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The hydrological budget is one of the fundamental tools for the sustainable management of water resources. In the last decades, the knowledge of the distribution of freshwater resources in space and time is becoming of great concern due to the growing pressure related to increasing population, water pollution, and climate change. Furthermore, in the scope of hydrological balance, the estimation of aquifer assumes particular concern in Italy. In fact, more than 80% of water withdrawal for domestic and drinkable use is derived from groundwater. In this context, the Italian Institute for Environmental Protection and Research (ISPRA) has developed a mathematical model for estimating the hydrological budget components at a national and macro-regional scale called BIGBANG. The aquifer recharge is estimated as a percentage of the monthly soil water surplus by the potential infiltration coefficient defined as a function of the permeability of the hydrogeological complexes beneath the soil layer. In this paper, a comparison highlighting the differences between the estimations of the long-term annual average of two of the main hydrological budget components, aquifer recharge and surface runoff, at national and sub-national levels, is carried out. The estimations are based on the new and more detailed Permeability Map of Italy produced by ISPRA and on the old map of the hydrogeological complexes currently used at national level used so far in the BIGBANG budget model.

Severe seepage presents a significant challenge to the sustainable management of water resources, and a lack of seepage data from the upper, middle, and lower reaches of the Hotan River hinders effective resource management. This study assessed the water infiltration rate in the riverbed using the double-ring method and evaluated the performance of four commonly used infiltration models. Results showed that infiltration rates were highest in the upper section, with permeability decreasing towards the banks. Water consumption, seepage volume, and seepage per unit river length decreased from upstream to downstream. Specifically, seepage volumes were greatest in the upstream section, followed by midstream and downstream. The seepage rate per unit riverbed was highest in the upstream section, followed by the midstream, and lowest in the downstream section. The mean sediment volume fractal dimension was 1.34, positively correlated with sand content, while higher clay and silt content resulted in finer textures and smaller fractal dimensions. These findings fill critical gaps in understanding water infiltration patterns and sediment characteristics in the Hotan River basin, providing essential data for water resource management and ecological protection. Among the models tested, the Kostiakov equation outperformed the Philip, Green-Ampt and Horton models in terms of accuracy and applicability.

Egypt’s limited water resources, rapid population growth, and climate change are increasing the gap between water demand and supply. Meanwhile, significant amounts of rain fall in some regions in Egypt during specific storm events, which in some cases, lead to disasters like flash floods and inundations. Rainwater harvesting (RWH) can be considered as a sustainable promising solution to water shortage and inundation problems. In this work, the feasibility of RWH for urban areas was assessed over 22 cities throughout Egypt. Results show that the annual volume of rainwater harvested can reach 142.5 MCM in the considered cities, provided that all rain falling on the urban areas is collected. High potential of rainfall harvesting was found for cities that located on the North Coast, e.g., the potential water saving from the share of RWH in Alexandria can satisfy around 12% of its future supplementary domestic water needs. In contrast, rainfall over the cities located on the middle and the south of the country is insignificant to be harvested. A case study for the 5th settlement region in Cairo was discussed in terms of groundwater recharge and surface runoff estimation for two conditions: No–RWH and RWH systems by implementing recharge wells to store rainwater into the aquifer. Land cover classification maps of urban areas were created by using the ARCGIS software to estimate equivalent infiltration coefficients. The results demonstrate that the implementation of such RWH system has a significant impact on the regional water cycle, where the effective infiltration coefficient increased from 10% (No–RWH) to 75% (RWH) in the case study. Accordingly, the runoff coefficient decreased in the case study from 0.8 (No–RWH) to 0.15 (RWH), and the volume of runoff decreased in the case of RWH by around 82% lower than that of the No–RWH condition. Thus, direct infiltration of RWH into an aquifer can play an important role in sound water management for urban environments, as this may lead to a significant reduction in risks of flooding and expenses of municipal drainage systems installation and operation.

Muddy water irrigation, an effective water-saving irrigation method, has been widely used in the Yellow River Basin in China. To investigate the effect of sand content on water infiltration and dense layer formation under one-dimensional vertical infiltration of muddy water, muddy water infiltration experiments were performed in the laboratory, and five sand contents of muddy water (5=0%, 3%, 6%, 9%, and 12%) were used. Models were established to describe the relationship between the cumulative infiltration amount [I(t)] and the infiltration duration (t); the relationship among the migration distance of the wetting front (Z), S, and t; the thickness of the sedimentary layer [H(t)]; and the relationship between S and t. The results revealed that I(t) and Z decreased significantly with the increase of sand contents, while H(t) increased significantly with the increase of sand contents. I(t) and Z were in the range of 7 cm and 20 cm for each treatment, respectively. The variation in I(t) with t fitted Kostiakov and Philip models, and the coefficients of determination were all greater than 0.99. With the increase in 5, the infiltration coefficient gradually decreased, the infiltration index gradually increased, and the sorptivity gradually decreased. The particle composition of the sedimentary layer was similar to that of the argillaceous sediment, and the content of particles with a size of less than 2 mm in the sedimentary layer was lower than that of the argillaceous sediment. Compared with the original soil, the content of particles with a size of less than 0.05 mm and physical clay particles (diameter less than 0.01 mm) in the soil with an infiltration depth of 0-2 cm increased. The retention layer was from the topsoil to the infiltration depth of approximately 2 cm. This study can provide a scientific basis for further research on soil infiltration mechanisms under muddy water.

In light of the frequent occurrence of extreme weather events such as rainstorm-induced waterlogging, which have had severe impacts on people’s production and daily lives, how to more effectively respond to these natural disasters to ensure sustainable urban human development has become a critical research topic that requires urgent attention.This study focuses on the mitigation measures for urban rainstorm waterlogging disasters, using Erdao District in Changchun City, Jilin Province, as a case area. Hydrodynamic methods, waterlogging models, infiltration coefficient calculations, and drainage capacity inversion methods are employed to construct a model simulating the mitigation process of urban rainstorm waterlogging for different land use types. The study emphasizes that increasing vegetation coverage and expediting the construction of sponge cities are crucial measures for alleviating urban rainstorm waterlogging disasters in China. The results indicate that: (1) Underlying surfaces limited to bare land, cultivated land, construction land, and roads result in severe rainstorm waterlogging in the study area, posing significant threats to residents’ safety, property, and traffic; (2) When the underlying surface is vegetation, it has a certain mitigating effect on rainstorm waterlogging, but insufficient vegetation cover in residential areas reduces its effectiveness.; (3) The scenario where the underlying surface comprises bare land, cultivated land, construction land, and roads demonstrates effective mitigation of rainstorm waterlogging; (4) The optimal mitigation effect for rainstorm waterlogging occurs when the underlying surface includes bare land, cultivated land, construction land, roads, and vegetation, showcasing the synergy between vegetation and sponge city construction.Based on this study, scientific evidence is provided for the prevention and mitigation of urban disasters, and technical support is offered for the sustainable development of cities. Moreover, the research emphasizes the importance of clarifying zoning standards in urban planning, mandating the implementation of green infrastructure, and enhancing public acceptance through demonstration projects, thereby providing references for the practical application of sponge city construction.

This study addresses the critical engineering challenge posed by embankment failures in over‐wet soil, which are susceptible to significant settlement and landslides due to rainfall infiltration. The primary objective is to quantify the reductions in soil shear strength both with depth and over time during rainfall infiltration in these embankments. We introduce the “rainfall infiltration coefficient,” a dimensionless parameter that reflects changes in the Euler number, indicative of the microstructural bonding among soil particles. The coefficient is crucial for understanding the degradation of soil structural integrity under wet conditions. Microstructural tests were performed to establish the relationships between the Euler number and the shear strength of over‐wet soil under varying rainfall infiltration conditions. We applied the Fourier sine transform method to solve the diffusion equation for rainfall in over‐wet soil, deriving a new expression that models the attenuation of soil shear strength relative to depth and infiltration time. Validation of these expressions through comparison with empirical data on rainfall infiltration in over‐wet soil confirms its accuracy and reliability. In conclusion, this study provides validated mathematical models that not only enhance the understanding of over‐wet soil shear strength attenuation during rainfall but also significantly contribute to the design and safety of embankments by enabling accurate predictions of soil strength deterioration under varying rainfall conditions.

【Objective】 Water flows over the soil surface and its infiltration in soil are two important parameters for irrigation design, and they are modulated by a multitude of biotic and abiotic factors. The aim of this paper is to investigate the advance and recession of water over the soil surface, as well as its infiltration in soil under border irrigation in attempts to provide a guidance to help border irrigation design. 【Method】 The analysis was based on both experiment and numerical simulation. A field experiment was conducted in borders grown with rotated maize and winter wheat. In the experiment, we measured spatiotemporal changes in both soil water and advance and recession of surface water inside the borders. The experimental data were used to calibrate and test the WinSRFR model to simulate water flows. 【Result】 The numerical model correctly reproduced water flow in both soil and over the soil surface, with the root mean square errors for advance and recession of the surface water in the border ranging from 0.05 to 0.41 h and 0.06 to 0.71 h, respectively, which accounted for 1.23% 7.16% and 1.21% 23.37% of the advancing and recessing time respectively. Crop type affected water flows, and water advancing speed over the soil surface in irrigating the winter wheat was 23.99% slower than irrigating the summer maize. Compared with the summer maize, the winter wheat increased soil water infiltration coefficient and surface roughness by 5% and 39.1% respectively, while reducing soil infiltration index by 34.61%. Curve fitting revealed that the infiltration coefficient was linearly related to the irrigation duration with R2 = 0.903 6. 【Conclusion】 The WinSRFR model was accurate to simulate water flow over the soil surface and its infiltration under border irrigation. Repeating irrigations gradually reduced the infiltration coefficient, infiltration index and surface infiltration capacity, thereby improving irrigation efficiency and uniformness. The infiltration coefficient was linearly related to irrigation duration.

Spring snowmelt has a significant impact on the hydrological cycle in seasonally frozen soil areas. However, scholars hold differing, and even opposing, views on the role of snowmelt during the thawing period in groundwater recharge. To explore the potential recharge effects of spring snowmelt on groundwater in seasonal frozen soil areas, this study investigated the vadose zone dynamics controlled by soil freeze–thaw processes and snowmelt infiltration in the Northeast of China for 194 days from 31 October 2020 to 12 May 2021. Responses of groundwater level and soil moisture to snowmelt infiltration show that most snowmelt was infiltrated under the site despite the ground being frozen. During the unstable thawing period, surface snow had already melted, and preferential flow in frozen soil enabled the recharge groundwater by snowmelt (rainfall), resulting in a significant rise in groundwater levels within a short time. The calculated and simulated snowmelt (rainfall) infiltration coefficient revealed that during the spring snowmelt period, the recharge capacity of snowmelt or rainfall to groundwater at the site is 3.2 times during the stable thawing period and 4.5 times during the non-freezing period.

Karst trough and valley landforms are prone to flooding, primarily because of the unique hydrogeological features of karst landforms, which are conducive to the spread of rapid runoff. Hydrological models that represent the complicated hydrological processes in karst regions are effective for predicting karst flooding, but their application has been hampered by their complex model structures and associated parameter set, especially for distributed hydrological models, which require large amounts of hydrogeological data. Distributed hydrological models for predicting flooding are highly dependent on distributed modelling, complicated boundary parameter settings and extensive hydrogeological data processing, which consumes large amounts of both time and computational power. Proposed here is a distributed physically based karst hydrological model known as the QMG (Qingmuguan) model. The structural design of this model is relatively simple, and it is generally divided into surface and underground double-layered structures. The parameters that represent the structural functions of each layer have clear physical meanings, and fewer parameters are included in this model than in the current distributed models. This allows karst areas to be modelled with only a small amount of necessary hydrogeological data. Eighteen flood processes across the karst underground river in the Qingmuguan karst trough valley are simulated by the QMG model, and the simulated values agree well with observations: the average values of the Nash–Sutcliffe coefficient and the water balance coefficient are both 0.92, while the average relative flow process error is 10 % and the flood peak error is 11 %. A sensitivity analysis shows that the infiltration coefficient, permeability coefficient and rock porosity are the parameters that require the most attention in model calibration and optimization. The improved predictability of karst flooding enabled by the proposed QMG model promotes a better mechanistic depiction of runoff generation and confluence in karst trough valleys.

Baseflow is an important component of river or streamflow. It plays a vital role in water utilization and management. An improved Eckhardt recursive digital filter (IERDF) is proposed in this study. The key filter parameter and maximum baseflow index (BFI max ) were estimated using the minimum smoothing method to improve baseflow estimation accuracy. The generally considered BFI max of 0.80, 0.50 and 0.25 according to the drainage basin’s predominant geological characteristics often leads to significant errors in the regions that have complex subsurface and hydrologic conditions. The IERDF improved baseflow estimation accuracy by avoiding arbitrary parameter values. The proposed method was applied for baseflow separation in the upstream of Yitong River, a tributary of the Second Songhua River, and its performance was evaluated by comparing the results obtained using isotope-tracer data. The performance of IERDF was also compared with nine baseflow separation techniques belonging to filter, BFI and HYSEP methods. The IERDF was also applied for baseflow separation and calculation of rainfall infiltration recharge coefficient at different locations along the Second Songhua River’s mainstream for the period 2000–2016. The results showed that the minimum smoothing method significantly improved BFI max estimation accuracy. The baseflow process line obtained using IEDRF method was consistent with that obtained using isotope 18 O. The IERDF estimated baseflow also showed stability and reliability when applied in the mainstream of the Second Songhua River. The BFI alone in the river showed an increase from the upstream to the downstream. The proportion of baseflow to total flow showed a decrease with time. The intra-annual variability of BFI was different at different locations of the river due to varying climatic conditions and subsurface characteristics. The highest BFI was observed at the middle reaches of the river in summer due to a water surplus from power generation. The research provided valuable information on baseflow characteristics and runoff mode determination, which can be used for water resources assessment and optimization of economic activity distribution in the region.