The Miocene Fluvial Moghra Aquifer in the North Western Desert of Egypt
The study integrates stable isotope analyses with aeromagnetic and hydrogeological datasets to accomplish the following: (1) define the primary source(s) of recharge to the Moghra aquifer, (2) assess aquifer connectivity with the Nile River aquifer, and (3) investigate the vertical connectivity of the Moghra aquifer with the underlying Nubian Aquifer System (NAS) through subvertical faults.
The findings reveal (1) significant heterogeneity in groundwater isotopic compositions (Group A: δ18O: 1.1–13.8 ‰; δD: 4.6–73.5 ‰, B: δ18O:−0.99 to 0.85; δD: −7.58 to 4.38 ‰; and C: δ18O:−1.1 to −3.4; δD: − 6.3 to −18.2 ‰) indicative of variability in recharge sources. (2) Groundwater compositions west (up to 30 km) of the Nile River (Group A) resemble enriched modern Nile waters following the Aswan High Dam (AHD) construction that give way further west to relatively depleted groundwater (Group B) resembling historical pre-AHD Nile water compositions. (3) Further west from Group B depleted Group C samples occur along intersections of multiple fault systems (NW and NE-oriented faults) interpreted as mixtures of rising highly-depleted paleo Nubian Aquifer System (NAS) waters and pre-AHD Nile waters. (4) The advocated structural control is reported in similar settings in Egypt, suggesting that intersections of multiple fault systems provide regional connections between deep and shallow aquifers in northeast Africa, recharge overlying shallow aquifers, and should be considered in groundwater management scenarios.
Zhengzhou section of the Jialu River.
In this study, the Zhengzhou section of the Jialu River was chosen to construct a watershed river network graph model based on graph theory, and this model could describe water volume distribution at diversion nodes and water balance relationships, which aimed to maximize the ecological landscape area. Considering residential aggregation along riverbanks, a waterfront accessibility matrix was used to derive an optimized water system connectivity scheme based on flow allocation at diversion nodes.
In the optimized scheme, flow distribution from 5 diversion nodes to downstream river sections ranged from 0.2 to 0.8, resulting in significant changes in the landscape area of 20 river segments. The ecological landscape area under the optimal scenario was 31.06 km2, which was 0.03 km2 more than the worst-case scenario. The water system connectivity allocation remained consistent before and after considering waterfront accessibility, and the optimal weighted landscape area was 12.69 km2 with waterfront accessibility in mind. Considering the accessibility of waterfront areas, the center of gravity of the water system connectivity scheme shad undergone a significant change before and after. The research results could provide theoretical support for the construction of regional ecological civilization.
Egypt is a country located in northeastern Africa.
The research evaluated the random forest (RF) and extreme gradient boosting (XGB) as single models and the models' hybrid to predict the ETo for the baseline and future (2015–2099) period from Shared Socioeconomic Pathways (SSP1–26, SSP2–45 and SSP5–85) based on 18 GCMs models.
The hybrid model has performed better than single models; compared RF and XGB to RF-XGB, the RMSE values were decreased in all zones esepically in zone 3 by 16.2 %, these results indicate that the highest performances of all models are observed in the middle and south Egypt, which exhibit the strongest correlation between temperature and ETo. For the SSP5–8.5 scenario, the ETo increased over the years for all zones; the ETo will increase by 4.38 %,3.71 %, 4.27 %, 2.16 %, 3.26 %, 1.35 %, 5.22 % at the year 2099 compared to the year 2015 for zone 1, 2, 3, 4, 5, 6 and 7 respectively. The Tmin and Tmax are the most critical factors that affect the ETo in all zones in the baseline and future scenarios. This study provides important insights into applying machine learning models to estimate ETo and its implications for future water management strategies. Such models hold promise for significantly enhancing regional agricultural water-resource planning and management.
The Yellow River Basin (a water-deficient region) in China.
The redistribution of virtual water through trade holds potential to enhance water security in the Yellow River Basin. We explored a virtual water tri-circulation model at the city level to mitigate water stress in the Yellow River Basin. The tri-circulation model includes internal, external and international virtual water flows. This research investigated the heterogeneity of virtual water trade between upstream and downstream regions, identified key regions and sectors to facilitate physical water redistribution and enhance regional cooperation.
This study revealed that the Yellow River Basin received virtual water amounting to 8.40 % of its total virtual water consumption, with external circulation being the key circulation. Upstream regions primarily exported water resources to downstream regions and developed regions outside through agricultural trade, while downstream regions received water from upstream regions and underdeveloped regions outside through trade in agri-food products and other service industries. International circulation exported virtual water through water-intensive agricultural products, contributing to increased local environmental burden. Increased attention should be paid to virtual water transfers of the external circulation, implementing compensation strategies, and fostering technical interaction between upstream and downstream regions, and safeguarding upstream agricultural and ecological water to promote the sustainable development of the Yellow River Basin.
Lake Velence.
Soda lakes are extreme habitats whose special hydrochemical characteristics can partly be explained by groundwater inflow. The relationship between groundwater and Lake Velence has never been properly investigated. A significant decrease in the lake’s level in recent years urged an evaluation of the components of the lake’s water budget, including groundwater as well. A 3D transient numerical groundwater flow simulation, using Visual MODFLOW, was performed between 1990 and 2021 to evaluate the lake’s relationship with groundwater and quantify the groundwater discharge into the lake. To assess future lake level changes until 2050, six lake level simulations were run based on three different regional climate models and two global warming scenarios (RCP2.6 and RCP8.5).
Our results showed that groundwater inflow accounts for up to 12 % of the total annual inflow into Lake Velence. It has been numerically shown that precipitation and evaporation are the primary drivers of lake level changes, meaning that the variation of these two parameters will impact the lake’s future. As for the future lake level changes, the RCP2.6 scenario resulted in an increase of 11 cm, while the RCP8.5 scenario led to a decrease of 30 cm compared to the observed annual average lake level until 2050. Our results emphasize the importance of integrating soda lakes into topography-driven groundwater flow systems to develop climate change adaptation strategies.
Yamuna River (Delhi), India.
The anthropogenic activities within the vicinity of the floodplain reduce the river's margin and subsequently alter the magnitude of the river's flow. The encroachment of riverbeds leads to waterlogging and flooding in urban areas, thereby causing damage to property, human life, etc. It necessitates a comprehensive study of the floodplain and changes in its proximity such as encroachment of floodplains to carry out any further activities with certainty. This study employs a two-dimensional model to simulate the Yamuna River's (YR) hydrodynamic characteristics, focusing on India's Delhi region.
Simulated flood flows are employed to evaluate floods of once in 10, 20, 25, and 30-year return periods using the flood frequency analysis for 1951–2013. The model validation results indicated that the model could mimic the flood depth in YR. Simulation results revealed that the floodplain's encroachment had increased the severity of the floods. The increase in the extremeness of flooding events, i.e., from once in a 10-year return period to a 30-year return period event, is expected to increase the areas at risk of floods by 12 %. The model also offers a potential platform for evaluating other alternatives, such as further encroachment, for a business-as-usual scenario or for restoring the Yamuna floodplains. With such a comprehensive perspective, floodplains' role enhances river basin resilience to climate and anthropogenic changes and increases flood safety.
Siwa Oasis is located very far (800 km) from the main water resources (Nile River) of Egypt and the people in the study area mainly rely on groundwater for all purposes
The deterioration of drinking water quality and the accumulation of potentially toxic elements (PTEs) in water at high levels in arid regions such as Siwa Oasis in Egypt can pose significant risks to humans and living organisms. The methodology of study involved performing geochemical modeling, contamination source detection, and optimizing a new model using machine learning model for prediction of integrated weight water quality index (IWQI), Health risk indices (HI and HQ) regarding oral and dermal exposure to potentially toxic elements (PTEs).
The key findings of this research showed that the Nubian sandstone aquifer (NSSA) is characterized mainly by mixed Ca-Mg-Cl/SO4 fresh water type and influenced by silicate weathering. The nitrates sources fell between atmospheric inputs in the case of NSSA, soil nitrogen in Tertiary carbonate aquifer (TCA), springs, and drains, while sewage water strongly affects the lakes. The IWQI values demonstrated that water resources in the deep aquifer (NSSA) is appropriate for drinking with ranking of quality range from medium to excellent quality (IWQI < 150). The shallow aquifer (TCA) is suitable for drinking in the south east of the Oasis only with intermediate quality ranking (100 < IWQI < 150), while the poor water quality needs further treatment in the western side of Siwa Oasis. The non-carcinogenic risks evaluation revealed the vulnerability of child and adult to oral exposure of PTEs in the west and center of the investigated area. The feed forward back propagation neural network (FFBP-NN) model was a powerful tool for predicting IWQI and HI, where the relationship between the actual and predicted value had R2 greater than 0.95 and mean square error (MSE) range from 5.4E-05–0.66, root mean square error (RMSE) between 0.006 and 0.81, and relative square error (RSE) between 0.001 and 2.4 E-05.