The vadose zone plays a significant role during artificial recharge via the infiltration basin. Its thickness, lithology, heterogeneity, among others greatly affect the recharge efficiency. The main objective of this research is to establish the role of the vadose zone and the impacts of infiltration basin features and vadose zone factors on water distributions. In this work, an ideal conceptual model was considered, and mathematical models were built using HYDRUS (2D/3D) software package version 2.05. A total of 138 numerical experiments were implemented under seven types of experimental conditions. The experimental data were analyzed with the aid of correlation and regression analysis. The results showed that infiltration basin features and vadose zone factors had various impacts on water distribution, low permeability formation had various effects on evaporation depending on its depth, and there were consistent, similar, or different variation trends between infiltration and recharge. In conclusion, it is recommended that when the vadose zones are to be chosen as an infiltration basin site, the trade-off among the infiltration, recharge, storage, and evaporation should be seriously considered. This paper may contribute to a better understanding of the vadose zone as a buffer zone for artificial recharge.

In semi-distributed hydrologic models, it is difficult to account for the impacts of wetlands on hydrologic processes, as they are based on lumped, subbasin-scale wetland concepts. It is a challenge to incorporate the influences of individual small wetlands into watershed-scale models by using lumped parameterization. The objective of this study was to improve watershed-scale hydrologic modeling by taking into account real wetland features during the wetland parameterization. To achieve this objective, a joint modeling framework was proposed to couple a surface delineation algorithm with a semi-distributed hydrologic model and then applied to the Upper Turtle River watershed in North Dakota, USA. The delineation algorithm identified the topographic properties of wetlands, which were further utilized for wetland parameterization. A nonlinear area–storage relationship was determined and used in the estimation of the wetland-related parameters. The results demonstrated that the new joint modeling approach effectively avoided misestimating the wetland-related parameters by accounting for real topographic characteristics (e.g., storage, ponding area, and contributing area) of identified wetlands and their influences, and provided improved modeling of the hydrologic processes in such a wetland-dominated watershed.

Climate change and land use/cover change (LUCC) are two major factors that alter hydrological processes. The upper reaches of the Tarim River, situated in the northwest region of China, experience a dry and less rainy climate and are significantly influenced by human activities. This study comprehensively assessed the impacts of individual and combined climate changes and LUCCs on streamflow. Three general circulation models (GCMs) were utilized to predict future climate changes under three shared socioeconomic pathways (SSP119, SSP245, and SSP585). Cellular Automata–Markov (CA–Markov) was employed to predict future LUCC under three scenarios (i.e., ecological protection, historical trend, and farmland development). Streamflow for the period 2021–2050 was simulated using the calibrated MIKE SHE model with multiple scenarios. The results showed that from 2021 to 2050, increments in both average annual precipitation and average annual temperature under the three SSPs were predicted to lead to an increased streamflow. In comparison to the conditions observed in 2000, under three LUCC scenarios for 2030, the grassland area decreased by 1.04% to 1.21%, while the farmland area increased by 1.97% to 2.26%, resulting in reduced streamflow. The related changes analysis indicated that the variation in streamflow during winter is most significant, followed by spring. The study predicted that climate change would increase streamflow, while LUCC would decrease it. Due to the greater impact of LUCC, considering the combined effect of both factors, runoff would decrease. The contribution analysis indicated that climate change contributed between −7.16% and −18.66%, while LUCC contributed between 107.16% and 118.66%.

The Jinan spring basin is located in the karst area of northern China, where springs serve as important sources of water supply. Several studies on spring protection and water supply have been carried out, and scholars have developed some laws on local groundwater flow dynamic and characteristics of aquifer structures. Unfortunately, there is a lack of detailed research on preferential recharge zones, which are the main recharge pathways of springs. Therefore, this research focuses on identifying preferential recharge zones based on the correlation between the spring level and precipitation. The results show that when precipitation is more intense or lasts longer, there is a stronger correlation between spring level and precipitation. It has been established that the precipitation at Donghongmiao station has the closest relationship with the dynamic of Baotu spring, which is found to be the most significant contribution to spring preservation. Two potential preferential recharge zones in the Jinan spring basin are detected through correlation analysis and geological exploration data. These findings support spring protection and water supply projects in karst regions.