High resolution soil drought simulations evaluated at an unprecedented broad-range of soil moisture networks in Germany

Abstract

<p><span>The 2018-2020 consecutive drought events in Germany resulted in impacts related with several sectors such as agriculture, forestry, water management, industry, energy production and transport. The key to increase preparedness for extreme drought events are high-resolution information systems. A major national operational drought information system is the German Drought Monitor (GDM), launched in 2014 [1]. It provides daily soil moisture (SM) simulated with the mesoscale hydrological model (mHM) and its related soil moisture index [2] at a spatial resolution of 4×4 km². The release of the new soil map BUEK200 allowed us to increase its model resolution to ≈1.2×1.2 km², which is used now for the second version of the GDM [3]. </span></p><p><span>To explore the ability of the GMD-v2 to provide drought information at one-kilometer scale, we evaluated mHM soil moisture simulations against an unprecedented large sample of soil moisture observations from 40 locations across Germany. These SM observations are obtained from single profile measurements, spatially distributed sensor networks, cosmic-ray neutron stations, and lysimeters over a wide range of climatic conditions, vegetation types and soil depths. Specifically, the study aimed at answering two resea</span><span>r</span><span>ch questions: 1) how well do high-resolution German-wide soil moisture simulations capture the dynamics in observed soil moisture that constitute the basis for the near real-time soil moisture drought monitoring system? 2) Does the mHM simulations obtained with the high spatial resolution dat</span><span>a</span><span> set provide soil moisture estimates with greater model efficiency than those obtained in the coarser resolution? </span></p><p><span>The results showed that the agreement of simulated and observed SM dynamics is especially high during the vegetation period (0.84 median </span><span>Spearman</span><span> correlation(r)) and lower in winter (0.59 median </span><span>r</span><span>). Moderate but significant improvements between the low- and high-resolution GDM versions to observed SM were found in correlations for autumn (+0.07 median r) and winter (+0.12 median r). The spatially distributed sensor networks outperformed single profile measurements with higher than average correlation values especially for the 25–60 cm depth, which supports the closer scale match of spatially distributed measurements to the simulations. The resu</span><span>l</span><span>ts indicate areas for potential improvement and shows limitations from both: model parameterization (e.g., improvement of local scale hydrological processes) and observations </span><span>methodology</span><span> (e.g., reduction of measurement errors). Finally, the results of this study underline th</span><span>e</span><span> fact th</span><span>at</span><span> nationwide drought information system</span><span>s</span><span> depend both on appropriate simulations of the water cycle and a broad, high-quality observational soil moisture database.</span></p><p><span>