Estimating the variation in runoff due to landcover changes using the SWAT model

Land use and land cover changes are majorly associated with the anthropogenic causes as well as human growth and urban expansion. The rapid increase in urban development is interlinked to fragmentation of landcover changes leading to a rise in flood events. The growth rate of urbanization has been quite significant in Ireland over the past 30 years. Ireland’s annual growth rate of urbanization was found to be 3.1% between 1990 to 2012. Several studies have further documented that Ireland experienced an overall higher degree of land conversion relative to other European countries, concluding that the urban land expansion in Ireland has been among the highest in Europe. The majority of the physically-based hydrological models that are used to simulate the discharge dynamics from river basin outlets require land cover information. One of the major limitations of those models is that they, in general, assume that the land cover information remains the same over time. However, changes in land cover are evolving over time, which needs to be considered while simulating runoff at a river basin. In situations where the hydrological model is used to simulate runoff for a short period of time, ranging from a few months to a few years, a static land cover information might be sufficient, however, when runoff simulations are required for longer periods of time (more than a decade), it is important to consider the changes in land cover over such a period. This study investigates how changes in land cover impact hydrological runoff simulations using a rainfall-runoff model called soil water assessment tool (SWAT). The study area considered is the Dodder River basin located in southern Dublin, Ireland. Runoff at the basin outlet was simulated using SWAT for 1993–2019 using five landcover maps obtained for 1990, 2000, 2006, 2012 and 2018. The hypothesis specifically points to the consideration of dynamic and time-varying landcover data during the development of hydrological modelling for runoff simulation. Furthermore, two composite quantile functions were generated by using a kappa distribution for monthly mean runoff and GEV distribution for monthly maximum runoff, based on model simulations obtained using different landcover data corresponding to different time-period.