Hydrology, Volume 5, Issue 3 (September 2018) – 21 articles

Estimating groundwater recharge in arid or semiarid regions can be a difficult and complex task, since it is dependent on a highly variable set of spatial and temporal hydrologic parameters and processes that are dependent on the local climate, the land surface properties, and subsurface characteristics. As a result, traditional methods for estimating the recharge can result in a wide range of derived values. This is evident in the southeastern Mojave Desert, where calculated recharge estimates by previous investigators that range over an order of magnitude (from ~2500 to ~37,000 acre feet per year) are reported. To narrow down this large span of recharge estimates to narrower and more plausible values, this study evaluates the previous recharge estimates in this region, to examine the sources of variability in the reported results and to constrain the recharge estimates based on the hydrologic conditions and the radiocarbon age-dating of spring flows—even without knowledge of the precise subsurface hydrology. The groundwater age and perennial flow characteristics of springs in this study could not be derived from waters sourced solely from local recharge. Therefore, the springs in this study require a significant groundwater contribution to their overall discharge. A previously described conceptual site model in the region established that Bonanza Spring is similarly hydrologically connected to the regional basin-fill aquifer, based on geologic and geochemical/isotopic analyses, and this conceptual site model for where perennial spring water is sourced should readily be extended to these other perennial springs in this region. Full article

The characterization of temporal and spatial patterns in phosphorus (P) loading in Lake Erie is essential in order to continue monitoring the excessive P condition that comes from the western Lake Erie Basin. This study aims to perform such a characterization using the continuous wavelet transform (CWT) and the discrete wavelet transform (DWT) methods. These wavelet transformations were conducted on streamflow data, TP loads, and soluble reactive phosphorus (SRP) of six stations located near Lake Erie of Northern Ohio. These stations are located near the outlet of Cuyahoga, Grand, Maumee, Vermilion, Raisin, and Sandusky watersheds. Long-term continuous P loading data, in which some dated back to 1970, were used in the analysis. The results obtained from the CWT and DWT approaches were found to complement each other. Streamflow had significant mixed variability at 1, 2, and 4 years. The variability for SRP was limited to 1 and 2 years while the TP variability was only seen at the 1-year scale. It was interesting to find that strong temporal patterns of SRP were observed in most of the watersheds only after the mid-1990s. The CWT wavelet spectra also reflected the land use characteristics of each watershed. For example, the wavelet spectra of surface runoff and TP for the agricultural watersheds (i.e., Raisin, Sandusky, and Maumee Rivers) were similar and characterized by significant variability primarily at the annual scale and at the two to four-year periodicities. The urbanized watershed (i.e., Cuyahoga River) did not show any association between either phosphorus (TP or SRP) with surface runoff and baseflow, which indicates that P in the urbanized watershed was not driven by the flow. Full article

The last decades have seen a massive advance in technologies for Earth observation (EO) and environmental monitoring, which provided scientists and engineers with valuable spatial information for studying hydrologic processes. At the same time, the power of computers and newly developed algorithms have grown sharply. Such advances have extended the range of possibilities for hydrologists, who are trying to exploit these potentials the most, updating and re-inventing the way hydrologic and hydraulic analyses are carried out. A variety of research fields have progressed significantly, ranging from the evaluation of water features, to the classification of land-cover, the identification of river morphology, and the monitoring of extreme flood events. The description of flood processes may particularly benefit from the integrated use of recent algorithms and monitoring techniques. In fact, flood exposure and risk over large areas and in scarce data environments have always been challenging topics due to the limited information available on river basin hydrology, basin morphology, land cover, and the resulting model uncertainty. The ability of new tools to carry out intensive analyses over huge datasets allows us to produce flood studies over large extents and with a growing level of detail. The present Special Issue aims to describe the state-of-the-art on flood assessment, monitoring, and management using new algorithms, new measurement systems and EO data. More specifically, we collected a number of contributions dealing with: (1) the impact of climate change on floods; (2) real time flood forecasting systems; (3) applications of EO data for hazard, vulnerability, risk mapping, and post-disaster recovery phase; and (4) development of tools and platforms for assessment and validation of hazard/risk models. Full article

Reflectivity factor bias caused by radar calibration errors would influence the accuracy of Quantitative Precipitation Estimations (QPE), and further result in spatial discontinuity in Multiple Ground Radars QPE (MGR-QPE) products. Due to sampling differences and random errors, the associated discontinuity cannot be thoroughly solved by the single-radar calibration method. Thus, a multiple-radar synchronous calibration approach was proposed to mitigate the spatial discontinuity of MGR-QPE. Firstly, spatial discontinuity was solved by the intercalibration of adjacent ground radars, and then calibration errors were reduced by referring to the Ku-Band Precipitation Radar (KuPR) carried by the Global Precipitation Measurement (GPM) Core Observatory as a standard reference. Finally, Mosaic Reflectivity and MGR-QPE products with spatial continuity were obtained. Using three S-band operational radars covering the lower reaches of the Yangtze River in China, this method was evaluated under four representative precipitation events. The result showed that: (1) the spatial continuity of reflectivity factor and precipitation estimation fields was significantly improved after bias correction, and the reflectivity differences between adjacent radars were reduced by 78% and 82%, respectively; (2) the MGR-QPE data were closer to gauge observations with the normalized absolute error reducing by 0.05 to 0.12. Full article

Estimating Manning’s roughness coefficient $(n)$ is one of the essential factors in predicting the discharge in a stream. Present research work is focused on prediction of Manning’s $n$ in meandering compound channels by using the Group Method of Data Handling Neural Network (GMDH-NN) approach. The width ratio $(\alpha )$ , relative depth $(\beta )$ , sinuosity $(s)$ , Channel bed slope $(S_o)$ , and meander belt width ratio $(\omega )$ are specified as input parameters for the development of the model. The performance of GMDH-NN is evaluated with two different machine learning techniques, namely the support vector regression (SVR) and multivariate adaptive regression spline (MARS) with various statistical measures. Results indicate that the proposed GMDH-NN model predicts the Manning’s $n$ satisfactorily as compared to the MARS and SVR model. This GMDH-NN approach can be useful for practical implementation as the prediction of Manning’s coefficient and subsequently discharge through Manning’s equation in the compound meandering channels are found to be quite adequate. Full article

Across the globe, station-based meteorological data are analyzed to estimate the rate of change in precipitation. However, in sparsely populated regions, like Mongolia, stations are few and far between, leaving significant gaps in station-derived precipitation patterns across space and over time. We combined station data with the observations of herders, who live on the land and observe nature and its changes across the landscape. Station-based trends were computed with the Mann–Kendall significance and Theil–Sen rate of change tests. We surveyed herders about their observations of changes in rain and snowfall amounts, rain intensity, and days with snow, using a closed-ended questionnaire and also recorded their qualitative observations. Herder responses were summarized using the Potential for Conflict Index (PCI₂), which computes the mean herder responses and their consensus. For one set of stations in the same forest steppe ecosystem, precipitation trends were similar and decreasing, and the herder-based PCI₂ consensus score matched differences between stations. For the other station set, trends were less consistent and the PCI₂ consensus did not match well, since the stations had different climates and ecologies. Herder and station-based uncertainties were more consistent for the snow variables than the rain variables. The combination of both data sources produced a robust estimate of climate change uncertainty. Full article

Atmospheric nutrient loading through wet and dry deposition is one of the least understood, yet can be one of the most important, pathways of nutrient transport into lakes and reservoirs. Nutrients, specifically phosphorus and nitrogen, are essential for aquatic life but in excess can cause accelerated algae growth and eutrophication and can be a major factor that causes harmful algal blooms (HABs) that occur in lakes and reservoirs. Utah Lake is subject to eutrophication and HABs. It is susceptible to atmospheric deposition due to its large surface area to volume ratio, high phosphorous levels in local soils, and proximity to Great Basin dust sources. In this study we collected and analyzed eight months of atmospheric deposition data from five locations near Utah Lake. Our data showed that atmospheric deposition to Utah Lake over the 8-month period was between 8 to 350 Mg (metric tonne) of total phosphorus and 46 to 460 Mg of dissolved inorganic nitrogen. This large range is based on which samples were used in the estimate with the larger numbers including results from “contaminated samples”. These nutrient loading values are significant for Utah Lake in that it has been estimated that only about 17 Mg year⁻¹ of phosphorus and about 200 Mg year⁻¹ of nitrogen are needed to support a eutrophic level of algal growth. We found that atmospheric deposition is a major contributor to the eutrophic nutrient load of Utah Lake. Full article

The Mkurumudzi River originates in the Shimba hills and runs through Kwale County on the Kenyan Coast. Study on this river has been informed by the many economic activities that the river supports, which include sugarcane plantations, mining, tourism and subsistence farming. The main objective of this study was to use the soil moisture accounting (SMA) model specified in the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) settings for the continuous modeling of stream flow in the Mkurumudzi catchment. Data from past years were compared with observed stream flow data in order to evaluate whether the model can be used for further prediction. The calibration was performed using data from 1988 to 1991 and validation for the period from 1992 to 1995 at a daily time step. The model performance was evaluated based on computed statistical parameters and visual checking of plotted hydrographs. For the calibration period of the continuous modeling, the performance of the model was very good, with a coefficient of determination R² = 0.80, Nash-Sutcliffe Efficiency NSE = 0.80, index of agreement d = 0.94, and a Root Mean Squared Error (RMSE)/observations’ standard deviation ratio—RSR = 0.46. Similarly, the continuous model performance for the validation period was good, with R² = 0.67, NSE = 0.65, RSR = 0.62 and d = 0.88. Based on these performance results, the SMA model in the HEC-HMS was found to give a satisfactory prediction of stream flow in the Mkurumudzi Catchment. The sensitivity analysis of the model parameters was performed, and the different parameters were ranked according to their sensitivity in terms of percent change in simulated runoff volume, peaks, Nash-Efficiency, seven-day low flow and base flow index. Sensitivity analysis helped to understand the relationships between the key model parameters and the variables. Full article

Timely and continuous information about flood dynamics are fundamental to ensure an effective implementation of the relief and rescue operations. Satellite data provided by optical sensors onboard meteorological satellites could have great potential in this framework, offering an adequate trade-off between spatial and temporal resolution. The latest would benefit from the integration of observations coming from different satellite systems, also helping to increase the probability of finding cloud free images over the investigated region. The Robust Satellite Techniques for detecting flooded areas (RST-FLOOD) is a sensor-independent multi-temporal approach aimed at detecting flooded areas which has already been applied with good results on different polar orbiting optical sensors. In this work, it has been implemented on both the 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) and the 375 m Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS). The flooding event affecting the Basilicata and Puglia regions (southern Italy) in December 2013 has been selected as a test case. The achieved results confirm the RST-FLOOD potential in reliably detecting, in case of small basins, flooded areas regardless of the sensor used. Flooded areas have indeed been detected with similar performance by the two sensors, allowing for their continuous and near-real time monitoring. Full article

Streamflow is one the most important variables controlling and maintaining aquatic ecosystem integrity, diversity, and sustainability. This study identified and quantified changes in 34 hydrologic characteristics and parameters at 30 long term (1939–2016) discharge stations in the Southeast Atlantic and Gulf Coast Hydrologic Region (Region 3) using Indicators of Hydrologic Alteration (IHA) variables. The southeastern United States (SEUS) is a biodiversity hotspot, and the region has experienced a number of rapid land use/land cover changes with multiple primary drivers. Studies in the SEUS have been mostly localized on specific rivers, reservoir catchments and/or species, but the overall region has not been assessed for the long-term period of 1939–2016 for multiple hydrologic characteristic parameters. The objectives of the study were to provide an overview of multiple river basins and 31 hydrologic characteristic parameters of streamflow in Region 3 for a longer period and to develop a conceptual map of impacts of selected stressors and changes in hydrology and climate in the SEUS. A seven step procedure was used to accomplish these objectively: Step 1: Download data from the 30 USGS gauging stations. Steps 2 and 3: Select and analyze the 31 IHA parameters using boxplots, scatter plots, and PDFs. Steps 4 and 5: Synthesize the drivers of changes and alterations and the various change points in streamflow in the literature. Step 6: Synthesize the climate of the SEUS in terms of temperature and precipitation changes. Step 7: Develop a conceptual map of impacts of selected stressors on hydrology using Driver–Pressure–State-Impact–Response (DPSIR) framework and IHA parameters. The 31 IHA parameters were analyzed. The meta-analysis of literature in the SEUS revealed the precipitation changes observed ranged from −30% to +35% and temperature changes from −2 °C to 6 °C by 2099. The fiftieth percentile of the Global Climate Models (GCM) predict no precipitation change and an increase in the temperature of 2.5 °C in the region by 2099. Among the GCMs, the 5th and 95th percentile of precipitation changes range between −40% and 110% and temperature changes between −2 °C and 6 °C by 2099. Meta-analysis of land use/land cover show the region has experienced changes. A number of rapid land use/land cover changes in 1957, 1970, and 1998 are some of the change points documented in the literature for precipitation and streamflow in the region. A conceptual map was developed to represent the impacts of selected drivers and the changes in hydrology and climate in the study region for three land use/land cover categories in three different periods. Full article

The Dahab watershed comprises three aquifers; the alluvial Quaternary, the Early Cambrian sandstone, and the fractured Pre-Cambrian basement aquifers. The Dahab watershed is located in the southeastern part of the arid Sinai Peninsula, where low precipitation and groundwater over-exploitation deteriorate the groundwater quality in the alluvial coastal plain aquifer located downstream. Multi-isotopes including δ¹⁸O and δ²H, ⁸⁷Sr/⁸⁶Sr, δ⁸¹Br and δ¹¹B coupled with groundwater geochemistry were utilized to assess the recharge source(s), water-rock interaction, and seawater mixing to aid sustainable groundwater management strategies. Br and Cl concentrations, used to measure groundwater salinity, were low in the upstream groundwater, while higher concentrations were observed in the deep drilled wells located downstream, in the main well field. The δ¹⁸O and δ²H isotopes were depleted in the upstream aquifers, but enriched in the shallow coastal aquifer, indicating slight evaporation and seawater intrusion. Higher mean values of ⁸⁷Sr/⁸⁶Sr and δ⁸¹Br were observed in the fresh groundwater from high in the watershed (⁸⁷Sr/⁸⁶Sr = 0.707716 and δ⁸¹Br = +2.05‰), while lower mean values were observed in the saline groundwater located downstream in the main well field (⁸⁷Sr/⁸⁶Sr = 0.706631 and δ⁸¹Br = +0.11‰). The cumulative mass balance mixing curves and the geochemical NETPATH model confirm the change of groundwater quality from the upper to lower watershed caused by the leaching and evaporation processes, as well as mixing with seawater. The corrected ¹⁴C age dating and stable isotopes show that the Quaternary and Pre-Cambrian basement aquifers contain modern groundwater, while the Early Cambrian aquifer holds paleo-groundwater, which has received considerable recharge from recent precipitation. The mixing ratiosin the Quaternary coastal aquifer range between 5% and 13% seawater to 95% and 87% fresh groundwater, respectively. These results indicate that future groundwater withdrawal must be well managed in order to limit further salinization. Groundwater withdrawal from the Quaternary coastal aquifer must be below the natural average recharge in order to be sustainable. Full article

The lack of reliable continuous rainfall records can exacerbate the negative impact of extreme storm events. The inability to describe the continuous characteristics of rainfall from storm events increases the likelihood that the design of hydraulic structures will be inadequate. To mitigate extreme storm impacts and improve water governance at the catchment scale, it is vital to improve the availability of data and the array of tools used to model and forecast hydrological processes. In this paper, we describe and discuss the implementation of a web-based system for the estimation of intensity–duration–frequency (IDF) curves (WEBSE_IDF) in Chile. The web platform was constructed using records from 47 pluviographic gauges available in central Chile (30–40° S), with at least 15 years of reliable records. IDF curves can be generated for durations ranging from 15 min to 24 h. In addition, the extrapolation of rainfall intensity from pluviograph to pluviometric gauges (i.e., 24-h rainfall accumulation) can be carried out using the storm index (S_I) method. IDF curves can also be generated for any spatial location within central Chile using the ordinary Kriging method. These procedures allow the generation of numerical and graphical displays of IDF curves, for any selected spatial location, and for any combination of probability distribution function (PDF), parameter estimation method, and type of IDF model. One of the major advantages of WEBSE_IDF is the flexibility of its database, which can be easily modified and saved to generate IDF curves under user-defined scenarios, that is, changing climate conditions. The implementation and validation of WEBSE_IDF serves as a decision support system, providing an important tool for improving the ability of the Chilean government to mitigate the impact of extreme hydrologic events in central Chile. The system is freely available for students, researchers, and other relevant professionals, to improve technical decisions of public and private institutions. Full article

Flood modelling and mapping typically entail flood frequency estimation, hydrodynamic modelling and inundation mapping, which require specific datasets that are often unavailable in developing regions due to financial, logistical, technical and organizational challenges. This review discusses fluvial (river) flood modelling and mapping processes and outlines the data requirements of these techniques. This paper explores how open-access remotely sensed and other geospatial datasets can supplement ground-based data and high-resolution commercial satellite imagery in data sparse regions of developing countries. The merits, demerits and uncertainties associated with the application of these datasets, including radar altimetry, digital elevation models, optical and radar images, are discussed. Nigeria, located within the Niger river basin of West Africa is a typical data-sparse country, and it is used as a case study in this review to evaluate the significance of open-access datasets for local and transboundary flood analysis. Hence, this review highlights the vital contribution that open access remotely sensed data can make to flood modelling and mapping and to support flood management strategies in developing regions. Full article

Integrating hydrology with climate is essential for a better understanding of the impact of present and future climate on hydrological extremes, which may cause frequent flooding, drought, and shortage of water supply. This study assessed the impact of future climate change on the hydrological extremes (peak and low flows) of the Zenne river basin (Belgium). The objectives were to assess how climate change impacts basin-wide extreme flows and to provide a detailed overview of the impacts of four future climate change scenarios compared to the control (baseline) values. The scenarios are high (wet) summer (projects a future with high storm rain in summer), high (wet) winter (predicts a future with high rainfall in winter), mean (considers a future with intermediate climate conditions), and low (dry) (projects a future with low rainfall during winter and summer). These scenarios were projected by using the Climate Change Impact on HYDRological extremes perturbation tool (CCI-HYDR), which was (primarily) developed for Belgium to study climate change. We used the Soil and Water Assessment Tool (SWAT) model to predict the impact of climate change on hydrological extremes by the 2050s (2036–2065) and the 2080s (2066–2095) by perturbing the historical daily data of 1961–1990. We found that the four climate change scenarios show quite different impacts on extreme peak and low flows. The extreme peak flows are expected to increase by as much as 109% under the wet summer scenario, which could increase adverse effects, such as flooding and disturbance of the riverine ecosystem functioning of the river. On the other hand, the low (dry) scenario is projected to cause a significant decrease in both daily extreme peak and low flows, by as much as 169% when compared to the control values, which would cause problems, such as droughts, reduction in agricultural crop productivity, and increase in drinking water and other water use demands. More importantly, larger negative changes in low flows are predicted in the downstream part of the basin where a higher groundwater contribution is expected, indicating the sensitivity of a basin to the impact of climate change may vary spatially and depend on basin characteristic. Overall, an amplified, as well as an earlier, occurrence of hydrological droughts is expected towards the end of this century, suggesting that water resources managers, planners, and decision makers should prepare appropriate mitigation measures for climate change for the Zenne and similar basins. Full article

The monitoring and prediction of water quality parameters are important tasks in the management of water resources. In this work, the performances of time series statistical models were evaluated to predict and forecast the dissolved oxygen (DO) concentration in several monitoring sites located along the main river Vouga, in Portugal, during the period from January 2002 to May 2015. The models being compared are a regression model with correlated errors and a state-space model, which can be seen as a calibration model. Both models allow the incorporation of water quality variables, such as time correlation or seasonality. Results show that, for the DO variable, the calibration model outperforms the regression model for sample modeling, that is, for a short-term forecast, while the regression model with correlated errors has a better performance for the forecasting h-steps ahead framework. So, the calibration model is more useful for water monitoring using an online or real-time procedure, while the regression model with correlated errors can be applied in order to forecast over a longer period of time. Full article

Variability and covariability of land properties (soil, vegetation and subsurface geology) and remotely sensed soil moisture over the southeast and south-central U.S. are assessed. The goal is to determine whether satellite soil moisture memory contains information regarding land properties, especially the distribution karst formations below the active soil column that have a bearing on land-atmosphere feedbacks. Local (within a few tens of km) statistics of land states and soil moisture are considered to minimize the impact of climatic variations, and the local statistics are then correlated across the domain to illuminate significant relationships. There is a clear correspondence between soil moisture memory and many land properties including karst distribution. This has implications for distributed land surface modeling, which has not considered preferential water flows through geologic formations. All correspondences are found to be strongest during spring and fall, and weak during summer, when atmospheric moisture demand appears to dominate soil moisture variability. While there are significant relationships between remotely-sensed soil moisture variability and land properties, it will be a challenge to use satellite data for terrestrial parameter estimation as there is often a great deal of correlation among soil, vegetation and karst property distributions. Full article

The release of nanophase metal particles from sulfide mineral decomposition in mining-impacted environments is a growing concern because of the potential for the transport of nanoscale particles that could increase the distribution of the metals and their environmental impact. An analysis of total (unfiltered) and dissolved (450-nm filtered) metal concentrations in the mining-impacted Coeur d’Alene River indicates the leaching of dissolved metal forms from sediments and transport to and within the river. The distribution of metals between total and dissolved forms is driven by seasonal temperatures, hydraulic gradients, and ligand availability. Cd and Zn were the least influenced by changes in gradient and biological productivity between the upper and lower basins. Cd and Zn primarily travel as dissolved forms, with the lowest ratio of dissolved-to-total concentrations in spring and the highest in summer. Fe and Pb primarily travel as suspended particles, but their dissolved forms were greater during all seasons in the lower basin. A principal components analysis of upper basin data indicates that temperature and conductivity were correlated with dissolved Cd and Zn, and total Fe and Pb were correlated with streamflow. In the lower basin, dissolved Cd and Zn, conductivity, and temperature were correlated, and suspended sediment, total metals, and dissolved Pb, but not streamflow, were correlated. The correlation of metals and sediment in the lower basin is not from erosion but the availability of organic matter and Fe that form a range of dissolved to suspended metal particles. The summer decrease in surface water levels releases sediment porewater containing nanoscale-to-microscale metal particles that are transported to open water, where they may impact human and wildlife health. Such releases are unmitigated with current remediation strategies of sediment stabilization. Full article

Terrain slope and drainage networks are useful components to the basins morphometric characterization as well as to hydrologic modelling. One way to obtain the slope, drainage networks, and basins delineation is by their extraction from Digital Elevation Models (DEMs) and, therefore, their accuracy depends on the accuracy of the used DEM. Regional DEMs with high detail and accuracy are produced in many countries by National Mapping Agencies (NMA). However, the use of these products usually has associated costs. An alternative to those DEMs are the Global Digital Elevation Models (GDEMs) that can be accessed freely and cover almost the entire surface of the world. However, they are not as accurate as the regional DEMs obtained with other techniques. This study intends to assess if generating new, modified DEMs using altimetric data from the original GDEMs and the watercourses available for download in the collaborative project OpenStreetMap (OSM) improves the accuracy of the rebuilt DEMs, the slope derived from them, as well as the delineation of basins and the horizontal and vertical accuracy of the extracted drainage networks. The methodology is presented and applied to a study area located in the United Kingdom. The GDEMs used are of 30 m spatial resolution from the Shuttle Radar Topography Mission (SRTM 30). The accuracy of the original data and the data obtained with the proposed methodology is compared with a reference DEM, with a spatial resolution of 50 m, and the rivers network available at the Ordnance Survey website. The results mainly show an improvement of the horizontal accuracy of the drainage networks, but also a decrease of the systematic errors of the new DEMs, the derived slope, and the vertical position of the drainage networks, as well as the basin’s identification for a set of pour points. Full article

In future years, extreme weather events are expected to frequently increase due to climate change, especially in the combination of climate change and events of El Niño–Southern Oscillation. This pays special attention to the construction of intensity–duration–frequency (IDF) curves at a tempo-spatial scale of sub-daily and sub-grid under a context of climate change. The reason for this is that IDF curves represent essential means to study effects on the performance of drainage systems, damps, dikes and reservoirs. Therefore, the objective of this study is to present an approach to construct future IDF curves with high temporo-spatial resolutions under climate change in central Vietnam, using the case of VuGia-ThuBon. The climate data of historical and future from a regional climate model RegCM4 forced by three global models MPI-ESM-MR, IPSL-CM5A-LR and ICHEC-EC-EARTH are used to re-grid the resolution of 10 km × 10 km grid spacing from 25 km × 25 km on the base of bilinear interpolation. A bias correction method is then applied to the finest resolution of a hydrostatic climate model for an ensemble of simulations. Furthermore, the IDF curves for short durations of precipitation are constructed for the historical climate and future climates under two representative concentration pathway (RCP) scenarios, RCP4.5 and RCP8.5, based on terms of correlation factors. The major findings show that the projected precipitation changes are expected to significantly increase by about 10 to 30% under the scenarios of RCP4.5 and RCP8.5. The projected changes of a maximum of 1-, 2-, and 3-days precipitation are expected to increase by about 30–300 mm/day. More importantly, for all return periods (i.e., 10, 20, 50, 100, and 200 years), IDF curves completely constructed for short durations of precipitation at sub-daily show an increase in intensities for the RCP4.5 and RCP8.5 scenarios. Full article

For decades, the Ébrié Lagoon in Côte d’Ivoire has been the receptacle of wastewater effluent and household waste transported by runoff water. This work assesses the spatio-temporal variability of the Ébrié lagoon water quality at the city of Abidjan. The methodological approach used in this study is summarized in three stages: the choice and standardization of the parameters for assessing water quality for uses such as aquaculture, irrigation, livestock watering, and sports and recreation; the weighting of these parameters using the Hierarchical Analysis Process (AHP) of Saaty; and finally, the aggregation of the weighted parameters or factors. Physicochemical and microbiological analysis data on the waters of the Ébrié lagoon for June and December of 2014 and 2015 were provided by the Ivorian Center for Anti-Pollution (Centre Ivoirien Anti-Pollution, CIAPOL), and the concentrations of trace elements in sediments (As, Cd, Cr, Pb, Zn) were used. The aggregation of standardized and weighted parameters allowed the calculation of the Water Quality Indices (WQI) by usage for each bays of the lagoon. The results show that in both 2014 and 2015, the waters of the Ébrié lagoon were generally of poor quality for the different uses examined in this study (aquaculture, irrigation, livestock watering, and sport and recreation) with an accentuation in 2015. However, some bays of the lagoon have waters of dubious to satisfactory quality. This study contributes an improved evaluation of the Ébrié lagoon waters. Full article

Flooding is a natural disaster that damages infrastructure, properties, and may even cause loss of life. Major floods occur in the Arda river basin, which is shared between Greece and Bulgaria in Southeastern Europe. A flood warning system can sufficiently minimize adverse effects by helping to create a more successful and well-organized response plan. This paper presents an extensive numerical simulation of flood hydrograph routing between levees of the downstream section of the Arda river for floods with return periods from 2 to 10,000 years, using the one-dimensional software HEC-RAS. The main objective is to calculate the inundation areas, travel times of flood waves, water depths, water levels, flow velocities, and overflow volumes by simulating the hydraulic behavior of the Arda river outside its mountain watershed, where it flows through agricultural plane land with very mild slope. The great importance of the water level at the confluence of the Arda and Evros rivers (downstream boundary condition) has been pointed out for the regions near the confluence because the flow is the subcritical type. A significant finding of this work is the determination of the upper limit of the peak discharge hydrograph entering from the Arda to the Evros river to prevent the flooding of the Evros river. This finding is very important for the management of the flood flows of the Evros river, which is a major river with a complicated river system. Full article