Modelling and assessment of hydrological changes in a developing urban catchment

Abstract

Urbanization strongly changes natural catchment by increasing impervious coverage and by creating a need for efficient drainage systems. Such land cover changes lead to more rapid hydrological response to storms and change distribution of peak and low flows. This study aims to explore and assess how gradual hydrological changes occur during urban development from rural area to a medium‐density residential catchment. The Stormwater Management Model (SWMM) is utilized to simulate a series of scenarios in a same developing urban catchment. Sub‐hourly hydro‐meteorological data in warm season is used to calibrate and validate the model in the fully developed catchment in 2006. The validated model is then applied to other cases in development stage and runoff management scenarios. Based on the simulations and observations, three key problems are solved: (1) how catchment hydrology changes with land cover change, (2) how urban development changes pre‐development flows, and (3) how stormwater management techniques affect catchment hydrology. The results show that the low‐frequency flow rates had remarkably increased from 2004 to 2006 along with the increase of impervious areas. Urbanization in the residential catchment expands the runoff contributing area, accelerates hydrological response, raises peak flows in an order of magnitude of over 10, and more than doubles the total runoff volume. The effects of several LID controls on runoff hydrograph were simulated, and the techniques were able to reduce flows towards the pre‐development levels. However, the partly restored flow regime was still clearly changed in comparison to the pre‐development flow conditions. Copyright © 2014 John Wiley & Sons, Ltd.

Coupling GIS with Stormwater Modelling for the Location Prioritization and Hydrological Simulation of Permeable Pavements in Urban Catchments

“…The study catchment was delineated and simulated in SWMM by Jato-Espino et al [59], who determined that it was formed of 79 subcatchments covering 10.535 ha and optimized its stormwater modelling using Design of Experiments (DOE) with three monitored calibration (CAL 1, CAL 2 and CAL 3) and validation (VAL 1, VAL 2 and VAL 3) rainfall events (see Table 3). The calibration of the simulations revealed that six parameters had a statistically significant impact on the discharge of the [57], whilst the Geological Survey of Finland revealed that the study catchment laid on a layer of sandy till with bedrock below it [23], which most likely corresponds to a HSG of B. A set of 60 points with values of Water Table Depth near the catchment area was extracted from the global grid created by Fan et al [58] at 1,603,781 sites worldwide from government archives and published literature.…”

“…The delineation and modelling of urban catchments is a widely addressed topic in literature, which provides multiple evidence of the capability of GIS and stormwater models to reproduce their hydrological response with accuracy [21][22][23]. Hence, the methodology presented in this study finds application in the next step to these tasks; i.e., in situations in which the stormwater modelling of urban catchments has been calibrated and validated and their simulation for design return periods leads to high peak runoff rates in the subcatchments forming them and flooding in the nodes of their drainage networks.…”

“…The values recommended by PPS-related institutes and associations to parameterize these layers [37][38][39][40][41] and previous studies on the use of SWMM to model these systems [23,42] led to define the three cross-sections shown in Table 2, which represent the three major PPS types highlighted by specialized literature sources [25,28,43]: Porous Asphalt (PA), Porous Concrete (PC) and Permeable Interlocking Concrete Pavement (PICP). These cross-sections are representative because institutes and associations specialized in the materials forming the pavement layer suggest them as characteristic.…”

The analysis of Ancol polder system as flood prevention infrastructure in Jakarta

“…The polder system faces threats because of the increasing population and the development of infrastructure in Jakarta that makes land uses change from forest and agricultural domains become of people settlements [6]. Rapid land-use changes and increase in extreme rainfall events due to climate changes could potentially result in high flood risk [7,8]. This will impact the performance and capacity of existing polder systems in Jakarta.…”

Impact of urbanization on rainfall-runoff processes: case study in the Liangshui River Basin in Beijing, China

“…For instance, Guan et al (2015) used the SWMM model to simulate a series of scenarios in a developing urban catchment. Koudelak and West (2008) and Peng et al (2015) adopted the InfoWorks model to simulate sewerage network flow in the city of Latvia and China, respectively.…”