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Data-model comparison of temporal variability in long-term time series of large-scale soil moisture
Stockholm University, Faculty of Science, Department of Physical Geography.
Stockholm University, Faculty of Science, Department of Physical Geography.
2016 (English)In: Journal of Geophysical Research - Atmospheres, ISSN 2169-897X, E-ISSN 2169-8996Article in journal (Refereed) Epub ahead of print
Abstract [en]

Soil moisture is at the heart of many processes connected to water cycle, climate, ecosystem and societal conditions. This paper investigates the ability of a relatively simple analytical soil-moisture model to reproduce temporal variability dynamics in long-term data series for: (i) remotely sensed large-scale water storage change in twenty-five large catchments around the world, and (ii) measured soil water content and groundwater level in individual stations within ten smaller catchments across the United States. The model-data comparison for large-scale water storage change (i) shows good model ability to reproduce the observed temporal variability around long-term average conditions in most of the large study catchments. Also the model comparison with locally measured data for soil water content and groundwater level in the smaller U.S. catchments (ii) shows good representation of relative seasonal and longer-term fluctuations and their timings and frequencies. Overall, the model results tend to underestimate rather than exaggerate the range of temporal soil moisture fluctuations and storage changes. The model synthesis of large-scale hydro-climatic data is based on fundamental catchment-scale water balance and is as such useful for identifying flux imbalance biases in the hydro-climatic data series that are used as model inputs.

Place, publisher, year, edition, pages
2016.
National Category
Oceanography, Hydrology, Water Resources
Research subject
Physical Geography
Identifiers
URN: urn:nbn:se:su:diva-132250DOI: 10.1002/2016JD025209OAI: oai:DiVA.org:su-132250DiVA: diva2:950829
Available from: 2016-08-02 Created: 2016-08-02 Last updated: 2016-09-14
In thesis
1. Modeling long-term variability and change of soil moisture and groundwater level - from catchment to global scale
Open this publication in new window or tab >>Modeling long-term variability and change of soil moisture and groundwater level - from catchment to global scale
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The water stored in and flowing through the subsurface is fundamental for sustaining human activities and needs, feeding water and its constituents to surface water bodies and supporting the functioning of their ecosystems. Quantifying the changes that affect the subsurface water is crucial for our understanding of its dynamics and changes driven by climate change and other changes in the landscape, such as in land-use and water-use. It is inherently difficult to directly measure soil moisture and groundwater levels over large spatial scales and long times. Models are therefore needed to capture the soil moisture and groundwater level dynamics over such large spatiotemporal scales.

This thesis develops a modeling framework that allows for long-term catchment-scale screening of soil moisture and groundwater level changes. The novelty in this development resides in an explicit link drawn between catchment-scale hydroclimatic and soil hydraulics conditions, using observed runoff data as an approximation of soil water flux and accounting for the effects of snow storage-melting dynamics on that flux. Both past and future relative changes can be assessed by use of this modeling framework, with future change projections based on common climate model outputs. By direct model-observation comparison, the thesis shows that the developed modeling framework can reproduce the temporal variability of large-scale changes in soil water storage, as obtained from the GRACE satellite product, for most of 25 large study catchments around the world. Also compared with locally measured soil water content and groundwater level in 10 U.S. catchments, the modeling approach can reasonably well reproduce relative seasonal fluctuations around long-term average values.

The developed modeling framework is further used to project soil moisture changes due to expected future climate change for 81 catchments around the world. The future soil moisture changes depend on the considered radiative forcing scenario (RCP) but are overall large for the occurrence frequency of dry and wet events and the inter-annual variability of seasonal soil moisture. These changes tend to be higher for the dry events and the dry season, respectively, than for the corresponding wet quantities, indicating increased drought risk for some parts of the world.

Place, publisher, year, edition, pages
Stockholm: Department of Physical Geography, Stockholm University, 2016. 36 p.
Series
Dissertations from the Department of Physical Geography, ISSN 1653-7211 ; 57
Keyword
hydrology, physically-based model, groundwater, soil moisture
National Category
Oceanography, Hydrology, Water Resources
Research subject
Physical Geography
Identifiers
urn:nbn:se:su:diva-128322 (URN)978-91-7649-387-8 (ISBN)
External cooperation:
Public defence
2016-09-22, De Geersalen, Geovetenskapens hus, Svante Arrhenius väg 14, Stockholm, 13:00 (English)
Opponent
Supervisors
Available from: 2016-08-30 Created: 2016-03-23 Last updated: 2016-08-31Bibliographically approved

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Verrot, LucileDestouni, Georgia
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