A signature‐based approach to quantify soil moisture dynamics under contrasting land‐uses. Issue 4 (6th April 2022)

• Record Type: Journal Article
• Authors: Araki, Ryoko; Branger, Flora; Wiekenkamp, Inge; McMillan, Hilary
• Is Part Of: Hydrological processes. Volume 36:Issue 4(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-04-06
• Subjects: hydrologic signature -- land‐use -- metrics‐based approach -- process‐based evaluation -- soil moisture -- soil moisture signature; Hydrology -- Periodicals; Hydrology -- Research -- Periodicals; Hydrologic models -- Periodicals; Hydrological forecasting -- Periodicals; 631.432
• DOI: 10.1002/hyp.14553
• Languages: English
• ISSNs: 0885-6087

Abstract

Abstract: 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. Abstract : We extracted nine process‐based metrics called 'soil moisture signatures' from dataset under 12 types of contrasting land‐uses. Most signatures showed a high ability to discriminate different dynamics among contrasting land‐uses. Process implications from event‐based and timeseries‐based signatures (signatures that are extracted per storm‐event and a complete time‐series) matched well with expert knowledge in literature.