The SWAT model primarily investigates sources of water pollution and conducts ecological assessments of surface water in contemporary hydrology and water resources research. To date, there have been limited accomplishments in the study of groundwater resources in China. The MODFLOW model currently primarily simulates groundwater levels and the migration of water quality, depending on the hydrological surface water data in the relevant area. This study aims to investigate the groundwater distribution characteristics of the middle and lower reaches of the Songhua River, a significant agricultural and grain production region in China. The research focuses on the middle and lower reaches of the Songhua River basin in Northeast China and employed the SWAT distributed hydrological model to simulate runoff. The monthly recorded runoff at Tongjiang Station in Jiamusi City was utilized to calibrate the model parameters. Consequently, the MODFLOW model was introduced to compare and assess the simulation outcomes of the SWAT model, ultimately ascertaining the distribution characteristics of shallow groundwater, groundwater recharge, recoverable volume, and groundwater levels in the Songhua River Basin. The findings indicate that: (1) The SWAT model demonstrates efficacy in the study region, achieving R² and NS values of 0.81 and 0.76, respectively, thereby fulfilling the fundamental criteria for scientific research. The MODFLOW model exhibits strong performance in the study region, achieving a periodic R² of 0.98 and a verification R² of 0.97, with the discrepancy between simulated and actual groundwater levels confined to 0.6 m, thereby satisfying the criteria for scientific research. (2) In 2011, 2014, and 2016, the groundwater recharge in the middle and lower sections of the Songhua River was 24.33 × 10⁸ m³, 30.79 × 10⁸ m³, and 32.25 × 10⁸ m³, respectively, aligning closely with the SWAT simulation results, while the average annual groundwater level depth was 8.17 m. (3) In the research area, groundwater recharging occurs primarily by atmospheric precipitation, while drainage predominantly transpires via groundwater as base flow, constituting 81.46%. Secondly, the recharge of shallow groundwater to deep aquifers is around 7.14%, with a minimal share attributed to vadose zone loss, constituting merely 2.1%. (4) From 2010 to 2016, the average groundwater runoff modulus of the middle and lower reaches of the Songhua River basin was 1.005 L/(s·km²), with a total recharge of 216.58 × 10⁸ m³ and a total recoverable amount of 105.11 × 10⁸ m³. The mean yearly supply was 25.11 × 10⁸ m³. The total groundwater recharge was 26.54 × 10⁸ m³ in the driest year (2011) and 33.25 × 10⁸ m³ in the year of most ample water (2016).

Understanding the spatiotemporal dynamics of runoff and its drivers is essential for water resources management in mid–high latitude basins. This study investigates runoff changes in the Songhua River Basin, Northeast China, during 1980–2022 using the Budyko framework, combined with Mann–Kendall trend analysis, Pettitt tests, Hurst index, and wavelet analysis. Results indicate significant climatic shifts, with basin-wide warming, heterogeneous precipitation changes, and declining relative humidity, leading to intensified cold-season drying. Temperature and evapotranspiration showed strong persistence, while precipitation exhibited high variability and periodicities linked to ENSO and East Asian monsoon anomalies. Runoff increased significantly in the mainstream Songhua and Nenjiang basins, especially in autumn, with abrupt changes clustered between 2009 and 2015. The Second Songhua Basin displayed weaker variability, largely influenced by reservoir regulation and land-use change. Attribution analysis confirmed precipitation as a primary driver, with elasticity coefficients exceeding 3 in the Nenjiang Basin during some summers, indicating extreme sensitivity. Evapotranspiration suppressed runoff under high temperatures, while freeze–thaw processes and human interventions became critical in spring and autumn. The aridity index revealed persistent winter deficits and rising spring–autumn drying trends after 2000, posing risks for snowmelt runoff and baseflow sustainability. Overall, runoff evolution reflects a shift from gradual to threshold-triggered regime changes driven by both climate variability and human regulation. These findings provide a basis for adaptive, basin-specific water management and climate resilience strategies in Northeast China.

The Integrated Valuation of Ecosystem Services and Trade-Offs (InVEST) model with the distributed hydrological model Soil and Water Assessment Tool (SWAT) were implemented. The SWAT model quantifies and visualizes water production and groundwater reserves in the Mudanjiang River Basin, employing the groundwater runoff modulus method to calculate groundwater recharge in the basin. This study aims to assess the model’s applicability in cold basins and subsequently analyze groundwater distribution characteristics, water reserves, and the exploitable volume. It serves as a reference for the judicious allocation of groundwater resources and the preservation of the local aquatic ecosystem. The study indicates the following: (1) Utilizing the monthly runoff data from the Mudan River hydrologic station, SWAT simulation and calibration were conducted, yielding a determination coefficient (R²) of 0.75 and a Nash–Sutcliffe efficiency coefficient (NS) of 0.77, thereby satisfying fundamental scientific research criteria. The water yield predicted by the InVEST model aligns closely with the water resources bulletin of the research region. (2) The data from the water production module of the InVEST model indicate that the average annual water production during the research period was 6.725 billion m³, with an average annual water production depth of 148 mm. In 2018, characterized by ample water supply, the water output was at its peak, with a depth of 242 mm. In 2014, the water depth recorded was merely 16 mm. (3) Throughout the study period, the average annual flow of the Mudan River was 4.2 billion m³, whereas the groundwater reserve was 24.13 (10⁸ m³·a⁻¹). In 2013, the maximum groundwater reserve was 38.42 (10⁸ m³·a⁻¹), while the minimum reserve in 2014 was 2.36 (10⁸ m³·a⁻¹), suggesting that the region was predominantly experiencing sustainable exploitation. (4) The mean groundwater runoff modulus is 0.28 L/(s·km²), with a peak annual recharge of 15.4 (10⁸ m³·a⁻¹) in 2013 and a lowest recharge of just 3.2 (10⁸ m³·a⁻¹) in 2011.

In the context of global warming and the intensification of human activities, the change in runoff is also increasing. It is very important to determine the change in runoff for the rational utilization of water resources. In order to determine the influencing factors of runoff change in Muling River, the SWAT model was used in this study to separate different coupling factors and calculate the contribution rate of a single factor to runoff change at the annual scale and quarterly scale, respectively. In the process of calibration, different single rate times were used to analyze the influence of different rate times on the calibration results. The results show that the runoff in the Muling River basin shows a downward trend, the quarterly temperature factor has the greatest influence on the runoff change, which is 50–60%, the annual precipitation has the greatest influence on the runoff change, which is 68%, and the maximum change in the runoff from the reservoir is 42.5% under the change in human activities. In the SWAT-CUP software, the optimal number of calibration for this basin is 500. This research provides a scientific basis for the flow analysis of the Muling River basin.