Controls on the development and persistence of soil moisture drought across Southwestern Germany

Abstract

Abstract. The drought of 2018 in Central and Northern Europe showed once more the large impact this natural hazard can have on the environment and society. Such droughts are often seen as slowly developing phenomena. However, root zone soil moisture deficits can rapidly develop during periods of lacking precipitation and meteorological conditions that favour high evapotranspiration rates. These periods of soil moisture drought stress can persist for as long as the meteorological drought conditions last, thereby negatively affecting vegetation and crop health. In this study, we aim to characterize past soil moisture drought stress events over the cropland of South-Western Germany as well as to relate the characteristics of these past events to different soil and climate properties. We first simulated daily soil moisture over the period 1989–2018 on a 1-km resolution grid using the physical based hydrological model TRAIN. We then derived various soil moisture drought stress characteristics; likelihood, development time and persistence, from the simulated time series of all agricultural grid cells (n ≈ 15 000). Logistic regression and correlation were then applied to relate the derived characteristics to the storage capacity of the root zone as well as to the climatological setting. Results reveal that the majority of the agricultural grid cells across the study region reached soil moisture drought stress during prominent drought years. The development time of these soil moisture drought stress events varied substantially, from as little as 10 days to up to 4 months. The persistence of soil moisture drought stress varied as well and was especially high for the drought of 2018. The dominant control on the likelihood and development time of soil moisture drought stress was found to be the storage capacity of the root zone, whereas the persistence was not strongly linearly related to any of the considered controls. Overall, results give insights in the large spatial and temporal variability of soil moisture drought stress characteristics and highlight the importance of considering differences in root zone soil storage for agricultural drought assessments.

Soil Moisture Memory: State-of-the-art and the way forward

“…1. Drought predictions: Soils characterized by extensive dry SMM are frequently affected by prolonged and persistent droughts [Abolafia-Rosenzweig et al, 2023;Soulsby et al, 2021]; although extensive wet SMM can also mitigate the effects of droughts Tijdeman and Menzel, 2020]. In this context, SMM, in conjunction with land-atmosphere interactions, can possibly improve the ability to predict drought (more specifically soil moisture drought) on seasonal to decadal timescales by converting a weak precipitation signal into a more predictable soil moisture signal [Esit et al, 2021].…”

“…Resilience against droughts: Elevated SMM makes soils resistant to drought events or can prolong soil moisture drought, influencing the severity and impact of droughts [Nicholson, 2000;Rahmati et al, 2023c]. Local meteorological conditions and the presence of sufficient storage capacity in the root zone can prevent soil moisture drought even during severe drought years [Tijdeman and Menzel, 2020]. 3.…”

“…These studies have generally focused on regional to global scales [Seneviratne et al, 2013;Tijdeman and Menzel, 2020;Wu and Dickinson, 2004]. For example, Rowntree and Bolton [1983] assessed the importance of initial soil moisture anomalies to short-term changes in climate and hydrology.…”

Separating the effects of climate change and human activities on drought propagation via a natural and human-impacted catchment comparison method

“…Drought is widely recognized as a complex, multidimensional phenomenon that occurs in most parts of the world (Wang et al, 2020;Tijdeman and Menzel, 2020;Jiang et al, 2019;Van Loon et al, 2016;Barker et al, 2016;Sheffield et al, 2012;Dai, 2011;Mishra and Singh, 2010). Drought starts with negative hydro-climatic signals (i.e., meteorological drought) and propagates through interconnected hydrological 7 / 70 and the SPI series, and the SPI accumulation period with the strongest PCC was used as an indicator of the drought propagation time (Barker et al, 2016;Wu et al, 2018).…”

Tropical drought risk: estimates combining gridded vulnerability and hazard data

“…Open access high resolution remote sensing data products are continuously increasing in quantity (AghaKouchak et al, 2015;Mariano et al, 2018). In this context, a variety of gridded datasets are available, including daily precipitation (Funk et al, 2015;Baez-Villanueva et al, 2018&2020), surface water (Beck et al, 2016), groundwater (Thomas et al, 2014), reservoirs (AghaKouchak et al, 2018, soil moisture (Samaniego et al, 2018;Tijdeman and Menzel, 2020), and vegetation (Pinzón and Tucker, 2014;Nguyen et al, 2019).…”