Dynamic Land Use Change in SWAT +: A Novel Application of Scenario Decision Tables

ABSTRACT

Land use and land cover (LULC) changes significantly impact hydrological processes, yet their dynamic representation in hydrological models remains a challenge. This paper introduces and pioneers the use of the newly implemented capability of SWAT+ to simulate dynamic LULC changes using “land use scenario decision tables”. Traditionally, LULC change assessments in hydrological modeling rely on a static “delta approach,” which often leads to inaccurate parameterization and limitations in capturing the true temporal evolution of hydrological responses. Our novel approach overcomes this limitation by enabling the user to dynamically alter LULC classifications throughout a model run. The functionality is demonstrated through an application to the forest‐clearing experiment in the Hubbard Brook Experimental Forest (NH, USA). We compare the results of the dynamic LULC change scenario against scenarios with no LULC change and static LULC change. The dynamic LULC change scenario improves the representation of discharge predictions, with average split KGE increasing to 0.62 versus 0.59 and 0.56 for the static and no LULC scenarios, respectively. While this implementation marks a crucial advancement in integrating dynamic LULC processes into SWAT+, challenges remain, such as incorporating time‐varying snow parameters and documenting existing functionalities. This work represents an important step towards more realistic and accurate hydrological simulations under evolving land use conditions.