{"id":33472,"date":"2026-06-17T17:03:27","date_gmt":"2026-06-17T15:03:27","guid":{"rendered":"https:\/\/www.dica.polimi.it\/?post_type=tribe_events&p=33472"},"modified":"2026-06-17T17:03:27","modified_gmt":"2026-06-17T15:03:27","slug":"the-vadose-zone-a-multifaceted-perspective","status":"publish","type":"tribe_events","link":"https:\/\/www.dica.polimi.it\/en\/evento\/the-vadose-zone-a-multifaceted-perspective\/","title":{"rendered":"The vadose zone: a multifaceted perspective"},"content":{"rendered":"
On Thursday, June 25<\/b>, two seminars will be held in Fass\u00f2 Room (Building 4A) at 14:30 CET.<\/div>\n
<\/div>\n
The first seminar will be given by\u00a0Anna Dabudyk<\/b>, ITES Strasbourg Institute of Earth and Environment, and is titled:\u00a0Optimization of Monte Carlo simulations for physically-based groundwater recharge modelling: convergence, sensitivity analysis and spatial upscaling<\/i><\/b>.<\/div>\n
<\/div>\n
Abstract<\/b><\/div>\n
Physically-based integrated hydrological models have become essential tools to inform quantitative management at the catchment scale. Recharge is a key process that is either computed internally or computed externally and then read as an input. In both cases, a high level of uncertainty is expected as no real measurement of recharge are available.<\/div>\n
In this work, we use a chain of physically-based models comprising a Land Surface Model for groundwater recharge and a hydrological model that couples surface and subsurface flow processes. The main goal is to assess the impact of anthropogenic withdrawals on low flows and provide a rigorous quantification of uncertainties for both piezometric level and surface discharge.<\/div>\n
Computing groundwater recharge using a physically-based LSM model is a rather parameter intensive approach. To quantify the uncertainties, this model uses a Monte Carlo framework to randomly sample 178 parameters per simulation. We first established that a minimum of 3,000 simulations was required for convergence. Next, we conducted a sensitivity analysis which revealed that uncertainties related to parameters are more significant than those related to meteorological forcing.<\/div>\n
Our next step is to focus on model efficiency. Using clustering methods, we intent to select relevant pixels to compute groundwater recharge before upscaling to the entire catchment. This is a critical step, as the groundwater recharge is then used as input data for the hydrological model, for which computation times are significantly more challenging.<\/div>\n
<\/div>\n

Bio-sketch<\/b><\/p>\n

Anna Dabudyk is a PhD student in hydrology at ITES (Strasbourg Institute of Earth and Environment). Her research focuses on catchment-scale quantitative hydrology, using numerical modelling and statistical approaches to evaluate simulation reliability and quantify uncertainty. The main goal of her work is to understand the relationship between anthropogenic withdrawals and surface and groundwater water dynamics. Her work aims to bridge the gap between complex hydrological modelling and practical decision-making by providing uncertainty-aware numerical solutions for water management.<\/p>\n

<\/div>\n
The second\u00a0seminar\u00a0will be given by\u00a0Tom\u00e1s Aquino<\/b>, IDAEA Spanish National Research Council institute, Barcelona, and is titled:\u00a0From geometry to velocity: How medium structure and water saturation shape global flow statistics.<\/i><\/b><\/div>\n
\u00a0<\/b><\/div>\n
<\/div>\n
Abstract<\/b><\/div>\n
Subsurface flows exhibit rich structure across multiple scales due to complex medium geometry. In the vadose zone, i.e., the partially-saturated region that acts as a reactive filter for nutrients and contaminants, flow heterogeneity is further enhanced by the simultaneous presence of air and water. Understanding, quantifying, and predicting transport and reaction in such systems requires models that can be parameterized based on incomplete information about the pore-scale structure and saturation, which are typically known only to a limited extent.<\/div>\n
Over the last few decades, stochastic models have gained in popularity as useful and elegant tools to fill this role. In addition to the classical inverse problem, where Monte Carlo type methods are traditionally employed to quantify uncertainty, recent stochastic transport and mixing models rely on statistical descriptions of the underlying flow field to make deterministic predictions of macroscopic quantities, such as breakthrough curves and dispersion, at larger scales. These methods typically rely on the probability of finding a certain velocity value anywhere in the domain together with a characteristic correlation length, without need for detailed knowledge of the spatial structure. Despite their success, the predictive power of such models remains limited by our inability to connect the statistics of geometric features, such as pore throat widths, to flow statistics. Indeed, current mean field theories fail to capture the flow statistics even in simple disordered media.<\/div>\n
In the first part of this talk, I will discuss a new theory of flow statistics for saturated, disordered media, which employs a pore network description to connect flow distributions to macroscopic metrics like the porosity and the coeMicient of variation of pore throat widths. I will show that this theory performs very well for simple model porous media in two dimensions, composed of disordered arrays of circular obstacles. In the second part of the talk, I will discuss how flow statistics models can be extended to partially saturated conditions.<\/div>\n
<\/div>\n
Bio-sketch<\/b><\/div>\n
Tom\u00e1s Aquino is a Researcher at the IDAEA, a Spanish National Research Council institute in Barcelona dedicated to environmental sciences. He obtained his undergraduate and MSc degrees in Physics from the University of Lisbon, Portugal, where he is originally from, and his PhD from the University of Notre Dame, IN, USA. He is the recipient of the ongoing ERC Starting Grant Uplift, which is dedicated to advancing our understanding of flow, transport, mixing and reaction in partially saturated porous media across scales.<\/div>","protected":false},"excerpt":{"rendered":"

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