Publication Details |
| Category | Software Publication |
| DOI | 10.5281/zenodo.5842486 |
| Licence |
|
| Title (Primary) | The Soil Moisture Index - SMI program (2.0.5) |
| Version | 2.0.5 |
| Author | Samaniego, L.
; Kumar, R.
; Zink, M.; Mai, J.; Boeing, F.
; Shrestha, P.K.; Kaluza, M.; Schäfer, D.; Thober, S. |
| Source Titel | Zenodo |
| Year | 2022 |
| Department | CHS; MET |
| Topic | T5 Future Landscapes |
| Abstract | Germany's 2018–2020 consecutive drought events resulted in multiple sectors – including agriculture, forestry, water management, energy production, and transport – being impacted. High-resolution information systems are key to preparedness for such extreme drought events. This study evaluates the new setup of the one-kilometer German drought monitor (GDM), which is based on daily soil moisture (SM) simulations from the mesoscale hydrological model (mHM). The simulated SM is compared against a set of diverse observations from single profile measurements, spatially distributed sensor networks, cosmic-ray neutron stations, and lysimeters at 40 sites in Germany. Our results show that the agreement of simulated and observed SM dynamics in the upper soil (0–25 cm) are especially high in the vegetative active period (0.84 median correlation R) and lower in winter (0.59 median R). The lower agreement in winter results from methodological uncertainties in both simulations and observations. Moderate but significant improvements between the coarser 4 km resolution setup and the ≈ 1.2 km resolution GDM in the agreement to observed SM dynamics is observed in autumn (+0.07 median R) and winter (+0.12 median R). Both model setups display similar correlations to observations in the dry anomaly spectrum, with higher overall agreement of simulations to observations with a larger spatial footprint. The higher resolution of the second GDM version allows for a more detailed representation of the spatial variability of SM, which is particularly beneficial for local risk assessments. Furthermore, the results underline that nationwide drought information systems depend both on appropriate simulations of the water cycle and a broad, high-quality, observational soil moisture database. |
| linked UFZ text publications | |
| Persistent UFZ Identifier | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=27384 |
| Samaniego, L., Kumar, R., Zink, M., Mai, J., Boeing, F., Shrestha, P.K., Kaluza, M., Schäfer, D., Thober, S. (2022): The Soil Moisture Index - SMI program (2.0.5) Version: 2.0.5 Zenodo 10.5281/zenodo.5842486 |
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