H156-08
Subseasonal depletion of soil moisture across Poland as derived from GLEAM

Monday, 14 December 2020: 17:51
Virtual
Urszula Somorowska, University of Warsaw; Faculty of Geography and Regional Studies, Department of Hydrology, Warsaw, Poland
Abstract:
Soil moisture plays an important role in hydrological cycle by controlling the water exchange between soil, vegetation and atmosphere. It affects the evapotranspiration flux for which the soil water resources are used. Given the importance of soil moisture for the maintenance of ecosystems, a fundamental understanding of its variability is required. In this study, the evolution of selected model-based drought metrics sensitive to soil moisture conditions is analysed. The Global Land Evaporation Amsterdam Model (GLEAM) data is used to present the most extreme drought events that occurred across the interior of Poland during last decades. Driven by RS data, GLEAM provides simulations of land surface stages, including surface and root zone soil moisture. The annual soil moisture cycle consists of the soil water storage depletion occurring from April until September-October, and the recharge taking place from October until February-March. Using a pentad means of soil moisture indices and a threshold criterion, the soil moisture anomalies are revealed at a sub seasonal time scale. The onset, propagation and termination of soil drought events are analysed in the spatio-temporal framework. The most extreme dry stages last several weeks from late spring until late summer and cover most of the territory of Poland. High sensitivity to precipitation deficiency and increased temperature translate the meteorological drought into significant subsurface water depletion. The most extreme soil drought events were detected in 2003 and 2015. In many locations in central part of the country, precipitation deficits in particular summer months reached 100% of the long-term norm, and the air temperature was 1-5oC higher as referred to average thermal conditions. Model-based soil moisture data provide the valuable alternative to sparse ground data helping to uncover the drought signal as it moves from anomalous meteorological conditions to soil surface and root zone.