Surface water floods (SWFs) do not only increasingly threaten cities, but also affect rural areas. So far, little research has been dedicated to the prediction of SWFs in rural environments, although in practice the process is already being considered in deterministic flood hazard assessments. To test the validity of such assessments, we select four raster-based models with differing complexity and evaluate whether they reliably predict inundated areas by SWF in rural areas. The uncalibrated models are first applied to four artificial surfaces and second, to eight case studies covering manifold geographical and meteorological settings. For the case studies, the models' prediction skills are assessed based on inundated areas inferred from various sources. The models’ performance is rather low for all case studies, which highlights the necessity for calibration and/or validation of such models. Moreover, the case studies provide more general conclusions concerning the modeling of SWFs in rural areas.

地表水洪（SWF）不仅日益威胁城市，而且还影响农村地区。到目前为止，尽管在实践中已经在确定性洪水危害评估中考虑了这一过程，但很少有研究致力于农村环境中的SWF。为了检验此类评估的有效性，我们选择了四个基于栅格的复杂度不同的模型，并评估了它们是否可以通过SWF可靠地预测农村地区的淹没区域。未经校准的模型首先应用于四个人造表面，其次应用于八个涵盖多种地理和气象环境的案例研究。对于案例研究，基于从各种来源推断出的淹没区域来评估模型的预测技能。在所有案例研究中，模型的性能都相当低，这突出了对此类模型进行校准和/或验证的必要性。此外，案例研究提供了有关农村地区主权财富基金建模的更一般性结论。