Responses of headwater stream networks to hydrological variability and extreme drought, including the role of geology, have not been well quantified. The effects of drainage area and subsurface conveyance capacity ( SCC ) on stream wetted cross-sectional area ( A wxs ) and probability of stream disconnection were quantified in a mountainous headwater watershed of coastal Northern California under seasonal variations and extreme drought in 2021. Field measurements of wetted characteristics, including A wxs and percentage of the reach that was dry, were made during the dry season. A wxs correlated negatively with SCC and positively with drainage area in the log-transformed regression. A wxs decreased and probability of disconnection ( P ( d ) ) increased with increasing distance from the headwaters due to high SCC in the lower reaches. Drainage area and SCC were both statistically significant predictors of A wxs , particularly in multivariate modes ( p << .01, R² = 0.4). Drainage area was more influential during wet conditions, while SCC was critical during dry periods. In logistic models, SCC was a stronger predictor of P ( d ) than drainage area ( p < 0.001). It is herein concluded that geology within this watershed is the dominant control on surface water expression during extreme drought conditions, resulting in unexpectedly decreasing wetted channel dimensions with increasing distance downstream. This dataset presents a unique opportunity to examine stream responses during critical drought conditions in a headwaters watershed that supports spawning and rearing habitat for endangered anadromous fish. Findings can help predict stream responses in similar watersheds to forecasted hydrological conditions and mitigate potential impacts to aquatic habitat.

Soil moisture signatures provide a promising solution to overcome the difficulty of evaluating soil moisture dynamics in hydrologic models. Soil moisture signatures are metrics that quantify the dynamic aspects of soil moisture timeseries and enable process-based model evaluations. To date, soil moisture signatures have been tested only under limited land-use types. In this study, we explore soil moisture signatures’ ability to discriminate different dynamics among contrasting land-uses. We applied a set of nine soil moisture signatures to datasets from six in-situ soil moisture networks worldwide. The dataset covered a range of land-use types, including forested and deforested areas, shallow groundwater areas, wetlands, urban areas, grazed areas, and cropland areas. Our set of signatures characterized soil moisture dynamics at three temporal scales: event, season, and a complete timeseries. Statistical assessment of extracted signatures showed that (1) event-based signatures can distinguish different dynamics for all the land-uses, (2) season-based signatures can distinguish different dynamics for some types of land-uses (deforested vs. forested, urban vs. greenspace, and cropped vs. grazed vs. grassland contrasts), (3) timeseries-based signatures can distinguish different dynamics for some types of land-uses (deforested vs. forested, urban vs. greenspace, shallow vs. deep groundwater, wetland vs. non-wetland, and cropped vs. grazed vs. grassland contrasts). Further, we compared signature-based process interpretations against literature knowledge; event-based and timeseries-based signatures generally matched well with previous process understandings from literature, but season-based signatures did not. This study will be a useful guideline for understanding how catchment-scale soil moisture dynamics in various land-uses can be described using a standardized set of hydrologically relevant metrics.

This paper presents a taxonomy (hierarchical organization) of hydrological processes; specifically, runoff generation processes in natural watersheds. Over 120 process names were extracted from a literature review of papers describing experimental watersheds, perceptual models, and runoff processes in a range of hydro-climatic environments. Processes were arranged into a hierarchical structure, and presented as a spreadsheet and interactive diagram. For each process, additional information was provided: a list of alternative names for the same process, a classification into hydrological function (e.g. partitioning, flux, storage, release) and a unique identifier similar to a hashtag. The taxonomy provides a method to label and search hydrological knowledge, thereby facilitating synthesis and comparison of processes across watersheds.