การพัฒนาแบบจำลองจัดการน้ำฝนไหลนองในพื้นที่มหาวิทยาลัยเชียงใหม่

Abstract

In historical contexts, human settlements predominantly manifested as small-scale communities. However, the evolution of societal dynamics over time has precipitated a transition towards larger urban conglomerations. Presently, numerous communities have matured into expansive urban centers. This contemporary urban proliferation phenomenon owes momentum to the convergence of technological innovations and socio-economic imperatives. Significant shifts have transpired within these settlements with this urban expansion, exemplified by the metamorphosis from rudimentary dirt tracks to modern asphalt thoroughfares and the substitution of verdant expanses with impermeable concrete surfaces. The proliferation of impervious areas diminishes the capacity for water absorption, precipitating challenges associated with accelerated surface runoff and consequent flooding events. Mitigating such challenges necessitates a strategic increase in the permeable footprint within urban landscapes. Thus, the primary objective of this research is to scrutinize the pivotal parameters essential for simulating the study area. This issue encompasses establishing steadfast metrics for quantifying soil infiltration, which is pivotal for delineating models of stormwater runoff management. Furthermore, the research endeavors to devise a comprehensive model to assess the efficacy of mitigating runoff by implementing rain gardens within select areas. The objective of this study pertains to the central stadium zone of Chiang Mai University, which is notable for its diverse spatial utilization paradigms. Employing simulation methodologies facilitated by the Storm Water Management Model (PCSWMM), a sophisticated computer program integrating geographical and hydrological data, this research aims to furnish a robust analytical framework. Crucially, the identification and calibration of model parameters are informed by an exhaustive review of pertinent literature and a meticulous assessment of the requisite specifications mandated by the PCSWMM platform. The variables under study encompass subcatchment characteristics, height data pertaining to the area, percentage slope, existing infrastructure, rainwater information, and parameters utilized in the design of the raingarden layer. Additionally, in the event of simulating the study area model, it becomes indispensable to ascertain the soil infiltration rate within the area. This research utilized a double-ring infiltrometer to assist in determining soil infiltration within the study area. The tests were conducted over a span of four months, once per month, encompassing October, November, December 2021, and February 2022. This data collection was conducted randomly for the sake of convenience. The results revealed that the data could be categorized into two distinct groups exhibiting different behaviors. Group 1 comprised the months of October and February, demonstrating an average infiltration rate of 8.00 millimeters per hour. Group 2, encompassing November and December, exhibited a notably higher average infiltration rate of 30.60 millimeters per hour. Notably, across all four months, the highest infiltration rate recorded was 7.2 millimeters per hour, while the lowest was 0.5 millimeters per hour. Upon comprehensive data collection, This research has divided the model into 2 types: Base case model and Alternative case model, which is a study area for simulating pervious areas using the principles of WSUD or LID, which has many different forms. It help reduce the amount of runoff, the simulated pervious areas will use the raingarden format in unused spaces or parking areas as appropriate. From the study, it was found that the Base case model made known the problem that occurred. It was Flooding in some subcatchments, which those areas would be simulated as an Alternative case model. And the results from the Alternative case model found that Raingarden can help reduce the area where Flooding occurs and reduce partial runoff quantity. Further experimentation, focusing on rain garden size reduction to find the appropriate size, it was found that The data has been divided into 4 groups: Group 1 has an average LID area of 8.84%, reducing total runoff (TR) by 9.38%. Group 2 has an average LID area of 20.66%, reducing TR by 20.67%. Group 3 has an average LID area of 41.85% reduced TR by 41.87% and Group 4 had an average LID area of 70.55% and reduced TR by 70.56%. Finally, it known adding a rain garden can actually reduce runoff, but the rate of reducing runoff will depend on size of the rain garden of that area. This research represents an initiative endeavor in the application of WSUD/LID principles within tangible urban settings. However, it's noteworthy that the PCSWMM program, while indispensable, may entail inherent computational limitations necessitating iterative refinement in runoff and flood value applications.