scholarly journals Comparing Q-Tree with Nested Grids for Simulating Managed River Recharge of Groundwater

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3516
Author(s):  
Weizhe Cui ◽  
Qichen Hao

The use of rivers to recharge groundwater is a key water resource management method. High-precision simulations of the groundwater level near rivers can be used to accurately assess the recharge effect. In this study, we used two unstructured grid refinement methods, namely, the quadtree (Q-tree) and nested grid refinement techniques, to simulate groundwater movement under river recharge. We comparatively analyzed the two refinement methods by considering the simulated groundwater level changes before and after the recharge at different distances from the river and by analyzing the groundwater flow and model computation efficiency. Compared to the unrefined model, the two unstructured grid refinement models significantly improve the simulation precision and more accurately describe groundwater level changes from river recharge. The unstructured grid refinement models have higher calculation efficiencies than the base model (the global refinement model) without compromising the simulation precision too much. The Q-tree model has a higher simulation precision and a lower computation time than the nested grid model. In summary, the Q-tree grid refinement method increases the computation efficiency while guaranteeing simulation precision at a certain extent. We therefore recommended the use of this grid refinement method in simulating river recharge to the aquifers.

1999 ◽  
Vol 26 (16) ◽  
pp. 2501-2504 ◽  
Author(s):  
Masao Ohno ◽  
Tsutomu Sato ◽  
Kenji Notsu ◽  
Hiroshi Wakita ◽  
Kunio Ozawa

Jurnal INKOM ◽  
2014 ◽  
Vol 8 (1) ◽  
pp. 29 ◽  
Author(s):  
Arnida Lailatul Latifah ◽  
Adi Nurhadiyatna

This paper proposes parallel algorithms for precipitation of flood modelling, especially applied in spatial rainfall distribution. As an important input in flood modelling, spatial distribution of rainfall is always needed as a pre-conditioned model. In this paper two interpolation methods, Inverse distance weighting (IDW) and Ordinary kriging (OK) are discussed. Both are developed in parallel algorithms in order to reduce the computational time. To measure the computation efficiency, the performance of the parallel algorithms are compared to the serial algorithms for both methods. Findings indicate that: (1) the computation time of OK algorithm is up to 23% longer than IDW; (2) the computation time of OK and IDW algorithms is linearly increasing with the number of cells/ points; (3) the computation time of the parallel algorithms for both methods is exponentially decaying with the number of processors. The parallel algorithm of IDW gives a decay factor of 0.52, while OK gives 0.53; (4) The parallel algorithms perform near ideal speed-up.


2011 ◽  
Vol 16 (2) ◽  
pp. 41-51 ◽  
Author(s):  
Soo-Hyoung Lee ◽  
Se-Yeong Hamm ◽  
Kyoo-Chul Ha ◽  
Yong-Cheol Kim ◽  
Beom-Keun Cheong ◽  
...  

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