Editor’s Choice Articles

Accurate precipitation estimation remains a challenge, though it is fundamental for most hydrological analyses. In this regard, this study aims to achieve two objectives. Firstly, we evaluate the performance of two precipitation products from the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM-IMERG) for Sicily, Italy, from 2016 to 2020 by a set of categorical indicators and statistical indices. Analyses indicate the favorable performance of daily estimates, while half-hourly estimates exhibited poorer performance, revealing larger discrepancies between satellite and ground-based measurements at sub-hourly timescales. Secondly, we propose four multi-source merged models within Artificial Neural Network (ANN) and Multivariant Linear Regression (MLR) blending frameworks to seek potential improvement by exploiting different combinations of Soil Moisture (SM) measurements from the Soil Moisture Active Passive (SMAP) mission and atmospheric factor of Precipitable Water Vapor (PWV) estimations, from the Advanced Microwave Scanning Radiometer-2 (AMSR2). Spatial distribution maps of some diagnostic indices used to quantitatively evaluate the quality of models reveal the best performance of ANNs over the entire domain. Assessing variable sensitivity reveals the importance of IMERG satellite precipitation and PWV in non-linear models such as ANNs, which outperform the MLR modeling framework and individual IMERG products. Full article

Max-stable process (MSP) models can be fit to data collected over a spatial domain to estimate areal-based exceedances while accounting for spatial dependence in extremes. They have theoretical grounding within the framework of extreme value theory (EVT). In this work, we fit MSP models to three-day duration cool season precipitation maxima in the Willamette River Basin (WRB) of Oregon and to 48 h mid-latitude cyclone precipitation annual maxima in the Upper Trinity River Basin (TRB) of Texas. In total, 14 MSP models were fit (seven based on the WRB data and seven based on the TRB data). These MSP model fits were developed and applied to explore how user choices of study area sampling density, gage extent, and model fitting method impact areal precipitation-frequency calculations. The impacts of gage density were also evaluated. The development of each MSP involved the application of a recently introduced trend surface modeling methodology. Significant reductions in computing times were achieved, with little loss in accuracy, applying random sample subsets rather than the entire grid when calculating areal exceedances for the Cougar dam study area in the WRB. Explorations of gage extent revealed poor consistency among the TRB MSPs with modeling the generalized extreme value (GEV) marginal distribution scale parameter. The gauge density study revealed the robustness of the trend surface modeling methodology. Regardless of the fitting method, the final GEV shape parameter estimates for all fourteen MSPs were greater than their prescribed initial values which were obtained from spatial GEV fits that assumed independence among the extremes. When two MSP models only differed by their selected fitting method, notable differences were observed with their dependence and trend surface parameter estimates and resulting areal exceedances calculations. Full article

To counter the impacts of climate change and urbanization, engineers have developed ingenious solutions to reduce flooding and capture stormwater contaminants through the use of Low Impact Developments (LIDs). The soil is generally considered to be completely saturated when designing for the LIDs. However, this may not always be an accurate or realistic approach, as the soil could be variably unsaturated leading to inaccurate designs. To analyse the flow under variably unsaturated conditions, Richards’ equation can be used. To solve the Richards’ equation, two nonlinear hydraulic properties, namely soil water characteristic curve (SWCC) and the unsaturated hydraulic conductivity function are required. Laboratory and field measurements of unsaturated hydraulic properties are cumbersome, expensive and time- consuming. Pedotransfer functions (PTFs) estimate soil hydraulic properties using routinely measured soil properties. This paper presents a comparison between the direct measurement obtained through experimental procedures and the use of PTFs to estimate soil hydraulic properties for two green roof and three bioretention soil medias. Comparison between the measured and estimated soil hydraulic properties was accomplished using two different approaches. Statistical analyses and visual comparisons were used to compare the measured and estimated soil hydraulic properties. Additionally, numerical modelling to predict the water balance at the ground surface was conducted using the measured and estimated soil hydraulic properties. In some instances, the use of predicted hydraulic properties resulted in overestimation of the cumulative net infiltration of as much as 60 % for the green roof substrate, but was considered negligible for the bioretention substrate. Design performance criteria for green roof and bioretention facilities were examined using the measured and estimated soil hydraulic properties under extreme precipitation analysis. Results indicate that there is a high level of uncertainty when using PTFs for LID materials. A percent difference between the measured and predicted properties for the green roof peak time delay under a 2-year storm can be as much as 300%. For the bioretention design criteria of a 25-year storm, the surface runoff was overestimated by 14.7 cm and by 100% for the ponding time percent difference. Full article

The process of how soil moisture profiles evolve into the soil and reach the root zone could be estimated by solving the appropriate strong nonlinear Richards’ equation. The nonlinearity of the equation occurs because diffusivity D is generally an exponential function of water content. In this work, the boundary conditions of the physical problem are considered fuzzy for various reasons (e.g., machine impression, human errors, etc.), and the overall problem is encountered with a new approximate fuzzy analytical solution, leading to a system of crisp boundary value problems. According to the results, the proposed fuzzy analytical solution is in close agreement with Philip’s semi-analytical method, which is used as a reference solution, after testing 12 different types of soils. Additionally, possibility theory is applied, enabling the decision-makers to take meaningful actions and gain knowledge of various soil and hydraulic properties (e.g., sorptivity, infiltration, etc.) for rational and productive engineering studies (e.g., irrigation systems). Full article

In the upper and middle reaches of rivers in Japan, river channels used to meander in a comparatively narrow floodplain and heavy rain runoff used to naturally expand over the entire floodplain, retarding floods toward the downstream. Recent continuous levee building to prevent river overflow has had two kinds of negative effects, namely an increase in flood damage in areas of a floodplain closed by levees and river terraces at the time of runoff over the river channel capacity, and an increase in the flood peak toward the downstream. This study introduces the concept of a running water-type retarding basin that mitigates flood damage by allowing excess runoff to pass through the floodplain, restoring a natural hydrological process. After a description of the concept of the facility design, a design example is presented for a closed floodplain of the Kinu River Floodplain, where excess runoff caused severe flood damage in 2015, to quantify the performance and effects of the running water-type retarding basin. Full article

Floods are lethal and destructive natural hazards. The Mediterranean, including Greece, has recently experienced many flood events (e.g., Medicanes Zorbas and Ianos), while climate change results in more frequent and intense flood events. Accurate flood mapping in river areas is crucial for flood risk assessment, planning mitigation measures, protecting existing infrastructure, and sustainable planning. The accuracy of results is affected by all simplifying assumptions concerning the conceptual and numerical model implemented and the quality of geospatial data used (Digital Terrain Models—DTMs). The current research investigates flood modelling sensitivity against geospatial data accuracy using the following DTM resolutions in a mountainous river sub-basin of Thessaly’s Water District (Greece): (a) open 5 m and (b) 2 m data from Hellenic Cadastre (HC) and (c) 0.05 m data from an Unmanned Aerial Vehicle (UAV) topographical mission. RAS-Mapper and HEC-RAS are used for 1D (steady state) hydraulic simulation regarding a 1000-year return period. Results include flood maps and cross section-specific flow characteristics. They are analysed in a graphical flood map-based empirical fashion, whereas a statistical analysis based on the correlation matrix and a more sophisticated Machine Learning analysis based on the interpretation of nonlinear relationships between input–output variables support and particularise the conclusions in a quantifiable manner. Full article

Accurate prediction of dam inflows is essential for effective water resource management and dam operation. In this study, we developed a multi-inflow prediction ensemble (MPE) model for dam inflow prediction using auto-sklearn (AS). The MPE model is designed to combine ensemble models for high and low inflow prediction and improve dam inflow prediction accuracy. We investigated the impact of datasets assigned to flow regimes on the ensemble composition and compared the performance of the MPE model to an AS-based ensemble model developed using a conventional approach. Our findings showed that the MPE model outperformed the conventional model in predicting dam inflows during flood and nonflood periods, reducing the root mean square error (RMSE) and mean absolute error (MAE) by 22.1% and 24.9% for low inflows, and increasing the coefficient of determination (R²) and Nash–Sutcliffe efficiency (NSE) by 21.9% and 35.8%, respectively. These results suggest that the MPE model has the potential to improve water resource management and dam operation, benefiting both the environment and society. Overall, the methodology of this study is expected to contribute to the development of a robust ensemble model for dam inflow prediction in regions with high climate variability. Full article

The productivity of metamorphic aquifers is generally lower than that of the more common alluvial and carbonates ones. However, in some Mediterranean areas, such as the Calabria region (Italy), water scarcity combined with the presence of extensive metamorphic water bodies requires the development of further studies to characterize the hydrodynamic properties of these groundwater systems in order to achieve their sustainable exploitation. The interest in this goal becomes even greater if climate change effects are considered. The purpose of this study was to provide the geological-structural and hydrogeological numerical modeling of a metamorphic aquifer, using direct and indirect data measurement, in a large area of the Sila Piccola in Calabria. The hydrodynamic characterization of the crystalline-metamorphic aquifer, constituted by granite and metamorphic rocks, is extremely complex. The MODFLOW-2005 groundwater model was used to simulate flow phenomena in the aquifer, obtaining hydraulic conductivity values of 2.7 × 10⁻⁶ m/s, which turned out to be two orders of magnitude higher than those obtained from the interpretation of the slug-tests performed in the study area. The mathematical model was also able to estimate the presence of a lateral recharge from a neighboring deep aquifer providing a significant water supply to the system under investigation. Full article

IWRM should include the integration of management instruments towards intersectoral efficient water allocation. A platform linking economywide and network-based models, available from a Spatial Decision Support System (SDSS), was used to analyze allocation decisions in 4-interlinked basins in Northeastern Brazil during a period of water scarcity. The SDSS can integrate water allocation issues considering hydrologic and socioeconomic aspects. In this study, we applied a normalized concentration index and exploratory spatial data analysis to socioeconomic data to identify job hotspots in economic sectors. Hydro-economic indicators were determined and used as economic weights of those hotspots and individual users for water allocation. This innovative method of allocation simulates the use of economic instruments. Removing the weights, the use of non-economic instruments is also simulated. The economic allocation transfers water from agriculture and industry to the services sector compared to the non-economic. This is justified given the low indicators of the main sectors of agriculture and industry in the region: sugarcane cultivation and the sugar–alcohol industry. Moreover, regional transfer results show that without using economic criteria and maintaining the current distribution network, there is a transfer of water stored in drier to humid regions. These results can support the decision-making process by defining effective management instruments. Full article

The potential for extreme climate events to cluster in space and time has driven increased interest in understanding and predicting compound climate risks. Through a case study on floods in the Ohio River Basin, we demonstrated that low-frequency climate variability could drive spatial and temporal clustering of the risk of regional climate extremes. Long records of annual maximum streamflow from 24 USGS gauges were used to explore the regional spatiotemporal patterns of flooding and their associated large-scale climate modes. We found that the dominant time scales of flood risk in this basin were in the interannual (6–7 years), decadal (11–13 years), and secular bands and that different sub-regions within the Ohio River Basin responded differently to large-scale forcing. We showed that the leading modes of streamflow variability were associated with ENSO and secular trends. The low-frequency climate modes translated into epochs of increased and decreased flood risk with multiple extreme floods or the absence of extreme floods, thus informing the nature of compound climate-induced flood risk. A notable finding is that the secular trend was associated with an east-to-west shift in the flood incidence and the associated storm track. This is consistent with some expectations of climate change projections. Full article

This paper examines the impacts of three different potential evapotranspiration (PET) models on drought severity and frequencies indicated by the standardized precipitation index (SPEI). The standardized precipitation-evapotranspiration index is a recent approach to operational monitoring and analysis of drought severity. The standardized precipitation-evapotranspiration index combines precipitation and temperature data, quantifying the severity of a drought as the difference in a timestep as the difference between precipitation and PET. The standardized precipitation-evapotranspiration index thus represents the hydrological processes that drive drought events more realistically than the standardized precipitation index at the expense of additional computational complexity and increased data demands. The additional computational complexity is principally due to the need to estimate PET within each time step. The standardized precipitation-evapotranspiration index was originally defined using the Thornthwaite PET model. However, numerous researchers have demonstrated the standardized precipitation-evapotranspiration index is sensitive to the PET model adopted. PET models requiring sparse meteorological inputs, such as the Thornthwaite model, have particular utility for drought monitoring in data scarce environments. The aridity index (AI) investigates the spatiotemporal changes in the hydroclimatic system. It is defined as the ratio between potential evapotranspiration and precipitation. It is used to characterize wet (humid) and dry (arid) regions. In this study, a sensitivity analysis for the standardized precipitation-evapotranspiration and aridity indexes was carried out using three different PET models; namely, the Penman–Monteith model, a temperature-based parametric model and the Thornthwaite model. The analysis was undertaken in six gauge stations in California region where long-term drought events have occurred. Having used the Penman–Monteith model as the PET model for estimating the standardized precipitation-evapotranspiration index, our findings highlight the presence of uncertainty in defining the severity of drought, especially for large timescales (12 months to 48 months), and that the PET parametric model is a preferable model to the Thornthwaite model for both the standardized precipitation-evapotranspiration index and the aridity indexes. The latter outcome is worth further consideration for when climatic studies are under development in data scarce areas where full required meteorological variables for Penman–Monteith assessment are not available. Full article

Storage tanks from rainwater harvesting systems (RWHs) are designed to provide flow equalization between rainfall and water demand. The minimum storage capacity required to take into account the maximum variations of stored water volumes, i.e., the active storage, depends basically on the magnitude and the variability of rainfall profiles and the size of the demand. Given the random nature of the variables involved in the hydrological process, probability theory is a suitable technique for active storage estimation. This research proposes a probabilistic approach to determine an analytical expression for the cumulative distribution function (CDF) of the active storage as a function of rainfall moments, water demand and the mean number of consecutive storm events in a deficit sub-period. The equation can be used by developers to decide on the storage capacity required at a desired non-exceedance probability and under a preset water demand. The model is validated through a continuous simulation of the tank behavior using rainfall time series from Milan (Northern Italy). Full article

Climate change is a significant problem that many countries are currently facing, and green roofs (GRs) are one of the suitable choices to confront it and decrease its impacts. The advantages of GRs are numerous, such as stormwater management, thermal need reduction, runoff quality, and life quality improvement. However, there are some limitations, including the weight, limits in water retention, irrigation in the drought period, suitability of harvested water for building usages, installation on sloped roofs, and high cost. Therefore, developing a novel system and design for GRs with higher efficiency and fewer negative points seems necessary and is the main scope of this research. In this regard, a novel multipurpose self-irrigated green roof with an innovative drainage layer combined with specific multilayer filters has been developed. The application of the proposed system in terms of water retention capacity, water storage volume, runoff treatment performance, irrigation system, drainage layer, application of the harvested water for domestic purposes, and some other aspects has been analyzed and compared with the conventional systems with a focus on extensive green roofs. The results demonstrate that this novel green roof would have many advantages including less weight due to the replacement of the gravel drainage layer with a pipeline network for water storage, higher water retention capacity due to the specific design, higher impacts on runoff treatment due to the existence of multilayer filters that can be changed periodically, easier installation on flat and sloped roofs, the possibility of using the collected rainfall for domestic use, and fewer irrigation water demands due to the sub-surface self-irrigation system. Full article

The aim of this study was to simulate dominant runoff generation processes (DRPs) in a mesoscale catchment in southwestern Germany with the physically-based distributed hydrological model WaSiM-ETH and to compare the resulting DRP patterns with a data-mining-based digital soil map. The model was parameterized by using 11 Pedo-transfer functions (PTFs) and driven by multiple synthetic rainfall events. For the pattern comparison, a multiple-component spatial performance metric (SPAEF) was applied. The simulated DRPs showed a large variability in terms of land use, applied rainfall rates, and the different PTFs, which highly influence the rapid runoff generation under wet conditions. Full article

The detection and mapping of riverscapes with Unmanned Aerial Vehicles (UAVs, drones) provide detailed, reliable, and operable spatial information in hydrological sciences, enhancing conventional field survey techniques. In this study, we present the results of long-term, optical RGB (red, green, blue) UAV monitoring of stream restoration projects to identify the positive and negative features that affect their sustainability. We determined quantitative and qualitative aspects of restoration, such as the restoration effect, the dynamics of fluvial processes, hydrological connectivity, and riparian vegetation. The study was based on six years of UAV monitoring in three restored streams in Prague, Czech Republic. The multitemporal riverscape models from the photogrammetric reconstruction served as a basis for the visual assessment, compliant with the standard hydromorphological assessment. Such a combined approach extends the potential of UAV monitoring by allowing for the use of existing classification schemes and data and the objective detection of critical features. The study pointed to the significant discrepancies in channel geometry between the planned restorations and realized restorations in all assessed projects as a general phenomenon. Multitemporal, optical RGB UAV monitoring then detected issues in qualitative aspects that limit restoration quality, such as water overuse, extensive eutrophication, or inefficient riparian shading. Full article

Very well-drained lands could have a positive impact in various soil health indicators such as soil erosion and soil texture. A drainage system is responsible for properly aerated soil. Until today, in order to design a drainage system, a big challenge remained to find the subsurface drain spacing because many of the soil and hydraulic parameters present significant uncertainties. This fact also creates uncertainties to the overall physical problem solution, which, if not included in the preliminary design studies and calculations, could have bad consequences for the cultivated lands and soils. Finding the drain spacing requires the knowledge of the unsteady groundwater movement, which is described by the linear Boussinesq equation (Glover-Dumm equation). In this paper, the Adomian solution to the second order unsteady linear fuzzy partial differential one-dimensional Boussinesq equation is presented. The physical problem concerns unsteady drain spacing in a semi-infinite unconfined aquifer. The boundary conditions, with an initially horizontal water table, are considered fuzzy and the overall problem is translated to a system of crisp boundary value problems. Consequently, the crisp problem is solved using an Adomian decomposition method (ADM) and useful practical results are presented. In addition, by application of the possibility theory, the fuzzy results are translated into a crisp space, enabling the decision maker to make correct decisions about both the drain spacing and the future soil health management practices, with a reliable degree of confidence. Full article

Land use changes and mounting water demands reduce freshwater inflows into estuaries, impairing estuarine ecosystems and accelerating coastal seawater intrusion. However, determining minimum river inflows for management guidelines is hampered by a lack of ecosystem-flow link data. This study describes the development of freshwater inflow guidelines for the Wami Estuary, combining scarce river flow data, hydrological modeling, inferring natural salinity regime from vegetation zonation and investigating freshwater requirements of people/wildlife. By adopting the Building Blocks Methodology, a detailed Environmental Flows Assessment was performed to know the minimum water depth/quality seasonal requirements for vegetation, terrestrial/aquatic wildlife and human communities. Water depth requirements were assessed for drought and normal rainfall years; corresponding discharges were obtained by a hydrological model (HEC-RAS) developed for the river channel upstream of estuary. Recommended flows were well within historically occurring flows. However, given the rapidly increasing water demand coupled with reduction in basin water storage due to deforestation/wetland loss, it is critical to ensure these minimum flows are present, without which essential ecosystem services (fisheries, water quality, mangrove forest resources and wildlife/tourism) will be jeopardized. The EFA process is described in painstaking detail to provide a reference for undertaking similar studies in data-poor regions worldwide. Full article

The mobility of a metal in mining-impacted sediments is determined by the environmental conditions that influence the metal’s oxidation state and bonding environment. Coeur d’Alene Lake, USA, has been impacted by legacy mining practices that allowed the hydrologic transport of mining waste to the lakebed, resulting in substantial amounts of redox-sensitive Fe and Mn along with Ag, As, Cd, Cu, Hg, Pb, Sb, and Zn. Future lake conditions may include algal blooms and additional algal detritus at the sediment–water interface, which may alter Fe and Mn forms that can influence their, and other metal(loid)s, mobility during seasonal anoxia. Cores of the lakebed sediments were exposed to anoxic and anoxic + algal detritus conditions for 8 weeks. Sediment samples were collected biweekly for analysis of Fe and Mn oxidation states and bonding environments by synchrotron-based X-ray absorption spectroscopy. Over the 8-week period and at a location 12.5 cm deep in the sediments, anoxic and anoxic + algae conditions produced limited changes in Fe and Mn oxidation states and bonding environments. At a location 2.5 cm below the sediment–water interface, the anoxic condition promoted a relatively stable environment in which Fe and Mn oxidation states and bonding environments did not vary greatly during the experiment. At the 2.5 cm depth, the anoxic + algae condition substantially altered the Mn oxidation state distribution and bonding environment, but this condition did not strongly influence the Fe oxidation state distribution or bonding environment. The anoxic + algae condition increased the presence of Mn³⁺, produced Mn⁴⁺ at select times, altered the Mn bonding environment, and temporarily increased the release of Mn into porewater. The algae influence on sediment and porewater Mn likely occurred because of the increased formation of organo-Mn complexes produced during algae-enhanced enzymatic processes. The lack of influence of algal detritus on sediment and porewater Fe and the formation of soluble organo-Mn complexes may limit the potential increase in the mobility of other metal(loid)s with future lake conditions. Full article

Accurate water flow measurement ensures proper irrigation water management by allocating the desired amount of water to the irrigation fields. The present study evaluated whether the non-intrusive smartphone application “DischargeApp” could be applicable and precise to measure small canal flow rates in the Koga irrigation Scheme. The app was tested in unlined canals with flow rates ranging from 15 to 65 l/s using a 90° V-notch weir. The app is found to overestimate high flow rates. Another source of uncertainty is that the app employed a constant surface velocity conversion factor (C = 0.8) to compute discharge. The accuracy was enhanced by recalculating the measured discharge using a new surface velocity conversion factor that depends on depths. The new conversion factor decreased the errors of MAE and RMSE by 47% and 52%, respectively. Where channel and other optional measuring techniques are not available without interfering with the flow operation conditions in place, the DischargeApp devices can be used to measure flows. The DischargeApp could be used to collect data using local citizens in data-scarce areas. This study suggested reconfiguring the DischargeApp with a new surface velocity conversion coefficient based on flow depths in field conditions for better performance. Full article

A method was developed to integrate the truncated power-law distribution of solid volumetric fraction into the widely used Kozeny–Carman (KC)-type equations to assess the potential uncertainty of permeability. The focus was on the heterogeneity of porosity (or solid volumetric fraction) in the KC equation. The truncated power-law distribution simulates a heterogeneous scenario in which the solid volumetric fraction varies over different portions of porous media, which is treated as stationary, so its spatial mean can be replaced by the ensemble mean. The model was first compared with the experimental results of 44 samples from the literature and a recent model of KC equation modification that targets the coefficients in the equation. The effects of the fractal dimension of characteristic length of the solid volumetric fraction on the mean and standard deviation of permeability are calculated and discussed. The comparison demonstrates that the heterogeneous solid volumetric fraction can have similar effects as adjusting the empirical constant in the KC equation. A narrow range smaller than mean ± standard deviation from the model agreed with the experimental data well. Incorporating the truncated power-law distribution into the classical KC model predicts a high mean permeability and uncertainty. Both the mean and standard deviation of the permeability decrease with an increasing fractal dimension. Full article

Point and nonpoint wastewater sources have a detrimental, negative effect on agriculture, soil, surface, and groundwater supplies. In this research, a wastewater treatment system made up of a sedimentation tank, a horizontal subsurface flow constructed wetland (HSSF-CW), a vertical subsurface flow constructed wetland (VF-CW), and a storage tank was proposed, designed, and cost estimated. Small populations in underdeveloped nations with dry and semi-arid climates can use the treatment system as an affordable construction, maintenance, and operational solution for wastewater treatment. The system will protect agricultural lands and groundwater from pollution. The system can service 6000 capita and has a wastewater discharge of 780 m³/d in the developing arid region in El-Moghra Oasis western desert of Egypt, where the 1.5 million acres used for the land reclamation project based on groundwater irrigation. The relaxed tanks in a series model based on the areal loading rates and background pollutants concentrations (P-K-C*) was utilized to size the HSSF and VF-CWs. The results indicated that the HSSF-CW design treatment surface area was 2375 m², and the hydraulic surface loading (q) and hydraulic retention time (RT) were 0.33 m/d and 0.55 d, respectively, and utilizing Phragmites australis and Papyrus for the biological treatment. The expected overall cumulative removal efficiencies were 96.7, 70, and 100% for the biological oxygen demand (BOD), total phosphors (TP), and fecal coliforms (FC), respectively. The VF-CW indicates that there was a 2193 m² design treatment surface area, q = 0.36 m/d, and RT of 0.63 d. The expected BOD, TP, and FC removal efficiencies were 75, 33.3, and 92.7%, respectively. In order to simplify the design stages and the cost estimation, design and investment cost curves were established for a population range from 500 to 9000. The total monthly water loss due to evapotranspiration for the HSSF and VF-CWs indicates a range from 3.7 to 8.5%, respectively. The total investment cost analysis for the proposed system corresponding to 780 m³/d wastewater discharge of indicates a total investment cost of EUR 146,804 and EUR 24.46/per-capita equivalent (P.E). This approach can be used by decision makers in the Mediterranean region and Middle Eastern countries to improve the water quality using social and economic criteria, leading to the effective implementation of ecological restoration projects as a low-cost treatment system and adding a nonconventional water source that can be used in irrigation. Full article

Reducing uncertainty in design flood estimates is an essential part of flood risk planning and management. This study presents results from flood frequency estimates and associated uncertainties for five commonly used probability distribution functions, extreme value type 1 (EV1), generalized extreme value (GEV), generalized pareto distribution (GPD), log normal (LN) and log Pearson type 3 (LP3). The study was conducted using Monte Carlo simulation (MCS) and bootstrapping (BS) methods for the 10 river catchments in eastern Australia. The parameters were estimated by applying the method of moments (for LP3, LN, and EV1) and L-moments (for GEV and GPD). Three-parameter distributions (e.g., LP3, GEV, and GPD) demonstrate a consistent estimation of confidence interval (CI), whereas two-parameter distributions show biased estimation. The results of this study also highlight the difficulty in flood frequency analysis, e.g., different probability distributions perform quite differently even in a smaller geographical area. Full article

This paper describes HYDRONET, a telemetry-based prototype of a streamflow monitoring network in the Greek territory, where such data are sparse. HYDRONET provides free and near-real-time online access to data. Instead of commercially available stations, in-house-designed and -built telemetric stations were installed, which reduced the equipment cost by approximately 50%. The labour of hydrometric campaigns was reduced by applying a new maximum-entropy method to estimate the discharge from surface velocity observations. Here, we describe these novelty elements succinctly. The potential of HYDRONET to provide civil protection services is exemplified by a flood warning demonstrator for Kalamata’s City Centre. The network’s operation, including the hydraulic criteria for monitoring site selection, the characteristics of the telemetric equipment, the operational monitoring and hydrometric procedures, and the specifics of data transmission, quality control, and storage are described in detail, along with experiences with problems encountered during this pilot phase. Full article

Wetlands are valuable natural capital and sensitive ecosystems facing significant risks from anthropogenic and climatic stressors. An assessment of the environmental risk levels for wetlands’ dynamic ecosystems can provide a better understanding of their current ecosystem health and functions. Different levels of environmental risk are defined by considering the categories of risk and the probability and severity of each in the environment. Determining environmental risk levels provides a general overview of ecosystem function. This mechanism increases the visibility of risk levels and their values in three distinct states (i.e., low, moderate, and high) associated with ecosystem function. The Bayesian belief network (BBN) is a novel tool for determining environmental risk levels and monitoring the effectiveness of environmental planning and management measures in reducing the levels of risk. This study develops a robust methodological framework for determining the overall level of risks based on a combination of varied environmental risk factors using the BBN model. The proposed model is adopted for a case study of Shadegan International Wetlands (SIWs), which consist of a series of Ramsar wetlands in the southwest of Iran with international ecological significance. A comprehensive list of parameters and variables contributing to the environmental risk for the wetlands and their relationships were identified through a review of literature and expert judgment to develop an influence diagram. The BBN model is adopted for the case study location by determining the states of variables in the network and filling the probability distribution tables. The environmental risk levels for the SIWs are determined based on the results obtained at the output node of the BBN. A sensitivity analysis is performed for the BBN model. We proposed model-informed management strategies for wetland risk control. According to the BBN model results, the SIWs ecosystems are under threat from a high level of environmental risk. Prolonged drought has been identified as the primary contributor to the SIWs’ environmental risk levels. Full article

This study configures the Weather Research and Forecasting (WRF) model with the updated urban fraction for optimal rainfall simulation over Kampala, Uganda. The urban parameter values associated with urban fractions are adjusted based on literature reviews. An extreme rainfall event that triggered a flood hazard in Kampala on 25 June 2012 is used for the model simulation. Observed rainfall from two gauging stations and satellite rainfall from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) are used for model validation. We compared the simulation using the default urban fraction with the updated urban fraction focusing on extreme rainfall amount and spatial-temporal rainfall distribution. Results indicate that the simulated rainfall is overestimated compared to CHIRPS and underestimated when comparing gridcell values with gauging station records. However, the simulation with updated urban fraction shows relatively better results with a lower absolute relative error score than when using default simulation. Our findings indicated that the WRF model configuration with default urban fraction produces rainfall amount and its spatial distribution outside the city boundary. In contrast, the updated urban fraction has peak rainfall events within the urban catchment boundary, indicating that a proper Numerical Weather Prediction rainfall simulation must consider the urban morphological impact. The satellite-derived urban fraction represents a more realistic urban extent and intensity than the default urban fraction and, thus, produces more realistic rainfall characteristics over the city. The use of explicit urban fractions will be crucial for assessing the effects of spatial differences in the urban morphology within an urban fraction, which is vital for understanding the role of urban green areas on the local climate. Full article

Cost-effective remediation is increasingly dependent on high-resolution site characterization (HRSC), which is supposed to be necessary prior to interventions. This paper aims to evaluate the use of low-flow purging and sampling water level data in estimating the horizontal hydraulic conductivity of soils. In a new quali-quantitative view, this procedure can provide much more information and knowledge about the site, reducing time and costs. In case of high heterogeneity along the well screen, the whole procedure, as well as the estimation method, could be less effective and rigorous, with related issues in the purging time. The result showed significant permeability weighted sampling, which could provide different results as the pump position changes along the well screen. The proposed study confirms this phenomenon with field data, demonstrating that the use of multiparameter well logs might be helpful in detecting the behaviour of low-permeability layers and their effects on purging and sampling. A lower correlation between low-flow permeability estimations and LeFranc test results was associated with high heterogeneity along the screen, with a longer purging time. In wells P43, MW08 and MW36, due to the presence of clay layers, results obtained differ for almost one order of magnitude and the purging time increases (by more than 16 min). However, with some precautions prior to the field work, the low-flow purging and sampling procedure could become more representative in a shorter time and provide important hydrogeological parameters such as hydraulic conductivity with many tests and high-resolution related results. Full article

Droughts are natural disasters with a significant impact on the economy and social life. Prolonged droughts can cause even more damage than floods. The novelty of this work lies in the definition of a synthetic drought hydrograph (SDH) which can be derived at each gaging station of a river network. Based on drought hydrographs (DHs) recorded for a selected gaging station, the SDH is statistically characterized and provides valuable information to water managers regarding available water resources during the drought period. The following parameters of the registered drought hydrograph (DH) are proposed: minimum drought discharge $Q_D^{min}$, drought duration $D_D$ and deficit volume $V_D$. All these parameters depend on the drought threshold $Q_T$, which is chosen based on either pure hydrological considerations or on socio-economic consequences. For the same statistical parameters of the drought, different shapes of the synthetic drought hydrograph (SDH) can be considered. In addition, the SDH varies according to the probabilities of exceedance of the minimum drought discharge and deficit volume. Full article

In environmental flows, field and laboratory measurements of suspended sediments show two kinds of concentration profiles. For coarse sediments, a near-bed upward convex profile is observed beneath the main upward concave profile. In this study, we consider two 1-DV models, namely, the classical advection–diffusion equation (ADE) based on the gradient diffusion model, and the kinetic model. Both need sediment diffusivity, which is related to the eddy viscosity, and an y-dependent β-function (i.e., the inverse of the turbulent Schmidt number). Our study shows that the kinetic model reverts to the classical ADE with an “apparent” settling velocity or sediment diffusivity. For the numerical resolution of the ADE, simple and accurate tools are provided for both the sediment diffusivity and hindered settling. The results for the concentration profiles show good agreement with the experimental data. An interpretation of the concentration profiles is provided by two “criteria” for shapes. The main for steady open-channel flows shows that the shape of the concentration profiles in the Cartesian coordinate depends on the vertical distribution of the derivative of $R$ (the ratio between the sediment diffusivity and the settling velocity of the sediments): dR/dy > −1 for the upward concave concentration profile while dR/dy < −1 for the near-bed upward convex profile. A generalization is proposed for oscillatory flows over sand ripples, where the time-averaged concentration profiles in the semi-log plots are interpreted by a relation between the second derivative of the logarithm of the concentration and the derivative of the product between the sediment diffusivity and an additional parameter related to the convective sediment entrainment process. Full article

Low-lying coastal communities are often threatened by compound flooding (CF), which can be determined through the joint occurrence of storm surges, rainfall and river discharge, either successively or in close succession. The trivariate distribution can demonstrate the risk of the compound phenomenon more realistically, rather than considering each contributing factor independently or in pairwise dependency relations. Recently, the vine copula has been recognized as a highly flexible approach to constructing a higher-dimensional joint density framework. In these, the parametric class copula with parametric univariate marginals is often involved. Its incorporation can lead to a lack of flexibility due to parametric functions that have prior distribution assumptions about their univariate marginal and/or copula joint density. This study introduces the vine copula approach in a nonparametric setting by introducing Bernstein and Beta kernel copula density in establishing trivariate flood dependence. The proposed model was applied to 46 years of flood characteristics collected on the west coast of Canada. The univariate flood marginal distribution was modelled using nonparametric kernel density estimation (KDE). The 2D Bernstein estimator and beta kernel copula estimator were tested independently in capturing pairwise dependencies to establish D-vine structure in a stage-wise nesting approach in three alternative ways, each by permutating the location of the conditioning variable. The best-fitted vine structure was selected using goodness-of-fit (GOF) test statistics. The performance of the nonparametric vine approach was also compared with those of vines constructed with a parametric and semiparametric fitting procedure. Investigation revealed that the D-vine copula constructed using a Bernstein copula with normal KDE marginals performed well nonparametrically in capturing the dependence of the compound events. Finally, the derived nonparametric model was used in the estimation of trivariate joint return periods, and further employed in estimating failure probability statistics. Full article

Hydropolitics is defined as the systematic study of conflict and cooperation in transboundary water basins, affecting around 40% of the world’s population. There has been great advancement in studies endeavoring to explore linkages between hydropolitical drivers and hydropolitical situations in transboundary basins. To add to this, we posit that hydropolitics would benefit from a system thinking approach that has remained less addressed in the literature. For this purpose, considering a transboundary basin as a system, this study is built on the main principle of system dynamics, which implies that a system’s structure determines its behavior. Incorporating system archetypes into hydropolitics can provide a framework for assessing hydropolitical behavior according to the potential structure of archetypes. In this paper, we discuss five hydropolitical system archetypes and their feedback loop structures, the required physical environments, and potential unintended behavior over time. Finally, an example of a diagnostic checklist is presented that will help riparian states recognize patterns of behavior they may face in the future. This paper lays the groundwork for gaining insight into using system archetypes in projecting plausible hydropolitical behaviors and understanding past behaviors in transboundary basins. Full article

This study summarizes reviews on climate change’s impact on the water environment and hydrological regime. The results indicate a strong relationship between the climatological parameters and hydrological patterns. This relationship can be determined in two steps: (1) define the variations in climatological factors, particularly temperature and precipitation, and (2) measure the variations in runoff and inflows to streams and river systems using different statistical and global climate modeling approaches. It is evident that the increasing global temperatures have significant positive effects on runoff variations and evapotranspiration. Similarly, the increase in temperature has speeded up the melting of glaciers and ice on hilly terrains. This is causing frequent flash floods and a gradual rise in the sea level. These factors have altered the timing of stream flow into rivers. Furthermore, the accumulation of greenhouse gases, variations in precipitation and runoff, and sea-level rise have significantly affected freshwater quality. These effects are likely to continue if timely mitigation and adaptation measures are not adopted. Full article

Hurst’s seminal characterisation of long-term persistence (LTP) in geophysical records more than seven decades ago continues to inspire investigations into the Hurst phenomenon, not just in hydrology and climatology, but in many other scientific fields. Here, we present a new theoretical development based on stochastic Hurst–Kolmogorov (HK) dynamics that explains the recent finding that the Hurst coefficient increases with the spatial scale of averaging for regional annual precipitation. We also present some further results on the scale dependence of H in regional precipitation, and reconcile an apparent inconsistency between sample results and theory. LTP in average basin scale precipitation is shown to be consistent with LTP in the annual flows of some large river basins. An analysis of the crossing properties of precipitation deficits in regions exhibiting LTP shows that the Hurst coefficient can be a parsimonious descriptor of the risk of severe precipitation deficits. No evidence is found for any systematic trend in precipitation deficits attributable to anthropogenic climate change across the regions analysed. Future precipitation deficit risk assessments should, in the first instance, be based on stochastic HK simulations that encompass the envelope of uncertainty synonymous with LTP, and not rely exclusively on GCM projections that may not properly capture long-term natural variability in the climate. Some views and opinions are expressed on the implications for policy making in sustainable water resources management. Full article

Changes in water resources within basins can significantly impact ecosystems, agriculture, and biodiversity, among others. Basins in northern Canada have a cold climate, and the recent changes in climate can have a profound impact on water resources in these basins. Therefore, it is crucial to study long term trends in water flow as well as their influential factors, such as temperature and precipitation. This study focused on analyzing long term trends in water flow across the Athabasca River Basin (ARB) and Peace River Basin (PRB). Long term trends in temperature and precipitation within these basins were also studied. Water flow data from 18 hydrometric stations provided by Water Survey of Canada were analyzed using the Mann-Kendall test and Sen’s slope. In addition, hybrid climate data provided by Alberta Environment and Parks at approximately 10 km spatial resolution were analyzed for the ARB and its surrounding regions during 1950–2019. Trend analysis was performed on the water flow data on monthly, seasonal, and annual scales, and the results were cross-checked with trends in temperature and precipitation and land use and land cover data. The overall temperature across the basins has been increasing since 1950, while precipitation showed an insignificant decrease during this period. Winter water flow in the upper ARB has been slowly and steadily increasing since 1956 because of the rising temperatures and the subsequent slow melting of snowpacks/glaciers. The warm season flows in the middle and lower subregions declined up to 1981, then started to show an increasing trend. The middle and lower ARB exhibited a rapid increase in warm-season water flow since 2015. A similar trend change was also observed in the PRB. The gradual increase in water flow observed in the recent decades may continue by the mid-century, which is beneficial for agriculture, forestry, fishery, and industry. However, climate and land cover changes may alter the trend of water flow in the future; therefore, it is important to have a proper management plan for water usage in the next decades. Full article

Zerovalent iron nanoparticles (nZVI) are becoming one of the most widely recommended nanomaterials for soil and groundwater remediation. However, when nZVI are injected in the groundwater flow, the behavior (mobility, dispersion, distribution) is practically unknown. This fact generally results in the use of enormous quantities of them at the field scale. The uncertainties are on the effective volumes reached from the plume of nZVI because their tendency to aggregate and their weight can cause their settling and deposition. So, the mobility of nanoparticles is a real issue, which can often lead to inefficient or expensive soil remediation. Furthermore, there is another aspect that must be considered: the fate of these nZVI in the groundwater and their possible impact on the subsoil environment. All these considerations have led us to propose an application of nZVI simulating the permeation technique through a laboratory experience, finalized to have a better, or even simpler description of their real behavior when injected in a flow in the subsoil. A two-dimensional laboratory-scale tank was used to study the dispersion and transport of nZVI. A nZVI solution, with a concentration equal to 4.54 g/L, was injected into glass beads, utilized as porous medium. The laboratory experiment included a digital camera to acquire the images. The images were then used for calibrating a numerical model. The results of the mass balance confirm the validity of the proposed numerical model, obtaining values of velocity (5.41 × 10⁻³ m/s) and mass (1.9 g) of the nZVI of the same order of those from the experimental tests. Several information were inferred from both experimental and numerical tests. Both demonstrate that nZVI plume does not behave as a solute dissolved in water, but as a mass showing its own mobility ruled mainly from the buoyancy force. A simple simulation of a tracer input and a nZVI plume are compared to evidence the large differences between their evolution in time and space. This means that commercial numerical models, if not corrected, cannot furnish a real forecast of the volume of influence of the injected nZVI. Further deductions can be found from the images and confirmed by means the numerical model where the detachment effect is much smaller than the attachment one (ratio k_d/k_a = 0.001). From what is reported, it is worthwhile to pay attention on the localization of the contaminants source/plume to reach an effective treatment and it is important to go further in the improvement of solution for the limiting the nanoparticles aggregation phenomenon. Full article

Deriving the proper structure of lotic habitats, namely the structuralization of lotic habitats, is crucial to monitoring and modeling water quality on a large scale. How to structuralize complicated lotic habitats for practical use remains challenging. This study novelly integrates remote sensing, geographic information system (GIS), and computer vision techniques to structuralize complicated lotic habitats. A method based on Sentinel-2 imagery and weighted focal statistic convolution (WFSC) is developed to structuralize the complicated lotic habitats into discrete river links. First, aquatic habitat image objects are delineated from Sentinel-2 imagery using geographic object-based image analysis (GEOBIA). These lotic habitat image objects are then separated from lentic habitat image objects using a hydrologically derived river network as a reference. Second, the binary image of the lotic habitat image objects is converted to a fuzzy magnitude surface using WFSC. The ridgelines on the magnitude surface are traced as the centerlines of river links. Finally, the centerlines of river links are used to split the complicated lotic habitats into discrete river links. Essential planar geometric attributes are then numerically derived from each river link. The proposed method was successfully applied to the braided river network in the Mobile River Basin in the U.S. The results indicate that the proposed method can properly structuralize lotic habitats with high spatial accuracy and correct topological consistency. The proposed method can also derive essential attributes that are difficult to obtain from conventional methods on a large scale. With sufficient measurements, a striking width–abundance pattern has been observed in our study area, indicating a promising logarithmic law in lotic habitat abundance. Full article

Rational Water Resources Management requires effective collaboration between decision-makers involved in the operational management of water resources and scientists, who can allow them to operate in an informed manner through forecasting and decision-making tools. In this article, we show the potential benefits resulting from this collaboration through the description of the emblematic case of Lake Como. The article describes the real case of a collaborative experience between decision makers, who made an effort to highlight and clarify the real management problems to scientists, who in turn needed to understand all the facets of the decision-making process prior to formulating the problem in mathematical terms and incorporating the solution into a decision support system. The resulting tool, which makes extensive hidden use of probabilistic forecasts, stochastic optimization, and Bayesian decision techniques, resulted in a user-friendly environment. After six months of testing, the tool proved to be essential for decision-making and has been in use on a daily basis since 1997. Full article

The development of a computationally efficient machine learning-based framework to understand the underlying causes for biases in climate model simulated fields is presented in this study. The framework consists of a two-step approach, with the first step involving the development of a Random Forest (RF) model, trained on observed data of the climate variable of interest and related predictors. The second step involves emulations of the climate variable of interest with the RF model developed in step one by replacing the observed predictors with those from the climate model one at a time. The assumption is that comparing these emulations with that of a reference emulation driven by all observed predictors can shed light on the contribution of respective predictor biases to the biases in the climate model simulation. The proposed framework is used to understand the biases in the Global Environmental Multiscale (GEM) model simulated surface soil moisture (SSM) for the April–September period, over a domain covering part of north-east Canada. The grid cell-based RF model, trained on daily SSM and related climate predictors (water availability, 2 m temperature, relative humidity, snowmelt, maximum snow water equivalent) from the fifth generation European Centre for Medium-Range Weather Forecasts reanalysis (ERA5), demonstrates great skill in emulating SSM, with root mean square error of 0.036. Comparison of the five RF emulations based on GEM predictors with that based on ERA5 predictors suggests that the biases in the mean April–September SSM can be attributed mainly to biases in three predictors: water availability, 2 m temperature and relative humidity. The regions where these predictors contribute to biases in SSM are mostly collocated with the regions where they are shown to be the among the top three influential predictors through the predictor importance analysis, i.e., 2 m temperature in the southern part of the domain, relative humidity in the northern part of the domain and water availability over rest of the domain. The framework, without having to undertake expensive simulations with the climate model, thus successfully identifies the main causes for SSM biases, albeit with slightly reduced skill for heavily perturbed simulations. Furthermore, identification of the causes for biases, by informing targeted climate model improvements, can lead to additional reductions in computational costs. Full article

This study aimed at the analysis and modelling of the groundwater temperature at the water table in different regions of Slovakia. In the first part, the analysis of the long-term trends of air and soil/ground temperature to a depth of 10 m is presented. The average annual soil/groundwater temperatures at different depths were the same but lower than the annual average air temperature by about 0.8 °C. The long-term trend analysis of the air temperature and soil temperature at a depth of up to 10 m in Slovakia showed that the air and soil/ground water temperature have risen by 0.6 and 0.5 °C, respectively, per decade over the past 30 years. The second part of the study aimed at modelling the daily groundwater temperatures at depths of 0.6–15 m below the surface. The simple groundwater temperature model was constructed based on a one-dimensional differential Fourier heat conduction equation. The given model can be used to estimate future groundwater temperature trends using regional air temperature projections calculated for different greenhouse gas emission scenarios. Full article

Drinking water systems’ energy footprints depend mostly on the source, quality, and volume of water supply, but also on local temperature and precipitation, both of which are changing with the global climate. From a previous survey, we develop an equation for modeling relative changes in U.S. water utilities’ annual energy use, in which their energy use increases with temperature and decreases with precipitation. To demonstrate, we insert gridded projections from three scenarios in the EPA’s Climate Resilience Evaluation and Awareness Tool (CREAT) and compare 2035 and 2060 periods with a 1981–2010 baseline. Averaged over the continental United States, the 2060 central scenario projects 2.7 °C warmer temperatures and 2.9 cm more annual precipitation. For the same water demand, we estimate that these conditions will cause U.S. water systems’ energy use to change by −0.7% to 13.7% depending on the location (average 8.5% across all grid cells). Warming accounts for a general increase, and local changes in precipitation can add to or subtract from it. We present maps showing the spatial variability for each scenario. Water systems are essential infrastructure that support sustainable communities, and the analysis underscores their needs for energy management, renewable energy, water conservation, and climate change resilience. Full article

Understanding the changes in climate and land use/land cover (LULC) over time is important for developing policies for minimizing the socio-economic impacts of riverine floods. The present study evaluates the influence of hydro-climatic factors and anthropogenic practices related to LULC on floods in the Kelani River Basin (KRB) in Sri Lanka. The gauge-based daily precipitation, monthly mean temperature, daily discharges, and water levels at sub-basin/basin outlets, and both surveyed and remotely sensed inundation areas were used for this analysis. Flood characteristics in terms of mean, maximum, and number of peaks were estimated by applying the peak over threshold (POT) method. Nonparametric tests were also used to identify the climatic trends. In addition, LULC maps were generated over the years 1988–2017 using Landsat images. It is observed that the flood intensities and frequencies in the KRB have increased over the years. However, Deraniyagala and Norwood sub-basins have converted to dry due to the decrease in precipitation, whereas Kithulgala, Holombuwa, Glencourse, and Hanwella showed an increase in precipitation. A significant variation in atmospheric temperature was not observed. Furthermore, the LULC has mostly changed from vegetation/barren land to built-up in many parts of the basin. Simple correlation and partial correlation analysis showed that flood frequency and inundation areas have a significant correlation with LULC and hydro-climatic factors, especially precipitation over time. The results of this research will therefore be useful for policy makers and environmental specialists to understand the relationship of flood frequencies with the anthropogenic influences on LULC and climatic factors. Full article

Propagation of pluvial floods in urban areas, occurring with return time periods of few years, can be well solved using dual models accounting for the mutual relationship between the water level in the streets and the discharges inside the sewer pipes. The extended WEC-flood model (EWEC), based on the use of unstructured triangular meshes and a diffusive formulation of the momentum equations in both the 2D and the 1D lower domains, is presented along with its novelty, limits, and advantages. The model is then applied to a small computational domain in the Palermo area, where only some ‘hard’ data given by one rain gauge has been used for calibration and validation, along with other ‘soft’ data like yes/no surcharge observations and water depths available from photos and interviews. Model input data are mainly geometrical parameters, and calibration parameters are restricted only to average Manning coefficients. In the test case a very good validation has been obtained of three historical events using the EWEC model, with only one average Manning coefficient calibrated using other two historical events. Full article

Assessing fish habitat suitability in a data-scarce tidal river is often challenging due to the absence of continuous water quantity and quality records. This study is comprised of an intensive field study on a 42 km reach which recorded bathymetry and physical water quality parameters (pH, electroconductivity, dissolved oxygen, and total dissolved solids) testing and corresponding water levels and velocity. Frequent water sampling was carried out on 17 out of 90 locations for laboratory water quality tests. Based on this, an interpolation technique, i.e., Inverse Distance Weighted (IDW), generates a map in a Geographic Information System (GIS) environment using ArcGIS software to determine the river water quality parameters. Additionally, a hydrodynamic model study was conducted to simulate hydraulic parameters using Delft3D software followed by a water quality distribution. During validation, the Delft3D-simulated water quality could reasonably mimic most field data, and GIS featured dissolved oxygen. The overall water quality distribution showed a lower dissolved oxygen level (~3 mg/L) in the industrial zone compared to the other two zones during the study period. On the other hand, these validated hydraulic properties were applied in the Physical Habitat Simulation Model (PHABSIM) set up to conduct the hydraulic habitat suitability for Labeo rohita (Rohu fish). Thus, the validated model could represent the details of habitat suitability in the studied river for future decision support systems, and this study envisaged applying it to other similar rivers. Full article

During recent decades, the South-Central part of Chile has shown strong vulnerability due to the effects of land use change (LUC). The interaction of these changes with local hydrology has not been adequately investigated and is poorly understood, especially in mountainous areas under irrigated agriculture. We applied the SWAT + agrohydrological model to study the effects of LUC on hydrological fluxes in the Longaví catchment, Maule region, South-Central Chile. Land use maps (LUMs) from 1997, 2009, and 2016 were used in conjunction with a 41-year (1979–2019) hydro-meteorological series of daily observations as forcing data. The dominant changes in land use during the study period relate to agriculture, shrublands, forestry of exotic species, and urban sprawl. First, the LUM of 1997 was used for model setup, sensitivity analysis, calibration, and validation. Second, the impact of LUC documented through LUMs 2009 and 2016 was analyzed. Our analysis clearly reveals that the overall water balance and internal moisture redistribution in the Longaví catchment have been considerably affected by decreases in precipitation, changes in land use and water use practices. Unless a comprehensive regulatory system is introduced that addresses current climatic conditions and territorial use, it is likely that the decrease in water resources will persist and worsen through climate changes. Full article

Streamflow measurements provide valuable hydrological information but, at the same time, are difficult to obtain. For this reason, discharge records of regular intervals are usually obtained indirectly by a stage–discharge rating curve, which establishes a relation between measured water levels to volumetric rate of flow. Rating curves are difficult to develop because they require simultaneous measurements of discharge and stage over a wide range of stages. Furthermore, the shear forces generated during flood events often change the streambed shape and roughness. As a result, over long periods, the stage–discharge measurements are likely to form clusters to which different stage–discharge rating curves apply. For the identification of these clusters, various robust statistical approaches have been suggested by researchers, which, however, have not become popular among practitioners because of their complexity. Alternatively, various researchers have employed machine learning approaches. These approaches, though motivated by the time-dependent nature of the rating curves, handle the data as of stationary origin. In this study, we examine the advantages of a very simple technique: use time as one of the machine learning model inputs. This approach was tested in three real-world case studies against a statistical method and the results indicated its potential value in the development of a simple tool for rating curves suitable for practitioners. Full article

In this article, we present the use of the coupled land surface model and groundwater flow model SWAT-MODFLOW with the decision support tool WEAP (Water Evaluation and Planning software) to predict future surface-water abstraction scenarios in a complex river basin under conditions of climate change. The modelling framework is applied to the Dee River catchment in Wales, United Kingdom. Regarding hydrology, the coupled model improves overall water balance and low-streamflow conditions compared with a stand-alone SWAT model. The calibrated SWAT-MODFLOW is employed with high-resolution climate model data from the UKCP18 project with the future scenario of RCP85 from 2020 to 2040. Then, water supply results from SWAT-MODFLOW are fed into WEAP as input for the river reach in the downstream region of the river basin. This system is utilized to create various future scenarios of the surface-water abstraction of public water supply in the downstream region—maximum licensed withdraw, 50% authorized abstractions, monthly time series with 1% increases in water use, and maximum water withdraw per year based on historical records repeated every year with 1% increases in water use—to estimate the unmet demands and streamflow requirement. This modelling approach can be used in other river basins to manage scenarios of supply and demand. Full article

The Harvard Water Program is more than sixty years old. It was directed by an academic Steering Committee consisting of the professors of Government and Political Science, Planning, Economics, and Water Engineering. In 2022 we would add to the notional Steering Committee the professors of Ecology, Sociology and Water Law, calling it the augmented Harvard eutopian approach to the design and operation of Water Resource Systems. We use the Greek word ‘eu-topos’ to mean ‘a good place’, figuratively speaking, and ‘dys-topos’ its antonym, ‘not a good place’. By opposing eutopia and dystopia (latin forms) (Utopian literature begins with Thomas More’s (1478–1535) fictional socio-political satire “Utopia”, written in Latin and published in 1516: “Libellus vere aureus, nec minus salutaris quam festivus, de optimo rei publicae statu deque nova insula Utopia”. “A little, true book, not less beneficial than enjoyable, about how things should be in a state and about the new island Utopia” [Wikipedia translation]. He coined the word ‘utopia’ from the Greek ou-topos meaning ‘no place’ or ‘nowhere’. It was a pun-the almost identical Greek word eu-topos means ‘a good place’), we pass judgement on three Irish case studies, in whole and in part. The first case study deals with the dystopian measurement of the land phase of the hydrological cycle. The system components are distributed among many government departments that see little need to cooperate, leading to proposition 1: A call for a new Water Law. The second case study deals with a project to restore a 200 km² polder landscape to its condition in 1957. The project came to the University with an hypothetical cause of the increased flooding and a tentative solution: dredge the Cashen estuary of its sand, speeding the flow of sluiced water to the sea, and the status quo ante would be restored. The first scientific innovation was the proof that restoration by dredging is impossible. Pumping is the only solution, but it raises disruptive questions that are not covered by Statute. The second important innovation was the discovery in the dynamic water balance, of large leakage into the polders, either around or between sluiced culverts, when the flap valves are nominally closed, impacting both their maintenance and minimization of pumping. Discussions on our findings ended in dystopian silence. Hence proposition 2: Moving towards eutopia may only be possible with a change in the Law. The third case study concerns the protection of Cork City from flooding: riverine, tidal and groundwater. The government’s “emerging solution” consists of major physical intervention in the city centre, driven hard against local opposition, as the only possible solution. Two hydro-electric reservoirs upstream were largely ignored as part of a solution because the relevant Statute did not mandate their use for flood control. The Supreme Court has recently overturned this interpretation of the governing Statute. A new theory of flood control with a cascade of reservoirs, dams and weirs is the scientific innovation here. Once more these findings have been greeted by government with dystopian silence. Hence proposition 3: Re-open the design process to find several much better solutions, approximating a eutopian water world. Full article

One of the most important parts of the hydrological cycle is evapotranspiration (ET). Accurate estimates of ET in irrigated regions are critical to the planning, control, and regulation of agricultural natural resources. Accurate ET estimation is necessary for agricultural irrigation scheduling. ET is a nonlinear and complex process that cannot be calculated directly. Reference evapotranspiration (RET) and potential evapotranspiration (PET) are two primary forms of ET. The ideas, equations, and application areas for PET and RET are different. These two terms have been confused and used interchangeably by researchers. Therefore, terminology clarification is necessary to ensure their proper use. The research indicates that PET and RET concepts have a long and distinguished history. Thornthwaite devised the original PET idea, and it has been used ever since, although with several improvements. The development of RET, although initially confused with that of PET, was formally defined as a standard method. In this study, the Preferred Reporting Item for Systematic reviews and Meta-Analysis (PRISMA) was used. Equations for RET estimation were retrieved from 44 research articles, and equations for PET estimation were collected from 26 studies. Both the PET and RET equations were divided into three distinct categories: temperature-based, radiation-based, and combination-based. The results show that, among temperature-based equations for PET, Thornthwaite’s (1948) equation was mentioned in 12,117 publications, whereas among temperature-based equations for RET, Hargreaves and Samani’s (1985) equation was quoted in 3859 studies. Similarly, Priestley (1972) had the most highly cited equation in radiation-based PET equations (about 6379), whereas Ritchie (1972) had the most highly cited RET equations (around 2382) in radiation-based equations. Additionally, among combination-based PET equations, Penman and Monteith’s (1948) equations were cited in 9307 research studies, but the equations of Allen et al. (1998) were the subject of a significant number of citations from 23,000 publications. Based on application, PET is most often applied in the fields of hydrology, meteorology, and climatology, whereas RET is more frequently utilized in the fields of agronomy, agriculture, irrigation, and ecology. PET has been used to derive drought indices, whereas RET has been employed for single crop and dual crop coefficient approaches. This work examines and describes the ideas and methodologies, widely used equations, applications, and advanced approaches associated with PET and RET, and discusses future enhancements to increase the accuracy of ET calculation to attain accurate agricultural irrigation scheduling. The use of advanced tools such as remote sensing and satellite technologies, in addition to machine learning algorithms, will help to improve the accuracy of PET and RET estimates. Researchers will be able to distinguish between PET and RET in the future with the use of the study’s results. Full article

Worldwide, floods are the most common and widespread type of disaster during the 21st century. These phenomena have caused human fatalities, destruction of infrastructures and properties, and other significant impacts associated with human socioeconomic activities. In this study, the exposure of infrastructure (social, industrial and commercial, transportation) and residential areas to floods in Greek territory was considered. To accomplish the goal of the current study, freely available data from OpenStreetMap and Corine 2018 databases were collected and analyzed, as well as the flood extent zones derived under the implementation of the European Union’s (EU) Floods Directive. The results will be useful for policy-making and prioritization of prone areas based not only on the extent of flood cover but also on the possible affected infrastructure types. Moreover, the aforementioned analysis could be the first step toward an integrated national-wide flood risk assessment. Full article

We compare three hydrological models of different complexities, GR4H (lumped, continuous), SMASH (distributed, continuous), and MARINE (distributed, event-based), for Mediterranean flash flood modeling. The objective was to understand how differently they simulate the catchment’s behavior, in terms of outlet discharge and internal dynamics, and how these can help to improve the relevance of the models. The methodology involved global sensitivity analysis, calibration/validation, and signature comparison at the event scale with good performances. For all models, we found transfer parameters to be sensitive in the case of Gardon and production parameters in the case of Ardeche. The non-conservative flow component of GR4H was found to be sensitive and could benefit the distributed models. At the event scale, the process-based MARINE model at finer resolution outperformed the two continuous hourly models at flood peak and its timing. SMASH, followed by GR4H, performed better in the volume of water exported. Using the operational surface model SIM2 to benchmark the soil moisture simulated by the three models, MARINE (initialized with SIM1) emerged as the most accurate. GR4H followed closely, while SMASH was the least accurate. Flexible modeling and regionalization should be developed based on multi-source signatures and worldwide physiographic databases. Full article

In Water Resources Planning and Management, decision makers, although unsure of future outcomes, must take the most reliable and assuring decisions. Deterministic and probabilistic prediction techniques, combined with optimization tools, have been widely used to meet the objective of improving planning as well as management. Bayesian decision approaches are available to link probabilistic predictions to optimized decision schemes, but scientists are not fully able to express themselves in a language familiar to decision makers, who fear basing their decisions on “uncertain” forecasts in the vain belief that deterministic forecasts are more informative and reliable. This situation is even worse in the case of climate change projections, which bring additional degrees of uncertainty into the picture. Therefore, a need emerges to create a common approach and means of communication between scientists, who deal with optimization tools, probabilistic predictions and long-term projections, and operational decision makers, who must be facilitated in understanding, accepting, and acknowledging the benefits arising from operational water resources management based on probabilistic predictions and projections. Our aim here was to formulate the terms of the problem and the rationale for explaining and involving decision makers with the final objective of using probabilistic predictions/projections in their decision-making processes. Full article