharda, V., & Gowda, P. (2020). DSSAT-MODFLOW: A new modeling framework for exploring groundwater conservation strategies in irrigated areas. Agricultural Water Management, 232, 106033. doi:https://doi.org/10.1016/j.agwat.2020.106033

Xu, S. (2021). Three-Dimensional Visualization Algorithm Simulation of Construction Management Based on GIS and VR Technology. Complexity. doi:https://doi.org/10.1155/2021/6631999.

Zaidi, S. M., Akbari, A., Abu Samah, A., Kong, N. S., Gisen, A., & Isabella, J. (2017). Landsat-5 Time Series Analysis for Land Use/Land Cover Change Detection Using NDVI and Semi-Supervised Classification Techniques. Polish Journal of Environmental Studies, 26(6).

Zang, F. (2022). Application of 3D Geological Modeling in Geological Exploration. Paper presented at the Frontier Computing, Singapore.

Zavari, M., Shahhosseini, V., Ardeshir, A., & Sebt, M. H. (2022). Multi-objective optimization of dynamic construction site layout using BIM and GIS. Journal of Building Engineering, 52, 104518. doi:https://doi.org/10.1016/j.jobe.2022.104518

Zeitoun, R., Vandergeest, M., Vasava, H. B., Machado, P. V. F., Jordan, S., Parkin, G., Wagner-Riddle, C., & Biswas, A. (2021). In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths. Sensors, 21(2), 447.


Refbacks

  • There are currently no refbacks.