Qualitative flood forecast in Lenzkirch based on soil moisture and water level data
Author:
Publisher
Springer Science and Business Media LLC
Subject
Water Science and Technology
Link
https://link.springer.com/content/pdf/10.1007/s35147-023-1868-5.pdf
Reference6 articles.
1. Komma, J.; Blöschl, G.; Reszler, C.: Soil moisture updating by Ensemble Kalman Filtering in real-time flood forecasting. In: Journal of Hydrology 357 (2008), Nr. 3-4, S. 228-242.
2. Alvarez-Garreton, C.; Ryu, D.; Western, A. W. et al.: Improving operational flood ensemble prediction by the assimilation of satellite soil moisture: Comparison between lumped and semi-distributed schemes. In: Hydrology and Earth System Sciences 19 (2015), Nr. 4, S. 1 659-1 676.
3. Kim, S.; Zhang, R.; Pham, H.; Sharma, A.: A review of satellite-derived soil moisture and its usage for flood estimation. In: Remote Sensing in Earth Systems Sciences 2 (2019), Nr. 4, S. 225-246.
4. Mewes, B.; Schumann, A. H.: An agent-based extension for object-based image analysis for the delineation of irrigated agriculture from remote sensing data. In: International Journal of Remote Sensing 40 (2019), Nr. 12, S. 4 623-4 641.
5. Fischer, S.; Bühler, P.; Büttner, U.; Schumann, A.: The use of maximum entropy to increase the informational content of hydrological networks by additional gauges. In: Hydrological Sciences Journal 65 (2020), Nr. 13, S. 2 274-2 285.
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