Journal of Hydro-environment Research最新文献

Due to climate change, the frequency and duration of meteorological drought have increased. In addition, local water supply capacity has not met water demand in many regions, which will eventually lead to serious water shortages. To mitigate the effects of drought on sustainable water use, it is necessary to understand how climate change affects regional water supply capacity and drought risk. To this end, this study evaluated the drought response capacity of regional water supply systems and assessed the comprehensive drought risk in terms of drought hazard, vulnerability, and response capacity. To avoid subjectivity in risk analysis, structural equation modeling was used to select primary indicators and probability and statistical methods were used to assign weights to the indicators. The changes in drought risk in different climate change scenarios were assessed using sensitivity analyses. The overall results indicate that the future drought risks in Gyeonggi, Gyeongsang, Chungcheong, Jeolla, and Gangwon are 18, 12, 13, 9, and 10% higher, respectively, than the current risk level. The sensitivity analyses showed that Jinju in Gyeongsang province, which has a high drought response capacity, had the largest decreasing rate in drought risk. The quantified changes in drought risk under future climate change scenarios will be useful for identifying areas with a high drought risk and making decisions about drought mitigation under climate change.

With the acceleration of global climate change and urbanization, the frequency and impact of flood disasters are increasing year by year, making flood emergency management increasingly crucial for safeguarding people’s lives, property, and societal stability. To enhance the accuracy of river flow prediction, this study employs an Improved Gray Wolf Optimization Algorithm (IGWO) to optimize parameters of the Long Short-Term Memory Network (LSTM) model. Experimental results demonstrate that the proposed algorithm significantly improves the accuracy of river flow prediction, achieving higher precision and better generalization compared to traditional machine learning algorithms. This method provides more reliable data support for flood warning systems, aiding in the accurate prediction of flood occurrence timing and intensity, thereby providing scientific basis for flood prevention and mitigation efforts. Moreover, this approach supports hydro-logical research, enhancing understanding of river water cycle processes and ecosystem changes.

A number of viscosity and flow curve models can be used to numerically investigate the non-Newtonian behavior of fluids. Although particle size, grain size distribution and concentration play a crucial role in determining the viscosity and flow behavior of suspensions and colloidal systems, they are either ignored or considered indirectly in almost all models. We present a mathematical extension of the widely used Cross flow curve model to account for the effect of concentration and particle size in modeling viscosity and flow curves. In particular, this study takes into account a variable total number of individual particles in unit volume, which is assumed to be constant in other models. The proposed extension allows the flow curve to model suspensions that are typically shear-thinning but can also be Newtonian, or shear-thickening for at different shear rates and concentrations. These considerations provide insight into studying and designing suspensions, colloidal systems, and other complex fluid–solid interactions.

As demands for river recreational activities increases, assessing their safety has become essential to prevent accidents. The hydraulic conditions of the river critically influence the safety of in-water activities, such as sailing, paddling, and boating. Localized hazardous areas can emerge due to the spatial variability of hydraulic phenomena. This potential risk necessitates providing information about safe zones. Therefore, this study proposes a spatial river recreational index (SRRI) to assess the safety of river recreational activities over river spaces based on hydraulic factors. We reproduce the spatial distribution of the hydraulic parameters under various discharge conditions using a 3D hydrodynamic model and then estimate the SRRI by integrating all membership degrees and weights of these parameters using fuzzy synthetic evaluation (FSE). The application of the SRRI in the confluence of the Nakdong-Guemho River, South Korea, reveals that each hydraulic parameter contributes differently to safety levels, depending on discharge and morphological conditions. Specifically, the flow direction substantially decreases safety near the river confluence, whereas the water depth plays an important role in the meandering reach of the Nakdong River. Under high-flow conditions, velocity becomes a critical factor, especially for nonpowered activities (sailing and paddling/wading). The SRRI indicates that sailing is unsafe in the main flow zone and near the river confluence due to high sensitivity to discharge changes. In contrast, paddling/wading and leisure boating are less sensitive to discharge changes, allowing these activities to be partly allowable even under high-flow conditions, except in the deep-water zones of meandering reach. These results suggest that the SRRI can assist water recreational activity users in safely engaging in river recreational activities by providing spatial safety information based on various hydraulic conditions.

Numerical simulations for a large river confluence were conducted to comprehend the influences of three factors: density difference, discharge ratio, and wind shear on tributary flow dispersion. The present study focused on the confluence channel of the Nakdong River and the Yangsan Stream in South Korea, with simulation conditions selected based on realistic conditions. Numerical results revealed that tributary flow can disperse upstream under high discharge ratio conditions, which becomes stronger with density stratification. In particular, when the tributary flow is denser than the mainstream, bathymetry around the junction determines the flowing direction of the density current. Thus, understanding tributary flow dispersion under varying conditions is vital due to its influence not only downstream but also upstream of the confluence. Additionally, wind shear impact on the mixing between mainstream and tributary flow is notable but less significant than density difference or discharge ratio.