System partitioning for effective simulation of civil infrastructure flow networks on parallel processors is a non-trivial problem. Arbitrary partitioning focused only on balancing processor workload can lead to a large inter-processor communication burden that limits parallel speedup. Thus, there is a need for intelligent partitioning algorithms that balance the estimated computational load while minimizing the number of connections between partitions. Graph Theory provides widely-used partitioning methods, but these are applicable to networks with power-law connectivity and where the computational workload is proportional to the number of system nodes -conditions that do not hold for finite-volume solution of water drainage networks (e.g. river systems, stormwater drainage systems). This paper presents the novel "BIPquick" algorithm, which is shown to be an effective approach to identifying network partitions with reduced connectivity for systems that are Directed Acyclic Graphs (DAG) and have a physical limit on the number of connections per network node.Novel developments include (i) a "node-cut" approach that allows a partitioning workload function to be exactly balanced in systems where the computational work is proportional to the link length between nodes, (ii) a finite-pass approach to partitioning that ensures a partitioning solution in a known time, and (iii) a new connectivity scaling metric that allows simple evaluation and comparison of different partitioning results. The BIPquick model is tested on a large river network with up to 10,000 partitions. Tiernan, March 21, 2022 limited to junctions with less than 10 connecting links. Thus, practical approaches to the partitioning networks with limited junction connectivity are of interest to civil engineering.To further limit our scope, in finite-volume, unsteady flow models in a network the links ("edges" in Graph Theory) between nodes are subdivided into smaller elements of roughly uniform size such that the computational work scales on the link lengths -which contrasts with traditional link-node models (e.g., EPANET, SWMM) where the link length does not directly affect the workload. Hence, we focus herein on partitioning with link-dependent load balancing for gravity-drainage networks solved with finite-volume algorithms.As a simple example of the importance of both inter-processor communication and workload in partitioning, consider a network with N links of uniform length partitioned onto K processors where N ≫ K. The workload on an individual processor is (in this case) the number of links assigned to the processor. The overall communication burden is the number of nodes that connect to more than one processor. Figure 1a illustrates a worst-case condition for communication by using random sort, i.e. link-balance partitioning of an unsorted set. The random sort achieves workload balance, but at the cost of the inter-processor communication load scaling on N . In contrast, Fig. 1(b) illustrates, the reverse problem, a partitioning scheme that minimi...