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Check dams are commonly constructed around the world for alleviating soil erosion and preventing sedimentation of downstream rivers and reservoirs.Check dams are more vulnerable to failure due to their less stringent flood control standards compared to other dams.Determining the critical precipitation that will result in overtopping of a dam is a useful approach to assessing the risk of failure on a probabilistic basis and for providing early waming in case of an emergency.However,many check dams are built in groups,spreading in several tributaries in cascade forms,comprising a complex network.Determining the critical precipitation for dam overtopping requires a knowledge of its upstream dams on whether they survived or were overtopped during the same storm,while these upstream dams in turn need the information for their upstream dams.The current paper presents an approach of decomposing the dam cluster into (1) the heading dam,(2) border dams,and (3) intermediate dams.The algorithm begins with the border dams that have no upstream dams and proceeds with upgraded maps without the previous border dams until all the dams have been checked.It is believed that this approach is applicable for small-scale check dam systems where the time lag of flood routing can be neglected.As a pilot study,the current paper presents the analytical results for the Wangmaogou Check Dam System that has 22 dams connected in series and parallel.The algorithm clearly identified 7 surviving dams,with the remaining ones being overtopped for a storm of 179.6 mm in 12 h,which is associated with a return period of one in 200 years.