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Mountains are vital water sources for humans and ecosystems, continuously replenishing lowland aquifers through surface runoff and mountain recharge. Quantifying these fluxes and their relative importance is essential for sustainable water resource management. However, our mechanistic understanding of the flow and transport processes determining the connection between the mountain block and the basin aquifer remains limited. Traditional conceptualizations assume groundwater circulation within the mountain block is predominantly shallow. This view neglects the role of deep groundwater flowpaths significantly contributing to the water, solute, and energy budgets. Overcoming these limitations requires a holistic characterization of the multiscale nature of groundwater flow along the mountain‐to‐valley continuum. As a proof‐of‐concept, we use a coupled groundwater flow and transport model to design a series of numerical experiments that explore the role of geology, topography, and weathering rates in groundwater circulation and their resulting resistivity patterns. Our results show that accumulating solutes near stagnation zones create contrasting electrical resistivity patterns that separate local, intermediate, and regional flow cells, presenting a target for magnetotelluric observations. To demonstrate the sensitivity of magnetotelluric data to features in our resistivity models, we use the MARE2DEM electromagnetic modeling code to perform forward and inverse simulations. This study highlights the potential of magnetotelluric surveys to image the resistivity structure resulting from multiscale groundwater circulation through relatively impervious crystalline basement rocks in mountainous terrains. This capability could change our understanding of the critical zone, offering a holistic perspective that includes deep groundwater circulation and its role in conveying solutes and energy.

 

Biogeochemical processes are often spatially discrete (hot spots) and temporally isolated (hot moments) due to variability in controlling factors like hydrologic fluxes, lithological characteristics, bio-geomorphic features, and external forcing. Although these hot spots and hot moments (HSHMs) account for a high percentage of carbon, nitrogen and nutrient cycling within the Critical Zone, the ability to identify and incorporate them into reactive transport models remains a significant challenge. This chapter provides an overview of the hot spots hot moments (HSHMs) concepts, where past work has largely focused on carbon and nitrogen dynamics within riverine systems. This work is summarized in the context of process-based and data-driven modeling approaches, including a brief description of recent research that casts a wider net to incorporate Hg, Fe and other Critical Zone elements, and focuses on interdisciplinary approaches and concepts. The broader goal of this chapter is to provide an overview of the gaps in our current understanding of HSHMs, and the opportunities therein, while specifically focusing on the underlying parameters and processes leading to their prognostic and diagnostic representation in reactive transport models. 

Storm direction modulates a hydrograph's magnitude and duration, thus having a potentially large effect on local flood risk. However, how changes in the preferential storm direction affect the probability distribution of peak flows remains unknown. We address this question with a novel Monte Carlo approach where stochastically transposed storms drive hydrologic simulations over medium and mesoscale watersheds in the Midwestern United States. Systematic rotations of these watersheds are used to emulate changes in the preferential storm direction. We found that the peak flow distribution impacts are scale‐dependent, with larger changes observed in the mesoscale watershed than in the medium‐scale watershed. We attribute this to the high diversity of storm patterns and the storms' scale relative to watershed size. This study highlights the potential of the proposed stochastic framework to address fundamental questions about hydrologic extremes when our ability to observe these events in nature is hindered by technical constraints and short time records.