Hydrology, Volume 9, Issue 5 (May 2022) – 28 articles

On 18 September 2020, the Karditsa prefecture of Thessaly region (Greece) experienced a catastrophic flood as a consequence of the IANOS hurricane. This intense phenomenon was characterized by rainfall records ranging from 220 mm up to 530 mm, in a time interval of 15 h. Extended public infrastructure was damaged and thousands of houses and commercial properties were flooded, while four casualties were recorded. The aim of this study was to provide forensic research on a reconstruction of the flood event in the vicinity of Karditsa city. First, we performed a statistical analysis of the rainfall. Then, we used two numerical models and observed data, either captured by satellites or mined from social media, in order to simulate the event a posteriori. Specifically, a rainfall–runoff CN-unit hydrograph model was combined with a hydrodynamic model based on 2D-shallow water equations model, through the coupling of the hydrological software HEC-HMS with the hydrodynamic software HEC-RAS. Regarding the observed data, the limited available gauged records led us to use a wide spectrum of remote sensing datasets associated with rainfall, such as NASA GPM–IMREG, and numerous videos posted on social media, such as Facebook, in order to validate the extent of the flood. The overall assessment proved that the exceedance probability of the IANOS flooding event ranged from 1:400 years in the low-lying catchments, to 1:1000 years in the upstream mountainous catchments. Moreover, a good performance for the simulated flooding extent was achieved using the numerical models and by comparing their output with the remote sensing footage provided by SENTINEL satellites images, along with the georeferenced videos posted on social media. Full article

In this paper, the quality of a source of drinking water is assessed by measuring eight water quality (WQ) parameters using 710 samples collected from a water-stressed region of India, Jodhpur Rajasthan. The entire sample was divided into ten groups representing different geographic locations. Using American Public Health Association (APHA) specified methodology, eight WQ parameters, viz., pH, total dissolved solids (TDS), total alkalinity (TA), total hardness (TH), calcium hardness (Ca-H), residual chlorine, nitrate (as NO₃⁻), and chloride (Cl⁻), were selected for describing the water quality for potability use. The quality of each parameter is examined as a function of the zone. Taking the average parametric values of different zones, a unique number was used to describe the overall quality of water. It was found that the average value of each parameter varies significantly with zones. Further, we used neural network (NN) modeling to map the nonlinear relationship between the above eight parametric inputs and the water quality index as the output. It can be observed that the NN designed in the present work acquired sufficient learning and can be satisfactorily used to predict the relational pattern between the input and the output. It can further be observed that the water quality index (WQI) from this work is highly efficient for a successful assessment of water quality in the study area. The major challenge to uniquely describing the drinking water quality lies in understanding the cumulative effect of various parameters affecting the quality of water; the quantified figure is subjected to debate, and this paper addresses the difficulty through a novel approach. The framework presented in this work can be automated with appropriate equipment and shall help government agencies understand changing water quality for better management. Full article

Artificial recharge ponds have been used increasingly in recent years to store water in underlying aquifers and modify baseline groundwater gradients or alter natural hydrologic fluxes and state variables in an aquifer system. The number of constructed ponds, their geographic spacing, and the volume of water diverted to each pond can have a significant impact on baseline system hydrologic fluxes and state variables such as groundwater head, with the latter sometimes rising to cause waterlogging in cultivated areas. This study seeks to quantify the impact of recharge ponds on groundwater state variables (head, saturated thickness) and associated fluxes within an irrigated stream-aquifer system. We use a numerical modeling approach to assess the impact of a set of 40 recharge ponds in a 246 km² region of the South Platte River Basin, Colorado on localized groundwater head, regional groundwater flow patterns, and groundwater interactions with the South Platte River. We then use this information to determine the overall influence of recharge ponds on the hydrologic system. A linked agroecosystem–groundwater (DayCent-MODFLOW) modeling system is used to simulate irrigation, crop evapotranspiration, deep percolation to the water table, groundwater pumping, seepage from irrigation canals, seepage from recharge ponds, groundwater flow, and groundwater–surface water interactions. The DayCent model simulates the plant–soil-water dynamics in the root zone and soil profile, while MODFLOW simulates the water balance in the aquifer system. After calibration and testing, the model is used in scenario analysis to quantify the hydrologic impact of recharge ponds. Results indicate that recharge ponds can raise groundwater levels by approximately 2.5 m in localized areas, but only 15 cm when averaged over the entire study region. Ponds also increase the rate of total groundwater discharge to the South Platte River by approximately 3%, due to an increase in groundwater hydraulic gradient, which generally offsets stream depletion caused by groundwater pumping. These results can assist with groundwater resource management in the study region, and generally provide valuable information for the interplay between pumping wells and recharge ponds, and their composite effect on groundwater–surface water interactions. In addition, the developed linked DayCent-MODFLOW modeling system presented herein can be used in any region for which recharge rates should be calculated on a per-field basis. Full article

Due to overexploitation and lower rainfall rates, it is essential to study the detailed water balance of the Keenjhar lake by considering the climate change impacts and higher water demands linked with the population growth. A hydrological model of Keenjhar Lake is developed based on a system dynamic approach using STELLA (Structural Thinking and Experiential Learning Laboratory with Animation). The model (STELLA) developed in the current research study comprises the following three sub-systems: population, water supply, and water demand. The hydrological and climate data for the period of seventeen years (2000–2016) is used in the current study. The monthly water budget of the Keenjhar Lake is determined by inflow components such as rainfall and the Kalri-Baghar Feeder (K.B.F) (upper) and outflow components such as evaporation, the K.B. Feeder (lower), and the Keenjhar-Gujju (K.G) canal from the lake. The water balance results revealed that the contribution of direct rainfall and the annual inflow components to the lake are 22.03% and 77.91%, respectively. Whereas the evaporation, outflow to K.B.F lower and water abstraction to the K.G. Canal constituted about 5.78%, 92.55%, and 1.57% of the total annual outflow from the lake, respectively. Moreover, the annual inflow components of the water budget of the lake showed a declining trend while the outflow components (water abstraction) intimated an increasing trend. The study results also acknowledged that the demand for water can increase from 3 × 10¹⁰ ft³/yr up to 1.2 × 10¹¹ ft³/yr by the year 2050 (influence of overdrawing of water due to population growth), and water supply may decrease to 9.066 × 10¹⁰ ft³ (rainfall depletion due to climate change). A detailed water balance explains the main water loss components and will help in developing better water management practices and well-informed policy decisions. Full article

The prediction of hydrological phenomena using simpler hydrological models requires less computing power and input data compared to the more complex models. Ordinarily, a more complex, white-box model would be expected to have better predictive capabilities than a simple grey box or black-box model. But complexity may not necessarily translate to better prediction accuracy or might be unfeasible in data scarce areas or when computer power is limited. Therefore, the shift of hydrological science towards the more process-based models needs to be justified. To answer this, the paper compares 2 hydrological models: (a) the simpler tank model; and (b) the more complex TOPMODEL. More precisely, the difference in performance between tank model as a lumped model and the TOPMODEL concept as a semi-distributed model in Atari River catchment, in Eastern Uganda was conducted. The objectives were: (1) To calibrate tank model and TOPMODEL; (2) To validate tank model and TOPMODEL; and (3) To compare the performance of tank model and TOPMODEL. During calibration, both models exhibited equifinality, with many parameter sets equally likely to make acceptable hydrological simulations. In calibration, the tank model and TOPMODEL performances were close in terms of ‘Nash-Sutcliffe efficiency’ and ‘RMSE-observations standard deviation ratio’ indices. However, during the validation period, TOPMODEL performed much better than tank model. Owing to TOPMODEL’s better performance during model validation, it was judged to be better suited for making runoff forecasts in Atari River catchment. Full article

The spatio-temporal dynamism of sediment discharge (Q_s) in rivers is influenced by various natural and anthropogenic factors. Unfortunately, most rivers are only monitored at a limited number of stations or not gauged at all. Therefore, this study aims to provide a remote-sensing-based alternative for Q_s monitoring. The at-a-station hydraulic geometry (AHG) power–law method was compared to the at-many-stations hydraulic geometry (AMHG) method; in addition, a novel AHG machine-learning (ML) method was introduced to estimate water discharge at three gauging stations in the Tisza (Szeged and Algyő) and Maros (Makó) Rivers in Hungary. The surface reflectance of Sentinel-2 images was correlated to in situ suspended sediment concentration (SSC) by support vector machine (SVM), random forest (RF), artificial neural network (ANN), and combined algorithms. The best performing water discharge and SSC models were employed to estimate the Q_s. Our novel AHG ML method gave the best estimations of water discharge (Szeged: R² = 0.87; Algyő: R² = 0.75; Makó: R² = 0.61). Furthermore, the RF (R² = 0.9) and combined models (R² = 0.82) showed the best SSC estimations for the Maros and Tisza Rivers. The highest Q_s were detected during floods; however, there is usually a clockwise hysteresis between the SSC and water discharge, especially in the Tisza River. Full article

Small urban catchments pose challenges in applying performance metrics when comparing measured and simulated hydrographs. Indeed, results are hampered by the short peak flows, due to rainfall variability and measurement synchronization errors, and it can be both difficult and inconvenient to remove base flows from the analysis, given their influence on combined sewer overflow (CSO) performance. A new approach, based on the application of metrics to peak flows for a selected set of different durations, is proposed and tested to support model quality assessment and calibration. Its advantages are: avoiding inconveniences arising from lags in peak flows and subjectivity of possible adjustments; favouring the assessment of the influence of base flow variability and flow lamination by CSOs; promoting integrated analysis for a wide range of rainfall events; facilitating bias identification and also guiding calibration. However, this new approach tends to provide results (e.g., for NSE, r² and PBIAS) closer to optimal values than when applying metrics to compare the measured and simulated values of hydrographs, so the comparison of results with thresholds widely used in the literature should be done with caution. The various case study examples highlight the importance of using a judicious set of different metrics and graphical analyses. Full article

Bluecat is a recently proposed methodology to upgrade a deterministic model (D-model) into a stochastic one (S-model), based on the hypothesis that the information contained in a time series of observations and the concurrent predictions made by the D-model is sufficient to support this upgrade. The prominent characteristics of the methodology are its simplicity and transparency, which allow its easy use in practical applications, without sophisticated computational means. In this paper, we utilize the Bluecat methodology and expand it in order to be combined with climate model outputs, which often require extrapolation out of the range of values covered by observations. We apply the expanded methodology to the precipitation and temperature processes in a large area, namely the entire territory of Italy. The results showcase the appropriateness of the method for hydroclimatic studies, as regards the assessment of the performance of the climate projections, as well as their stochastic conversion with simultaneous bias correction and uncertainty quantification. Full article

Dry detention basins (DB) are commonly used to reduce the rate of runoff in urban areas and may provide open space for recreation between storms. However, most are not effective at nitrogen removal in comparison to other measures, such as constructed wetlands. The study goal was to assess the nitrogen treatment efficiency of a DB that exhibited some wetland characteristics, including saturated soil near the inlet and wetland vegetation that covered 40% of the surface area. Influent and effluent samples were collected during multiple stages of eight storm events for nitrogen concentration analyses. High-frequency water stage, pH, dissolved oxygen (DO), and temperature loggers were deployed at the inlet and outlet prior to anticipated rain. As stormwater passed through the DB, the event mean concentrations (EMCs) and masses of TN declined by 20.7% and 52.3%, respectively, while the DO and pH dropped by 62% and 20.5%, respectively. Load reductions of TN exceeding 93% were observed during two small storms with rain depths of less than 0.16 cm and when the outflow volumes were reduced by greater than 82%. Temperature was significantly correlated (p < 0.001; r = 0.964) with volume reductions (via infiltration and evapotranspiration), and, thus, the treatment was better during warmer periods. The DB was effective at removing inorganic nitrogen, likely via nitrification, denitrification, and immobilization, but frequently exported higher EMCs of organic nitrogen. Overall, the DB exceeded the 10% TN removal expectation for dry basins. The findings from this study suggest that the TN treatment efficiency of DBs may be improved by incorporating wetland characteristics. Full article

This paper presents a comparative geometric analysis of the conditional bias (CB)-informed Kalman filter (KF) with the Kalman filter (KF) in the Euclidean space. The CB-informed KFs considered include the CB-penalized KF (CBPKF) and its ensemble extension, the CB-penalized Ensemble KF (CBEnKF). The geometric illustration for the CBPKF is given for the bi-state model, composed of an observable state and an unobservable state. The CBPKF co-minimizes the error variance and the variance of the Type-II error. As such, CBPKF-updated state error vectors are larger than the KF-updated, the latter of which is based on minimizing the error variance only. Different error vectors in the Euclidean space imply different eigenvectors and covariance ellipses in the state space. To characterize the differences in geometric attributes between the two filters, numerical experiments were carried out using the Lorenz 63 model. The results show that the CBEnKF yields more accurate confidence regions for encompassing the truth, smaller errors in the ensemble mean, and larger norms for Kalman gain and error covariance matrices than the EnKF, particularly when assimilating highly uncertain observations. Full article

The Apuan Alps (Italy) are an internationally renowned karst region where several karst springs have a mean discharge exceeding 100 L/s, thus representing important water resources. One of the major springs, the Pollaccia, was monitored for approximately one year. This spring drains a structurally complex metamorphic karst aquifer that is characterized by multiple hydrologic sectors with variable recharge and infiltration styles. Spring discharge, water temperature, and electrical conductivity were compared to precipitation data, and time lag analysis was performed on 27 storm hydro/thermo/chemographs (HTC-graphs) that occurred in different hydrological phases. A marked seasonality was observed for all the monitored parameters and for the measured lags. The comparison of the storm HTC-graphs with no precipitation phases permitted recognition of the differential contribution of the various sectors. The Pollaccia’s hydrodynamic behavior was related to three different scenarios in the recharge area: (1) allogenic runoff recharge in the noncarbonate sectors; (2) autogenic recharge and runoff over the steeply dipping marble outcrops, characterized by fast epiphreatic flow through master conduits and low epikarst storage; (3) autogenic recharge through highly fractured, gently dipping marble outcrops, characterized by quick hydraulic pressure transfer to the phreatic zone and relevant epikarst storage. Full article

The article presents findings of a two-year systematic study of stable isotope content in two karst groundwater resources in Primorsko-goranska county (Croatia): the Martinšćica wells (MWs) and the Dobrica spring (DBC). The temporal and spatial variation of hydrogen and oxygen isotopes is commonly studied in conjunction with hydrogeological conditions such as groundwater dynamics and discharge conditions. However, since this information was incomplete, we were forced to work with limited data and rely on analyses of stable isotope monitoring results. The obtained results show that winter precipitation is the most common recharge source for the systems, and the average residence time of water in the subsurface is less than a year. Furthermore, the MWs system is a typical dual-porosity system with dominant base flow. The results of the nonparametric regression analysis show that the possibility of seawater intrusion into the spring affecting DBC isotope content cannot be ruled out. We believe that the results presented in the paper demonstrate that when combined with statistical analyses, environmental stable isotopes are a powerful tool for gaining insights in karst hydrogeology. Full article

The focus of this study is to investigate the effects of climate change on the hydrologic regimes in Ontario, Canada. The variables include total precipitation, the form of precipitation (snowfall and rainfall), and the temperature during winter. The winter season is hydrologically significant for Canadian conditions. The historical data for 70 years, from 1939 to 2008, on total precipitation, snowfall, rainfall, and temperature over the winter period were analyzed using least-squares regressions, Alexandersson’s Standard Normal Homogeneity Test, and the Mann–Kendall test for 13 stations across Ontario to identify positive and negative trends and their significance. The analysis of the precipitation indices reveals no significant trend in the winter total precipitation, decreasing trends in winter snowfall, and increasing trends in winter rainfall. The snowy day analysis depicts a large scatter across the province, with the number ranging from 40 days to 80 days, which shows that the number of snowy days varies considerably over the years at all stations. The analysis showed that the change in snowy-rainy days is attributed to the significant upward trend of the daily mean winter minimum temperature for almost all the stations. Therefore, the changes in the form of precipitation during winter may affect water management including streamflow, tile drainage flow, soil erosion, sediment and nutrient transport to surface water bodies, and the effectiveness of best management practices being used for managing non-point source pollution. Full article

Changing water supplies and demands, inherent to climate fluctuations and human activities, are pushing for a paradigm shift in water management worldwide. The occurrence of extreme hydrometeorological and climate events such as extended wet periods and droughts, compounded with contaminants, impair the access to water resources, demanding novel designs, construction, and management across multiple hydrologic scales and biogeochemical processes. A constraint to studying hydrologic and biogeochemical disturbances and improving best management practices for water quantity and quality at the watershed scale resides in the suitable monitoring, data availability, and the creation of frameworks. We hypothesize that streamflow and contaminants, simulated by the hydrologic model Soil and Water Assessment Tool (SWAT) and evaluated during drought and extended wet periods, capture the nonlinearities of contaminants of multiple biogeochemical complexities, indicating the adaptive abilities of watersheds. Our objectives are to (1) use rain gauge and radar data and linear regression to consolidate long-term precipitation data to simulate streamflow and water quality using the SWAT model in the Shell Creek (SC) watershed, Nebraska, U.S.; (2) use drought and extended wet events analytics on observed and simulated hydroclimate and water quality variables to identify SWAT’s performance; and (3) identify the temporal attributions of streamflow and water quality to complex biogeochemical patterns of variability. We implement a watershed modeling approach using the SWAT model forced with rain gauge and radar to simulate the intraseasonal and interannual variability streamflow, sediments, nutrients, and atrazine loads in the SC watershed. SWAT performance uses a calibration period between 2000 and 2005 and a validation period between 2005 and 2007. We examine the model’s ability to simulate hydrologic and biogeochemical variables in response to dry and extended wet flow regimes. The hydrologic model forced by either radar or rain gages performs similarly in the calibration (NSE = 0.6) and validation (NSE = 0.92) periods. It reproduces medium flows closer to the observations, although it overestimates low–flows up to 0.1 m³/s while underestimates high flows by 1 m³/s. The water quality model shows higher NSE for streamflow and sediments followed by nutrients, whereas it poorly reproduces atrazine. We conclude that seasonal changes and hydroclimate conditions led to the emergence of patterns of variability associated to the nonlinearities and coupling between processes of natural and human-origin sources. As climate change propels the occurrence of hydroclimate extremes, the simulation of water quantity and quality nonlinearities—as properties of complex adaptive hydrologic systems—can contribute to improve the predictability of climate-resilient water resources. Full article

Hydrological drought is critical from both water management and ecological perspectives. Depending on its hydrological and physical features, the resilience level of a catchment to groundwater drought can differ from that of meteorological drought. This study presents a comparison of hydrological and meteorological drought indices based on groundwater levels from 1987 to 2018. A small catchment area in Croatia, consisting of two sub-catchments with a continental climate and minimum land-use changes during the observed period, was studied. The first analysis was made on a comparison of standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI). The results showed their very high correlation. The correlation between the standardized precipitation index (SPI) and standardized groundwater index (SGI) of different time scales (1, 3, 6, 12, 24 and 48 months) showed different values, but had the highest value in the longest time scale, 48 months, for all observation wells. Nevertheless, the behavior of the SPI and groundwater levels (GW) correlation showed results more related to physical catchment characteristics. The results showed that groundwater drought indices, such as SGI, should be applied judiciously because of their sensitivity to geographical, geomorphological, and topographical catchment characteristics, even in small catchment areas. Full article

Water plays a vital role in the weathering process of grottoes. Precipitation is a main water source in the grotto hosting mountain rock. In this study, time-lapse electrical resistivity tomography was adopted to track the movement of infiltrated water in a profile in the Yungang Grottoes. Our one-year monitoring data indicated a good resistivity response to rainfall in the shallow unconsolidated soil layers. There were only resistivity decreases in the near surface 5 m across the whole monitoring profile, and resistivity values quickly returned to a neutral state after the rain stopped. Based on the analysis of a typical rainfall event during the rainy season, we found that the infiltrated water cannot continuously move downwards to recharge local groundwater. It moves horizontally to a nearby gully due to the existence of a hydraulic conductive fine sand layer and low permeable mudstone and sandstone base rocks. An artificial infiltration experiment was carried out to further verify the fate of infiltrated water. Based on mass balance analysis, with 10 m³ of infiltrated water, it only saturated dry soil in the top 1.36 m soil layer on average and this was roughly consistent with our field borehole wetting front verifications at 1.2 and 1.3 m. There were limited horizontal expansions from the infiltrated water. Therefore, based on our monitoring data and analysis, infiltrated water was not the main source of the water involved in the weathering process of the Yungang Grottoes. Full article

The consequences of climate change have challenged researchers to generate models and projections to understand climate behavior under different scenarios. In Costa Rica, as in other countries, climate-change (CC) models and projections are essential to make decisions about the management of natural resources, mainly water. To understand climate change’s impact on hydraulic parameters such as velocity, depth, and river surface area, we studied the Pejibaye river basin, located in Jiménez in Cartago, Costa Rica. This watershed is characterized by having more than 90% of its surface area covered by forest. We used the precipitation and temperature data from meteorological stations (2000 to 2009) and climate-change scenarios (2000–2099) to predict the response of the basin in different periods. First, we calibrated (NSE = 0.77) and validated (NSE = 0.81) the HBV hydrological model using ten years of daily data from 2000 to 2009. The climate-change data (2000–2099) were incorporated into the calibrated HBV model. This allowed us to determine the impact of CC on the basin water regime for the periods 2040–2059 (CCS1) and 2080–2099 (CCS2). The IBER mathematical model was used to determine the changes in the hydraulic variables of the river flow. For the CCS1, we determined a 10.9% decrease in mean velocity and a 0.1-meter decrease in depth, while for CCS2, the effect will be an 11.3% reduction in mean velocity and a 0.14-meter decrease in depth. The largest decreases in river surface area per kilometer will occur in May (1710 m²) for CCS1 and April (2250 m²) for CCS2. Full article

Environmental isotopes are essential in hydrogeological studies, thanks to their contribution to the understanding of aquifers dynamics, vulnerability, water resources assessment, and management issues. The environmental isotopic approach plays a vital role in tracing the hydrological cycle and identifying various sources of contamination in the environment and gives independent information concerning what can be determined by a traditional hydrogeological study. Even in the framework of COP-26, isotopes have been indicated as fingerprints of climate change and therefore suitable for the evaluation of water balance and assessment of processes involved therein; in pollution studies they are used as fundamental support of traditional geochemical measures. Tritium, in particular, has been used since the 1960s to identify potential leaks in the containment walls of waste disposal sites, since its presence in the leachate (at very high levels in some cases) depends on the incorrect waste disposal of some peculiar items. Its use as a tracer of pollution by landfills is highlighted and emphasized by the very low concentrations of tritium in the natural environment. By comparing tritium content of leachate to that of water downflow from the waste disposal site, it is therefore possible to establish with a good success rate whether leachate have migrated or not out of the landfill, in the surrounding environment. An additional potential of tritium is to give a prompt indication of pollution risk in the environment indicating leaching even before the chemical indicator of pollution can be detected. This article wants to provide a contribution to the scientific community, collecting all the existing research in this field and providing data and benchmarks about this method, in particular stressing the role of tritium as an indicator of leachate transfer out of waste disposal sites. Full article

The transition from supercritical to subcritical flow around a fully submerged abrupt negative step in a horizontal rectangular open channel has been investigated. In a laboratory experiment the one-dimensional energy and the momentum conservation equations were studied by means of depth and pressure measurements by piezometers installed along the bottom and the step face. Froude number varied in the range 1.9 to 5.8 while the step height to critical depth ratio was in the range 1.34 to 2.56. The results are presented in dimensionless form using mainly a characteristic length scale that is the sum of critical depth and step height and the Froude number of the supercritical flow upstream. Five different types of rapidly varying flow are observed when the subcritical downstream tailwater depth varied. The supercritical water jet at the top of the step either strikes the bottom downstream of the step when the maximum pressure head is greater, or moves to the surface of the flow when it is lower than tailwater depth, and the separation of the two flow regimes occurs when the tailwater depth to the characteristic length scale is around 1.05. The normalized energy loss and a closure parameter for the momentum equation are presented in dimensionless diagrams for practical use by the design engineer. Finally, the one-dimensional equations of motion including Boussinesq terms are solved numerically and the results found are congruent to the experimental findings. Full article

The optimal design of a looped water distribution system is a problem that is addressed frequently in the literature. Usually, the flow velocity in the pipes is not taken into account. Nevertheless, in real-life applications, there are velocity restrictions that must be considered for the proper function of water distribution systems. An algorithm has been presented recently for the optimal design of such systems, relying entirely on the hydraulic characteristics of the system, and not involving any parameters to be adjusted. This paper presents a new suitably designed algorithm that retained the features of the original algorithm and handled the problem of velocity restrictions without recourse to penalty functions. The new algorithm was tested and compared with others that used penalty functions to handle the velocity constraints. The results demonstrated its efficiency, reliability, and better performance. Full article

The application of image velocimetry to measure surface streamflow velocities requires meticulous preparation, including surveying and securing both the existence of floating features on the water surface, and, as in every hydrometry method, appropriate hydraulic conditions (e.g., uniform flow, turbulent velocity profile, etc.). Though these requirements can be easily satisfied when all stages involved in image velocimetry are prepared and executed by specialists, this is not guaranteed when the video footage is recorded by citizens. This kind of spontaneously obtained data are frequently the only available information of extreme flood events; therefore, and despite their non-scientific origin and standardization, these data are very important for hydrology. In this study, we evaluate image velocimetry under a variety of conditions, including conditions resembling citizen videos. Furthermore, we conclude on the manual analysis as a means of verification of the accuracy of the velocity estimations. An interesting finding from the case study with non-uniform flow conditions was that the surface velocities occurring at the middle section of the river, estimated using large-scale particle image velocimetry algorithms, exhibited a significant error, whereas the manual estimation was more accurate. This finding calls for further investigation and a more careful approach in similar conditions. Full article

When using numerical models for hydraulic simulations of rivers, calibration is key to be able to reflect accurately the interaction of water flow in the channel and to make it resemble what is observed. In this study, a calibrated two-dimensional hydraulic model was created for two control paths located in the Ahogados and Tempisquito rivers. Paths were analyzed morphologically from a grain-size analysis and the different roughness coefficients were calculated through a numerical model using the empirical equations known as “Strickler-type” as a first approximation and later adjustment by a factor obtained from comparing the observed and simulated data. It was identified that both paths are mountain rivers with beds of coarse material, mostly boulders (cobble gravel) and pebble gravel. Calibrated roughness coefficients were determined with an error percentage between the area of the pattern formed by the simulated and observed of less than 10%, and new empirical equations adjusted to the characteristics of the riverbeds were formulated. Full article

The Okaloosa darter (Etheostoma okaloosae) is a diminutive, perch-like, benthic fish that inhabits only six small, clear, and shallow creek systems that flow almost entirely within Eglin Air Force Base in the panhandle of northwest Florida. Listed as Endangered by the U.S. Fish and Wildlife Service (USFWS) in 1973, improvements in erosion control and habitat restoration led to the Okaloosa darter being downlisted from Endangered to Threatened in 2011. However, the long-term management of the species is hampered by the lack of knowledge of the spatial extent of the recharge areas that ultimately support creek flow through groundwater discharge. To address this lack of data, we collected groundwater samples from the sand and gravel aquifer beneath 11 headwater and 11 downgradient sites across six creek basins during February and December 2020. The groundwater samples were collected from 1 to 1.2 m beneath the creek bottom. Concentrations of sulfur hexafluoride (SF₆) were analyzed and used to calculate groundwater age (residence time), and indicated that at the 11 headwater sites, recharge occurred between 11 and 28 years ago. Groundwater ages in downgradient parts of the same creeks indicated that recharge occurred between 5 and 25 years ago. When combined with representative values of hydraulic conductivity for the sand and gravel aquifer, the ages reveal that the extent of the maximum recharge distance from the sampling sites ranged from about 222 to 2011 m from the creeks. This new information can be used by natural resource managers as additional evidence to support the USFWS Recovery Plan and proposed delisting of the Okaloosa darter from the Endangered Species List. Moreover, these results may also be useful to fisheries biologists to incorporate groundwater inputs to facilitate fisheries management. Full article

This study investigates the surface processes taking place in an ungauged catchment in the Foro region in Eritrea (East Africa). We focus on estimating river discharge, sediment transport, and surface runoff to characterize hydrological fluxes in the area and provide a preliminary quantification of sediment transport and erosion. In this context, an overarching objective of the research is the study of the catchment associated with the Foro Dam. The latter comprises a silted reservoir formerly employed for agricultural water supply. The main traits associated with the system behavior across the watershed are assessed for a variety of combinations of the parameters governing the hydrological model selected. A detailed sensitivity analysis is performed to quantify the effects of the hydrological parameters on the estimated results. Numerical analyses are then performed to obtain an appraisal of expected water and sediment fluxes. Outputs of interest are largely dominated by the curve number parameter. Full article

Ombrian curves, i.e., curves linking rainfall intensity to return period and time scale, are well-established engineering tools crucial to the design against stormwaters and floods. Though the at-site construction of such curves is considered a standard hydrological task, it is a rather challenging one when large regions are of interest. Regional modeling of ombrian curves is particularly complex due to the need to account for spatial dependence together with the increased variability of rainfall extremes in space. We develop a framework for the parsimonious modeling of the extreme rainfall properties at any point in a given area. This is achieved by assuming a common ombrian model structure, except for a spatially varying scale parameter which is itself modeled by a spatial smoothing model for the 24 h average annual rainfall maxima that employs elevation as an additional explanatory variable. The fitting is performed on the pooled all-stations data using an advanced estimation procedure (K-moments) that allows both for reliable high-order moment estimation and simultaneous handling of space-dependence bias. The methodology is applied in the Thessaly region, a 13,700 km² water district of Greece characterized by varying topography and hydrometeorological properties. Full article

This study presents three global precipitation products and their downscaled versions (CHIRPSv2, TAMSATv3, PERSIANN_CDR, CHIRPS_D, PERSIANNN_CDR_D, and TAMSAT_D) estimated with observed values from 1983 to 2014. Performance evaluation of global precipitation products and their downscaled versions is important for accurate use of those measured values in water resource management, climate, and hydrological applications, particularly in the data-sparse Wabi Shebelle River Basin, Ethiopia. Categorical and quantitative evaluation index techniques were applied. The spatial downscaled global precipitation products outperformed raw spatial resolution estimates in all statistical indicators. TAMSAT-D had acceptable performance ratings in terms of RMSE, CC, and scatter plots (R²). CHIRPSv2 showed the least performance at a daily timestep. Performance of global precipitation products and their downscaled versions increased when daily data were aggregated to the monthly data. CHIRPS-D performed better than other products with a minimum error value (RMSE) and higher CC at a monthly timestep. On the other hand, PERSIANN_CDR_D showed a relatively good performance with a lower, positive Pbias and higher POD values compared to other products for daily and monthly timescales. For spatial mismatch analysis, the bias and RMSE from reference data (individual rain gauge station vs. the average of all available eight stations) against satellite rainfall estimates (PERSIANN_CDR) had a significantly different weight, which could be related to the position of the gauge station to provide the “true” spatial rainfall amount. Overall, TAMSATv3 and CHIRPSv2 and their downscaled version satellite estimates showed good performance at daily and monthly timesteps, respectively. PERSIANN_CDR performed best with low Pbias and the highest POD values. Thus, this study decided that the downscaled version of CHIRPSv2 and PERSIANN_CDR-D satellite estimates could be applicable as an alternative to gauge data on a monthly timestep for hydrological and drought-monitoring applications, respectively. Full article