Editor’s Choice Articles

This paper addresses the questions of acceptable upper limits for storage development and how best to deploy storage capacity in the long-term planning of built surface water storage in river basins. Storage-yield curves are used to establish sustainable storage development pathways and limits for a basin under a range of environmental flow release scenarios. Optimal storage distribution at a sub-basin level, which complies with an identified storage development pathway, can also be estimated. Two new indices are introduced—Water Supply Sustainability and Environmental Flow Sustainability—to help decide which pathways and management strategies are the most appropriate for a basin. Average pathways and conservative and maximum storage limits are illustrated for two example basins. Conservative and maximum withdrawal limits from storage are in the range of 45–50% and 60–65% of the mean annual runoff. The approach can compare the current level of basin storage with an identified pathway and indicate which parts of a basin are over- or under-exploited. A global storage–yield–reliability relationship may also be developed using statistics of annual basin precipitation to facilitate water resource planning in ungauged basins. Full article

Fluoride ions present in drinking water are beneficial to human health when at proper concentration levels (0.5–1.5 mg L⁻¹), but an excess intake of fluoride (>1.5 mg L⁻¹) may pose several health problems. In this context, reducing high fluoride concentrations in water is a major worldwide challenge. The World Health Organization has recommended setting a permissible limit of 1.5 mg L⁻¹. The application of electrocoagulation (EC) processes has received widespread and increasing attention as a promising treatment technology and a competitive treatment for fluoride control. EC technology has been favourably applied due to its economic effectiveness, environmental versatility, amenability of automation, and low sludge production. This review provides more detailed information on fluoride removal from water by the EC process, including operating parameters, removal mechanisms, energy consumption, and operating costs. Additionally, it also focuses attention on future trends related to improve defluoridation efficiency. Full article

Owing to the reduction of surface-water resources and frequent droughts, the exploitation of groundwater resources has faced critical challenges. For optimal management of these valuable resources, careful studies of groundwater potential status are essential. The main goal of this study was to determine the optimal network structure of a Bayesian network (BayesNet) machine-learning model using three metaheuristic optimization algorithms—a genetic algorithm (GA), a simulated annealing (SA) algorithm, and a Tabu search (TS) algorithm—to prepare groundwater-potential maps. The methodology was applied to the town of Baghmalek in the Khuzestan province of Iran. For modeling, the location of 187 springs in the study area and 13 parameters (altitude, slope angle, slope aspect, plan curvature, profile curvature, topography wetness index (TWI), distance to river, distance to fault, drainage density, rainfall, land use/cover, lithology, and soil) affecting the potential of groundwater were provided. In addition, the statistical method of certainty factor (CF) was utilized to determine the input weight of the hybrid models. The results of the OneR technique showed that the parameters of altitude, lithology, and drainage density were more important for the potential of groundwater compared to the other parameters. The results of groundwater-potential mapping (GPM) employing the receiver operating characteristic (ROC) area under the curve (AUC) showed an estimation accuracy of 0.830, 0.818, 0.810, and 0.792, for the BayesNet-GA, BayesNet-SA, BayesNet-TS, and BayesNet models, respectively. The BayesNet-GA model improved the GPM estimation accuracy of the BayesNet-SA (4.6% and 7.5%) and BayesNet-TS (21.8% and 17.5%) models with respect to the root mean square error (RMSE) and mean absolute error (MAE), respectively. Based on metric indices, the GA provides a higher capability than the SA and TS algorithms for optimizing the BayesNet model in determining the GPM. Full article

A distributed-framework basin modeling system (DFBMS) was developed to simulate the runoff generation and movement on a basin scale. This study is part of a series of papers on DFBMS that focuses on the hydraulic calculation methods in runoff concentration on underlying surfaces and flow movement in river networks and lakes. This paper introduces the distributed-framework river modeling system (DF-RMS) that is a professional modeling system for hydraulic modeling. The DF-RMS contains different hydrological feature units (HFUs) to simulate the runoff movement through a system of rivers, storage units, lakes, and hydraulic structures. The river network simulations were categorized into different types, including one-dimensional river branch, dendritic river network, loop river network, and intersecting river network. The DF-RMS was applied to the middle and downstream portions of the Huai River Plain in China using different HFUs for river networks and lakes. The simulation results showed great consistency with the observed data, which proves that DF-RMS is a reliable system to simulate the flow movement in river networks and lakes. Full article

Precipitation, throughfall, stemflow, and soil water content were measured, whereas interception, transpiration, evaporation, deep percolation, and soil water recharge were estimated in three plots, including oak (Lithocarpus glaber), Chinese fir (Cunninghamia lanceolata) forestlands, and maize (Zea mays) farmland in the Three Gorges Reservoir in China. A physical process-based model (CoupModel) was set up with climatic measurements as input and was calibrated with throughfall and vertical frequency domain reflectometry measurements from January 2018 to December 2019. Simulated values of soil moisture were fairly consistent with measured ones, with a determination coefficient (R²) of 0.73–0.91. Evapotranspiration was the main output of water balance, with a percentage of up to 61%, and such output was ranked as follows: oak forest (720 mm/y) > Chinese fir forest (700 mm/y) > maize farmland (600 mm/y). Afforestation influenced water balance, and water recharge was generally less significant in oak forestland than in Chinese fir forestland. Annual simulated deep percolation decreased by 60 mm for oak and 47 mm for Chinese fir compared with that for farmland (452 mm/y) and even more significantly in wet years. This decrease was mainly attributed to increased interception (122–159 mm/y) and transpiration (49–84 mm/y) after afforestation. Simulations indicated that vegetation species significantly influenced the magnitude of water balance components, calling for further attention to the selection of regrown tree species in the planning for afforestation projects, particularly for such projects that aim to improve the quantity of water infiltrating groundwater. Soil and water conservation measures should also be applied scientifically when converting farmland to forest in this area, particularly in the oak forest stand. Full article

Climatic change is affecting streamflow regimes of the permafrost region, altering mean and extreme streamflow conditions. In this study, we analyzed historical trends in annual mean flow (Q_mean), minimum flow (Q_min), maximum flow (Q_max) and Q_max timing across 84 hydrometric stations in the permafrost region of Canada. Furthermore, we related streamflow trends with temperature and precipitation trends, and used a multiple linear regression (MLR) framework to evaluate climatic controls on streamflow components. The results revealed spatially varied trends across the region, with significantly increasing (at 10% level) Q_min for 43% of stations as the most prominent trend, and a relatively smaller number of stations with significant Q_mean, Q_max and Q_max timing trends. Temperatures over both the cold and warm seasons showed significant warming for >70% of basin areas upstream of the hydrometric stations, while precipitation exhibited increases for >15% of the basins. Comparisons of the 1976 to 2005 basin-averaged climatological means of streamflow variables with precipitation and temperature revealed a positive correlation between Q_mean and seasonal precipitation, and a negative correlation between Q_mean and seasonal temperature. The basin-averaged streamflow, precipitation and temperature trends showed weak correlations that included a positive correlation between Q_min and October to March precipitation trends, and negative correlations of Q_max timing with October to March and April to September temperature trends. The MLR-based variable importance analysis revealed the dominant controls of precipitation on Q_mean and Q_max, and temperature on Q_min. Overall, this study contributes towards an enhanced understanding of ongoing changes in streamflow regimes and their climatic controls across the Canadian permafrost region, which could be generalized for the broader pan-Arctic regions. Full article

Here we review an extensive series of studies of Barataria Basin, an economically and ecologically important coastal basin of the Mississippi Delta. Human activity has greatly altered the hydrology of the basin by decreasing riverine inflows from leveeing of the river and its distributaries, increasing runoff with high nutrient concentrations from agricultural fields, and channelization of wetlands of the basin interior that has altered flow paths to often bypass wetlands. This has resulted in degraded water quality in the upper basin and wetland loss in the lower basin. Trophic state analysis found the upper basin to be eutrophic and the lower basin to be mesotrophic. Gross aquatic primary production (GAPP) was highest in the upper basin, lowest in the mid basin, and intermediate in the lower basin. Forested wetlands in the upper basin have degraded over the past several decades due to increased periods of flooding, while there has been massive loss of emergent wetlands in the lower basin due to increasing water levels and pervasive alteration of hydrology. Restoration will entail reconnection of waterways with surrounding wetlands in the upper basin, and implementation of river sediment diversions, marsh creation using dredged sediments and barrier island restoration. Findings from this review are discussed in terms of the functioning of deltas globally. Full article

The upstream Yangtze River is located in the southwest of central China, where it flows through several ecosystems and densely populated regions that constitute a unique complex coupled system. To determine how the characteristics of supply and demand in a water-coupled system will vary under the influence of climate change and human activity in this area in the next 85 years, the upper Yangtze basin was considered as the study area and was divided into seven sub-basins according to seven main control sections: Shigu, Panzhihua, Xiluodu, Xiangjiaba, Zhutuo, Cuntan, and Yichang; a method for water supply and demand research considering climate change was proposed. Based on simulated runoff in the study area under changing environmental conditions, this study analyzed the available water supply and constructed a long-term water demand forecasting model using the classified water use index method under macro regulation in the study area from 2016 to 2100. The results show that the total water demand in the upstream Yangtze River appears to first increase and then decrease in 2016–2100 and will reach its peak around 2028. The ecological pressure in the upstream Yangtze River increases gradually from upstream to downstream but will not reach the surface water utilization stress threshold (hereinafter referred to as stress threshold) for the next 85 years. The contradiction between monthly supply and demand is more prominent under ecological restrictions. Under the RCP4.5 scenario, water demand exceeds the stress threshold in each sub-basin across several months (mainly March, April, and May), and the water demand nearly reaches the damage threshold in May as the basin extends below the Zhutuo section. Full article

This paper presents the application of a distributed-framework basin modeling system (DFBMS) in Taihu Basin, China. The concepts of professional modeling systems and system integration/coupling have been summarized in the first three series papers. This study builds a hydrologic and hydrodynamic model for Taihu Basin, which is in the lowland plain areas with numerous polder areas. Digital underlying surface area data agree with the survey results from the water resource development and utilization. The runoff generated in each cell was calculated with the model based on the digital underlying surface data. According to the hydrological feature units (HFU) concept from the DFBMS, Taihu Basin was conceptualized into six different HFUs. The basic data of rainfall, evaporation, water surface elevation (WSE), discharge, tide level, and water resources for consumption and discharge in 2000 were used to calibrate the model. The simulated results of WSE and discharge matched the observed data well. The observed data of 1998, 1999, 2002, and 2003 were used to validate the model, with good agreement with the simulation results. Finally, the basic data from 2003 were used to simulate and evaluate the management scheme of water diversion from the Yangtze River to Taihu Lake. Overall, the DFBMS application in Taihu Basin showed good performance and proved that the proposed structure for DFBMS was effective and reliable. Full article

The Ili-Balkhash basin (IBB) is considered a key region for agricultural development and international transport as part of China’s Belt and Road Initiative (BRI). The IBB is exemplary for the combined challenge of climate change and shifts in water supply and demand in transboundary Central Asian closed basins. To quantify future vulnerability of the IBB to these changes, we employ a scenario-neutral bottom-up approach with a coupled hydrological-water resource modelling set-up on the RiverWare modelling platform. This study focuses on reliability of environmental flows under historical hydro-climatic variability, future hydro-climatic change and upstream water demand development. The results suggest that the IBB is historically vulnerable to environmental shortages, and any increase in water consumption will increase frequency and intensity of shortages. Increases in precipitation and temperature improve reliability of flows downstream, along with water demand reductions upstream and downstream. Of the demand scenarios assessed, extensive water saving is most robust to climate change. However, the results emphasize the competition for water resources among up- and downstream users and between sectors in the lower Ili, underlining the importance of transboundary water management to mitigate cross-border impacts. The modelling tool and outcomes may aid decision-making under the uncertain future in the basin. Full article

Anthropogenic activities performed in the Ecuadorian Amazon have released potentially toxic elements (PTEs) into the rivers, causing severe environmental pollution and increasing the risk of exposure to the residents of the surrounding areas. This study aims to carry out a human health risk assessment using deterministic and probabilistic methods to estimate the hazard index (HI) and total cancer risk (TCR) related to multi-pathway human exposure to PTEs in polluted rivers. Concentrations of Al, Cd, Cr, Cu, Hg, Ni, Pb, and Zn in surface water and sediment samples from rivers on the Ecuadorian Amazon were considered to assess the potential adverse human health effects. As a result, deterministic and probabilistic estimations of cancer and non-cancer risk through exposure to surface waters and sediments were above the safety limit. A sensitivity analysis identified the concentration of PTEs and the exposure duration (ED) as the two most important variables for probabilistic health risk assessment. The highest risk for receptors was related to exposure to polluted sediments through incidental ingestion and dermal contact routes. According to the deterministic estimation, the human health risk through ingestion of water was above the threshold in specific locations. This study reveals the potential health risk to which the population is exposed. This information can be used as a baseline to develop public strategies to reduce anthropogenic pollution and exposure to PTEs in Ecuadorian Amazon rivers. Full article

Maine, USA is the largest producer of wild blueberries (Vaccinium angustifolium Aiton), an important native North American fruit crop. Blueberry fields are mainly distributed in coastal glacial outwash plains which might not experience the same climate change patterns as the whole region. It is important to analyze the climate change patterns of wild blueberry fields and determine how they affect crop health so fields can be managed more efficiently under climate change. Trends in the maximum (T_max), minimum (T_min) and average (T_avg) temperatures, total precipitation (P_total), and potential evapotranspiration (PET) were evaluated for 26 wild blueberry fields in Downeast Maine during the growing season (May–September) over the past 40 years. The effects of these climate variables on the Maximum Enhanced Vegetation Index (EVI_max) were evaluated using Remote Sensing products and Geographic Information System (GIS) tools. We found differences in the increase in growing season T_max, T_min, T_avg, and P_total between those fields and the overall spatial average for the region (state of Maine), as well as among the blueberry fields. The maximum, minimum, and average temperatures of the studied 26 wild blueberry fields in Downeast, Maine showed higher rates of increase than those of the entire region during the last 40 years. Fields closer to the coast showed higher rates of warming compared with the fields more distant from the coast. Consequently, PET has been also increasing in wild blueberry fields, with those at higher elevations showing lower increasing rates. Optimum climatic conditions (threshold values) during the growing season were explored based on observed significant quadratic relationships between the climate variables (T_max and P_total), PET, and EVI_max for those fields. An optimum T_max and PET for EVI_max at 22.4 °C and 145 mm/month suggest potential negative effects of further warming and increasing PET on crop health and productivity. These climate change patterns and associated physiological relationships, as well as threshold values, could provide important information for the planning and development of optimal management techniques for wild blueberry fields experiencing climate change. Full article

The science needed to inform management of environmental flows to temporarily closed estuaries and coastal lagoons is decades behind the state of knowledge for rivers and large embayments. These globally ubiquitous small systems, which are often seasonally closed to the ocean’s influence, are under particular threat associated with hydrologic alteration because of changes in atershed land use, water use practices, and climate change. Managing environmental flows in these systems is complicated by their tight coupling with watershed processes, variable states because of intermittently closing mouths, and reliance on regional scale sediment transport and littoral processes. Here we synthesize our current understanding of ecohydrology in temporarily closed estuaries (TCEs) and coastal lagoons and propose a prioritized research agenda aimed at advancing understanding of ecological responses to altered flow regimes in TCEs. Key research needs include agreeing on a consistent typology, improving models that couple watershed and ocean forcing at appropriate spatial and temporal scales, quantifying stress–response relationships associated with hydrologic alteration, improving tools to establish desired conditions that account for climate change and consider cultural/indigenous objectives, improving tools to measure ecosystem function and social/cultural values, and developing monitoring and adaptive management programs that can inform environmental flow management in consideration of other stressors and across different habitat types. Coordinated global efforts to address the identified research gaps can help guide management actions aimed at reducing or mitigating potential impacts of hydrologic alteration and climate change through informed management of freshwater inflows. Full article

Despite the Sahara being one of the most arid regions on Earth, it has experienced rainfall conditions in the past and could hold plentiful groundwater resources. Thus, groundwater is one of the most precious water resources in this region, which suffers from water shortage due to the limited rainfall caused by climatic conditions. This article will assess the knowledge-driven techniques employed to develop a model to integrate the multicriteria derived from geologic, geomorphic, structural, seismic, hydrologic, and remotely sensed data. This model was tested on the defunct Kom Ombo area of Egypt’s Nile river basin in the eastern Sahara, which covers ~28,200 km², to reveal the promising areas of groundwater resources. To optimize the output map, we updated the model by adding the automated depression resulting from a fill-difference approach and seismic activity layers combined with other evidential maps, including slope, topography, geology, drainage density, lineament density, soil characteristics, rainfall, and morphometric characteristics, after assigning a weight for each using a Geographic Information System (GIS)-based knowledge-driven approach. The paleochannels and soil characteristics were visualized using Advanced Land Observing Satellite (ALOS)/Phased Array type L-band Synthetic Aperture Radar (PALSAR) data. Several hydromorphic characteristics, sinks/depressions, and sub-basin characteristics were extracted using Shuttle Radar Topography Mission (SRTM) data. The results revealed that the assessed groundwater potential zones (GPZs) can be arranged into five distinctive groups, depending on their probability for groundwater, namely very low (6.56%), low (22.62%), moderate (30.75%), high (29.71%), and very high (10.34%). The downstream areas and Wadi Garara have very high recharge and storage potential. Interferometry Synthetic Aperture Radar (InSAR) coherence change detection (CCD) derived from Sentinel-1 data revealed a consistency between areas with high InSAR CCD (low change) that received a plausible amount of surface water and those with very low InSAR CCD values close to 0 (high change). Landsat data validated the areas that received runoff and are of high potentiality. The twenty-nine groundwater well locations overlaid on the GPZs, to assess the predicted model, indicated that about 86.17% of the wells were matched with very good to moderate potential zones. Full article

Near real-time rainfall monitoring at local scale is essential for urban flood risk mitigation. Previous research on precipitation visual effects supports the idea of vision-based rain sensors, but tends to be device-specific. We aimed to use different available photographing devices to develop a dense network of low-cost sensors. Using Transfer Learning with a Convolutional Neural Network, the rainfall detection was performed on single images taken in heterogeneous conditions by static or moving cameras without adjusted parameters. The chosen images encompass unconstrained verisimilar settings of the sources: Image2Weather dataset, dash-cams in the Tokyo Metropolitan area and experiments in the NIED Large-scale Rainfall Simulator. The model reached a test accuracy of 85.28% and an F1 score of 0.86. The applicability to real-world scenarios was proven with the experimentation with a pre-existing surveillance camera in Matera (Italy), obtaining an accuracy of 85.13% and an F1 score of 0.85. This model can be easily integrated into warning systems to automatically monitor the onset and end of rain-related events, exploiting pre-existing devices with a parsimonious use of economic and computational resources. The limitation is intrinsic to the outputs (detection without measurement). Future work concerns the development of a CNN based on the proposed methodology to quantify the precipitation intensity. Full article

The fundamental importance of groundwater for urban drinking water supplies in sub-Saharan Africa is increasingly recognised. However, little is known about the trends in urban groundwater development by individual households and its role in securing safely-managed drinking water supplies. Anecdotal evidence indicates a thriving self-supply movement to exploit groundwater in some urban sub-Saharan African settings, but empirical evidence, or analysis of the benefits and drawbacks, remains sparse. Through a detailed analysis of official datasets for Lagos State, Nigeria we examine the crucial role played by groundwater and, specifically, by household self-supply for domestic water provision. We then set this in the context of Nigeria and of sub-Saharan Africa. One of the novelties of this multi-scalar approach is that it provides a granular understanding from large-scale datasets. Our analysis confirms the importance of non-piped water supplies in meeting current and future drinking water demand by households in parts of sub-Saharan Africa and the role played, through self-supply, by groundwater. Our results demonstrate inconsistencies between datasets, and we make recommendations for the future. We argue that a key actor in the provision of drinking water supplies, the individual household, is largely overlooked by officially reported data, with implications for both policy and practice. Full article

Recent advances in deep learning, especially the long short-term memory (LSTM) networks, provide some useful insights on how to tackle time series prediction problems, not to mention the development of a time series model itself for prediction. Runoff forecasting is a time series prediction problem with a series of past runoff data (water level and discharge series data) as inputs and a fixed-length series of future runoff as output. Most previous work paid attention to the sufficiency of input data and the structural complexity of deep learning, while less effort has been put into the consideration of data quantity or the processing of original input data—such as time series decomposition, which can better capture the trend of runoff—or unleashing the effective potential of deep learning. Mutual information and seasonal trend decomposition are two useful time series methods in handling data quantity analysis and original data processing. Based on a former study, we proposed a deep learning model combined with time series analysis methods for daily runoff prediction in the middle Yangtze River and analyzed its feasibility and usability with frequently used counterpart models. Furthermore, this research also explored the data quality that affect the performance of the deep learning model. With the application of the time series method, we can effectively get some information about the data quality and data amount that we adopted in the deep learning model. The comparison experiment resulted in two different sites, implying that the proposed model improved the precision of runoff prediction and is much easier and more effective for practical application. In short, time series analysis methods can exert great potential of deep learning in daily runoff prediction and may unleash great potential of artificial intelligence in hydrology research. Full article

The tight coupling of the social-ecological system (SES) of the Mississippi Delta calls for balanced natural hazard vulnerability and risk assessments. Most existing assessments have approached these components in isolation. To address this, we apply the Global Delta Risk Index (GDRI) in the Mississippi Delta at high-resolution census tract level. We assess SES spatial patterns of drought, hurricane-force wind, and coastal flood vulnerability and integrate hazard and exposure data for the assessment of coastal flood risk. Moreover, we compare current coastal flood risk to future risk in 2025 based on the modelled effects of flood depth, exposure, and changes in ecosystem area in the context of ongoing efforts under the 2017 Louisiana Coastal Master Plan. Results show that the Master Plan will lead to decreases in risk scores by 2025, but the tracts that are currently the most vulnerable benefit less from risk reduction efforts. Along with our index output, we discuss the need for further advancements in SES methodology and the potential for catastrophic hazard events beyond the model parameters, such as extreme rainfall events and very strong hurricanes. Assessing SES risk components can lead to more targeted policy recommendations, demonstrated by the need for Master Plan projects to consider their unequal spatial effects on vulnerability and risk reduction. Full article

Documenting how ground- and surface water systems respond to climate change is crucial to understanding water resources, particularly in the U.S. Great Lakes region, where drastic temperature and precipitation changes are observed. This study presents baseflow and baseflow index (BFI) trend analyses for 10 undisturbed watersheds in Michigan using (1) multi-objective optimization (MOO) and (2) modified Mann–Kendall (MK) tests corrected for short-term autocorrelation (STA). Results indicate a variability in mean baseflow (0.09–8.70 m³/s) and BFI (67.9–89.7%) that complicates regional-scale extrapolations of groundwater recharge. Long-term (>60 years) MK trend tests indicate a significant control of total precipitation (P) and snow- to rainfall transitions on baseflow and BFI. In the Lower Peninsula Rifle River watershed, increasing P and a transition from snow- to rainfall has increased baseflow at a lower rate than streamflow; an overall pattern that may contribute to documented flood frequency increases. In the Upper Peninsula Ford River watershed, decreasing P and a transition from rain- to snowfall had no significant effects on baseflow and BFI. Our results highlight the value of an objectively constrained BFI parameter for shorter-term (<50 years) hydrologic trend analysis because of a lower STA susceptibility. Full article

The design and operation of reservoirs based on conventional flood-limited water levels (FLWL) implicitly adopts the assumption of hydrological stationarity. As such, historical-record-based FLWL may not be the best choice for flood-control operations due to the inherent non-stationarity of rainfall inputs. With maturing flood forecasts, this study focuses on establishing linkage between FLWL and skill of forecast, thus developing a “dynamic pre-storm level” approach for reservoir flood-control operations. The approach utilizes forecast flood magnitude, forecast skill and exceedance probability of forecast error to determine the pre-storm reservoir storage for each flood event. The exceedance probability of forecast error for each incoming flood is used as the reservoir flood control standard instead of the probability of a static return interval flood. This approach is demonstrated in a hypothetical situation in the Three Gorges Reservoir in China. The results show that under zero-forecast-skill conditions, the proposed dynamic pre-storm level matches well with the Three Gorges Reservoir-designed FLWL; and, as the forecast accuracy/skill increase, the proposed approach can make better use of the increased forecast accuracy, thereby maximizing floodwater utilization and reservoir storage. In this way, coupling the new approach with FLWL allows for more efficient and economic day-to-day reservoir operations without adding any flood risk. This study validates the usefulness of dynamic water level control during flood season, considering the improvement of flood forecast accuracy. Full article

Groundwater–surface water exchange in salt marsh ecosystems mediates nearshore salt, nutrient, and carbon budgets with implications for biological productivity and global climate. Despite their importance, a synthesis of salt marsh groundwater studies is lacking. In this review, we summarize drivers mediating salt marsh hydrogeology, review field and modeling techniques, and discuss patterns of exchange. New data from a Delaware seepage meter study are reported which highlight small-scale spatial variability in exchange rates. A synthesis of the salt marsh hydrogeology literature reveals a positive relationship between tidal range and submarine groundwater discharge but not porewater exchange, highlighting the multidimensional drivers of marsh hydrogeology. Field studies are heavily biased towards microtidal systems of the US East Coast, with little global information available. A preliminary estimate of marsh porewater exchange along the Mid-Atlantic and South Atlantic Bights is 8–30 × 10¹³ L y⁻¹, equivalent to recirculating the entire volume of seawater overlying the shelf through tidal marsh sediments in ~30–90 years. This review concludes with a discussion of critical questions to address that will decrease uncertainty in global budget estimates and enhance our capacity to predict future responses to global climate change. Full article

Drought is a fundamental physical feature of the climate pattern worldwide. Over the past few decades, a natural disaster has accelerated its occurrence, which has significantly impacted agricultural systems, economies, environments, water resources, and supplies. Therefore, it is essential to develop new techniques that enable comprehensive determination and observations of droughts over large areas with satisfactory spatial and temporal resolution. This study modeled a new drought index called the Combined Terrestrial Evapotranspiration Index (CTEI), developed in the Ganga river basin. For this, five Machine Learning (ML) techniques, derived from artificial intelligence theories, were applied: the Support Vector Machine (SVM) algorithm, decision trees, Matern 5/2 Gaussian process regression, boosted trees, and bagged trees. These techniques were driven by twelve different models generated from input combinations of satellite data and hydrometeorological parameters. The results indicated that the eighth model performed best and was superior among all the models, with the SVM algorithm resulting in an R² value of 0.82 and the lowest errors in terms of the Root Mean Squared Error (RMSE) (0.33) and Mean Absolute Error (MAE) (0.20), followed by the Matern 5/2 Gaussian model with an R² value of 0.75 and RMSE and MAE of 0.39 and 0.21 mm/day, respectively. Moreover, among all the five methods, the SVM and Matern 5/2 Gaussian methods were the best-performing ML algorithms in our study of CTEI predictions for the Ganga basin. Full article

Coastal aquifers are strategic and fundamental in the development of touristic areas. The coastal aquifer within the Manglaralto River Basin in Ecuador is essential, as it is the only source of water supply for a large part of the northern part of the Santa Elena province. It is a semi-arid region where high volumes of water are pumped from the aquifer, causing a significant drawdown of groundwater levels, thus affecting the water quality. This work aims to characterize the characteristics of groundwater in the coastal aquifer using hydrochemistry and stable isotopes to propose a hydrogeological conceptual model. The methodology for determining the chemical and isotopic characteristics of groundwater follows the following scheme: (i) studies of ionic concentrations using the Piper diagram, (ii) assessment of the origin of salinity through the Cl/Br ratio, the presence of seawater intrusion through the Hydrochemical Facies Evolution Diagram HFE-D, (iii) characterization of precipitation events using stable isotopes (¹⁸O and ²H), and, (iv) development of a hydrogeological conceptual model of the study area. The results indicate that in the basin there are mixing processes of the existing water in the aquifer with recharge water, direct cation exchange processes in the freshening process during recharge, and evaporation in the unsaturated zone. A conceptual model of the flow system in the basin is built, based on the mentioned processes. The main conclusions are: seawater intrusion is present in the areas of the wells located closest to the coast, urban activity through septic tanks is affecting the quality of the aquifer, and rainfall is highly relevant in the different hydrochemical and isotopic processes that operate in the basin. Full article

Systems exposed to hydroclimatic variability, such as the integrated electric system in Uruguay, increasingly require real-time multiscale information to optimize management. Monitoring of the precipitation field is key to inform the future hydroelectric energy availability. We present an operational implementation of an algorithm that merges satellite precipitation estimates with rain gauge data, based on a 3-step technique: (i) Regression of station data on the satellite estimate using a Generalized Linear Model; (ii) Interpolation of the regression residuals at station locations to the entire grid using Ordinary Kriging and (iii) Application of a rain/no rain mask. The operational implementation follows five steps: (i) Data download and daily accumulation; (ii) Data quality control; (iii) Merging technique; (iv) Hydrological modeling and (v) Electricity-system simulation. The hydrological modeling is carried with the GR4J rainfall-runoff model applied to 17 sub-catchments of the G. Terra basin with routing up to the reservoir. The implementation became operational at the Electricity Market Administration (ADME) on June 2020. The performance of the merged precipitation estimate was evaluated through comparison with an independent, dense and uniformly distributed rain gauge network using several relevant statistics. Further validation is presented comparing the simulated inflow to the estimate derived from a reservoir mass budget. Results confirm that the estimation that incorporates the satellite information in addition to the surface observations has a higher performance than the one that only uses rain gauge data, both in the rainfall statistical evaluation and hydrological simulation. Full article

In semi-arid regions, groundwater resources play a crucial role in all economic, environmental, and social processes. However, the occurrence, movement, and recharge of these hidden and valuable resources vary from place to place. Therefore, better management practices and mapping of groundwater recharge potential zones are needed for the sustainable groundwater resources. For an example, groundwater resources in Willochra Basin are vitally important for drinking, irrigation, and stock use. This study shows the significance of the application of three decision-making approaches, including multi-influencing factor, analytical hierarchy process, and frequency ratio techniques in the identification of groundwater potential zones. A total of seven criteria, including lithology, slope, soil texture, land-use, rainfall, drainage density, and lineament density, were extracted from conventional and remote sensing data sources. The parameters and their assigned weights were integrated using Geographic Information System (GIS) software to generate recharge potential maps. The resultant maps were evaluated using the area under the curve method. The results showed that the southern regions of the Willochra Basin are more promising for groundwater recharge potential. The map produced using the frequency ratio model was the most efficient (84%), followed by the multi-influencing factor model (70%) and then the analytical hierarchy process technique (62%). The area under the curve method agreed when evaluated using published weights and rating values. Full article

Groundwater arsenic in Uruguay is an important environmental hazard, hence, predicting its distribution is important to inform stakeholders. Furthermore, occurrences in Uruguay are known to variably show dependence on depth and geology, arguably reflecting different processes controlling groundwater arsenic concentrations. Here, we present the distribution of groundwater arsenic in Uruguay modelled by a variety of machine learning, basic expert systems, and hybrid approaches. A pure random forest approach, using 26 potential predictor variables, gave rise to a groundwater arsenic distribution model with a very high degree of accuracy (AUC = 0.92), which is consistent with known high groundwater arsenic hazard areas. These areas are mainly in southwest Uruguay, including the Paysandú, Río Negro, Soriano, Colonia, Flores, San José, Florida, Montevideo, and Canelones departments, where the Mercedes, Cuaternario Oeste, Raigón, and Cretácico main aquifers occur. A hybrid approach separating the country into sedimentary and crystalline aquifer domains resulted in slight material improvement in a high arsenic hazard distribution. However, a further hybrid approach separately modelling shallow (<50 m) and deep aquifers (>50 m) resulted in the identification of more high hazard areas in Flores, Durazno, and the northwest corner of Florida departments in shallow aquifers than the pure model. Both hybrid models considering depth (AUC = 0.95) and geology (AUC = 0.97) produced improved accuracy. Hybrid machine learning models with expert selection of important environmental parameters may sometimes be a better choice than pure machine learning models, particularly where there are incomplete datasets, but perhaps, counterintuitively, this is not always the case. Full article

The United Nations Sustainable Development Goals (SDGs) and their corresponding targets are significantly interconnected, with many interactions, synergies, and trade-offs between individual goals across multiple temporal and spatial scales. This paper proposes a framework for the Integrated Assessment Modelling (IAM) of a complex deltaic socio-ecological system in order to analyze such SDG interactions. We focused on the Sundarban Biosphere Reserve (SBR), India, within the Ganges-Brahmaputra-Meghna Delta. It is densely populated with 4.4 million people (2011), high levels of poverty, and a strong dependence on rural livelihoods. It is adjacent to the growing megacity of Kolkata. The area also includes the Indian portion of the world’s largest mangrove forest––the Sundarbans––hosting the iconic Bengal Tiger. Like all deltaic systems, this area is subject to multiple drivers of environmental change operating across scales. The IAM framework is designed to investigate socio-environmental change under a range of explorative and/or normative scenarios and explore associated policy impacts, considering a broad range of subthematic SDG indicators. The following elements were explicitly considered: (1) agriculture; (2) aquaculture; (3) mangroves; (4) fisheries; and (5) multidimensional poverty. Key questions that can be addressed include the implications of changing monsoon patterns, trade-offs between agriculture and aquaculture, or the future of the Sundarbans’ mangroves under sea-level rise and different management strategies. The novel, high-resolution analysis of SDG interactions allowed by the IAM will provide stakeholders and policy makers the opportunity to prioritize and explore the SDG targets that are most relevant to the SBR and provide a foundation for further integrated analysis. Full article

The assessment of transboundary aquifers is essential for the development of groundwater management strategies and the sustainable use of groundwater resources. The Transboundary Aquifer Assessment Program (TAAP) is a joint effort by the United States and Mexico to evaluate shared aquifers. This study examines the TAAP Cooperative Framework as a guide for further transboundary groundwater collaboration. We compared lessons learned from six transboundary aquifers that currently have mechanisms for groundwater collaboration to identify common elements of collaboration. Though the TAAP Cooperative Framework governs an assessment-only program, the elements of collaboration included are consistent with the principles of other institutional agreements around the world. Importantly, all the analyzed agreements included a knowledge-improvement phase, which is the main objective of the TAAP Cooperative Framework. The present study finds evidence of successful outcomes within the TAAP Cooperative Framework consistent with available transboundary groundwater management agreements, demonstrating that this approach is suited to serve as a model for those wishing to engage in transborder aquifer assessments. Furthermore, the TAAP elements of collaboration can help to establish the meaningful and robust binational cooperation necessary for the development of U.S.-Mexico groundwater management agreements at the aquifer level. Full article

Supplying safe, secure, and reliable drinking water is a growing challenge particularly in regions where catchments have diverse land uses, rapidly growing populations, and are subject to increasing weather extremes such as in the subtropics. Catchments represent the first barrier in providing ecosystem services for water quality protection and bulkwater suppliers are therefore investing in mitigation measures to reduce risk to drinking water quality for consumers. This paper presents an approach to combine data on erosion processes, pathogenic bacteria and protozoa from several sources, determine the highest risks from these hazards and identify an optimum portfolio of intervention activities that provide maximum risk reduction at water treatment plants (WTP) for a given budget using a simulated annealing optimizer. The approach is demonstrated in a catchment with six WTPs servicing small rural to urban populations. The catchment is predominantly used for agriculture. Results show that drinking water risk from protozoa can be reduced for most WTPs for moderate investment budget, while bacteria risk reduction requires significantly larger budget due to the greater number of significant source sites relative to protozoa. Total suspended sediment loads remain a very high risk to most of the WTPs due to the large extent of channel and gully erosion and landslides. A map of priority areas and associated suite of interventions are produced to guide on groundwork. Full article

Ratified in 2019, the Nibi Declaration of Treaty #3 voices the relationship with water (Nibi) and jurisdictional responsibility that all Anishinaabe citizens have within the Treaty #3 territory. It affirms the responsibilities and relationships that others living within the territory should have with the water and ensures that the spirit of Nibi is central to decision-making and water governance. This article details the process of developing The Declaration, in accordance with the Treaty #3 lawmaking process and, which was driven by women, in ceremony, with the help of Gitiizii m-inaanik, and with the input of The Nation as a whole. This process embodies nationhood, sovereignty, and Anishinaabe jurisdiction as it relates to the environment and water, in accordance with the Manito Aki Inakonigaawin (Mother Earth law). Every person has a relationship with water. The process of nurturing that relationship through the teachings exemplified in the implementation of The Declaration will provide clarity on the responsibilities and partnerships that must be developed to protect the water for future generations. Full article

Developing accurate stream maps requires both an improved understanding of the drivers of streamflow spatial patterns and field verification. This study examined streamflow locations in three semiarid catchments across an elevation gradient in the Colorado Front Range, USA. The locations of surface flow throughout each channel network were mapped in the field and used to compute active drainage densities. Field surveys of active flow were compared to National Hydrography Dataset High Resolution (NHD HR) flowlines, digital topographic data, and geologic maps. The length of active flow declined with stream discharge in each of the catchments, with the greatest decline in the driest catchment. Of the tributaries that did not dry completely, 60% had stable flow heads and the remaining tributaries had flow heads that moved downstream with drying. The flow heads were initiated at mean contributing areas of 0.1 km² at the lowest elevation catchment and 0.5 km² at the highest elevation catchment, leading to active drainage densities that declined with elevation and snow persistence. The field mapped drainage densities were less than half the drainage densities that were represented using NHD HR. Geologic structures influenced the flow locations, with multiple flow heads initiated along faults and some tributaries following either fault lines or lithologic contacts. Full article

In recent years, a large volume of literature has been published regarding the removal of phosphorus (P) from wastewater. Various sorbing materials, such as metal oxides and hydroxides, carbonates and hydroxides of calcium (Ca) and magnesium (Mg), hydrotalcite, activated carbon, anion exchange resins, industrial solid wastes and organic solid wastes, have been suggested for P removal. Many of these sorbents are expensive and/or may cause some environmental problems. In contrast, biochar, as an economical and environmentally friendly sorbing material, has received much attention in recent years and has been used as a novel sorbent for the removal of different organic and inorganic pollutants. Biochar is a type of sustainable carbonaceous material that is produced from the thermal treatment of agricultural organic residues and other organic waste streams under oxygen free conditions. This paper reviews the potential use of biochar and the key controlling factors affecting P removal from wastewater. The ability of biochar to remove P from wastewater depends on its physical and chemical properties. Some of the most important physicochemical properties of biochar (structural characteristics, electrical conductivity (EC), mineral composition, pH, zeta potential, cation exchange capacity (CEC) and anion exchange capacity (AEC)) are affected by the feedstock type as well as temperature of pyrolysis and the P sorption capacity is highly dependent on these properties. The P removal is also affected by the water matrix chemistry, such as the presence of competing ions and bulk pH conditions. Finally, several recommendations for future research have been proposed to facilitate and enhance the environmental efficiency of biochar application. Full article

A problem for drainage systems managers is the increase in extreme rain events that are increasing in various parts of the world. Their occurrence produces hydraulic overload in the drainage system and consequently floods. Adapting the existing infrastructure to be able to receive extreme rains without generating consequences for cities’ inhabitants has become a necessity. This research shows a new way to improve drainage systems with minimal investment costs, using for this purpose a novel methodology that considers the inclusion of hydraulic control elements in the network, the installation of storm tanks and the replacement of pipes. The presented methodology uses the Storm Water Management Model for the hydraulic analysis of the network and a modified Genetic Algorithm to optimize the network. In this algorithm, called the Pseudo-Genetic Algorithm, the coding of the chromosomes is integral and has been used in previous studies of hydraulic optimization. This work evaluates the cost of the required infrastructure and the damage caused by floods to find the optimal solution. The main conclusion of this study is that the inclusion of hydraulic controls can reduce the cost of network rehabilitation and decrease flood levels. Full article

Watersheds in cold regions provide water, food, biodiversity and ecosystem service. However, the increasing demand for water resources and climate change challenge our ability to provide clean freshwater. Particularly, watersheds in cold regions are more sensitive to changing climate due to their glaciers’ retreat and permafrost. This review revisits watershed system and processes. We analyze principles of watershed modelling and characteristics of watersheds in cold regions. Then, we show observed evidence of their impacts of cold processes on hydrological and biogeochemical processes and ecosystems, and review the watershed modeling and their applications in cold regions. Finally, we identify the knowledge gaps in modeling river basins according to model structures and representations of processes and point out research priorities in future model development. Full article

Groundwater stored in aquifers experiences a wide variety of natural, induced and/or anthropogenic disturbances. Among them, groundwater extraction is the main disturbance that affects most of the aquifers in the world. Aquifer’s resilience, understood as the potential of the aquifer to sustain disturbances on the long term and to guarantee essential qualities and functions, provides a key tool when assessing sustainable groundwater management alternatives. The aim of this work is to illustrate an aquifer resilience framework that can support groundwater sustainable management. A theoretical framework is based on the identification of the key variables that parameterize the quantitative and qualitative responses of the groundwater flow system to pumping. An example from the literature based in Denmark is provided as an illustration of the proposed framework. The results show that long-term high quality data are essential to make a step further in aquifers dynamic responses. The quantitative understanding of the aquifer’s behavior before, during and after groundwater extraction provides a valuable source of information in order to identify thresholds of change (tipping points, transitions or regime shifts) which could permit pro-active groundwater management decisions. Moreover, a deeper understanding on the aquifer’s dynamics provides useful information in order to avert threats that may put the sustainability of the system at risk. Full article

Excessive nutrient loadings from drainage areas and resulting water quality degradation in rivers are the major environmental issues around the world. The water quality further deteriorates for the large seasonal variation of precipitation and water flow. Environmental decision makers have been exploring affordable and effective ways of securing environmental flow (EF) to improve the water quality, especially in dry seasons, and agricultural reservoirs have attracted the attention of policymakers as an alternative source of EF. This study proposed an analysis framework for assessing the EF supply potential of agricultural reservoirs as alternative sources of EF. A reservoir water balance model was prepared to mathematically represent the reservoir water balance and quantify temporal variations of the amount of water available for the EF supply. The simulation model was designed to explicitly consider inflow from the upstream drainage areas, irrigation water requirement, and hydrological processes happening in the reservoirs. The proposed framework was applied to four agricultural reservoirs located in South Korea to evaluate its efficiency. Results showed that the additional storage capacity added by the dam reinforcement enabled the study reservoirs to satisfy both needs, EF and irrigation water supply. The surplus capacity turned out to be enough to satisfy various EF supply scenarios at the annual time scale. However, the current operation plans do not consider the seasonal variations of reservoir hydrology and thus cannot supply EF without violating the original operational goal, irrigation water, especially in dry months. The results demonstrate that it is necessary to consider the temporal variations of EF when developing reservoir operation rules and plans to secure EF. This study also highlights the unconventional roles of agricultural reservoirs as resources for improved environmental quality. The methods presented in this study are expected to be a useful tool for the assessment of agricultural reservoirs’ EF supply potential. Full article

This paper shows the results of a field appliance study of the hydraulic well method to prevent embankment piping, which is proposed by the Japanese Matsuyama River National Highway Office. The large-scale embankment experiment and seepage analysis were conducted to examine the hydraulic well. The experimental procedure is focused on the pore water pressure. The water levels of the hydraulic well were compared with pore water pressure data, which were used to look over the seepage variations. Two different types of large-scale experiments were conducted according to the installation points of hydraulic wells. The seepage velocity results by the experiment were almost similar to those of the analyses. Further, the pore water pressure oriented from the water level variations in the hydraulic well showed similar patterns between the experiment and numerical analysis; however, deeper from the surface, the larger pore water pressure of the numerical analysis was calculated compared to the experimental values. In addition, the piping effect according to the water level and location of the hydraulic well was quantitatively examined for an embankment having a piping guide part. As a result of applying the hydraulic well to the point where piping occurred, the hydraulic well with a 1.0 m water level reduced the seepage velocity by up to 86%. This is because the difference in the water level between the riverside and the protected side is reduced, and it resulted in reducing the seepage pressure. As a result of the theoretical and numerical hydraulic gradient analysis according to the change in the water level of the hydraulic well, the hydraulic gradient decreased linearly according to the water level of the hydraulic well. From the results according to the location of the hydraulic well, installation of it at the point where piping occurred was found to be the most effective. A hydraulic well is a good device for preventing the piping of an embankment if it is installed at the piping point and the proper water level of the hydraulic well is applied. Full article

Despite the impact of flow cessation on aquatic ecology, the hydrology of intermittent rivers has been largely overlooked. This has resulted in a lack of monitoring projects, and consequently, datasets spanning a period of sufficient duration to characterise both hydrological extremes. This report documents an investigation into the potential for statistical modelling to simulate the spatiotemporal dynamics of flowing, ponded and dry hydrological states in an internationally rare hydrological state dataset. The models presented predict unrecorded hydrological state data with performance metrics exceeding 95%, providing insights into the relationship between ponding prevalence and the performance of statistical simulation of this ecologically important intermediate state between drying and flowing conditions. This work demonstrates the potential for hydrological intermittence to be simulated in areas where hydrological state data are often sparse, providing opportunities for quality control and data infilling. This further understanding of the processes driving intermittence will inform future water resource assessments and the influence of climate change on hydrological intermittence. Full article

This study assessed natural variation in the macroinvertebrate assemblages (MIB) and water quality in one of the main basins with the largest agricultural activities in Chile (Aconcagua River Basin). We sampled throughout the annual cycle; nine sampling sites were established along the basin, classifying according to agricultural area coverage as least-disturbed, intermediate, and most-disturbed. We collected 56 macroinvertebrate taxa throughout the entire study area. Multivariate analysis shows significant differences among the three disturbance categories in different seasons, both water quality variables and the MIB structure. Distance-based linear model (DistLM) analysis for all seasons explained more than 95.9% of the macroinvertebrate assemblages, being significantly explained by chemical oxygen demand, pH, total coliforms, nitrites, elevation, and water temperature. ANOVA test revealed significant differences in the proportion of noninsect individuals, macroinvertebrates density, and the number of taxa among the three disturbance categories (p < 0.05). In general, water temperature, conductivity, chemical oxygen demand, ammonium, nitrites, and nitrates increased their values downstream in the basin. Our results indicate that the elevation gradient and increment in agricultural land use in the basin had a strong influence on water quality and MIB. A better understanding of these ecosystems could help conservation and integrated watershed management. Full article

Fluorescence (excitation-emission matrices, EEMs) spectroscopy coupled with PARAFAC (parallel factor) modelling and UV-Vis (ultraviolet visible) spectra were used to ascertain the sources, distribution and biogeochemical transformation of dissolved organic matter (DOM) in the Duliujian River catchment. Dissolved organic carbon (DOC), chromophoric dissolved organic matter (a₃₃₅) (CDOM), and hydrophobic components (a₂₆₀) were higher in summer than in other seasons with 53.3 m⁻¹, while aromaticity (SUVA₂₅₄) was higher in spring. Four fluorescent components, namely terrestrial humic acid (HA)-like (A/C), terrestrial fulvic acid (FA)-like (A/M), autochthonous fulvic acid (FA)-like (A/M), and protein-like substances (Tuv/T), were identified using EEM-PARAFAC modelling in this river catchment. The results demonstrated that terrestrial HA-like substances enhance its contents in summer ARE compared with BRE, whilst terrestrial FA-like substances were newly input in summer ARE, which was entirely absent upstream and downstream, suggesting that rain events could significantly input the terrestrial soil-derived DOM in the ambient downward catchments. Autochthonous FA-like substances in summer BRE could derive from phytoplankton in the downstream waters. The results also showed that DOM from wetland exhibited lower fluorescent intensity of humic-like peak A/C and fulvic-like peak A/M, molecular weight (S_R) and humification index (HIX) during the low-flow season. Built-up land, cropland, and unused land displayed higher a₃₃₅ (CDOM). A higher proportion of forest and industrial land in the SCs showed higher SUVA₂₅₄ values. Humic-like moiety, molecular weight and aromaticity were more responsive to land use during stormflow in summer. Rainfall could increase the export of soil DOM from cropland and unused land, which influences the spatial variation of HIX. The results in this study highlighted that terrestrial DOM has a significant influence on the biogeochemical alterations of DOM compositions and thus water quality in the downward watershed catchments, which might significantly vary according to the land-use types and their alterations by human activities. Full article

This study investigates the impacts of climate change on the hydrological response of a Mediterranean mesoscale catchment using a hydrological model. The effect of climate change on the discharge of the Alata River Basin in Mersin province (Turkey) was assessed under the worst-case climate change scenario (i.e., RCP8.5), using the semi-distributed, process-based hydrological model Hydrological Predictions for the Environment (HYPE). First, the model was evaluated temporally and spatially and has been shown to reproduce the measured discharge consistently. Second, the discharge was predicted under climate projections in three distinct future periods (i.e., 2021–2040, 2046–2065 and 2081–2100, reflecting the beginning, middle and end of the century, respectively). Climate change projections showed that the annual mean temperature in the Alata River Basin rises for the beginning, middle and end of the century, with about 1.35, 2.13 and 4.11 °C, respectively. Besides, the highest discharge timing seems to occur one month earlier (February instead of March) compared to the baseline period (2000–2011) in the beginning and middle of the century. The results show a decrease in precipitation and an increase in temperature in all future projections, resulting in more snowmelt and higher discharge generation in the beginning and middle of the century scenarios. However, at the end of the century, the discharge significantly decreased due to increased evapotranspiration and reduced snow depth in the upstream area. The findings of this study can help develop efficient climate change adaptation options in the Levant’s coastal areas. Full article

Rainfall-induced shallow landslides represent a serious threat in hilly and mountain areas around the world. The mountainous landscape of the Cinque Terre (eastern Liguria, Italy) is increasingly popular for both Italian and foreign tourists, most of which visit this outstanding terraced coastal landscape to enjoy a beach holiday and to practice hiking. However, this area is characterized by a high level of landslide hazard due to intense rainfalls that periodically affect its rugged and steep territory. One of the most severe events occurred on 25 October 2011, causing several fatalities and damage for millions of euros. To adequately address the issues related to shallow landslide risk, it is essential to develop landslide susceptibility models as reliable as possible. Regrettably, most of the current land-use and urban planning approaches only consider the susceptibility to landslide detachment, neglecting transit and runout processes. In this study, the adoption of a combined approach allowed to estimate shallow landslide susceptibility to both detachment and potential runout. At first, landslide triggering susceptibility was assessed using Machine Learning techniques and applying the Ensemble approach. Nine predisposing factors were chosen, while a database of about 300 rainfall-induced shallow landslides was used as input. Then, a Geographical Information System (GIS)-based procedure was applied to estimate the potential landslide runout using the “reach angle” method. Information from such analyses was combined to obtain a susceptibility map describing detachment, transit, and runout. The obtained susceptibility map will be helpful for land planning, as well as for decision makers and stakeholders, to predict areas where rainfall-induced shallow landslides are likely to occur in the future and to identify areas where hazard mitigation measures are needed. Full article

Biofuels produced from photosynthetic microorganisms such as microalgae and cyanobacteria could potentially replace fossil fuels as they offer several advantages over fuels produced from lignocellulosic biomass. In this study, energy production potential in the form of bioethanol was examined using different biomasses derived from the growth of a cyanobacteria-based microbial consortium on a chemical medium and on agro-industrial wastewaters (i.e., dairy wastewater, winery wastewater and mixed winery–raisin effluent) supplemented with a raisin residue extract. The possibility of recovering fermentable sugars from a microbial biomass dominated by the filamentous cyanobacterium Leptolynbgya sp. was demonstrated. Of the different acid hydrolysis conditions tested, the best results were obtained with sulfuric acid 2.5 N for 120 min using dried biomass from dairy wastewater and mixed winery–raisin wastewaters. After optimizing sugar release from the microbial biomass by applying acid hydrolysis, alcoholic fermentation was performed using the yeast Saccharomyces cerevisiae. Raisin residue extract was added to the treated biomass broth in all experiments to enhance ethanol production. Results showed that up to 85.9% of the theoretical ethanol yield was achieved, indicating the potential use of cyanobacteria-based biomass in combination with a raisin residue extract as feedstock for bioethanol production. Full article

The loss of nitrogen and phosphate fertilizers in agricultural runoff is a global environmental problem, attracting worldwide attention. In the last decades, the constructed wetland has been increasingly used for mitigating the loss of nitrogen and phosphate from agricultural runoff, while the substrate, plants, and wetland structure design remain far from clearly understood. In this paper, the optimum substrates and plant species were identified by reviewing their treatment capacity from the related studies. Specifically, the top three suitable substrates are gravel, zeolite, and slag. In terms of the plant species, emergent plants are the most widely used in the constructed wetlands. Eleocharis dulcis, Typha orientalis, and Scirpus validus are the top three optimum emergent plant species. Submerged plants (Hydrilla verticillata, Ceratophyllum demersum, and Vallisneria natans), free-floating plants (Eichhornia crassipes and Lemna minor), and floating-leaved plants (Nymphaea tetragona and Trapa bispinosa) are also promoted. Moreover, the site selection methods for constructed wetland were put forward. Because the existing research results have not reached an agreement on the controversial issue, more studies are still needed to draw a clear conclusion of effective structure design of constructed wetlands. This review has provided some recommendations for substrate, plant species, and site selections for the constructed wetlands to reduce nutrients from agricultural runoff. Full article

The control system’s point is to bring the pumping curve close to the set-point curve. That concept is essential for proper design of a pumping station. An adequate design is focused not only on selecting the total number of pumps and the type of control to use (flow or pressure), but it also is important to determine the optimal number of fixed speed pumps (FSPs) and variable speed pumps (VSPs) for each flow rate. This work discusses the most common methods and procedures for control systems on a design of pumping stations with a proposed methodology. This methodology consists of expressing the characteristics of the pumping curve and the set-point curve in a dimensionless form so that the methodology is standardized for any pump model and set-point curve. These formulations allow us to discuss how the characteristic of a pump and the set-point curve of the network influence the optimal number of FSPs and VSPs in energy terms. In general, the objective of this work is to determine the most suitable total number of pumps in a pumping station design and to determine the optimal pumping configuration in every flow rate, thus the consumed energy would be the minimum. Additionally, this methodology develops an expression to estimate the performance of a frequency inverter when a VSP operates at different rotational speeds. This work will be applied to different study cases, and the obtained results allow us to question several usual procedures for pumping control system. In general, it can be concluded that the number of pumps of a pumping system cannot be inferred in a simple form without a deep analysis of a control system. Full article

Large-scale disasters, such as hurricanes, cyclones, tsunamis, and forest fires, have caused considerable damage in recent years. This study investigated two case studies of discontinuous open levees (kasumi-tei), which are a traditional Japanese river technology, on the Matsuura River at the sites of Okawano and Azame-no-se, and evaluated the advantages of these levees from the perspective of ecosystem-based disaster risk reduction (Eco-DRR). These case studies were conducted through literature surveys, flood observations, and oral interviews. The systems in both the cases were flood control systems utilizing ecosystem services. The traditional river technology (the flood plain open levee) served as an effective Eco-DRR in both cases. Additionally, the flood plain levee technology enhanced the ecosystem services at both sites, including not only flood control capabilities, but also other ecosystem services. Furthermore, the open levees offered substantial cost advantages over their alternatives. These results suggest that other traditional Japanese river technologies may also be effective in strengthening Eco-DRR. Full article

Scientific papers present a wide range of methods of flood analysis and forecasting. Floods are a phenomenon with significant socio-economic implications, for which many researchers try to identify the most appropriate methodologies to analyze their temporal and spatial development. This research aims to create an overview of flood analysis and forecasting methods. The study is based on the need to select and group papers into well-defined methodological categories. The article provides an overview of recent developments in the analysis of flood methodologies and shows current research directions based on this overview. The study was performed taking into account the information included in the Web of Science Core Collection, which brought together 1326 articles. The research concludes with a discussion on the relevance, ease of application, and usefulness of the methodologies. Full article

The excess pressure available in water distribution networks (WDNs) is a relevant aspect in the management and appropriate handling of water resources. If a WDN meets the minimum performance criteria (minimum pressure and maximum flow), excess pressure can occur throughout the day, which is usually lost. These excesses could be considered as potentially recoverable energy (PRE). One way of taking advantage of this energy is to find the nodes on the network where this excess pressure is evident and try to analyze the possible amount of PRE. This work presents a methodology to determine the maximum PRE in a WDN. This methodology includes the locations of the points where the installation of recovery devices leads to this maximum PRE. The method is based on reducing pressures but maintaining circulating points through the lines. Additionally, a new energy balance that allows visualizing and breaking down in more detail all the energy found in a WDN is proposed. The analysis is carried out in an extended period considering different feeding points either by gravity or pumping. Finally, a network resilience index called the Potentially Recoverable Energy Index (PREI) in WDNs is proposed, with which it is possible to diagnose and determine how much energy could be recovered from the network. Study cases presented demonstrate the effectiveness of the methodology and will allow the development of optimizations in the operation of WDNs in favor of the good management of water and energy resources. Full article

This article originates from the theoretical and empirical characterization of factors in the World Trade Model (WTM). It first illustrates the usefulness of this type of model for water research to address policy questions related to virtual water trade, water constraints and water scarcity. It also illustrates the importance of certain key decisions regarding the heterogeneity of water and its relation to the technologies being employed and the prices obtained. With regard to WTM, the global economic input–output model in which multiple technologies can produce a “homogeneous output”, it was recently shown that two different mechanisms should be distinguished by which multiple technologies can arise, i.e., from “technology-specific” or from “shared” factors, which implies a mechanism-specific set of prices, quantities and rents. We discuss and extend these characterizations, notably in relation to the real-world characterization of water as a factor (for which we use the terms technology specific, fully shared and “mixed”). We propose that the presence of these separate mechanisms results in the models being sensitive to relatively small variations in specific numerical values. To address this sensitivity, we suggest a specific role for specific (sub)models or key choices to counter unrealistic model outcomes. To support our proposal we present a selection of simulations for aggregated world regions, and show how key results concerning quantities, prices and rents can be subject to considerable change depending on the precise definitions of resource endowments and the technology-specificity of the factors. For instance, depending on the adopted water heterogeneity level, outcomes can vary from relatively low-cost solutions to higher cost ones and can even reach infeasibility. In the main model discussed here (WTM) factor prices are exogenous, which also contributes to the overall numerical sensitivity of the model. All this affects to a large extent our interpretation of the water challenges, which preferably need to be assessed in integrated frameworks, to account for the main socioeconomic variables, technologies and resources. Full article

Arsenic is found in groundwater above regulatory limits in many countries and its origin is often from natural sources, making the definition of Natural Background Levels (NBLs) crucial. NBL is commonly assessed based on either dedicated small-scale monitoring campaigns or large-scale national/regional groundwater monitoring networks that may not grab local-scale heterogeneities. An alternative method is represented by site-specific monitoring networks in contaminated/polluted sites under remediation. As a main drawback, groundwater quality at these sites is affected by human activities. This paper explores the potential for groundwater data from an assemblage of site-specific datasets of contaminated/polluted sites to define NBLs of arsenic (As) at the meso-scale (order of 1000 km²). Common procedures for the assessment of human influence cannot be applied to this type of dataset due to limited data homogeneity. Thus, an “unorthodox” method is applied involving the definition of a consistent working dataset followed by a statistical identification and critical analysis of the outliers. The study was conducted in a highly anthropized area (Ferrara, N Italy), where As concentrations often exceed national threshold limits in a shallow aquifer. The results show that site-specific datasets, if properly pre-treated, are an effective alternative for the derivation of NBLs when regional monitoring networks fail to catch local-scale variability. Full article