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Seepage from unlined irrigation canals is a signi ficant source of groundwater recharge for shallow aquifers in many parts of the world, especially in arid and semi-arid regions such as Egypt. This is the case for Ismailia canal, the most important branch canal of the River Nile in Egypt, which suffers seepage losses along its entire length (129.5 km). Groundwater modeling was performed using MODFLOW to determine the effect of lining of four sections of the canal, with a total length of 61 km on the water balance of the underlying unconsolidated porous-medium aquifer and to optimize the locations of the lined sections. The model was developed using existing hydrogeological data from the area and was calibrated using water table data for the period 2004–2013. The simulation results indicated that the optimum locations of lined sections to minimize the seepage losses are located at distances along the canal from 19 to 45 kms, from 70 to 93 km and from 109 to 117 km from the head regulator at km (0.00) near Cairo. The minimum seepage losses, in that case, is equal to 7.3% of the canal total discharge. The modeling also indicated that seepage from the unlined canal provides about 3.5 million m3/day recharge to the underlying aquifer and these seepage losses represent about 21.6% of the canal total discharge. The optimum lining of the canal reduced the recharge to the aquifer by 65% (from 3,426,500 to 1,199,500 m3/day. The discharge from the model.domain (outward the boundaries) and the added recharge to the aquifer storage reduced by 50% from about 4.0 million m3/day to about 2.02 million m3/day between 2016 and 2021.

Egyptian policymakers and researchers have been working to address the challenge of bridging the gap between limited water resources and the growing population’s needs for agricultural and food production. The National Great Project for Lining and Rehabilitation of All Open Canals of the Irrigation Network aims to reduce irrigation water losses through seepage, evaporation, and evapotranspiration. This study evaluated water losses from the Al Maanna canal network in the Assiut governorate, Middle Egypt, using empirical formulas and field ponding methods. The results show the Moleth–Worth formula was more compatible with field measurements, with estimated seepage losses of 2.07 and 2.20 million m3/month, respectively. Moreover, maximum evaporation and evapotranspiration losses were 0.086 and 1.133 million m3/month, respectively. Consequently, total water losses from the Al Maanna canal are estimated to be 3.42 million m3/month, accounting for 13.63% of the total discharge. After canal rehabilitation, evaporation and evapotranspiration losses significantly decreased, while seepage losses were lowered to 0.472 million m3/month, as estimated using the field ponding method. Hence, lining the Al Maanna canal network could reduce water losses by 84%, promoting lining processes that yield significant benefits such as moral, cultural, and environmental benefits. This approach outweighs implementation expenses and ensures a sustainable water supply.

Subtle bedrock depressions called gnammas allow the water in ephemeral pools to maintain contact with bare rock, thus serving as natural rock‐weathering experiments. Following filling by precipitation, evaporation is often assumed to be the sole process of water loss from gnammas. We evaluated this assumption by monitoring evolving stable isotope compositions of gnamma waters hosted in granite of Colorado's Front Range. Surprisingly, we found that a significant fraction of the water was lost by seepage through the underlying bedrock. Seepage dominated, with only 10%–20% loss by evaporation. We propose a conceptual model of gnamma formation in which enhanced weathering of the bedrock beneath the gnamma increases the water holding capacity and permeability of the underlying rock that in turn promotes efficient water loss through seepage and further weathering of the surrounding rock. This model has implications for bare‐rock weathering and hence the evolution of landscapes over geologic timescales. Plain Language Summary Rates and styles of rock weathering influence the evolution of soil, landforms, and climate over geologic timescales. Gnammas are depressions in solid bedrock that periodically fill with rainwater or snowmelt to form ephemeral pools that can provide critical but temporary water sources in arid, bare‐rock surface environments. In contrast to previous assumptions that gnamma water is lost solely by evaporation, our work shows that a significant fraction of the water can be lost by seepage into the underlying rock. These findings suggest a feedback between enhanced seepage into underlying bedrock and enhanced degradation of the surrounding rock that potentially explains the growth and persistence of these unique isolated ecosystems, and informs debates about the role of bare bedrock weathering in landscape evolution. Key Points Water stable isotopes constrain the hydrologic evolution of gnammas Gnammas lose water via seepage through the underlying bedrock, not only by evaporation Seepage may drive a feedback process that enhances bedrock weathering but limits gnamma size evolution

In the water balance of reservoir system, evaporation plays a crucial role particularly so for the reservoir systems of smaller size located in the semi-arid or arid regions. Such regions are most often characterized by significant seepage losses from reservoirs, besides evaporation losses. Usually, in the optimization of a reservoir system, it is a common practice to assume evaporation loss either as some constant value or as negligible. Such assumptions, however, may affect the results of reservoir optimization. This is demonstrated in this study by a case study in the optimal scheduling of Pilavakkal reservoir system in Vaipar basin of Tamilnadu, India. For modeling reservoir losses, many models are available, of which, Penman combination model is most commonly used. In this study, an alternative approach based on Genetic Programming (GP) is proposed. The results of GP and Penman model for both evaporation loss estimation and reservoir scheduling are compared. It is found that while GP and Penman combination model performs equally well for estimating evaporation losses, GP is also able to model seepage losses (or other losses from reservoir) to a much better degree. It is also shown the reservoir scheduling does get influenced based on how the reservoir losses are modeled in the reservoir water balance equation.

Seepage-induced losses of fine particles from the matrix of coarse fraction (i.e., suffusion) and the subsequent collapse of the force transmission structure of the gap-graded soil is a severe threat to the stability of hydraulic structure such as dams. The gap-graded soil element at different locations within such geo-structure suffers different anisotropic stress conditions and flow directions. The influences of both anisotropic stress condition and flow direction on suffusion must be considered in practice, but it remains unclear. This paper presents a three-dimensional coupled CFD-DEM investigation into suffusion considering different anisotropic stress conditions and flow directions in gap-graded granular soils from both macroscopic and microscopic perspectives. It is found that the fine particles in the samples with higher anisotropic stress ratios have larger initial contact anisotropy and friction mobilization, both facilitating the erosion of these participles. For the sample with high initial contact anisotropy, the soil contact fabric is approaching isotropic during suffusion due to the erosion of the fine particles even though the stress anisotropy of the sample is kept. The sample with the major principal stress direction close to the seepage flow direction is prone to be eroded during suffusion, since the seepage forces applied to the particles increase the contact number and contact forces in the flow direction, which enhances the contact anisotropy and stress anisotropy of sample and thus increases the cumulative fine particles loss. It is also found that the contact-based fabric anisotropy variable A can be used to feature the suffusion susceptibility of samples under combined effects of stress anisotropy and flow directions.

In their recent paper in ERL, ‘Egypt’s water budget deficit and suggested mitigation policies for the Grand Ethiopian Renaissance Dam (GERD) filling scenarios,’ Heggy et al (2021 Environ. Res. Lett. 16 074022) paint an alarming picture of the water deficits and economic impacts for Egypt that will occur as a consequence of the filling of the GERD. Their median estimate is that filling the GERD will result in a water deficit in Egypt of ∼31 billion m3 yr−1. They estimate that under a rapid filling of the GERD over 3 yr, the Egyptian economy would lose US$51 billion and 4.74 million jobs, such that in 2024, Gross Domestic Product (GDP) per capita would be 6% lower than under a counterfactual without the GERD. These and other numbers in Heggy et al (2021 Environ. Res. Lett. 16 074022) article are inconsistent with the best scientific and economic knowledge of the Nile Basin and are not a dependable source of information for policy-makers or the general public. In this response to Heggy et al (2021 Environ. Res. Lett. 16 074022) we draw on high quality peer-reviewed literature and appropriate modeling methods to identify and analyze many flaws in their article, which include (a) not accounting for the current storage level in the High Aswan Dam reservoir (b) inappropriately using a mass-balance approach that does not account for the Nile’s hydrology or how water is managed in Egypt, Sudan and Ethiopia; (c) extreme and unfounded assumptions of reservoir seepage losses from the GERD; and (d) calculations of the economic implications for Egypt during the period of reservoir filling which are based on unfounded assumptions. In contrast to Heggy et al (2021 Environ. Res. Lett. 16 074022), robust scientific analysis has demonstrated that, whilst there is a risk of water shortages in Egypt if a severe drought were to occur at the same time as the GERD reservoir is filling, there is minimal risk of additional water shortages in Egypt during the filling period if flows in the Blue Nile are normal or above average. Moreover, the residual risks could be mitigated by effective and collaborative water management, should a drought occur.

This study develops and applies a geospatially driven computational framework to enhance the operational efficiency of irrigation canals, demonstrated through the Kadi branch of the Narmada Main Canal in Gujarat, India. Canal seepage and subsequent waterlogging are major contributors to reduced irrigation efficiency and secondary salinization in command areas. To characterize these processes, multi-temporal Landsat datasets (1990–2024), high-resolution UAV Ortho-mosaics, and ground-based geophysical measurements were analysed to generate long-term vegetation and surface-moisture indices, specifically the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI). A multi-objective optimization model, formulated on the principles of the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), was implemented to identify intervention strategies that minimize seepage losses and waterlogged area while sustaining irrigation deliveries. The analysis revealed recurring moisture persistence and vegetative anomalies adjacent to the canal alignment, confirming progressive seepage patterns. Optimization results indicated that selective lining of high-loss segments combined with targeted sub-surface drainage could achieve approximately 20% reduction in seepage without adversely affecting supply reliability. The study demonstrates how the integration of remote sensing, UAV data, and evolutionary algorithms can support data-driven, cost-effective canal management, contributing to more sustainable and resilient irrigation infrastructure planning in India.

When the collapse column of overburden is disturbed by the working face, the grain loss in the karst collapse column occurs by the dissolution and corrosion of groundwater, thereby inducing the water inrush disaster. The test samples are prepared based on the fractal theory and the Talbol grading theory, and the seepage evolution law of fractured rock in collapse column under triaxial stress is studied, by employing the triaxial seepage test equipment. Besides, the seepage mechanics model of broken rock is established and calculated in the COMSOL Multiphysics, and the water-conducting channel under mass loss condition in the collapse column is further elucidated. The research results indicate that the loss ratio of mass is inversely proportional to the Talbol power index, and grain mass loss rate increases with the decrease of the Talbol power index. During the infiltration process, the evolution of pore structure is related with grain size distribution. With the increase of the Talbol power index, the overall porosity increases. Grain loss is an internal factor in seepage loss stability. Flow speed is accelerating, and seepage pathways are communicated with each other to induce the water inrush disaster.

The Grand Ethiopian Renaissance Dam (GERD) filling and operation is a highly sensitive issue for Egypt and Sudan. A recently accepted manuscript by Heggy et al (2021 Environ. Res. Lett. 16 074022) assessed the water deficit for Egypt based on different scenarios for the first filling of GERD lake and estimated 31 billion cubic meters per year under a 3 year filling scenario. We would like to present grossly mischaracterized assumptions, inaccurate data, and controversial conclusions found in this accepted manuscript through this rebuttal. Although the accepted manuscript does not include any new analysis of the River Nile Hydrology, the results of previous substantive studies were misinterpreted or ignored. Moreover, we have serious concerns about the basic hydrological assumptions that are the basis for the economic impacts and the potential loss of the Egyptian agricultural lands. The main methodological flaws of concerns are (a) how the deficit is calculated, losses from GERD, especially the evaporation losses that contradicts several previous studies (e.g. Wheeler et al 2016 Water Int. 41 611–34; Eldardiry and Hossain 2020 J. Hydrol. 125708; Wheeler et al 2020 Nat. Commun. 11 1–9); (b) neglecting the normal role of High Aswan Dam (HAD) reservoir and directly linking the deficit of the water budget to an immediate loss of agricultural lands with all other associated exaggerated economic impacts estimates; (c) including highly exaggerated seepage losses from the GERD lake; (d) neglecting the updated situation of Aswan High Dam reservoir levels and the GERD’s infrastructure itself, and (e) quantifying the impacts of potential changes of water level on HAD reservoir on the Nubian aquifer. We herein present a direct fact-checking approach including the studies cited in the accepted manuscript. We believe that this critical comment paper can serve as a basis for defending scientific integrity and contributes to cooperation and peace in the region.

Canal lining is customarily used to raise water-use effectiveness and reduce seepage loss. The major water losses in an irrigation channel are due to leakage and evaporation. The Egyptian General Integrated Management for Water Resources and Irrigation introduced a proposal for lining the Al-Hagar canal based on these losses. This study investigates the effect of lining in the Al-Hagar canal on flow characteristics, and compares the canal before and after introducing the lining. Additionally, it discusses the most common type of water loss, namely, losses due to seepage. Fieldwork was conducted on the Al-Hagar canal, Al-Saff Center, South of Helwan city, Egypt. The result revealed that the discharge of the canal after the lining is approximately 1.362-1.573 times greater than that of the un-lined section. Water losses in the Al-Hagar canal were 38.736% when un-lined but decreased to 29.253% when lined. The conveyance effectiveness in the un-lined canal, which is approximately 61.26%, increased to 70.75% when the entire canal is lined, which means a 9.483% improvement of conveyance. New relations were introduced using Artificial Neural Network and Gene Expression Programming to forecast the seepage loss in the lined and the un-lined canal as a function of Manning's coefficient, Froude number and hydraulic radius. The consequences were better using the GEP program than using ANN for the lined and the un-lined canals. The value of the determination coefficient was 0.98, Correlation factor was 0.99, and the RMSE was 0.0017 for lined canals and the value of determination coefficient was 1, Correlation factor was 1, and the RMSE was 0.0003 for un-lined canals.