For a single site (of a rain gauge, say), the statistics of extreme precipitation are conveniently summarized by depth-duration-frequency (DDF) curves. Considering a spatial domain of some extent, one may ask: how often does it happen that the precipitation depth accumulated over 10 min exceeds 60 mm somewhere on this domain? Naturally, this frequency is higher than the frequency of exceedance of the same depth at a site; it depends on the size and shape of the domain and on the spatial dependence of extreme precipitation. In the present study, statistics of this spatial dependence are estimated from 11 years of gauge-adjusted radar-based precipitation data collected over the Netherlands, assuming spatial homogeneity. These statistics are the values of the extremal coefficient function (ECF) for selected spatial domains. From these values, a simple model is derived for predicting return periods or return values of the highest precipitation depth within an arbitrary spatial domain, based on a given DDF relation. In the model, the footprint of an individual downpour over its lifetime is simplified to a rectangular strip of fixed size ranging from 1.7 km $\times$ 12 km for a duration of 10 min to 5.1 km $\times$ 21 km for a duration of 12 h. Confidence intervals of the predictions are estimated by bootstrapping. The model is checked for fitness for its application to the design and maintenance of the drainage of highways, and the scope for further improvement is discussed.

对于单个站点（例如雨量计），极端降水的统计数据可以方便地通过深度-持续时间-频率 (DDF) 曲线进行汇总。考虑到某种程度的空间域，有人可能会问：在这个域的某个地方，10 min 内累积的降水深度超过 60 mm 的频率是多少？自然地，这个频率高于一个站点相同深度的超越频率；它取决于域的大小和形状以及极端降水的空间依赖性。在本研究中，假设空间同质性，这种空间依赖性的统计数据是根据在荷兰收集的 11 年的基于测量仪调整的基于雷达的降水数据估计的。这些统计数据是所选空间域的极值系数函数 (ECF) 的值。从这些值中，基于给定的 DDF 关系，推导出一个简单的模型，用于预测任意空间域内最高降水深度的返回周期或返回值。在模型中，单个倾盆大雨在其生命周期内的足迹被简化为一个固定大小的矩形条带，范围从 1.7 公里$\times$12 公里，持续 10 分钟至 5.1 公里$\times$21 公里，持续 12 小时。通过自举估计预测的置信区间。对该模型在高速公路排水设计和维护中的适用性进行了检查，并讨论了进一步改进的范围。