Improving the estimation approach of percentage of impervious area for the storm water management model — A case study of the Zengwen reservoir watershed, Taiwan
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引用次数: 0
Abstract
The Zengwen Reservoir, located within the Zengwen River watershed, is a crucial water supply source in southern Taiwan. Water resources can be estimated using the rainfall-runoff model of the Storm Water Management Model (SWMM). However, the percentage of impervious area (PIA) is one of the significant factors influencing the SWMM. The purpose of this study is to utilize remote sensing imagery to rapidly and accurately estimate land use as PIA for the SWMM rainfall-runoff model. The rainfall-runoff model of SWMM was calibrated and validated based on observed discharge data in 2005 and 2017. The results of goodness-of-fit indicators of NSE value and R2 value showed in the acceptable range of 0.745, 0.764 in 2005, 0.715, and 0.883 in 2007, respectively. The modified composite of the built-up index and PIA (MCBI-PIA) was used for rainfall-runoff simulation in 2005, 2009, 2014, 2017, and 2021. The simulation results revealed the NSE value varied from 0.484 to 0.851, and the R2 value between 0.519 and 0.894 which represented a statistically acceptable performance of the simulation model. It indicates that the proposed method can be applied to estimate the PIA for land use patterns during different periods and utilized as the actual PIA for rainfall-runoff simulation with the SWMM.
期刊介绍：
The journal ''Remote Sensing Applications: Society and Environment'' (RSASE) focuses on remote sensing studies that address specific topics with an emphasis on environmental and societal issues - regional / local studies with global significance. Subjects are encouraged to have an interdisciplinary approach and include, but are not limited by: " -Global and climate change studies addressing the impact of increasing concentrations of greenhouse gases, CO2 emission, carbon balance and carbon mitigation, energy system on social and environmental systems -Ecological and environmental issues including biodiversity, ecosystem dynamics, land degradation, atmospheric and water pollution, urban footprint, ecosystem management and natural hazards (e.g. earthquakes, typhoons, floods, landslides) -Natural resource studies including land-use in general, biomass estimation, forests, agricultural land, plantation, soils, coral reefs, wetland and water resources -Agriculture, food production systems and food security outcomes -Socio-economic issues including urban systems, urban growth, public health, epidemics, land-use transition and land use conflicts -Oceanography and coastal zone studies, including sea level rise projections, coastlines changes and the ocean-land interface -Regional challenges for remote sensing application techniques, monitoring and analysis, such as cloud screening and atmospheric correction for tropical regions -Interdisciplinary studies combining remote sensing, household survey data, field measurements and models to address environmental, societal and sustainability issues -Quantitative and qualitative analysis that documents the impact of using remote sensing studies in social, political, environmental or economic systems
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