Hydrology, Volume 8, Issue 3 (September 2021) – 49 articles

The development of strategies to adapt to and mitigate the potential adverse consequences of natural hazards requires support from risk assessment studies that quantify the impacts of hazardous events on our society. A comprehensive analysis of risk commonly evaluates the elements exposed to the hazard probabilistic scenarios and their vulnerabilities. However, while significant advances have been made in the assessment of direct losses, indirect impacts are less frequently examined. This work assesses the indirect consequences of two hydrologic hazards, i.e., pluvial and fluvial floods, in an urban context from a system perspective. It presents a methodology to estimate the services accessibility risk (SAR) that considers the accessibility of roads and the connection between providers and users of services in a city. The feasibility of the proposed approach is illustrated by an application to a pilot study in Monza city (northern Italy) considering pluvial and fluvial flood hazard with different return periods. The results in terms of the social and economic impacts are analyzed considering features of age, disability, and the different economic sectors. Full article

Floods are the one of the most significant natural disasters, with a damaging effect on human life and properties. Recent global warming and climate change exacerbate the flooding by increasing the frequency and intensity of severe floods. This study explores the role of groundwater during the floods at the Miho catchment in South Korea. The Hydrological-Ecological Integrated watershed-scale Flow model (HEIFLOW) model is used for the flood simulations to investigate the impact of groundwater and streamflow interactions during floods. The HEIFLOW model is assessed by the Nash–Sutcliffe model efficiency coefficient (NSE) and Root Mean Square Error (RMSE) for the surface water and groundwater domains, respectively. The model evaluation shows the acceptable model performance (0.64 NSE and 0.25 m–2.06 m RMSE) with the hourly time steps. The HEIFLOW shows potential as one of the methods for the flood risk management in South Korea. The major findings of this study indicate that the stream runoff at the Miho catchment is highly affected by the groundwater flows during the dry and flood seasons. Thus, the interactions between surface water and groundwater domains should be fully considered to mitigate the water hazards at the catchment scale. Full article

The Mekong River Basin is one of the world’s major transboundary basins. The hydrology, agriculture, ecology, and other watershed functions are constantly changing as a result of a variety of human activities carried out inside and by neighboring countries including China, Myanmar, Thailand, Laos, Cambodia, and Vietnam in order to meet increased food and water demands for an increasing population. The Mekong River, which provides irrigation and fishing for a population of over 60 million people, also has an estimated 88,000 MW of untapped hydropower potential. The construction of dams for energy supply has a wide-ranging impact on downstream reservoir regions, resulting in unprecedented changes in hydrologic functions, the environment, and people’s livelihoods. We present a holistic view of how external stressors such as climate change and variability, land cover, and land-use change affect supply and demand. We present an integrated modeling framework for analyzing the supply–demand scenarios and tradeoffs between different sectors. Specifically, we evaluated the impacts of future climate on irrigation, hydropower, and other needs in the basin through a feedback loop. We focused on hydrologic extremes to evaluate their impacts on the reservoir operations during flood and low flow events. The inflow is projected to change by +13% to −50% in the future, while a 0.25% (15.24 billion m³) reduction is projected for the net irrigation water requirement (NIWR). A unit percentage increase in irrigation demand will reduce energy generation by 0.15%, but climate change has a beneficial impact on dam performance with a predicted increase in energy generation and supply to all sectors. Flood events will cause excessive stress on reservoir operation to handle up to six times more flow volumes; however, the low-flow events will marginally affect the system. While the flow and storage rule curves consider both supply and demand, changing human water use comes second to changing climate or other biophysical considerations. This paper emphasizes the importance of considering feedback between climate–water–human society in the systems modeling framework in order to meet societal and ecological challenges. The findings will provide information on the risks and tradeoffs that exist in the water, energy, and food sectors of the basin. Full article

In this study, batch experiments were carried out to investigate the effectiveness of persulfate (PS) as an oxidant agent to remediate benzene, toluene, ethylbenzene, and xylenes (BTEX) in saline environments and at high water temperatures (30 °C). This hydrological setting is quite common in contaminated groundwater aquifers in Middle Eastern countries. In general, increasing the system temperature from 10 to 30 °C greatly enhanced the effectiveness of PS, and resulted in a faster oxidation rate for the target contaminants. When PS was added to the reactor at 30 °C, the targeted contaminants were almost completely oxidized over a 98-day reaction period. During the chemical oxidation of the BTEX, carbon and hydrogen isotope fractionations were monitored and utilized as potential proof of contaminant degradation. The calculated carbon-enrichment values were −1.9‰ for benzene, −1.5‰ for ethylbenzene and toluene, −0.4‰ for ρ,m-xylene, and −1.4‰ for o-xylene, while the hydrogen enrichment values were −9.5‰, −6.8‰, −2.1‰, −6.9‰, and −9.1‰, respectively. In comparison with other processes, the hydrogen and carbon isotope fractionations during the chemical oxidation by PS were smaller than the isotope fractionations resulting from sulfate reduction and denitrification. This observation demonstrates the differences in the transformation pathways and isotope fractionations when compounds undergo chemical oxidation or biodegradation. The distinct trend observed on the dual isotope plot (Δδ¹³C vs. Δδ²H) suggests that compound-specific isotope analysis can be utilized to monitor the chemical oxidation of BTEX by PS, and to distinguish treatment zones where PS and biodegradation technologies are applied simultaneously. Full article

Identifying the core hydrological processes of catchments is a critical step for operative hydrological modeling. This study attempts to assess the long-term alterations in streamflow in three adjacent catchments of Upper East Fork White River, Indiana USA, by employing the SWAT hydrological model. The model simulations are spanning from 1980 up to 2015 and distributed in three configurations periods to identify monthly alterations in streamflow. For this purpose, water abstraction, land use, tillage, and agricultural field drainage practices have been incorporated in the model to provide accurate data input. The model setup also integrates spatially disaggregated sectorial water use data from surface and groundwater resources integrating the significant increases of water abstractions mainly for agricultural and public water supply purposes. The land cover of the study area is governed by rotating crops, while agricultural practices and tile drainage are crucial model parameters affecting the regional hydrological balance. Streamflow prediction is based on the SUFI-2 algorithm and the SWAT-CUP interface has been used for the monthly calibration and validation phases of the model. The evaluation of model simulations indicate a progressively sufficient hydrological model setup for all configuration periods with NSE (0.87, 0.88, and 0.88) and PBIAS (14%, −7%, and −2.8%) model evaluation values at the Seymour outlet. Surface runoff/precipitation as well as percolation/precipitation ratios have been used as indicators to identify trends to wetter conditions. Model outputs for the upstream areas, are successful predictions for streamflow assessment studies to test future implications of land cover and climate change. Full article

Major droughts in the United States have heavily impacted the hydrologic system, negatively effecting energy and food production. Improved understanding of historical drought is critical for accurate forecasts. Data from global climate models (GCMs), commonly used to assess drought, cannot effectively evaluate local patterns because of their low spatial scale. This research leverages downscaled (~4 km grid spacing) temperature and precipitation estimates from nine GCMs’ data under the business-as-usual scenario (Representative Concentration Pathway 8.5) to examine drought patterns. Drought severity is estimated using the Palmer Drought Severity Index (PDSI) with the Thornthwaite evapotranspiration method. The specific objectives were (1) To reproduce historical (1966–2005) drought and calculate near-term to future (2011–2050) drought patterns over the conterminous USA. (2) To uncover the local variability of spatial drought patterns in California between 2012 and 2018 using a network-based approach. Our estimates of land proportions affected by drought agree with the known historical drought events of the mid-1960s, late 1970s to early 1980s, early 2000s, and between 2012 and 2015. Network analysis showed heterogeneity in spatial drought patterns in California, indicating local variability of drought occurrence. The high spatial scale at which the analysis was performed allowed us to uncover significant local differences in drought patterns. This is critical for highlighting possible weak systems that could inform adaptation strategies such as in the energy and agricultural sectors. Full article

The purpose of this study was to evaluate the potential enhancement of ground-source heat pipes by groundwater advection at two sites within an alluvial fan of Toyohira River, Sapporo. Two sites were selected: one in the fan toe, for negligible groundwater flow (Site 1), and the other in the apex for fast flows, the latter characterized by a specific discharge of 1.0 m/d from the losing river (Site 2). The evaporator section(s) of a single (double) heat pipe(s) was installed in a borehole at each site; the condenser section(s) on the ground was placed inside cooled brine at a set temperature, resulting in heat extraction under steady conditions. The single heat pipe experiments showed that the heat extraction rates ranged between 0.23 and 0.79 kW and were not clearly different at the two sites, considering some uncertainty. For double heat pipes, the heat extraction rates were unchanged at Site 1, but were about 146% higher at Site 2 compared to the single tests, due to groundwater advection. This study revealed that the number of ground-source heat pipes required could be reduced from three to two in areas near Site 2. Full article

Assessing the impact of climate change on streamflow is crucial for depicting the vulnerability of water resources and for identifying proper adaptation measures. This study used the Soil and Water Assessment Tool (SWAT) to simulate the impact of climate change on the streamflow of El Kalb river, a major perennial river in Lebanon. The model performance was tested for monthly flow at two stations under a nine-year calibration period (2003–2011) and a four-year validation period (2012–2015). The model results indicated satisfactory precision in fitting observed and simulated flow using various acceptable statistical indices. Future projections of climate change were obtained for three Representative Concentration Pathways (RCPs) (2.6, 4.5, and 8.5). The model indicated that the average annual discharge of El Kalb River in the near future (2021–2040) will decrease by around 28–29% under the three RCP scenarios. End-of-century projections (2081–2100) indicated that the flow will decrease by 23%, 28%, and 45% under RCP 2.6, RCP 4.5, and RCP 8.5, respectively. Full article

Regional climate change is one of the key factors that should be taken into account when planning the development of the coastal tourism, including investments and construction of tourism-related infrastructure. A case study for the Black Sea coast of Russia shows a series of potential negative hydrological, meteorological, and biological factors that accompany regional warming of the Black Sea Region, that can impede the development of coastal tourism and devalue billions of dollars in investments by the State, private companies, and individuals. We discuss such natural phenomena as air and sea warming, extreme weather events, coastal upwelling, heavy rains, river plumes, wind and waves, tornado, rip currents, sea-level rise, algal bloom, introduced species, and other features characteristic for the region that seriously impact coastal tourism today, and may intensify in the nearest future. Sporadic occurrence of extreme weather events, unpleasant and sometimes dangerous sea and atmosphere phenomena during the summer tourist season, and from year to year can be of critical psychological importance when choosing your next vacation and tourism destination. The research does not include anthropogenic factors, geopolitical, and socio-economic processes, and the COVID-19 pandemic that play an important role in the sustainable development of coastal tourism as well. Full article

Rainwater harvesting is an ancient water management practice that has been used to cover potable and non-potable water needs. In recent years, this practice is adopted as a promising alternative and sustainable source of water to meet irrigation needs in agriculture in arid and semi-arid regions. In the present study, a daily water balance model was applied to investigate the size of rainwater tanks for irrigation use in greenhouse begonia and tomato cultivation in two regions of Greece with significant greenhouse areas. For the application of the water balance model, daily rainfall depth values of a 12-year time series (2008–2020) from representative rainfall stations of the study areas were used, as well as the daily water needs of the crops. The greenhouse roof was assumed to be the water collection area of the rainwater harvesting system with values ranging from 1000 to 10,000 m². The analysis of the results showed that in the case of the begonia crop, the covered tanks ranged from 100 to 200 m³ per 1000 m² greenhouse area with a reliability coefficient that ranged from 65 to 72%, respectively, to meet the water needs of plants. Further increase of the reliability coefficient was carried out with disproportionately large volumes of tanks. In the case of the tomato crop, covered tank volumes ranged from 100 to 290 m³ per 1000 m² of greenhouse area, and had a reliability coefficient of 90% to 100%, respectively, while uncovered tanks had a maximum reliability coefficient of 91% for a critical tank volume of 177 m³ per 1000 m² of greenhouse area and decreased for any further increase of tank volume. Full article

Precision agriculture has been at the cutting edge of research during the recent decade, aiming to reduce water consumption and ensure sustainability in agriculture. The proposed methodology was based on the crop water stress index (CWSI) and was applied in Greece within the ongoing research project GreenWaterDrone. The innovative approach combines real spatial data, such as infrared canopy temperature, air temperature, air relative humidity, and thermal infrared image data, taken above the crop field using an aerial micrometeorological station (AMMS) and a thermal (IR) camera installed on an unmanned aerial vehicle (UAV). Following an initial calibration phase, where the ground micrometeorological station (GMMS) was installed in the crop, no equipment needed to be maintained in the field. Aerial and ground measurements were transferred in real time to sophisticated databases and applications over existing mobile networks for further processing and estimation of the actual water requirements of a specific crop at the field level, dynamically alerting/informing local farmers/agronomists of the irrigation necessity and additionally for potential risks concerning their fields. The supported services address farmers’, agricultural scientists’, and local stakeholders’ needs to conform to regional water management and sustainable agriculture policies. As preliminary results of this study, we present indicative original illustrations and data from applying the methodology to assess UAV functionality while aiming to evaluate and standardize all system processes. Full article

Land use changes can significantly influence the water balance, and thus especially the development of flood-triggering runoff peaks. Hence, it is advisable to assess possible changes already at the level of municipal planning. Since many different actors are usually involved in spatial planning, it is useful to provide a shared platform where stakeholders can access the same information to analyze and evaluate flood hazards. Therefore, a GIS routine for the prediction of soil sealing induced runoff peaks and resulting potential flooding in the watercourse was developed, which is embedded in a GIS based decision support system (GIS-DSS). The so-called storm water routine (SWR) is founded on preprocessed flood characteristics, calculated by means of hydrological/hydraulic models (described in part 1). The potential impact of land use change is assessed purely in GIS as flow difference which is routed through the river system. To validate this simplified method, a process model was set up with an exemplary land use change and its results were compared with the GIS-based results. For 16 of the 18 rainfall scenarios tested, the SWR provided very good to good agreement with the detailed model. For short and highly dynamic rain events the SWR approach is less reliable. Several supplements like the integration of LID are conceivable. Full article

Evapotranspiration (ET) is a fundamental factor in energy and hydrologic cycles. Although highly precise in-situ ET monitoring is possible, such data are not always available due to the high spatiotemporal variability in ET. This study estimates daily potential ET (PET) in real-time for the Korean Peninsula, via an artificial neural network (ANN), using data from the GEO-KOMPSAT 2A satellite, which is equipped with an Advanced Meteorological Imager (GK2A/AMI). We also used passive microwave data, numerical weather prediction (NWP) model data, and static data. The ANN-based PET model was trained using data for the period 25 July 2019 to 24 July 2020, and was tested by comparing with in-situ PET for the period 25 July 2020 to 31 July 2021. In terms of accuracy, the PET model performed well, with root-mean-square error (RMSE), bias, and Pearson’s correlation coefficient (R) of 0.649 mm day⁻¹, −0.134 mm day⁻¹, and 0.954, respectively. To examine the efficiency of the GK2A/AMI-derived PET data, we compared it with in-situ ET measured at flux towers and with MODIS PET data. The accuracy of the GK2A/AMI-derived PET, in comparison with the flux tower-measured ET, showed RMSE, bias, and Pearson’s R of 1.730 mm day⁻¹, 1.212 mm day⁻¹, and 0.809, respectively. In comparison with the in-situ PET, the ANN model produced more accurate estimates than the MODIS data, indicating that it is more locally optimized for the Korean Peninsula than MODIS. This study advances the field by applying an ANN approach using GK2A/AMI data and could play an important role in examining hydrologic energy for air-land interactions. Full article

Adequate water resources management includes understanding patterns and spatiotemporal variability of precipitation, as this variable is determinant for ecosystems’ stability, food security, and most human activities. Based on satellite estimations validated through ground measurements from 59 meteorological stations, the objective of this study is to evaluate the long-term spatiotemporal variability and trends of the average monthly precipitation in the Magdalena Department, Colombia, for the 1981–2018 period. This heterogeneous region comprises many different ecoregions in its 23,188 km² area. The analysis of spatial variability allowed for the determination of four different subregions based on the differences in the average values of precipitation and the degree of rainfall variability. The trend analysis indicates that the current rainfall patterns contradict previous estimates of a progressive decrease in annual averages due to climate change in the study region, as most of the department does not exhibit statistically significant trends, except for the Sierra Nevada de Santa Marta area, where this study found reductions between 10 mm yr⁻¹ and 30 mm yr⁻¹. The findings of this study also suggest the existence of some links between precipitation patterns with regional phenomena of climate variability and solar activity. Full article

Due to the fact of water resource deterioration from human activities and increased demand over the last few decades, optimization of management practices and policies is required, for which more reliable data are necessary. Cost and time are always of importance; therefore, methods that can provide low-cost data in a short period of time have been developed. In this study, the ability of an artificial neural network (ANN) and a multiple linear regression (MLR) model to predict the electrical conductivity of groundwater samples in the GallikosRiver basin, northern Greece, was examined. A total of 233 samples were collected over the years 2004–2005 from 89 sampling points. Descriptive statistics, Pearson correlation matrix, and factor analysis were applied to select the inputs of the water quality parameters. Input data to the ANN and MLR were Ca, Mg, Na, and Cl. The best results regarding the ANN were provided by a model that included one hidden layer of three neurons. The mean absolute percentage error, modeling efficiency, and root mean square error were used to evaluate the performances of the methods and to compare the prediction capabilities of the ANN and MLR. We concluded that the ANN and MLR models were valid and had similar accuracy (using the same inputs) with a large number of samples, but in the case of a smaller data set, the MLR showed a better performance. Full article

The flow in rivers is turbulent. The main parameter related to turbulence in rivers is the eddy viscosity, which is used to model a turbulent flow and is involved in the determination of both velocities and sediment concentrations. A well-known and largely used vertical distribution of eddy viscosity in free surface flows (open channels and rivers) is given by the parabolic profile that is based on the logarithmic velocity profile assumption and is valid therefore only in the log-law layer. It was improved thanks to the log-wake law velocity profile. These two eddy viscosities are obtained from velocity profiles, and the main shortcoming of the log-wake profile is the empirical Coles’ parameter. A more rigorous and reliable analytical eddy viscosity model is needed. In this study, we present two analytical eddy viscosity models based on the concepts of velocity and length scales, which are related to the exponentially decreasing turbulent kinetic energy (TKE) function and mixing length, namely, (1) the exponential-type profile of eddy viscosity and (2) an eddy viscosity based on an extension of von Karman’s similarity hypothesis. The eddy viscosity from the second model is ${\mathit{Re}}_{*}$-independent, while the eddy viscosity from the first model is ${\mathit{Re}}_{*}$-dependent (where ${\mathit{Re}}_{*}$ is the friction Reynolds number). The proposed analytical models were validated through computation of velocity profiles, obtained from the resolution of the momentum equation and comparisons to experimental data. With an additional correction function related to the damping effect of turbulence near the free surface, both models are similar to the log-wake-modified eddy viscosity profile but with different values of the Coles’ parameter, i.e., $\Pi =0.2$ for the first model and $\Pi =0.15$ for the second model. These values are similar to those found in open-channel flow experiments. This provides an explanation about the accuracy of these two analytical models in the outer part of free surface flows. For large values of ${\mathit{Re}}_{*}$ (${\mathit{Re}}_{*}$ > 2000), the first model becomes ${\mathit{Re}}_{*}$ independent, and the two coefficients reach asymptotic values. Finally, the two proposed eddy viscosity models are validated by experimental data of eddy viscosity. Full article

Different methods are known for interpolating spatial data. Introduced a few years ago, the initial version of the Most Probable Precipitation Method (MPPM) proved to be a valuable competitor against the Thiessen Polygons Method, Inverse Distance Weighting and kriging for estimating the regional trend of precipitation series. Climate Analyzer, introduced here, is a user-friendly toolkit written in Matlab, which implements the initial and modified version of MPPM and new selection criteria of the series that participate in estimating the regional precipitation series. The software provides the graphical output of the estimated regional series, the modeling errors and the comparisons of the results for different segmentations of the time interval used in modeling. This article contains the description of Climate Analyzer, accompanied by a case study to exemplify its capabilities. Full article

The spatial characteristics and patterns of snow accumulation and ablation inform the amount of water stored and subsequently available for runoff and the timing of snowmelt. This paper characterizes the snow accumulation phase to investigate the spatiotemporal snow water equivalent (SWE) distribution by fitting a function to the trajectory plot of the standard deviation versus mean SWE across a domain. Data were used from 90 snow stations for a 34-year period across the Southern Rocky Mountains in the western United States. The stations were divided into sub-sets based on elevation, latitude, and the mean annual maximum SWE. The best function was a linear fit, excluding the first 35 mm of SWE. There was less variability with SWE data compared to snow depth data. The trajectory of the accumulation phase was consistent for most years, with limited correlation to the amount of accumulation. These trajectories are more similar for the northern portion of the domain and for below average snow years. This work could inform where to locate new stations, or be applied to other earth system variables. Full article

We describe modified sampling and analysis methods to quantify nutrient atmospheric deposition (AD) and estimate Utah Lake nutrient loading. We address criticisms of previous published collection methods, specifically collection table height, screened buckets, and assumptions of AD spatial patterns. We generally follow National Atmospheric Deposition Program (NADP) recommendations but deviate to measure lake AD, which includes deposition from both local and long-range sources. The NADP guidelines are designed to eliminate local contributions to the extent possible, while lake AD loads should include local contributions. We collected side-by-side data with tables at 1 m (previous results) and 2 m (NADP guidelines) above the ground at two separate locations. We found no statistically significant difference between data collected at the different heights. Previous published work assumed AD rates would decrease rapidly from the shore. We collected data from the lake interior and show that AD rates do not significantly decline away from the shore. This demonstrates that AD loads should be estimated by using the available data and geostatistical methods even if all data are from shoreline stations. We evaluated screening collection buckets. Standard unscreened AD samples had up to 3-fold higher nutrient concentrations than screened AD collections. It is not clear which samples best represent lake AD rates, but we recommend the use of screens and placed screens on all sample buckets for the majority of the 2020 data to exclude insects and other larger objects such as leaves. We updated AD load estimates for Utah Lake. Previous published estimates computed total AD loads of 350 and 153 tons of total phosphorous (TP) and 460 and 505 tons of dissolve inorganic nitrogen (DIN) for 2017 and 2018, respectively. Using updated collection methods, we estimated 262 and 133 tons of TP and 1052 and 482 tons of DIN for 2019 and 2020, respectively. The 2020 results used screened samplers with lower AD rates, which resulted in significantly lower totals than 2019. We present these modified methods and use data and analysis to support the updated methods and assumptions to help guide other studies of nutrient AD on lakes and reservoirs. We show that AD nutrient loads can be a significant amount of the total load and should be included in load studies. Full article

The variability of climate, increase in population, and lack of territorial plans in Costa Rica have caused intense disasters with human and economic losses. In 2016, Hurricane Otto hit the country’s northern area, leaving substantial damages, including landslides, debris flows, and flooding. The present study evaluated different scenarios to estimate flooded areas for Newtonian (clean water), and non-Newtonian flows with volumetric sediment concentrations (Cv) of 0.3, 0.45, 0.55, and 0.65 using Hydro-Estimator (HE), rain gauge station, and the 100-year return period event. HEC–HMS modeled the rainfall products, and FLO-2D modeled the hydrographs and Cv combinations. The simulation results were evaluated with continuous statistics, contingency table, Nash Sutcliffe Efficiency, measure of fit (F), and mean absolute differences (E) in the floodplains. Flow depths, velocities, and hazard intensities were obtained in the floodplain. The debris flood was validated with field data and classified with a Cv of 0.45, presenting lower MAE and RMSE. Results indicated no significant differences in flood depths between hydrological scenarios with clean-water simulations with a difference of 8.38% in the peak flow. The flood plain generated with HE rainfall and clear-water condition presented similar results compared to the rain gauge input source. Additionally, hydraulic results with HE and Cv of 0.45 presented E and F values similar to the simulation of Cv of 0.3, demonstrating that the HE bias did not influence the determination of the floodplain depth and extent. A mean bias factor can be applied to a sub-daily temporal resolution to enhance HE rain rate quantifications and floodplain determination. Full article

The hilly landscape of the Periadric area in Central Italy is characterized by mainly marly–clayey foredeep basin deposits (Plio–Pleistocene age). These lithotypes are generally considered aquicludes, if compared with the regional limestone aquifers of Apennines. However, a coarsening upward trend characterizes the upper portion of this stratigraphic sequence, with arenaceous deposits and even conglomerates on the top. From a geomorphological viewpoint, the areas with coarser outcrops show a flat shape and sub-vertical slopes, like boundaries. At the base of these scarps, springs can be found at the interface between coarse and fine deposits, whereas these arenaceous bodies are actual aquifers. Until now, the hydrodynamics and hydrochemical features of this kind of aquifer have not been investigated deeply, because they have always been considered a worthy water resource. However, they could play a crucial role in integrated water management, especially to cope with climate changes and drought periods. Considering these, the main purpose of this study was to investigate from a hydrogeological point of view and to assess the groundwater quantity and quality. Five examples throughout the Abruzzo region were considered. For evaluation and comparisons between water resources, the water volume that infiltrates yearly at each squared kilometer of an aquifer (Mm³/y/km²) was applied. This value was calculated through three different approaches to provide a recharge estimation for this kind of aquifer that is as exhaustive and representative as possible. The results allowed us to characterize the hydrogeological model and to quantify the resources between 0.1 and 0.16 Mm³/y/km², to be suitable for multi–purpose utilization. Full article

The integration of artificial intelligence into various aspects of daily life is developing at a rapid pace in Japan. Discussions to govern applications of artificial intelligence to the field of social infrastructure are also critical and need to match the rapid pace of development. However, the legal implications and risks of applying artificial intelligence to the management of lifelines such as drinking water supply and wastewater treatment have not yet been fully explored. This paper reviews the existing legislations and ongoing discussions on governance regarding applications of artificial intelligence to water and wastewater management. Based on the review, we discuss the ability of legislative frameworks in Japan to respond to the applications of artificial intelligence, as well as identifying potential gaps and challenges thereof, including access to accurate data, demarcation of rights and responsibilities, risk hedging and risk management, monitoring and evaluation, and handling of intellectual property rights. This paper concludes with key recommendations to national and local governments to support the application of artificial intelligence in the field of water and wastewater. Full article

The primary goal of this study is to comprehend the effects of El Niño Southern Oscillation (ENSO) climate pattern on groundwater storage (GWS) in the South Atlantic-Gulf Region. Groundwater issues are complex and different studies focused on groundwater depletion while few emphasized “groundwater rise”. The current research is designed to develop an outline for assessing how climate patterns can affect groundwater fluctuation, which might lead to groundwater rise. The study assessed the effect of ENSO phases on spatiotemporal variability of groundwater using Spearman Rank Correlation. A significant positive correlation between ENSO and GWS was observed. An increasing trend was detected in GWS where most grids were observed in Florida by utilizing the non-parametric Mann–Kendall test. A positive trend magnitude was also detected by utilizing Theil–Sen’s Slope method with a high magnitude in the mid-Florida region. The highest GWS anomalies were observed in the peak of El Niño events and the lowermost GWS was observed during La Niña events. Furthermore, most of the stations were above normal groundwater conditions. This study provides a better insight on the research gap among groundwater rise and ENSO. Full article

Groundwater management of alluvial aquifers facing the northern Italian Apennines is an important issue that is becoming more complicated due to ongoing climate changes and increased water demands. The large groundwater withdrawals, coupled with an overall worsening of the water quality, require detailed knowledge of the recharge mechanisms of these aquifers that can be useful for further adaptation measures. We have focused our attention on a selected alluvial fan in which 49 slug injections of hyperconcentrated solutions of NaCl allowed river discharges to be estimated in seven different hydraulic sections. Consequently, losses from the streambed were assessed for the six river reaches along with the corresponding uncertainties in the estimates. The study confirms the suitability of such tests for identifying sectors in which streambed losses are promoted and for quantifying the total recharge conveyed to underlying aquifers. In addition, it has been demonstrated that the total streambed losses can be further linked to river discharges in any gauge upstream of the alluvial fan thanks to linear regression. Once obtained, the latter makes monitoring groundwater recharge by stream losses in real time possible if a permanent measurement device (such as the common telemetry used for river discharge monitoring) is available. Full article

It is unambiguous that climate change alters the intensity and frequency of precipitation and temperature distribution at the global and local levels. The rate of change in temperature in the northern latitudes is higher than the worldwide average. The annual distribution of precipitation over the Himalayas in the northern latitudes shows substantial spatial and temporal heterogeneity. Precipitation and temperature are the major driving factors that impact the streamflow and water availability in the basin, illustrating the importance of research on the impact of climate change on streamflow by varying the precipitation and temperature in the Thuli Bheri River Basin (TBRB). Multiple climate models were used to project and evaluate the precipitation and temperature distribution changes in temporal and spatial domains. To analyze the potential impact of climate change on the streamflow in the basin, the Soil and Water Assessment Tool (SWAT) hydrological model was used. The climate projection was carried out in three future time windows. The result shows that the precipitation fluctuates between approximately +12% and +50%, the maximum temperature varies between −7% and +7%, and the minimum temperature rises from +0.7% to +5% in intermediate- and high-emission scenarios. In contrast, the streamflow in the basin varies from −40% to +85%. Thus, there is a significant trend in the temperature increase and precipitation reduction in the basin. Further, the relationship between precipitation and temperature with streamflow shows a substantial dependency between them. The variability in precipitation and streamflow is successfully represented by the water yield in the basin, which plays an important role in the sustainability of the water-related projects in the basin and downstream to it. This also helps quantify the amount of water available for hydropower generation, agricultural production, and the water ecosystem in the TBRB. Full article

Rare earths and yttrium (REY) distribution patterns of the hydrosphere reveal systematic correlations of Gd and Y anomalies besides the non-correlated redox-dependent Ce and Eu anomalies. Eu anomalies are inherited by dissolution of feldspars in igneous rocks, whereas Ce, Gd and Y anomalies develop in aqueous systems in contact with minerals and amorphous matter. Natural, positive Gd and Y anomalies in REY patterns characterize high-salinity fluids from the Dead Sea, Israel/Jordan, the Great Salt Lake, USA, the Aral Sea, Kazakhstan/Uzbekistan, ground- and surface water worldwide. Extreme Gd anomalies mostly originate from anthropogenic sources. The correlation of Gd and Y anomalies at low temperature in water bodies differ from geothermal ones. In nature, dynamic systems prevail in which either solids settle in water columns or water moves through permeable sediments or sedimentary rocks. In both cases, the anomalies in water develop due to repeated equilibration with solid matter. Thus, these anomalies provide information about the hydrological history of seawater, fresh groundwater and continental brines. When migrating, the interaction of aqueous phases with mineral surfaces leads to increasing anomalies because the more hydrophillic Gd and Y preferentially remain in the aqueous phase compared to their nearest neighbors. The correlation coefficients between Gd and Y anomalies in groundwater is 0.5–0.9. In lakes and oceans, it is about 0.1–0.8, under anomalous conditions it can increase to 1. Full article

Ever expanding urbanized landscapes are increasingly impacting streams that run through them. Among other stressors, urban streams often are host to elevated concentrations of nutrients, salts, and heavy metals. The pollutants, coupled with high temperatures, are drivers of ecosystem degradation in urban streams. The installation of artificial floating wetlands (AFWs) has been successful in mitigating the effects of urbanization in lakes and wastewater treatment ponds, but rarely have they been tested in streams. This pilot-study examined the ability of an AFW to improve water quality in an urban stream. The small, 90 m² AFW was installed to improve the aquatic habitat and aesthetics of a small section of the Chicago River, Chicago, IL USA. Water samples and in-situ measurements were collected from the surface and at 0.3 m depth of upstream and downstream of the AFW. Samples were analyzed for nitrate-as-nitrogen, phosphate, chloride, and heavy metals. Comparison of upstream and downstream waters showed that the AFW lowered the concentrations of nitrate-as-nitrogen and phosphate during the growing season by 6.9% and 6.0%, respectively. Nitrate was also removed during the dormant season; however, phosphate was not removed during that time. Plant or microbial uptake of the nutrients are believed to be the dominant mechanisms in the growing season with denitrification serving as the primary pathway in the dormant season. Despite not having a measurable effect on the water temperature, the AFW was an effective means to reduce concentrations of nitrate and phosphorus, decreasing the potential for eutrophication. Full article

The Hula Valley in northern Israel was partly covered by swamps and a shallow lake. The entire valley was drained and converted for agricultural cultivation. Later, an additional soil reclamation operation was implemented, including eco-tourism. From the early 1990s, winter migratory cranes have attracted visitors, thus supporting the hydrological management of the entire valley that protects the downstream Lake Kinneret. It was documented that these birds have a minor impact on phosphorus pollution, but severely damaged agricultural crops are protected by mild deportation and daily, short, periodical corn seed feeding. Full article

In 2009, the University of Alabama-Huntsville configured their GOES satellited-based solar radiation product to include Puerto Rico, the US Virgin Islands (USVI), Dominican Republic, Haiti, Jamaica, and Cuba. The half-hourly and daily integrated data are available at 1 km resolution for Puerto Rico and the USVI and 2 km for Hispaniola, Jamaica, and Cuba. These data made it possible to implement estimates of satellite radiation-based evapotranspiration methods on all of the islands. The use of the solar radiation data in combination with estimates of other climate parameters facilitated the development of a water and energy balance algorithm for Puerto Rico. The purpose of this paper is to describe the theoretical background and technical approach for estimating the components of the daily water and energy balance. The operational water and energy balance model is the first of its kind in Puerto Rico. Model validation results are presented for reference and actual evapotranspiration, soil moisture, and streamflow. Mean errors for all analyses were less than 7%. The water and energy balance model results can benefit such diverse fields as agriculture, ecology, coastal water management, human health, renewable energy development, water resources, drought monitoring, and disaster and emergency management. This research represents a preliminary step in developing a suite of gridded hydro-climate products for the Caribbean Region. Full article