Collective memory plays a controlling role in adaptation to potential flood risks, by learning from past disasters. However, with little quantitative empirical data, previous socio‐hydrological models have conceptualized the decaying process of flood memory in an oversimple approach. Here, based on survey data of 683 respondents on Ningxia Floodplain, we confirmed that flood memory decays overtime via two channels: oral communication (communicative memory) and physical recording of information (cultural memory). Using the Universal Decay Model (UDM) proposed by previous researchers provides better fitting of results to the decay of flooding memory (adjusted R² coefficient are 0.97, 0.90, 0.95 when data of all, rural or urban respondents used, respectively) compared with the original exponential model (adjusted R² coefficient are 0.91, 0.74, 0.59, corresponding). Then, significantly reduced losses for the same flood sequence predicted by integrating the UDM into a socio‐hydrological model by 16% and the differences between different clusters (urban and rural respondents) can even reach 22.81%. These differences suggest that previous socio‐hydrological models have been too simplistic in their conceptualizations of decaying processes associated with collective memory, which may have limited deeper insights into flood risk management.

中文翻译：

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改进集体记忆在社会水文模型中的表示方式，以及对洪水风险管理的新见解

通过从过去的灾难中学习，集体记忆在适应潜在洪灾风险中起着控制作用。但是，由于缺乏定量的实证数据，以前的社会水文学模型已经以一种过于简单的方法将洪水记忆的衰减过程概念化。在此，根据宁夏洪泛区683名受访者的调查数据，我们确认洪水记忆会通过两种途径随时间而衰减：口头交流（交流记忆）和信息的物理记录（文化记忆）。使用以前的研究人员提出的通用衰减模型（UDM），可以使结果更好地适合洪水记忆的衰减（调整后的R ²与原始指数模型（调整后的R ²系数分别为0.91、0.74、0.59，相对应）相比，当使用所有农村或城市受访者的数据时，系数分别为0.97、0.90、0.95。然后，通过将UDM集成到社会水文模型中所预测的同一洪水序列的损失大大减少了16％，不同集群（城市和农村受访者）之间的差异甚至可以达到22.81％。这些差异表明，以前的社会水文模型对与集体记忆有关的衰减过程的概念过于简单，这可能会限制对洪水风险管理的深入了解。