Journal of Hydrologic Engineering

Bifurcated fractures are the basic units of fracture networks. In this paper, a bifurcated fracture model is designed using Fluent software to characterize the fluid flow in a fracture network. The characterization of water flow was investigated by changing the geometrical properties, namely, joint roughness coefficient ($JRC$), angle between two outlet fractures ($\theta$), and the mechanical aperture ($e$) of either outlet fracture. The effect of Reynolds numbers (Re), hydraulic gradient ($J$), flow rate ($Q$), flow velocity ($V$), critical Reynolds numbers (${\mathrm{Re}}_{\mathrm{c}}$), and hydraulic aperture ($E$) on the flow were systematically analyzed. The results showed that (1) given the increase in roughness and $\theta$, the flow ratio in the branches increases nonlinearly, whereas the aperture ratio showed an opposite characteristic; (2) the deflected flow caused by the variation in $\theta$ is mainly attributed to inertial forces, whereas that caused by the change in $JRC$ and the aperture ratio is due to the combination of the viscous and inertial forces; (3) when Re was small, the ratio of $E·e^{-\mathit{1}}$ was slightly lower than 1, and with an increase in Re, the $E·e^{-\mathit{1}}$ strength of the outlet fractures was weak; and (4) the aperture is the most important parameter affecting the deflected flow, followed by $\theta$ and $JRC$.

Baseflow is the portion of streamflow that comes from groundwater and subsurface sources. Although baseflow is essential for sustaining streams during low flow and drought periods, we have little information about how and why it has changed over large regions of the continental United States. The objective of this study was to evaluate how changes in the climate system have affected observed monthly baseflow records at 3,283 USGS gauges over the last 30 years (1989–2019). We developed a statistical modeling framework to determine the relationship between monthly baseflow and monthly climate predictors (i.e., precipitation, temperature, and antecedent wetness). Overall, we found that baseflow trends and the factors influencing them vary by region and month. In the US Northeast, increases were detected earlier in the year (February and March) and in the summer (May and June), and were likely due to increasing precipitation, warmer temperature, and subsequent changes in snowmelt. Increasing baseflow in the US Pacific Northwest and Midwest were associated with increases in precipitation and antecedent wetness throughout the year. Decreasing trends were located in the US Southeast and Southwest. Baseflow trends in the US Southeast were only detected in March, possibly as a result of decreased precipitation during the spring. On the other hand, decreases in baseflow in the Central Southwestern United States occurred throughout the year. These trends were associated with a lack of precipitation and increases in temperature. Finally, we examined the relationship between monthly baseflow trends and changes in total water storage using monthly Gravity Recovery and Climate Experiment mascon products from the Jet Propulsion Laboratory. In this study, trends in total water storage were strongly associated with baseflow trends across the United States. The spatial and temporal variability in baseflow response to climate reported here can aid water managers in adapting to future climate change.

During in situ groundwater remediation, reactions occur in a narrow reaction front in which the amendment and contaminant are close enough to mix. Active spreading, in which injection or extraction wells create spatially variable velocity fields, can be used to increase the surface area of the reaction front, thereby enhancing reaction. This study used four active spreading flow fields that are building blocks to more complex remediation hydraulics to evaluate how the flow field and the plume position control contaminant degradation in both homogeneous and heterogeneous aquifers. At the plume scale, reaction depended on mechanical dispersion across the reaction front, which is proportional to both the local velocity and the local contaminant concentration gradient. Mechanical dispersion and, consequently, the amount of degradation, was highest when the reaction front was perpendicular to the local velocity, producing a high local dispersion coefficient. This effect was amplified where flow was diverging due to sharpening of the concentration gradient.

To predict runoff under different annual precipitation and reflect the impact of annual precipitation and its inner-annual distribution on the runoff process, the soil and water assessment tool (SWAT) model is combined with the stochastic simulation of precipitation based on the torrential rain analysis. Taking the watershed above Wangkuai Reservoir in China as an example, the SWAT model is constructed. and the stochastic simulation models of precipitation under three annual precipitation states are established. Then, based on the torrential rain analysis, five precipitation scenarios with annual precipitation of 300, 600, and 900 mm are assumed, and the daily precipitation process of each scenario is generated as the input of the SWAT model. The results are as follows: the SWAT model has a very good performance for monthly runoff simulation; the maximum monthly runoffs of the five precipitation scenarios are 5.99, 7.09, 9.14, 17.48, and $23.71{\mathrm{m}}^3/\mathrm{s}$, respectively, and the annual runoffs are 2.24, 3.02, 3.30, 4.75, and $5.08{\mathrm{m}}^3/\mathrm{s}$, respectively. When the annual precipitation is about 600 mm, the influence of precipitation inner-annual distribution on the monthly runoff process is mainly reflected in July to October. When the annual precipitation is about 900 mm, the influence is mainly reflected in August. This study provides a new idea for runoff prediction and provides reference for the study of the rainfall–runoff uncertainty relationship. Moreover, the improved precipitation stochastic simulation and its combination with the SWAT model can be applied to the study of other basins for further discovery.