Abstract
Accurate draindown modelling is essential for the design, operation, and closure of heap leach facilities, particularly in scenarios involving complex geometries or challenging operational conditions. Traditional 2D and 3D numerical models, while robust, often require significant computational resources and time, limiting their practicality for iterative design processes or real-time decision-making. To address these challenges, we present an innovative tool that integrates Hydrus 1D with Python to enable automated, large-scale iterative simulations for a pseudo-3D modelling approach.
This tool combines the computational efficiency of Hydrus 1D, a widely used software for simulating water flow and solute transport in variably saturated media, with Python scripting to automate the execution of multiple 1D simulations. By discretizing in time, the heap leach facility into a network of vertical 1D columns, the tool captures the time-dependent spatial variability in material properties, stacking sequences, and geometries, providing a comprehensive time-dependent 3D representation of the system without the computational burden of full 2D or 3D models.
The methodology is demonstrated through two case studies. The first case study focuses on a conceptual heap leach design with simplified geometry but a challenging stacking sequence. The objective is to predict heap leach outflow rates during operation and closure to support leachate management decisions. The second case study involves an operational heap leach facility situated in mountainous terrain with highly complex geometry. Here, the tool is used to predict the draindown time required for the outflow rate post-closure to reach the evaporation rate of the outflow pond.
The results from both case studies highlight the tool’s ability to provide actionable insights for both operational and closure planning. Key advantages of this time-dependent pseudo-3D approach include reduced modelling time, enhanced flexibility in scenario analysis, and the ability to incorporate site-specific complexities. Additionally, the integration of Python scripting facilitates seamless models running, data processing, visualization, and sensitivity analysis, further enhancing the tool's utility for practitioners.
This novel approach bridges the gap between the simplicity of 1D modelling and the complexity of higher-dimensional models, in particular in 3D. It offers a practical and efficient solution for draindown modelling in heap leach systems. This tool has the potential to streamline design and operational workflows by reducing reliance on resource-intensive modelling techniques.
Presenter
Imanol Vega | Civil Engineer, SRK Argentina
