soil moisture dynamics
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CATENA ◽  
2022 ◽  
Vol 211 ◽  
pp. 105987
Author(s):  
Vedran Krevh ◽  
Vilim Filipović ◽  
Lana Filipović ◽  
Valentina Mateković ◽  
Dragutin Petošić ◽  
...  

Author(s):  
Ryoko Araki ◽  
Flora Branger ◽  
Inge Wiekenkamp ◽  
Hilary McMillan

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.


2021 ◽  
Author(s):  
Vilna Tyystjärvi ◽  
Julia Kemppinen ◽  
Miska Luoto ◽  
Tuula Aalto ◽  
Tiina Markkanen ◽  
...  

2021 ◽  
Vol 133 ◽  
pp. 108379
Author(s):  
D.M. Barnard ◽  
M.J. Germino ◽  
J.B. Bradford ◽  
R.C. O'Connor ◽  
C.M. Andrews ◽  
...  

CATENA ◽  
2021 ◽  
Vol 206 ◽  
pp. 105505
Author(s):  
Min Luo ◽  
Fanhao Meng ◽  
Chula Sa ◽  
Yongchao Duan ◽  
Yuhai Bao ◽  
...  

2021 ◽  
pp. 126797
Author(s):  
Junhao He ◽  
Mohamed M. Hantush ◽  
Latif Kalin ◽  
Mehdi Rezaeianzadeh ◽  
Sabahattin Isik

Author(s):  
Ryoko Araki ◽  
Flora Branger ◽  
Inge Wiekenkamp ◽  
Hilary McMillan

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 represent catchment dynamics extracted from time series of data 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 covers a range of land-use types, including forested and deforested areas, shallow groundwater areas, wetlands, housing areas, grazed areas, and cropland areas. These signatures characterize soil moisture dynamics at three temporal scales: event, seasonal, and time-series scales. Statistical and visual assessment of extracted signatures showed that (1) storm event-based signatures can distinguish different dynamics for most land-uses, (2) season-based signatures are useful to distinguish different dynamics for some types of land-uses (forested vs. deforested area, greenspace vs. housing area, and deep vs. shallow groundwater area), (3) timeseries-based signatures can distinguish different dynamics for some types of land-uses (forested vs. deforested area, deep vs. shallow groundwater area, non-wetland vs. wetland area, and ungrazed vs. grazed area). We compared signature-based process interpretations against literature knowledge: event-based and time series-based signatures were generally matched well with previous process understandings from literature, but season-based signatures did not. This study demonstrates the best practices of extracting soil moisture signatures under various land-use and climate environments and applying signatures for model evaluations.


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