Advances in Watershed Hydro-Environment Simulation: From Process Mechanisms to Sustainable Management

1. Introduction

Groundwater (GW) and surface water (SW), two crucial factors in the water cycle, are often viewed in an artificially segmented way within scientific research, resulting in insufficient interactions between them, especially in areas in which frequent SW–GW interactions occur [1]. At the basin scale, precipitation infiltration, GW discharge to the stream, and significant changes in SW or GW, driven by natural and anthropogenic factors, have led to complex transformations of SW and GW in the basin [2]. In water resource utilization and water ecology protection, accurate simulation and prediction of SW and GW in the basin can provide a precise basis for water resource scheduling, as well as a hydrological framework for ecosystem maintenance. On the river section scale, the local SW–GW interaction needs to be accurately simulated and predicted, the results of which will be of guiding significance for the evolution of local river channels, the design of water conservation projects, and the clear establishment of water environment remediation programs [3].

With improvements in numerical simulation capability and the rapid development of machine learning, opportunities for SW and GW simulation are increasingly available [4]. Variability in basin land cover, climate change [5], heterogeneity and the time-varying characteristics of riverbed sediments and riparian zones, as well as human activities such as cross-basin water transfer, water conservation project storage, artificial GW recharge and the ecological recharge of rivers and channels, has led to significant changes in SW and GW conditions, which have made it difficult to simulate SW and GW [6]. Researchers expect to obtain new results on the changes in SW and GW regimes in the basin, as well as information on the driving mechanisms, the processes of SW–GW interaction under climate change, and the impacts of riverbed topography and hydraulic engineering on SW–GW interactions in the river channel [7]. Furthermore, they can expect to develop a renewed understanding of SW–GW interactions, facilitated by the use of data from gravity satellites and other remotely sensed data [8], as well as furthering developing SW and GW research, new numerical simulations and new machine learning algorithms [9].

Therefore, this Special Issue, “Advances in Surface Water and Groundwater Simulation in River Basin”, aims to foster a more thorough understanding of the application value of simulation methods for SW and GW and the interaction between them. This is of great significance for improving the safety of water resources, the hydro-environment and hydro-ecology. Since the call for papers was announced in October 2024, eight original papers were accepted for publication after a rigorous peer-review process. To facilitate understanding, in this Special Issue, we summarize the highlights of the published papers below.

2. An Overview of Published Articles

This Special Issue presents a collection of cutting-edge research that delves into the multi-scale processes of hydro-environmental systems, from aquifers to reservoirs, and from riverine flows to internal waves in lakes. By integrating isotopic tracing, numerical modeling, machine learning, and physical mechanism analysis, the studies herein provide innovative methodologies and critical insights for understanding complex hydrological systems and addressing pressing challenges within water resource management.

2.1. GW Systems: From Genesis to Active Management

Research on GW systems has advanced beyond mere characterization to unravel formation mechanisms and underpin proactive management. In the Nanmiao Emergency Groundwater Source Area, China, List of Contribution 1 employed hydrochemical and isotopic analyses to reveal that atmospheric precipitation is the primary recharge source, with GW chemistry controlled by silicate weathering and cation exchange, outlining a deep-circulation hydrogeochemical process of the area. In Punjab, Pakistan, List of Contribution 2 demonstrated how MODFLOW can optimize a large-scale Managed Aquifer Recharge (MAR) strategy, proving its effectiveness in replenishing the aquifer and boosting water security to support intensive agricultural systems. Collectively, these studies chart a clear path from understanding natural GW genesis to implementing active management and engineered replenishment.

2.2. SW Simulation: Intelligent Algorithms Fused with Physical Constraints

In SW simulation, particularly in reservoir operation, the integration of machine learning with physical principles is pioneering a new paradigm. List of Contribution 3 developed a Physics-Constrained Random Forest (PC-RF) model for cascade reservoir outflow simulation, effectively eliminating unrealistic outcomes like negative outflows. Their model significantly enhanced prediction accuracy (with R² increased by 37.13%) while providing interpretable insights into key operational drivers, marking a critical step towards physically consistent data-driven modeling in hydrology.

2.3. Hydrological and Ecological Impacts of Watershed Engineering

The impacts of anthropogenic engineering on watershed hydrology and its regulation are another key focus. In the Hui River, China, List of Contribution 4 employed the MIKE21 model to quantify the hydrological impacts of a waterway regulation project. They revealed that while navigation conditions were enhanced, the project also induced water level drawdown, flow velocity redistribution, and localized bank erosion risk, leading to proposed mitigation strategies like ecological revetments. Furthermore, List of Contribution 5, focusing on karst aquifers, highlighted how precipitation characteristics (intensity and duration) significantly influence the estimation of karst water storage variation by altering GW level dynamics and spring recession curves. This work underscores the importance of accurately characterizing natural recharge processes in the context of water resource assessment.

2.4. Aquatic Physical Processes in Response to Climate Variability

The response of complex aquatic physical processes to climate forcing is crucial for predicting ecosystem behavior. In Lake Biwa, Japan, List of Contribution 6 employed numerical experiments to reveal the profound effects of interannual climate variability on internal waves. Their findings show that higher air temperatures intensify stratification and enhance near-inertial internal waves in the thermocline, whereas increased wind speeds amplify wave energy across all layers. These insights are vital for projecting material transport processes and energy budgets in stratified aquatic ecosystems under future projected climate scenarios.

3. Conclusions

This Special Issue published multidisciplinary scholarly works focusing on the coupling mechanism, system behavior, the observation system and simulation techniques on the SW and GW in a river basin within a changing environment. Grounded on the previous gaps reported above, there are several potential directions of research that could be implemented to advance the simulation of SW and GW. This Special Issue identifies the following research directions:

(1)

Multi-Process Coupling: There is an urgent need to advance the coupled simulation of hydrodynamic, water quality, and ecological processes, as well as the systematic analysis of SW–GW interactions.

(2)

Model Fusion: The complementary strengths of physical models and data-driven approaches (as exemplified by the PC-RF model) represent a significant future direction.

(3)

Uncertainty Management: Quantifying and mitigating uncertainties—arising from karst media heterogeneity, isotopic fractionation effects, or complex reservoir operation rules—remains critical to improving simulation reliability.

(4)

From Science to Decision-Support: Research findings are increasingly being translated into management practices, as illustrated by the evaluation of MAR projects, the optimization of ecological water replenishment strategies, and the insights supporting the regulation of engineering impacts and lake management.

Looking ahead, we encourage further exploration into the deep integration of artificial intelligence and physical models, the establishment of multi-scale validation frameworks integrated with multi-source data assimilation (e.g., remote sensing, ecohydrological flux observations), and the enhancement of interdisciplinary collaboration to address complex watershed challenges. The innovative methods and profound insights contained in this Special Issue will significantly contribute to advancing watershed water security, ecological protection, and sustainable development.