Monitoring and quantification of stormwater runoff from mixed land use and land cover catchment in response to land development

Understanding the influence of land use and land cover (LULC) change in stormwater runoff is important for watershed management. In this study, integration of 31 storm events, monthly monitoring of LULC change, Pearson's correlation, multiple linear regression analysis (MLR) and Personalized Computer Storm Water Management Model (PCSWMM) were applied to quantify the influence of LULC change on stormwater quality from mixed LULC catchment with ongoing land development in Yongin, South Korea. Due to ongoing land development in the catchment, bare land and urban LULC were exponentially increased while agriculture, forest, grassland and water LULC decreased in spatial extent. The correlation analysis showed that stormwater quality was positively correlated to bare land (0.595; Cl - 0.891; TSS, p < 0.05) and urban (0.768; TN - 0.987; TSS, p < 0.05); negatively correlated to forest (-0.593; Cu - 0.532; BOD5, p < 0.05) and grassland (-0.587; TSS - 0.512; BOD5, p < 0.05) and; either positively or no correlation to agriculture (0.064; Cu - 0.871; TSS, p < 0.05) and water (-0.131; Cl - 0.221; TP, p < 0.05). Furthermore, the MLR analysis showed that combinations of different LULC were able to describe the overall stormwater quality of the catchment. Moreover, the LULC scenario analysis demonstrate that under dominant agriculture (S1), bare land (S2) and urban areas (S5), the average pollutant concentrations would increase by as much as 13.22% (Cl; S2; pre-) to 59.25% (TSS; S5; early-active); while under dominant forest (S3) and grassland (S4) the average pollutant concentration would decrease by as much as -53% (Pb; S3; late-active) to -3.22% (BOD5; S4; pre-). These findings explained that the variability of pollutant concentrations in different phase of land development was affected by expansion of bare land and urban spatial extent, increase of hydrological characteristics (total rainfall and average rainfall intensity) and massive soil activities (soil digging and soil transfer). Therefore, results of this study will provide scientific information to establish a cost-effective stormwater management, development of empirical model, and designing monitoring strategies and guidelines to minimize the negative impact of LULC change on stormwater runoff.