Abstract

The efficiency of artificial surface ponds (SPs) for managed aquifer recharge (MAR) is mostly controlled by the topmost portion of the soil. The most significant soil property controlling recharge is the infiltration capacity (I_c), which is highly variable in space. Assessing its spatial distribution in detail is prohibitive in practice due to high costs, time effort, and limited site accessibility. We present an alternative method for a quick and low-cost quantitative estimation of the spatial distribution of I_c based on satellite images. The fact that hydraulic properties of topsoils and color intensities of digital images depend on some common factors such as moisture content, nature and organization of grains, proportion of iron, and organic and clay content among others, allow us to infer infiltration capacities from color intensities. The relationship between these two variables is site specific and requires calibration. A pilot SP site in Catalonia (Spain) is used as an application example. Two high-resolution digital images of the site are provided at no cost by the local cartographic institute as well as from a popular Internet-based map server. An initial set of local infiltration experiments, randomly located, were found to correlate to color intensities of the digital images. This relationship was then validated against additional independent measurements. The resulting maps of infiltration were then used to estimate the total maximum infiltration of the artificial pond area, the results being consistent with an independent flooding test performed at the site.

Abstract

Large wood plays a vital role in river systems, shaping habitats and supporting biodiversity. However, during floods, large wood transport can threaten infrastructure and communities. Traditional flood models often overlook wood material, despite its natural presence in rivers. To address this gap, the calculation module Iber-Wood was developed and integrated into the Iber model. Iber-Wood combines the Eulerian Iber 2D hydrodynamics with a Lagrangian model to simulate wood as dynamic elements. The model accounts for wood-flow-sediment, wood-wood, wood-infrastructure, and wood-terrain interactions, using two-way coupling. It has been validated with flume experiments and applied to various real rivers using field data. Applications include studying wood-sediment-flow dynamics and bridge-related wood accumulation. Though deterministic, Iber-Wood enables scenario testing and hypothesis exploration for complex wood dynamics.