Analysis of Low Impact Development Using Continuous Simulation Hydrologic Modeling

摘要

Continuous simulation (CS) refers to the computational modeling of a physical system in which the model continuously tracks and accounts for system responses to changes over time. This branch of deterministic modeling is well suited to the study of complex systems with multiple interactive feedback mechanisms. There are a wide range of applications in fields that include medicine, engineering, space exploration, and defense. The use of CS in hydrologic analyses was first implemented in the United States in 1960, with the development of the Stanford watershed model under Dr. Ray Linsley at Stanford University. Hydrologic analysis using CS remained fairly uncommon outside of academia up to and beyond the advent of modern desktop computing and the age of big data. This has remained so due in part to the perception that the data needs are too large and the processing times are too extensive. Another barrier to a more broad use of this technique is perhaps the lack of guidance and documentation for using this technique within existing and well established modeling platforms such as the U.S. Army Corps of Engineers Hydrologic Engineering Center hydrologic modeling system (HEC-HMS) and the U.S. Environmental Protection Agency's storm water management model (SWMM). The application of CS in the hydrologic analysis of low impact development (LID) implementation in the urban and suburban watershed offers the ability to perform predictive analysis of system performance under both static and changing land use and watershed management strategies. It offers a tool to evaluate the potential influence of LID on the sources of hydromodification and pollutant loading. Applying statistical analyses to the output from CS provides the ability to assign probability to observed system responses. For instance, what effect does a particular watershed management or development activity have on the recurrence interval for the bank full flow within a receiving stream? This paper presents a brief introduction to CS, a discussion of the LID modeling capabilities of SWMM, an introduction to CS capabilities of SWMM, and a simple example of a CS simulation of LID.