Version 1
: Received: 20 July 2024 / Approved: 22 July 2024 / Online: 22 July 2024 (16:28:35 CEST)
How to cite:
Du, Z.; Liu, Y.; Dong, Y.; Chen, Y.; Zhai, Y. Aquitard Structure Plays Important Role in Leakage: Evidence from Knn Method. Preprints2024, 2024071739. https://doi.org/10.20944/preprints202407.1739.v1
Du, Z.; Liu, Y.; Dong, Y.; Chen, Y.; Zhai, Y. Aquitard Structure Plays Important Role in Leakage: Evidence from Knn Method. Preprints 2024, 2024071739. https://doi.org/10.20944/preprints202407.1739.v1
Du, Z.; Liu, Y.; Dong, Y.; Chen, Y.; Zhai, Y. Aquitard Structure Plays Important Role in Leakage: Evidence from Knn Method. Preprints2024, 2024071739. https://doi.org/10.20944/preprints202407.1739.v1
APA Style
Du, Z., Liu, Y., Dong, Y., Chen, Y., & Zhai, Y. (2024). Aquitard Structure Plays Important Role in Leakage: Evidence from Knn Method. Preprints. https://doi.org/10.20944/preprints202407.1739.v1
Chicago/Turabian Style
Du, Z., Yaoxuan Chen and Yuanzheng Zhai. 2024 "Aquitard Structure Plays Important Role in Leakage: Evidence from Knn Method" Preprints. https://doi.org/10.20944/preprints202407.1739.v1
Abstract
Leakage is important in groundwater cycle research and water resource management, the key is to construct the spatial distribution of aquitard. Influenced by natural and anthropogenic factors, the density of boreholes restricts the accuracy of aquitard structure. This paper explores the K-Nearest Neighbor (KNN) method to construct multi-layer aquitard structure in the hinterland of Songnen Plain, Northeast China, with limited boreholes, and compare it with Inverse Distance Weight (IDW) and Ordinary Kriging (OK) methods to evaluate the leakage. The KNN needs to first identify the eigenvalue-k of each layer, which is used to enhance the trainset to obtain the testset with a larger amount of sample data enhanced, and to make a prediction to obtain the 3-dimensional structure of aquitard. KNN is more accurate than the IDW and OK. The aquitrad structure obtained by the KNN is different from the IDW and OK, the thickness difference is 3.53%-54.00%, the area difference is 2.28%-23.91%, and the difference in leakage can be up to 24.51%. KNN also has a high degree of identification of aquitard edges, which can help the prevention of groundwater pollution. The results provide guidance for water balance analysis, borehole engineering design, water resources management and exploitation.
Environmental and Earth Sciences, Water Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
