This model may partition the study basin into many sub-basins, which can further be segmented into multiple Hydrologic Response Units (HRUs). This classification can more precisely examine hydrological processes, including evapotranspiration and runoff generation, across various land uses and soil types in the research area [7]. The SWAT model has been extensively utilized in basin management, water resources evaluation, and agricultural management both domestically and internationally; nevertheless, its application in groundwater resource assessment remains limited compared to its use in surface water resource evaluation. In recent years, certain domestic experts have endeavored to employ the SWAT model to assess water resources in regional inland water bodies [8]. In 2020, [PERSON] et al. conducted a systematic analysis of the evolutionary patterns and influencing factors of groundwater resources in China over the preceding 60 years, utilizing data from the National Water Resources Survey, Evaluation, and Water Resources Bulletin while also performing extensive investigations and assessments of the hydraulic environment in the karst mountainous regions of southwest China [9]. Based on the identification of the water-bearing medium's structure and the principles governing groundwater circulation, 56 tertiary drainage basins and 696 quaternary groundwater systems were delineated. A total of 2763 subterranean rivers were identified, spanning a cumulative length of 12,687 km and exhibiting a flow of 470 million cubic meters per annum during the dry season. The southern karst regions are significantly impacted by global climate change and unique karst geological features, resulting in severe drought and water scarcity. The annual growth and use potential of the southwest karst regions is estimated at 46.875 billion m\({}^{3}\). Scholar [PERSON] developed a SWAT distributed hydrological model, employed the SUFI-2 algorithm for the parameter sensitivity analysis, and conducted a month-by-month analysis of the outflow hydrological station in the Malian River region [10]. In the model validation phase, the R\({}^{2}\) and NS values attained 0.75 and 0.64, respectively, satisfying the fundamental criteria of the Groundwater Resources Assessment Report, thereby demonstrating the enhanced accuracy of this model's fitting results. [PERSON] [11] used the SWAT model to assess groundwater resources in the Pearl River Basin. The rainfall guarantee rate was established to provide an artificial classification of wet, normal, and dry years to aid in the forecasting of groundwater resources. The groundwater recharge modulus for each hydrogeological unit was computed using the existing SWAT model to conduct parameter inversion. The derived distribution law of the annual rainfall infiltration coefficient aligns with the distribution law of groundwater recharge modulus, thus demonstrating the SWAT model's efficacy in groundwater resource assessment. This paper used the SWAT model to assess and quantify runoff and groundwater reserves in the study area, yielding extremely accurate simulation findings based on prior research. The applicability of the SWAT model for calculating groundwater reserves has been demonstrated. The Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, created in 2007 by Stanford University and the World Wide Fund for Nature, aims to facilitate effective natural resource management decisions and achieve equilibrium between development and conservation while pursuing optimal models for natural resource management and economic advancement. The InVEST model primarily has the following three modules: freshwater ecosystem assessment, marine ecosystem assessment, and terrestrial ecosystem assessment [12]. The InVEST model's input parameters are readily available and straightforward to utilize, necessitating relatively few inputs, hence diminishing the complexity and expense of data acquisition.