Hydrology

41 pages, 24123 KiB

Open AccessEditor’s ChoiceArticle

Coupling HEC-RAS and AI for River Morphodynamics Assessment Under Changing Flow Regimes: Enhancing Disaster Preparedness for the Ottawa River

by Mohammad Uzair Anwar Qureshi, Afshin Amiri, Isa Ebtehaj, Silvio José Guimere, Juraj Cunderlik and Hossein Bonakdari

Hydrology 2025, 12(2), 25; https://doi.org/10.3390/hydrology12020025 - 4 Feb 2025

Cited by 2 | Viewed by 1356

Abstract

Despite significant advancements in flood forecasting using machine learning (ML) algorithms, recent events have revealed hydrological behaviors deviating from historical model development trends. The record-breaking 2019 flood in the Ottawa River basin, which exceeded the 100-year flood threshold, underscores the escalating impact of [...] Read more.

Despite significant advancements in flood forecasting using machine learning (ML) algorithms, recent events have revealed hydrological behaviors deviating from historical model development trends. The record-breaking 2019 flood in the Ottawa River basin, which exceeded the 100-year flood threshold, underscores the escalating impact of climate change on hydrological extremes. These unprecedented events highlight the limitations of traditional ML models, which rely heavily on historical data and often struggle to predict extreme floods that lack representation in past records. This calls for integrating more comprehensive datasets and innovative approaches to enhance model robustness and adaptability to changing climatic conditions. This study introduces the Next-Gen Group Method of Data Handling (Next-Gen GMDH), an innovative ML model leveraging second- and third-order polynomials to address the limitations of traditional ML models in predicting extreme flood events. Using HEC-RAS simulations, a synthetic dataset of river flow discharges was created, covering a wide range of potential future floods with return periods of up to 10,000 years, to enhance the accuracy and generalization of flood predictions under evolving climatic conditions. The Next-Gen GMDH addresses the complexity and limitations of standard GMDH by incorporating non-adjacent connections and optimizing intermediate layers, significantly reducing computational overhead while enhancing performance. The Gen GMDH demonstrated improved stability and tighter clustering of predictions, particularly for extreme flood scenarios. Testing results revealed exceptional predictive accuracy, with Mean Absolute Percentage Error (MAPE) values of 4.72% for channel width, 1.80% for channel depth, and 0.06% for water surface elevation. These results vastly outperformed the standard GMDH, which yielded MAPE values of 25.00%, 8.30%, and 0.11%, respectively. Additionally, computational complexity was reduced by approximately 40%, with a 33.88% decrease in the Akaike Information Criterion (AIC) for channel width and an impressive 581.82% improvement for channel depth. This methodology integrates hydrodynamic modeling with advanced ML, providing a robust framework for accurate flood prediction and adaptive floodplain management in a changing climate. Full article

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25 pages, 9673 KiB

Open AccessEditor’s ChoiceArticle

A Systematic Modular Approach for the Coupling of Deep-Learning-Based Models to Forecast Urban Flooding Maps in Early Warning Systems

by Juliana Koltermann da Silva, Benjamin Burrichter, Andre Niemann and Markus Quirmbach

Hydrology 2024, 11(12), 215; https://doi.org/10.3390/hydrology11120215 - 12 Dec 2024

Viewed by 1133

Abstract

Deep learning (DL) approaches to forecast precipitation and inundation areas in the short-term forecast horizon have up until now been treated as independent research problems from the model development perspective. However, for the urban hydrology area, the coupling of these models is necessary [...] Read more.

Deep learning (DL) approaches to forecast precipitation and inundation areas in the short-term forecast horizon have up until now been treated as independent research problems from the model development perspective. However, for the urban hydrology area, the coupling of these models is necessary in order to forecast the upcoming inundation area maps and is, therefore, of the utmost importance for successful flood risk management. In this paper, three deep-learning-based models are coupled in a systematic modular approach with the aim to analyze the performance of this model chain in an operative setup for urban pluvial flooding nowcast: precipitation nowcasting with an adapted version of the NowcastNet model, the forecast of manhole overflow hydrographs with a Seq2Seq model, and the generation of a spatiotemporal sequence of inundation areas in an urban catchment for the upcoming hour with an encoder–decoder model. It can be concluded that the forecast quality still largely depends on the accuracy of the precipitation nowcasting model. With the increasing development of DL models for both precipitation and flood nowcasting, the presented modular approach for model coupling enables the substitution of individual blocks for better and newer models in the model chain without jeopardizing the operation of the flooding forecast system. Full article

(This article belongs to the Special Issue New Perspectives in the Flood Forecasting Chain (Weather Prediction, Rainfall-Runoff Modeling, and Communication with Stakeholders))

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22 pages, 13992 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Simulation of Seawater Intrusion and Upconing Processes in Mediterranean Aquifer in Response to Climate Change (Plana de Castellón, Spain)

by Barbara del R. Almazan-Benitéz, Maria V. Esteller-Alberich, Arianna Renau-Pruñonosa and José L. Expósito-Castillo

Hydrology 2024, 11(12), 205; https://doi.org/10.3390/hydrology11120205 - 28 Nov 2024

Cited by 1 | Viewed by 1216

Abstract

In coastal regions, groundwater is often the only freshwater resource available for human consumption, agriculture, and other productive activities. From a management point of view, it is essential to understand the processes that occur in a coastal aquifer affected by seawater intrusion and [...] Read more.

In coastal regions, groundwater is often the only freshwater resource available for human consumption, agriculture, and other productive activities. From a management point of view, it is essential to understand the processes that occur in a coastal aquifer affected by seawater intrusion and upconing processes and evaluate their potential response to climate change as these scenarios usually indicate a decrease in aquifer recharge. Therefore, the dynamics of seawater intrusion and the upconing process in the Plana de Castellón aquifer on the Mediterranean coast were analysed by building and calibrating a new numerical model of flow and transport using the MODFLOW and SEAWAT codes. The model was used to examine two Shared Socioeconomic Pathway (SSP) climate change scenarios (SSP1–2.6 and SSP5–8.5) when considering field data with constant extraction conditions. The results suggest that by 2050, groundwater levels could rise by 0.18 m (on average) in the SSP1–2.6 scenario and by 0.12 m for the SSP5–8.5 scenario. In these cases, aquifer recharge and groundwater discharge to the sea could increase compared to the historical period, as precipitation is not expected to decrease significantly during this timeframe, even in the most unfavourable scenario (SSP5–8.5). The result would be the attenuation of seawater intrusion and a decrease in the volume of the aquifer that is affected by the upconing process, resulting in total dissolved solids values below 2000 mg/L. The innovation of this research lies in the fact that the numerical model allowed the dynamics of seawater intrusion and the upconing process to be adequately represented, especially in the latter process, as it was not possible to model it with real data in another study. These results can improve and facilitate decision-making for the management of the aquifer and contribute to plans for future exploitation strategies. Full article

(This article belongs to the Section Hydrology–Climate Interactions)

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17 pages, 5575 KiB

Open AccessEditor’s ChoiceArticle

The Importance of Solving Subglaciar Hydrology in Modeling Glacier Retreat: A Case Study of Hansbreen, Svalbard

by Eva De Andrés, José M. Muñoz-Hermosilla, Kaian Shahateet and Jaime Otero

Hydrology 2024, 11(11), 193; https://doi.org/10.3390/hydrology11110193 - 12 Nov 2024

Viewed by 1376

Abstract

Arctic tidewater glaciers are retreating, serving as key indicators of global warming. This study aims to assess how subglacial hydrology affects glacier front retreat by comparing two glacier–fjord models of the Hansbreen glacier: one incorporating a detailed subglacial hydrology model and another simplifying [...] Read more.

Arctic tidewater glaciers are retreating, serving as key indicators of global warming. This study aims to assess how subglacial hydrology affects glacier front retreat by comparing two glacier–fjord models of the Hansbreen glacier: one incorporating a detailed subglacial hydrology model and another simplifying the subglacial discharge to a single channel centered in the flow line. We first validate the subglacial hydrology model by comparing its discharge channels with observations of plume activity. Simulations conducted from April to December 2010 revealed that the glacier front position aligns more closely with the observations in the coupled model than in the simplified version. Furthermore, the mass loss due to calving and submarine melting is greater in the coupled model, with the calving mass loss reaching 6 Mt by the end of the simulation compared to 4 Mt in the simplified model. These findings highlight the critical role of subglacial hydrology in predicting glacier dynamics and emphasize the importance of detailed modeling in understanding the responses of Arctic tidewater glaciers to climate change. Full article

(This article belongs to the Section Hydrological and Hydrodynamic Processes and Modelling)

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18 pages, 3661 KiB

Open AccessEditor’s ChoiceArticle

Estimation of Reservoir Storage Capacity Using the Gould-Dincer Formula with the Aid of Possibility Theory

by Nikos Mylonas, Christos Tzimopoulos, Basil Papadopoulos and Nikiforos Samarinas

Hydrology 2024, 11(10), 172; https://doi.org/10.3390/hydrology11100172 - 11 Oct 2024

Viewed by 1364

Abstract

This paper presents a method for estimating reservoir storage capacity using the Gould–Dincer normal formula (G-DN), enhanced by the possibility theory. The G-DN equation is valuable for regional studies of reservoir reliability, particularly under climate change scenarios, using regional statistics. However, because the [...] Read more.

This paper presents a method for estimating reservoir storage capacity using the Gould–Dincer normal formula (G-DN), enhanced by the possibility theory. The G-DN equation is valuable for regional studies of reservoir reliability, particularly under climate change scenarios, using regional statistics. However, because the G-DN formula deals with measured data, it introduces a degree of uncertainty and fuzziness that traditional probability theory struggles to address. Possibility theory, an extension of fuzzy set theory, offers a suitable framework for managing this uncertainty and fuzziness. In this study, the G-DN formula is adapted to incorporate fuzzy logic, and the possibilistic nature of reservoir capacity is translated into a probabilistic framework using α-cuts from the possibility theory. These α-cuts approximate probability confidence intervals with high confidence. Applying the proposed methodology, in the present crisp case with the storage capacity D = 0.75, the value of the capacity C was found to be

1271 \times 10^{6} m^{3}

, and that for D = 0.5 was

634.5 \times 10^{6} m^{3}

. On the other hand, in the fuzzy case using the possibility theory, the value of the capacity for D = 0.75 is the internal

[315, 5679] \times 10^{6} m^{3}

and for D = 0.5 the value is interval

[158, 2839] \times 10^{6} m^{3}

, with a probability of ≥95% and a risk level of α = 5% for both cases. The proposed approach could be used as a robust tool in the toolkit of engineers working on irrigation, drainage, and water resource projects, supporting informed and effective engineering decisions. Full article

(This article belongs to the Special Issue Water Resources Management under Uncertainty and Climate Change)

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22 pages, 3626 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Estimating Non-Stationary Extreme-Value Probability Distribution Shifts and Their Parameters Under Climate Change Using L-Moments and L-Moment Ratio Diagrams: A Case Study of Hydrologic Drought in the Goat River Near Creston, British Columbia

by Isaac Dekker, Kristian L. Dubrawski, Pearce Jones and Ryan MacDonald

Hydrology 2024, 11(9), 154; https://doi.org/10.3390/hydrology11090154 - 14 Sep 2024

Viewed by 1734

Abstract

Here, we investigate the use of rolling-windowed L-moments (RWLMs) and L-moment ratio diagrams (LMRDs) combined with a Multiple Linear Regression (MLR) machine learning algorithm to model non-stationary low-flow hydrological extremes with the potential to simultaneously understand time-variant shape, scale, location, and probability distribution [...] Read more.

Here, we investigate the use of rolling-windowed L-moments (RWLMs) and L-moment ratio diagrams (LMRDs) combined with a Multiple Linear Regression (MLR) machine learning algorithm to model non-stationary low-flow hydrological extremes with the potential to simultaneously understand time-variant shape, scale, location, and probability distribution (PD) shifts under climate change. By employing LMRDs, we analyse changes in PDs and their parameters over time, identifying key environmental predictors such as lagged precipitation for September 5-day low-flows. Our findings indicate a significant relationship between total August precipitation L-moment ratios (LMRs) and September 5-day low-flow LMRs (

τ_{2}

-Precipitation and

τ_{2}

-Discharge: R² = 0.675, p-values < 0.001;

τ_{3}

-Precipitation and

τ_{3}

-Discharge: R² = 0.925, p-value for slope < 0.001, intercept not significant with p = 0.451, assuming

α

= 0.05 and a 31-year RWLM), which we later refine and use for prediction within our MLR algorithm. The methodology, applied to the Goat River near Creston, British Columbia, aids in understanding the implications of climate change on water resources, particularly for the yaqan nuʔkiy First Nation. We find that future low-flows under climate change will be outside the Natural Range of Variability (NROV) simulated from historical records (assuming a constant PD). This study provides insights that may help in adaptive water management strategies necessary to help preserve Indigenous cultural rights and practices and to help sustain fish and fish habitat into the future. Full article

(This article belongs to the Section Hydrological and Hydrodynamic Processes and Modelling)

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17 pages, 27193 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

A Machine Learning Approach to Map the Vulnerability of Groundwater Resources to Agricultural Contamination

by Victor Gómez-Escalonilla and Pedro Martínez-Santos

Hydrology 2024, 11(9), 153; https://doi.org/10.3390/hydrology11090153 - 13 Sep 2024

Viewed by 2031

Abstract

Groundwater contamination poses a major challenge to water supplies around the world. Assessing groundwater vulnerability is crucial to protecting human livelihoods and the environment. This research explores a machine learning-based variation of the classic DRASTIC method to map groundwater vulnerability. Our approach is [...] Read more.

Groundwater contamination poses a major challenge to water supplies around the world. Assessing groundwater vulnerability is crucial to protecting human livelihoods and the environment. This research explores a machine learning-based variation of the classic DRASTIC method to map groundwater vulnerability. Our approach is based on the application of a large number of tree-based machine learning algorithms to optimize DRASTIC’s parameter weights. This contributes to overcoming two major issues that are frequently encountered in the literature. First, we provide an evidence-based alternative to DRASTIC’s aprioristic approach, which relies on static ratings and coefficients. Second, the use of machine learning approaches to compute DRASTIC vulnerability maps takes into account the spatial distribution of groundwater contaminants, which is expected to improve the spatial outcomes. Despite offering moderate results in terms of machine learning metrics, the machine learning approach was more accurate in this case than a traditional DRASTIC application if appraised as per the actual distribution of nitrate data. The method based on supervised classification algorithms was able to produce a mapping in which about 45% of the points with high nitrate concentrations were located in areas predicted as high vulnerability, compared to 6% shown by the original DRASTIC method. The main difference between using one method or the other thus lies in the availability of sufficient nitrate data to train the models. It is concluded that artificial intelligence can lead to more robust results if enough data are available. Full article

(This article belongs to the Section Surface Waters and Groundwaters)

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20 pages, 3519 KiB

Open AccessEditor’s ChoiceArticle

The Implementation of Multimodal Large Language Models for Hydrological Applications: A Comparative Study of GPT-4 Vision, Gemini, LLaVa, and Multimodal-GPT

by Likith Anoop Kadiyala, Omer Mermer, Dinesh Jackson Samuel, Yusuf Sermet and Ibrahim Demir

Hydrology 2024, 11(9), 148; https://doi.org/10.3390/hydrology11090148 - 11 Sep 2024

Cited by 9 | Viewed by 4046

Abstract

Large Language Models (LLMs) combined with visual foundation models have demonstrated significant advancements, achieving intelligence levels comparable to human capabilities. This study analyzes the latest Multimodal LLMs (MLLMs), including Multimodal-GPT, GPT-4 Vision, Gemini, and LLaVa, with a focus on hydrological applications such as [...] Read more.

Large Language Models (LLMs) combined with visual foundation models have demonstrated significant advancements, achieving intelligence levels comparable to human capabilities. This study analyzes the latest Multimodal LLMs (MLLMs), including Multimodal-GPT, GPT-4 Vision, Gemini, and LLaVa, with a focus on hydrological applications such as flood management, water level monitoring, agricultural water discharge, and water pollution management. We evaluated these MLLMs on hydrology-specific tasks, testing their response generation and real-time suitability in complex real-world scenarios. Prompts were designed to enhance the models’ visual inference capabilities and contextual comprehension from images. Our findings reveal that GPT-4 Vision demonstrated exceptional proficiency in interpreting visual data, providing accurate assessments of flood severity and water quality. Additionally, MLLMs showed potential in various hydrological applications, including drought prediction, streamflow forecasting, groundwater management, and wetland conservation. These models can optimize water resource management by predicting rainfall, evaporation rates, and soil moisture levels, thereby promoting sustainable agricultural practices. This research provides valuable insights into the potential applications of advanced AI models in addressing complex hydrological challenges and improving real-time decision-making in water resource management Full article

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21 pages, 2741 KiB

Open AccessEditor’s ChoiceArticle

Continental Scale Regional Flood Frequency Analysis: Combining Enhanced Datasets and a Bayesian Framework

by Duy Anh Alexandre, Chiranjib Chaudhuri and Jasmin Gill-Fortin

Hydrology 2024, 11(8), 119; https://doi.org/10.3390/hydrology11080119 - 11 Aug 2024

Cited by 2 | Viewed by 1789

Abstract

Flood frequency analysis at large scales, essential for the development of flood risk maps, is hindered by the scarcity of gauge flow data. Suitable methods are thus required to predict flooding in ungauged basins, a notoriously complex problem in hydrology. We develop a [...] Read more.

Flood frequency analysis at large scales, essential for the development of flood risk maps, is hindered by the scarcity of gauge flow data. Suitable methods are thus required to predict flooding in ungauged basins, a notoriously complex problem in hydrology. We develop a Bayesian hierarchical model (BHM) based on the generalized extreme value (GEV) and the generalized Pareto distribution for regional flood frequency analysis at high resolution across a large part of North America. Our model leverages annual maximum flow data from ≈20,000 gauged stations and a dataset of 130 static catchment-specific covariates to predict extreme flows at all catchments over the continent as well as their associated statistical uncertainty. Additionally, a modification is made to the data layer of the BHM to include peaks over threshold flow data when available, which improves the precision of the discharge level estimates. We validated the model using a hold-out approach and found that its predictive power is very good for the GEV distribution location and scale parameters and improvable for the shape parameter, which is notoriously hard to estimate. The resulting discharge return levels yield a satisfying agreement when compared with the available design peak discharge from various government sources. The assessment of the covariates’ contributions to the model is also informative with regard to the most relevant underlying factors influencing flood-inducing peak flows. According to the developed aggregate importance score, the key covariates in our model are temperature-related bioindicators, the catchment drainage area and the geographical location. Full article

(This article belongs to the Section Water Resources and Risk Management)

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37 pages, 2150 KiB

Open AccessEditor’s ChoiceArticle

Monitoring Slope Movement and Soil Hydrologic Behavior Using IoT and AI Technologies: A Systematic Review

by Md Jobair Bin Alam, Luis Salgado Manzano, Rahul Debnath and Ahmed Abdelmoamen Ahmed

Hydrology 2024, 11(8), 111; https://doi.org/10.3390/hydrology11080111 - 24 Jul 2024

Cited by 8 | Viewed by 2942

Abstract

Landslides or slope failure pose a significant risk to human lives and infrastructures. The stability of slopes is controlled by various hydrological processes such as rainfall infiltration, soil water dynamics, and unsaturated soil behavior. Accordingly, soil hydrological monitoring and tracking the displacement of [...] Read more.

Landslides or slope failure pose a significant risk to human lives and infrastructures. The stability of slopes is controlled by various hydrological processes such as rainfall infiltration, soil water dynamics, and unsaturated soil behavior. Accordingly, soil hydrological monitoring and tracking the displacement of slopes become crucial to mitigate such risks by issuing early warnings to the respective authorities. In this context, there have been advancements in monitoring critical soil hydrological parameters and slope movement to ensure potential causative slope failure hazards are identified and mitigated before they escalate into disasters. With the advent of the Internet of Things (IoT), artificial intelligence, and high-speed internet, the potential to use such technologies for remotely monitoring soil hydrological parameters and slope movement is becoming increasingly important. This paper provides an overview of existing hydrological monitoring systems using IoT and AI technologies, including soil sampling, deploying on-site sensors such as capacitance, thermal dissipation, Time-Domain Reflectometers (TDRs), geophysical applications, etc. In addition, we review and compare the traditional slope movement detection systems, including topographic surveys for sophisticated applications such as terrestrial laser scanners, extensometers, tensiometers, inclinometers, GPS, synthetic aperture radar (SAR), LiDAR, and Unmanned Aerial Vehicles (UAVs). Finally, this interdisciplinary research from both Geotechnical Engineering and Computer Science perspectives provides a comprehensive state-of-the-art review of the different methodologies and solutions for monitoring landslides and slope failures, along with key challenges and prospects for potential future study. Full article

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18 pages, 5340 KiB

Open AccessEditor’s ChoiceArticle

Measurement and Calculation of Sediment Transport on an Ephemeral Stream

by Loukas Avgeris, Konstantinos Kaffas and Vlassios Hrissanthou

Hydrology 2024, 11(7), 96; https://doi.org/10.3390/hydrology11070096 - 30 Jun 2024

Cited by 1 | Viewed by 1604

Abstract

Sediment transport remains a significant challenge for researchers due to the intricate nature of the physical processes involved and the diverse characteristics of watercourses worldwide. A type of watercourse that is of particular interest for study is the ephemeral streams, found primarily in [...] Read more.

Sediment transport remains a significant challenge for researchers due to the intricate nature of the physical processes involved and the diverse characteristics of watercourses worldwide. A type of watercourse that is of particular interest for study is the ephemeral streams, found primarily in semiarid and arid regions. Due to their unique nature, a new measurement algorithm was created and a modified bed load sampler was built. Measurement of the bed load transport rate and calculation of the water discharge were conducted in an ephemeral stream in Northeastern Greece, where the mean calculated streamflow rate ranged from 0.019 to 0.314 m³/s, and the measured sediment load transport rates per unit width varied from 0.00001 to 0.00213 kg/m/s. The sediment concentration was determined through various methods, including nonlinear regression equations and formulas developed by Yang, with the coefficients of these formulas calibrated accordingly. The results demonstrated that the equations derived from Yang’s multiple regression analysis offered a superior fit compared to the original equations. As a result, two modified versions of Yang’s stream sediment transport formulas were developed and are presented to the readership. To assess the accuracy of the modified formulas, a comparison was conducted between the calculated total sediment concentrations and the measured total sediment concentrations based on various statistical criteria. The analysis shows that none of Yang’s original formulas fit the available data well, but after optimization, both modified formulas can be applied to the specific ephemeral stream. The results indicate also that the formulas derived from the nonlinear regression can be successfully used for the determination of the total sediment concentration in the ephemeral stream and have a better fit compared to Yang’s formulas. The correlation from the nonlinear regression equations suggests that total sediment transport is primarily influenced by water discharge and rainfall intensity, with the latter showing a high correlation coefficient of 0.998. Full article

(This article belongs to the Special Issue Advances in Catchments Hydrology and Sediment Dynamics)

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18 pages, 12564 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Climate Change Projections of Potential Evapotranspiration for the North American Monsoon Region

by Eylon Shamir, Lourdes Mendoza Fierro, Sahar Mohsenzadeh Karimi, Norman Pelak, Emilie Tarouilly, Hsin-I Chang and Christopher L. Castro

Hydrology 2024, 11(6), 83; https://doi.org/10.3390/hydrology11060083 - 14 Jun 2024

Cited by 2 | Viewed by 3347

Abstract

We assessed and quantified future projected changes in terrestrial evaporative demand by calculating Potential Evapotranspiration (PET) for the North American Monsoon region in the Southwestern U.S. and Mexico. The PET projections were calculated using the daily Penman–Monteith equation. The terrestrial meteorological variables needed [...] Read more.

We assessed and quantified future projected changes in terrestrial evaporative demand by calculating Potential Evapotranspiration (PET) for the North American Monsoon region in the Southwestern U.S. and Mexico. The PET projections were calculated using the daily Penman–Monteith equation. The terrestrial meteorological variables needed for the equation (i.e., minimum and maximum daily temperature, specific humidity, wind speed, incoming shortwave radiation, and pressure) were obtained from the North American–CORDEX initiative. We used dynamically downscaled projections of three CMIP5 GCMs for RCP8.5 emission scenarios (i.e., HadGEM2-ES, MPI-ESM-LR, and GFDL-ESM2M), and each was dynamically downscaled to ~25 km by two RCMs (i.e., WRF and regCM4). All terrestrial annual PET projections showed a statistically significant increase when comparing the historical period (1986–2005) to future projections (2020–2039 and 2040–2059). The regional spatial average of the six GCM-RCM combinations projected an increase in the annual PET of about +4% and +8% for 2020–2039 and 2040–2059, respectively. The projected average 20-year annual changes over the study area range for the two projection periods were +1.4%–+8.7% and +3%–+14.2%, respectively. The projected annual PET increase trends are consistent across the entire region and for the six GCM-RCM combinations. Higher annual changes are projected in the northeast part of the region, while smaller changes are projected along the pacific coast. The main drivers for the increase are the projected warming and increase in the vapor pressure deficit. The projected changes in PET, which represent the changes in the atmospheric evaporative demand, are substantial and likely to impact vegetation and the hydrometeorological regime in the area. Quantitative assessments of the projected PET changes provided by this study should be considered in upcoming studies to develop resilience plans and adaptation strategies for mitigating the projected future changes. Full article

(This article belongs to the Special Issue Advances in Evaporation and Evaporative Demand: Part II)

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18 pages, 5743 KiB

Open AccessEditor’s ChoiceArticle

Trend Analysis of Hydro-Meteorological Variables in the Wadi Ouahrane Basin, Algeria

by Mohammed Achite, Tommaso Caloiero, Andrzej Wałęga, Alessandro Ceppi and Abdelhak Bouharira

Hydrology 2024, 11(6), 77; https://doi.org/10.3390/hydrology11060077 - 31 May 2024

Cited by 1 | Viewed by 1608

Abstract

In recent decades, a plethora of natural disasters, including floods, storms, heat waves, droughts, and various other weather-related events, have brought destruction worldwide. In particular, Algeria is facing several natural hydrometeorological and geological hazards. In this study, meteorological parameters (precipitation, temperature, relative humidity, [...] Read more.

In recent decades, a plethora of natural disasters, including floods, storms, heat waves, droughts, and various other weather-related events, have brought destruction worldwide. In particular, Algeria is facing several natural hydrometeorological and geological hazards. In this study, meteorological parameters (precipitation, temperature, relative humidity, wind speed, and sunshine) and runoff data were analyzed for the Wadi Ouahrane basin (northern Algeria), into which drains much of the surrounding agricultural land and is susceptible to floods. In particular, a trend analysis was performed using the Mann–Kendall (MK) test, the Sen’s slope estimator, and the Innovative Trend Analysis (ITA) method to detect possible trends in the time series over the period 1972/73–2017/2018. The results revealed significant trends in several hydro-meteorological variables. In particular, neither annual nor monthly precipitation showed a clear tendency, thus failing to indicate potential changes in the rainfall patterns. Temperature evidenced a warming trend, indicating a potential shift in the local climate, while streamflow revealed a decreasing trend, reflecting the complex interaction between precipitation and other hydrological factors. Full article

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24 pages, 6357 KiB

Open AccessEditor’s ChoiceArticle

Fuzzy Finite Elements Solution Describing Recession Flow in Unconfined Aquifers

by Christos Tzimopoulos, Kyriakos Papadopoulos, Nikiforos Samarinas, Basil Papadopoulos and Christos Evangelides

Hydrology 2024, 11(4), 47; https://doi.org/10.3390/hydrology11040047 - 30 Mar 2024

Cited by 2 | Viewed by 1999

Abstract

In this work, a novel fuzzy FEM (Finite Elements Method) numerical solution describing the recession flow in unconfined aquifers is proposed. In general, recession flow and drainage problems can be described by the nonlinear Boussinesq equation, while the introduced hydraulic parameters (Conductivity K [...] Read more.

In this work, a novel fuzzy FEM (Finite Elements Method) numerical solution describing the recession flow in unconfined aquifers is proposed. In general, recession flow and drainage problems can be described by the nonlinear Boussinesq equation, while the introduced hydraulic parameters (Conductivity K and Porosity S) present significant uncertainties for various reasons (e.g., spatial distribution, human errors, etc.). Considering the general lack of in situ measurements for these parameters as well as the certain spatial variability that they present in field scales, a fuzzy approach was adopted to include the problem uncertainties and cover the disadvantage of ground truth missing data. The overall problem is encountered with a new approximate fuzzy FEM numerical solution, leading to a system of crisp boundary value problems. To prove the validity and efficiency of the new fuzzy FEM, a comparative analysis between the proposed approach and other well-known and tested approximations was carried out. According to the results, the proposed FEM numerical solution agrees with Karadinumerical method for the crisp case and is in close agreement with the original analytical solution proposed by Boussinesq in 1904 with the absolute reduced error to be 4.6‰. Additionally, the possibility theory is applied, enabling the engineers and designers of irrigation, drainage, and water resources projects to gain knowledge of hydraulic properties (e.g., water level, outflow volume) and make the right decisions for rational and productive engineering studies. Full article

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21 pages, 7741 KiB

Open AccessEditor’s ChoiceArticle

A Thermal Regime and a Water Circulation in a Very Deep Lake: Lake Tazawa, Japan

by Kazuhisa A. Chikita, Hideo Oyagi and Kazuhiro Amita

Hydrology 2024, 11(3), 40; https://doi.org/10.3390/hydrology11030040 - 16 Mar 2024

Cited by 1 | Viewed by 2274

Abstract

A thermal system in the very deep Lake Tazawa (maximum depth, 423 m) was investigated by estimating the heat budget. In the heat budget estimate, the net heat input at the lake’s surface and the heat input by river inflow and groundwater inflow [...] Read more.

A thermal system in the very deep Lake Tazawa (maximum depth, 423 m) was investigated by estimating the heat budget. In the heat budget estimate, the net heat input at the lake’s surface and the heat input by river inflow and groundwater inflow were considered. Then, the heat loss by snowfall onto the lake’s surface was taken into account. Meanwhile, the lake water temperature was monitored at 0.2 m to the bottom by mooring temperature loggers for more than two years. The heat storage change of the lake from the loggers was calibrated by frequent vertical measurements of water temperature at every 0.1 m pitch by a profiler with high accuracy (±0.01 °C). The heat storage change (W/m²) obtained by the temperature loggers reasonably accorded to that from the heat budget estimate. In the heat budget, the net heat input at lake surface dominated the heat storage change, but significant heat loss by river inflow sporadically occurred, caused by the relatively large discharge from a reservoir in the upper region. How deeply the vertical water circulation in the lake occurs in winter was judged according to the differences between water temperatures at 0.2 m depth and at the bottom and between vertical profiles of dissolved oxygen over winter. It is strongly suggested that the whole water circulation process does not occur every winter, and if it does, it is very weak. A consistent increase in the water temperature at the bottom is probably due to the conservation of geothermal heat by high frequency of incomplete vertical water circulation. Full article

(This article belongs to the Topic Climate Change and Human Impact on Freshwater Water Resources: Rivers and Lakes)

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18 pages, 4007 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Agricultural Water Footprints and Productivity in the Colorado River Basin

by George B. Frisvold and Dari Duval

Hydrology 2024, 11(1), 5; https://doi.org/10.3390/hydrology11010005 - 30 Dec 2023

Cited by 4 | Viewed by 4746

Abstract

The Colorado River provides water to 40 million people in the U.S. Southwest, with river basin spanning 250,000 square miles (647,497 km²). Quantitative water rights assigned to U.S. states, Mexico, and tribes in the Colorado Basin exceed annual streamflows. Climate change [...] Read more.

The Colorado River provides water to 40 million people in the U.S. Southwest, with river basin spanning 250,000 square miles (647,497 km²). Quantitative water rights assigned to U.S. states, Mexico, and tribes in the Colorado Basin exceed annual streamflows. Climate change is expected to limit streamflows further. To balance water demands with supplies, unprecedented water-use cutbacks have been proposed, primarily for agriculture, which consumes more than 60% of the Basin’s water. This study develops county-level, Basin-wide measures of agricultural economic water productivity, water footprints, and irrigation cash rent premiums, to inform conservation programs and compensation schemes. These measures identify areas where conservation costs in terms of foregone crop production or farm income are high or low. Crop sales averaged USD 814 per acre foot (AF) (USD 0.66/m³) of water consumed in the Lower Basin and 131 USD/AF (USD 0.11/m³) in the Upper Basin. Crop sales minus crop-specific input costs averaged 485 USD/AF (USD 0.39/m³) in the Lower Basin and 93 USD/AF (USD 0.08 per m³) in the Upper Basin. The blue water footprint (BWF) was 1.2 AF/USD 1K (1480 m³/USD1K) of water per thousand dollars of crop sales in the Lower Basin and 7.6 AF/USD 1K (9374 m³/USD1K) in the Upper Basin. Counties with higher water consumption per acre have a lower BWF. Full article

(This article belongs to the Special Issue Water Resources Management under Uncertainty and Climate Change)

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25 pages, 33171 KiB

Open AccessEditor’s ChoiceArticle

Spatial Estimation of Snow Water Equivalent for Glaciers and Seasonal Snow in Iceland Using Remote Sensing Snow Cover and Albedo

by Andri Gunnarsson and Sigurdur M. Gardarsson

Hydrology 2024, 11(1), 3; https://doi.org/10.3390/hydrology11010003 - 26 Dec 2023

Cited by 1 | Viewed by 3267

Abstract

Efficient water resource management in glacier- and snow-dominated basins requires accurate estimates of the snow water equivalent (SWE) in late winter and spring and melt onset timing and intensity. To understand the high spatio-temporal variability of snow and glacier ablation, a spatially distributed [...] Read more.

Efficient water resource management in glacier- and snow-dominated basins requires accurate estimates of the snow water equivalent (SWE) in late winter and spring and melt onset timing and intensity. To understand the high spatio-temporal variability of snow and glacier ablation, a spatially distributed energy balance model combining satellite-based retrievals of albedo and snow cover was applied. Incoming short-wave energy, contributing to daily estimates of melt energy, was constrained by remotely sensed surface albedo for snow-covered surfaces. Fractional snow cover was used for non-glaciated areas, as it provides estimates of snow cover for each pixel to better constrain snow melt. Thus, available daily estimates of melt energy in a given area were the product of the possible melt energy and the fractional snow cover of the area or pixel for non-glaciated areas. This provided daily estimates of melt water to determine seasonal snow and glacier ablation in Iceland for the period 2000–2019. Observations from snow pits on land and glacier summer mass balance were used for evaluation, and observations from land and glacier-based automatic weather stations were used to evaluate model inputs for the energy balance model. The results show that the interannual SWE variability was generally high both for seasonal snow and glaciers. For seasonal snow, the largest SWE (>1000 mm) was found in mountainous and alpine areas close to the coast, notably in the East- and Westfjords, Tröllaskaga, and in the vicinity of glacier margins. Lower SWE values were observed in the central highlands, flatter inland areas, and at lower elevations. For glaciers, more SWE (glacier ablation) was associated with lower glacier elevations while less melt was observed at higher elevations. For the impurity-rich bare-ice areas that are exposed annually, observed SWE was more than 3000 mm. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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32 pages, 6394 KiB

Open AccessEditor’s ChoiceArticle

Evaluating the Benefits of Flood Warnings in the Management of an Urban Flood-Prone Polder Area

by Felipe Duque, Greg O’Donnell, Yanli Liu, Mingming Song and Enda O’Connell

Hydrology 2023, 10(12), 238; https://doi.org/10.3390/hydrology10120238 - 13 Dec 2023

Viewed by 3169

Abstract

Polders are low-lying areas located in deltas, surrounded by embankments to prevent flooding (river or tidal floods). They rely on pumping systems to remove water from the inner rivers (artificial rivers inside the polder area) to the outer rivers, especially during storms. Urbanized [...] Read more.

Polders are low-lying areas located in deltas, surrounded by embankments to prevent flooding (river or tidal floods). They rely on pumping systems to remove water from the inner rivers (artificial rivers inside the polder area) to the outer rivers, especially during storms. Urbanized polders are especially vulnerable to pluvial flooding if the drainage, storage, and pumping capacity of the polder is inadequate. In this paper, a Monte Carlo (MC) framework is proposed to evaluate the benefits of rainfall threshold-based flood warnings when mitigating pluvial flooding in an urban flood-prone polder area based on 24 h forecasts. The framework computes metrics that give the potential waterlogging duration, maximum inundated area, and pump operation costs by considering the full range of potential storms. The benefits of flood warnings are evaluated by comparing the values of these metrics across different scenarios: the no-warning, perfect, deterministic, and probabilistic forecast scenarios. Probabilistic forecasts are represented using the concept of “predictive uncertainty” (PU). A polder area located in Nanjing was chosen for the case study. The results show a trade-off between the metrics that represent the waterlogging and the pumping costs, and that probabilistic forecasts of rainfall can considerably enhance these metrics. The results can be used to design a rainfall threshold-based flood early warning system (FEWS) for a polder area and/or evaluate its benefits. Full article

(This article belongs to the Section Hydrological and Hydrodynamic Processes and Modelling)

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15 pages, 1852 KiB

Open AccessEditor’s ChoiceArticle

Evaluating Non-Stationarity in Precipitation Intensity-Duration-Frequency Curves for the Dallas–Fort Worth Metroplex, Texas, USA

by Binita Ghimire, Gehendra Kharel, Esayas Gebremichael and Linyin Cheng

Hydrology 2023, 10(12), 229; https://doi.org/10.3390/hydrology10120229 - 2 Dec 2023

Cited by 1 | Viewed by 3227

Abstract

Extreme precipitation has become more frequent and intense with time and space. Infrastructure design tools such as Intensity-Duration-Frequency (IDF) curves still rely on historical precipitation and stationary assumptions, risking current and future urban infrastructure. This study developed IDF curves by incorporating non-stationarity trends [...] Read more.

Extreme precipitation has become more frequent and intense with time and space. Infrastructure design tools such as Intensity-Duration-Frequency (IDF) curves still rely on historical precipitation and stationary assumptions, risking current and future urban infrastructure. This study developed IDF curves by incorporating non-stationarity trends in precipitation annual maximum series (AMS) for Dallas–Fort Worth, the fourth-largest metropolitan region in the United States. A Pro-NEVA tool was used to develop non-stationary IDF curves, taking historical precipitation AMS for seven stations that showed a non-stationary trend with time as a covariate. Four statistical indices—the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Root Mean Square Error (RMSE), and Nash–Sutcliffe Efficiency (NSE)—were used as the model goodness of fit evaluation. The lower AIC, BIC, and RMSE values and higher NSE values for non-stationary models indicated a better performance compared to the stationary models. Compared to the traditional stationary assumption, the non-stationary IDF curves showed an increase (up to 75%) in the 24 h precipitation intensity for the 100-year return period. Using the climate change adaptive non-stationary IDF tool for the DFW metroplex and similar urban regions could enable decision makers to make climate-informed choices about infrastructure investments, emergency preparedness measures, and long-term urban development and water resource management planning. Full article

(This article belongs to the Special Issue Trends and Variations in Hydroclimatic Variables)

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11 pages, 752 KiB

Open AccessEditor’s ChoiceReview

Stream-Aquifer Systems in Semi-Arid Regions: Hydrologic, Legal, and Management Issues

by Neil S. Grigg, Ryan T. Bailey and Ryan G. Smith

Hydrology 2023, 10(12), 224; https://doi.org/10.3390/hydrology10120224 - 29 Nov 2023

Viewed by 2204

Abstract

Integrated solutions to groundwater management problems require effective analysis of stream-aquifer connections, especially in irrigated semi-arid regions where groundwater pumping affects return flows and causes streamflow depletion. Scientific research can explain technical issues, but legal and management solutions are difficult due to the [...] Read more.

Integrated solutions to groundwater management problems require effective analysis of stream-aquifer connections, especially in irrigated semi-arid regions where groundwater pumping affects return flows and causes streamflow depletion. Scientific research can explain technical issues, but legal and management solutions are difficult due to the complexities of hydrogeology, the expense of data collection and model studies, and the inclination of water users not to trust experts, regulatory authorities, and in some cases, their management organizations. The technical, legal, and management issues are reviewed, and experiences with integrated management of stream-aquifer systems are used to illustrate how governance authorities can approach engineering, legal, regulatory, and management challenges incrementally. The situations in three basins of the State of Colorado with over-appropriated water resources are explained to identify modeling and control issues confronting regulators and managers of water rights. Water rights administration in the state follows the strict appropriation method and a workable technical-legal approach to establishing regulatory and management strategies has been developed. The explanations show how models and data management are improving, but the complexities of hydrogeology and institutional systems must be confronted on a case-by-case basis. Stream-aquifer systems will require more attention in the future, better data will be needed, model developers must prove superiority over simpler methods, and organizational arrangements will be needed to facilitate successful collective action amidst inevitable legal challenges. Continued joint research between technical, legal, and management communities will also be needed. Full article

(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Integrated Surface Water and Groundwater Resources Management)

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23 pages, 3457 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Calibration of Land-Use-Dependent Evaporation Parameters in Distributed Hydrological Models Using MODIS Evaporation Time Series Data

by Markus C. Casper, Zoé Salm, Oliver Gronz, Christopher Hutengs, Hadis Mohajerani and Michael Vohland

Hydrology 2023, 10(12), 216; https://doi.org/10.3390/hydrology10120216 - 21 Nov 2023

Cited by 2 | Viewed by 2698

Abstract

The land-use-specific calibration of evapotranspiration parameters in hydrologic modeling is challenging due to the lack of appropriate reference data. We present a MODIS-based calibration approach of vegetation-related evaporation parameters for two mesoscale catchments in western Germany with the physically based distributed hydrological model [...] Read more.

The land-use-specific calibration of evapotranspiration parameters in hydrologic modeling is challenging due to the lack of appropriate reference data. We present a MODIS-based calibration approach of vegetation-related evaporation parameters for two mesoscale catchments in western Germany with the physically based distributed hydrological model WaSiM-ETH. Time series of land-use-specific actual evapotranspiration (ETa) patterns were generated from MOD16A2 evapotranspiration and CORINE land-cover data from homogeneous image pixels for the major land-cover types in the region. Manual calibration was then carried out for 1D single-cell models, each representing a specific land-use type based on aggregated 11-year mean ETa values using SKout and PBIAS as objective functions (SKout > 0.8, |PBIAS| < 5%). The spatio-temporal evaluation on the catchment scale was conducted by comparing the simulated ETa pattern to six daily ETa grids derived from LANDSAT data. The results show a clear overall improvement in the SPAEF (spatial efficiency metric) for most land-use types, with some deficiencies for two scenes in spring and late summer due to phenological variation and a particularly dry hydrological system state, respectively. The presented method demonstrates a significant improvement in the simulation of ETa regarding both time and spatial scale. Full article

(This article belongs to the Special Issue Water Resources Management under Uncertainty and Climate Change)

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17 pages, 10228 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Locating Potential Groundwater Pathways in a Fringing Reef Using Continuous Electrical Resistivity Profiling

by Matthew W. Becker, Francine M. Cason and Benjamin Hagedorn

Hydrology 2023, 10(11), 206; https://doi.org/10.3390/hydrology10110206 - 25 Oct 2023

Cited by 3 | Viewed by 2537

Abstract

Groundwater discharge from high tropical islands can have a significant influence on the biochemistry of reef ecosystems. Recent studies have suggested that a portion of groundwater may underflow the reefs to be discharged, either through the reef flat or toward the periphery of [...] Read more.

Groundwater discharge from high tropical islands can have a significant influence on the biochemistry of reef ecosystems. Recent studies have suggested that a portion of groundwater may underflow the reefs to be discharged, either through the reef flat or toward the periphery of the reef system. Understanding of this potential discharge process is limited by the characterization of subsurface reef structures in these environments. A geophysical method was used in this study to profile the reef surrounding the high volcanic island of Mo’orea, French Polynesia. Boat-towed continuous resistivity profiling (CRP) revealed electrically resistive features at about 10–15 m depth, ranging in width from 30 to 200 m. These features were repeatable in duplicate survey lines, but resolution was limited by current-channeling through the seawater column. Anomalous resistivity could represent the occurrence of freshened porewater confined within the reef, but a change in porosity due to secondary cementation cannot be ruled out. Groundwater-freshened reef porewater has been observed near-shore on Mo’orea and suggested elsewhere using similar geophysical surveys, but synthetic models conducted as part of this study demonstrate that CRP alone is insufficient to draw these conclusions. These CRP surveys suggest reefs surrounding high islands may harbor pathways for terrestrial groundwater flow, but invasive sampling is required to demonstrate the role of groundwater in terrestrial runoff. Full article

(This article belongs to the Topic Monitoring Inland Water Quality and Ecological Status)

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16 pages, 2147 KiB

Open AccessEditor’s ChoiceArticle

Efficient Flood Early Warning System for Data-Scarce, Karstic, Mountainous Environments: A Case Study

by Evangelos Rozos, Vasilis Bellos, John Kalogiros and Katerina Mazi

Hydrology 2023, 10(10), 203; https://doi.org/10.3390/hydrology10100203 - 19 Oct 2023

Cited by 5 | Viewed by 2839

Abstract

This paper presents an efficient flood early warning system developed for the city of Mandra, Greece which experienced a devastating flood event in November 2017 resulting in significant loss of life. The location is of particular interest due to both its small-sized water [...] Read more.

This paper presents an efficient flood early warning system developed for the city of Mandra, Greece which experienced a devastating flood event in November 2017 resulting in significant loss of life. The location is of particular interest due to both its small-sized water basin (20 km

^{2}

upstream of the studied cross-section), necessitating a rapid response time for effective flood warning calculations, and the lack of hydrometric data. To address the first issue, a database of pre-simulated flooding events with a 2D hydrodynamic model corresponding to synthetic precipitations with different return periods was established. To address the latter issue, the hydrological model was calibrated using qualitative information collected after the catastrophic event, compensating for the lack of hydrometric data. The case study demonstrates the establishment of a hybrid (online–offline) flood early warning system in data-scarce environments. By utilizing pre-simulated events and qualitative information, the system provides valuable insights for flood forecasting and aids in decision-making processes. This approach can be applied to other similar locations with limited data availability, contributing to improved flood management strategies and enhanced community resilience. Full article

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25 pages, 6833 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Nutrient Loadings to Utah Lake from Precipitation-Related Atmospheric Deposition

by Mitchell M. Brown, Justin T. Telfer, Gustavious P. Williams, A. Woodruff Miller, Robert B. Sowby, Riley C. Hales and Kaylee B. Tanner

Hydrology 2023, 10(10), 200; https://doi.org/10.3390/hydrology10100200 - 11 Oct 2023

Cited by 3 | Viewed by 2512

Abstract

Atmospheric deposition (AD) is a less understood and quantified source of nutrient loading to waterbodies. AD occurs via settling (large particulates), contact (smaller particulates and gaseous matter), and precipitation (rain, snow) transport pathways. Utah Lake is a shallow eutrophic freshwater lake located in [...] Read more.

Atmospheric deposition (AD) is a less understood and quantified source of nutrient loading to waterbodies. AD occurs via settling (large particulates), contact (smaller particulates and gaseous matter), and precipitation (rain, snow) transport pathways. Utah Lake is a shallow eutrophic freshwater lake located in central Utah, USA, with geophysical characteristics that make it particularly susceptible to AD-related nutrient loading. Studies have shown AD to be a significant contributor to the lake’s nutrient budget. This study analyzes nutrient samples from nine locations around the lake and four precipitation gauges over a 6-year study period using three different methods to estimate AD from the precipitation transport pathway. The methods used are simple averaging, Thiessen polygons, and inverse distance weighting, which we use to spatially interpolate point sample data to estimate nutrient lake loads. We hold that the inverse distance weighting method produces the most accurate results. We quantify, present, and compare nutrient loads and nutrient loading rates for total phosphorus (TP), total inorganic nitrogen (TIN), and ortho phosphate (OP) from precipitation events. We compute loading rates for the calendar year (Mg/yr) from each of the three analysis methods along with monthly loading rates where Mg is 10⁶ g. Our estimated annual precipitation AD loads for TP, OP, and TIN are 120.96 Mg/yr (132.97 tons/yr), 60.87 Mg/yr (67.1 tons/yr), and 435 Mg/yr (479.5 tons/yr), respectively. We compare these results with published data on total AD nutrient loads and show that AD from precipitation is a significant nutrient source for Utah Lake, contributing between 25% and 40% of the total AD nutrient load to the lake. Full article

(This article belongs to the Topic Monitoring Inland Water Quality and Ecological Status)

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17 pages, 4960 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

A Soil Moisture Profile Conceptual Framework to Identify Water Availability and Recovery in Green Stormwater Infrastructure

by Matina Shakya, Amanda Hess, Bridget M. Wadzuk and Robert G. Traver

Hydrology 2023, 10(10), 197; https://doi.org/10.3390/hydrology10100197 - 6 Oct 2023

Cited by 4 | Viewed by 4571

Abstract

The recovery of soil void space through infiltration and evapotranspiration processes within green stormwater infrastructure (GSI) is key to continued hydrologic function. As such, soil void space recovery must be well understood to improve the design and modeling and to provide realistic expectations [...] Read more.

The recovery of soil void space through infiltration and evapotranspiration processes within green stormwater infrastructure (GSI) is key to continued hydrologic function. As such, soil void space recovery must be well understood to improve the design and modeling and to provide realistic expectations of GSI performance. A novel conceptual framework of soil moisture behavior was developed to define the soil moisture availability at pre-, during, and post-storm conditions. It uses soil moisture measurements and provides seven critical soil moisture points (A, B, C, D, E, F, F″) that describe the soil–water void space recovery after a storm passes through a GSI. The framework outputs a quantification of a GSI subsurface hydrology, including average soil moisture, the duration of saturation, soil moisture recession, desaturation time, infiltration rates, and evapotranspiration (ET) rates. The outputs the framework provide were compared to the values that were obtained through more traditional measurements of infiltration (through spot field infiltration testing), ET (through a variety of methods to quantify GSI ET), soil moisture measurements (through the soil water characteristics curve), and the duration of saturation/desaturation time (through a simulated runoff test), all which provided a strong justification to the framework. This conceptual framework has several applications, including providing an understanding of a system’s ability to hold water, the post-storm recovery process, GSI unit processes (ET and infiltration), important water contents that define the soil–water relationship (such as field capacity and saturation), and a way to quantify long-term changes in performance all through minimal monitoring with one or more soil moisture sensors. The application of this framework to GSI design promotes a deeper understanding of the subsurface hydrology and site-specific soil conditions, which is a key advancement in the understanding of long-term performance and informing GSI design and maintenance. Full article

(This article belongs to the Special Issue Soil–Water–City Nexus in Urban Environment: Experimental Investigations and Numerical Analysis in Urban Hydrology Science)

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22 pages, 8605 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Assessing Terrestrial Water Storage Variations in Southern Spain Using Rainfall Estimates and GRACE Data

by Eulogio Pardo-Igúzquiza, Jean-Philippe Montillet, José Sánchez-Morales, Peter A. Dowd, Juan Antonio Luque-Espinar, Neda Darbeheshti and Francisco Javier Rodríguez-Tovar

Hydrology 2023, 10(9), 187; https://doi.org/10.3390/hydrology10090187 - 15 Sep 2023

Cited by 3 | Viewed by 2422

Abstract

This paper investigates the relationship between rainfall, groundwater and Gravity Recovery and Climate Experiment (GRACE) data to generate regional-scale estimates of terrestrial water storage variations in the Andalucía region of southern Spain. These estimates can provide information on groundwater depletion (caused by periods [...] Read more.

This paper investigates the relationship between rainfall, groundwater and Gravity Recovery and Climate Experiment (GRACE) data to generate regional-scale estimates of terrestrial water storage variations in the Andalucía region of southern Spain. These estimates can provide information on groundwater depletion (caused by periods of low rainfall or droughts) and groundwater recovery. The spatial distribution of groundwater bodies in southern Spain is complex and current in situ groundwater monitoring methods are deficient, particularly in terms of obtaining representative samples and in implementing and maintaining groundwater monitoring networks. The alternative approach proposed here is to investigate the relationship between precipitation time series and changes in the terrestrial water storage estimated from GRACE observations. The results were validated against the estimated fluctuation in regional groundwater. The maximum correlation between the mean groundwater level and the GRACE observations is 0.69 and this occurs at a lag of one month because the variation in gravity is immediate, but rainfall water requires around one month to travel across the vadose zone before it reaches the groundwater table. Using graphical methods of accumulated deviations from the mean, we show that, in general, groundwater storage follows the smooth, multi-year trends of terrestrial water storage but with less short-term trends; the same is true of rainfall, for which the local trends are more pronounced. There is hysteresis-like behaviour in the variations in terrestrial water storage and in the variations of groundwater. In practical terms, this study shows that, despite the abnormal dryness of the Iberian Peninsula during the 2004–2010 drought, the depleted groundwater storage in Andalucía recovered almost to its pre-drought level by 2016. In addition, groundwater storage and terrestrial water storage show very similar trends but with a delay in the groundwater trend. Full article

(This article belongs to the Section Hydrology–Climate Interactions)

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19 pages, 9333 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Urban Flood Modelling under Extreme Rainfall Conditions for Building-Level Flood Exposure Analysis

by Christos Iliadis, Panagiota Galiatsatou, Vassilis Glenis, Panagiotis Prinos and Chris Kilsby

Hydrology 2023, 10(8), 172; https://doi.org/10.3390/hydrology10080172 - 17 Aug 2023

Cited by 12 | Viewed by 4845

Abstract

The expansion of urban areas and the increasing frequency and magnitude of intense rainfall events are anticipated to contribute to the widespread escalation of urban flood risk across the globe. To effectively mitigate future flood risks, it is crucial to combine a comprehensive [...] Read more.

The expansion of urban areas and the increasing frequency and magnitude of intense rainfall events are anticipated to contribute to the widespread escalation of urban flood risk across the globe. To effectively mitigate future flood risks, it is crucial to combine a comprehensive examination of intense rainfall events in urban areas with the utilization of detailed hydrodynamic models. This study combines extreme value analysis techniques applied to rainfall data ranging from sub-hourly to daily durations with a high-resolution flood modelling analysis at the building level in the centre of Thessaloniki, Greece. A scaling procedure is employed to rainfall return levels assessed by applying the generalised extreme value (GEV) distribution to annual maximum fine-temporal-scale data, and these scaling laws are then applied to more reliable daily rainfall return levels estimated by means of the generalised Pareto distribution (GPD), in order to develop storm profiles with durations of 1 h and 2 h. The advanced flood model, CityCAT, is then used for the simulation of pluvial flooding, providing reliable assessments of building-level exposure to flooding hazards. The results of the analysis conducted provide insights into flood depths and water flowpaths in the city centre of Thessaloniki, identifying major flowpaths along certain main streets resulting in localised flooding, and identifying around 165 and 186 buildings highly exposed to inundation risk in the study area for 50-year storm events with durations of 1 h and 2 h, respectively. For the first time in this study area, a detailed analysis of extreme rainfall events is combined with a high-resolution Digital Terrain Model (DTM), used as an input into the advanced and fully featured CityCAT hydrodynamic model, to assess critical flowpaths and buildings at high flood risk. The results of this study can aid in the planning and design of resilient solutions to combat urban flash floods, as well as contribute to targeted flood damage mitigation and flood risk reduction. Full article

(This article belongs to the Special Issue Urban Hydrology and Urban Water Works under Rapid Urbanisation and Climate Change Conditions in Metropolitan Areas and Mega Cities)

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22 pages, 9908 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Decoupling of Ecological and Hydrological Drought Conditions in the Limpopo River Basin Inferred from Groundwater Storage and NDVI Anomalies

by Kyung Y. Kim, Todd Scanlon, Sophia Bakar and Venkataraman Lakshmi

Hydrology 2023, 10(8), 170; https://doi.org/10.3390/hydrology10080170 - 12 Aug 2023

Cited by 5 | Viewed by 3703

Abstract

Droughts are projected to increase in intensity and frequency with the rise of global mean temperatures. However, not all drought indices equally capture the variety of influences that each hydrologic component has on the duration and magnitude of a period of water deficit. [...] Read more.

Droughts are projected to increase in intensity and frequency with the rise of global mean temperatures. However, not all drought indices equally capture the variety of influences that each hydrologic component has on the duration and magnitude of a period of water deficit. While such indices often agree with one another due to precipitation being the major input, heterogeneous responses caused by groundwater recharge, soil moisture memory, and vegetation dynamics may lead to a decoupling of identifiable drought conditions. As a semi-arid basin, the Limpopo River Basin (LRB) is a severely water-stressed region associated with unique climate patterns that regularly affect hydrological extremes. In this study, we find that vegetation indices show no significant long-term trends (S-statistic 9; p-value 0.779), opposing that of the modeled groundwater anomalies (S-statistic -57; p-value 0.05) in the growing season for a period of 18 years (2004–2022). Although the Mann-Kendall time series statistics for NDVI and drought indices are non-significant when basin-averaged, spatial heterogeneity further reveals that such a decoupling trend between vegetation and groundwater anomalies is indeed significant (p-value < 0.05) in colluvial, low-land aquifers to the southeast, while they remain more coupled in the central-west LRB, where more bedrock aquifers dominate. The conclusions of this study highlight the importance of ecological conditions with respect to water availability and suggest that water management must be informed by local vegetation species, especially in the face of depleting groundwater resources. Full article

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26 pages, 7730 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Improvements and Evaluation of the Agro-Hydrologic VegET Model for Large-Area Water Budget Analysis and Drought Monitoring

by Gabriel B. Senay, Stefanie Kagone, Gabriel E. L. Parrish, Kul Khand, Olena Boiko and Naga M. Velpuri

Hydrology 2023, 10(8), 168; https://doi.org/10.3390/hydrology10080168 - 10 Aug 2023

Cited by 3 | Viewed by 3389

Abstract

We enhanced the agro-hydrologic VegET model to include snow accumulation and melt processes and the separation of runoff into surface runoff and deep drainage. Driven by global weather datasets and parameterized by land surface phenology (LSP), the enhanced VegET model was implemented in [...] Read more.

We enhanced the agro-hydrologic VegET model to include snow accumulation and melt processes and the separation of runoff into surface runoff and deep drainage. Driven by global weather datasets and parameterized by land surface phenology (LSP), the enhanced VegET model was implemented in the cloud to simulate daily soil moisture (SM), actual evapotranspiration (ETa), and runoff (R) for the conterminous United States (CONUS) and the Greater Horn of Africa (GHA). Evaluation of the VegET model with independent data showed satisfactory performance, capturing the temporal variability of SM (Pearson correlation r: 0.22–0.97), snowpack (r: 0.86–0.88), ETa (r: 0.41–0.97), and spatial variability of R (r: 0.81–0.90). Absolute magnitudes showed some biases, indicating the need of calibrating the model for water budget analysis. The seasonal Landscape Water Requirement Satisfaction Index (L-WRSI) for CONUS and GHA showed realistic depictions of drought hazard extent and severity, indicating the usefulness of the L-WRSI for the convergence of an evidence toolkit used by the Famine Early Warning System Network to monitor potential food insecurity conditions in different parts of the world. Using projected weather datasets and landcover-based LSP, the VegET model can be used not only for global monitoring of drought conditions, but also for evaluating scenarios on the effect of a changing climate and land cover on agriculture and water resources. Full article

(This article belongs to the Topic Hydrology and Water Resources in Agriculture and Ecology)

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24 pages, 10756 KiB

Open AccessEditor’s ChoiceArticle

Flood Inundation and Depth Mapping Using Unmanned Aerial Vehicles Combined with High-Resolution Multispectral Imagery

by Kevin J. Wienhold, Dongfeng Li, Wenzhao Li and Zheng N. Fang

Hydrology 2023, 10(8), 158; https://doi.org/10.3390/hydrology10080158 - 28 Jul 2023

Cited by 7 | Viewed by 3608

Abstract

The identification of flood hazards during emerging public safety crises such as hurricanes or flash floods is an invaluable tool for first responders and managers yet remains out of reach in any comprehensive sense when using traditional remote-sensing methods, due to cloud cover [...] Read more.

The identification of flood hazards during emerging public safety crises such as hurricanes or flash floods is an invaluable tool for first responders and managers yet remains out of reach in any comprehensive sense when using traditional remote-sensing methods, due to cloud cover and other data-sourcing restrictions. While many remote-sensing techniques exist for floodwater identification and extraction, few studies demonstrate an up-to-day understanding with better techniques in isolating the spectral properties of floodwaters from collected data, which vary for each event. This study introduces a novel method for delineating near-real-time inundation flood extent and depth mapping for storm events, using an inexpensive unmanned aerial vehicle (UAV)-based multispectral remote-sensing platform, which was designed to be applicable for urban environments, under a wide range of atmospheric conditions. The methodology is demonstrated using an actual flooding-event—Hurricane Zeta during the 2020 Atlantic hurricane season. Referred to as the UAV and Floodwater Inundation and Depth Mapper (FIDM), the methodology consists of three major components, including aerial data collection, processing, and flood inundation (water surface extent) and depth mapping. The model results for inundation and depth were compared to a validation dataset and ground-truthing data, respectively. The results suggest that UAV-FIDM is able to predict inundation with a total error (sum of omission and commission errors) of 15.8% and produce flooding depth estimates that are accurate enough to be actionable to determine road closures for a real event. Full article

(This article belongs to the Special Issue Flood Inundation Mapping in Hydrological Systems)

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19 pages, 3306 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

ANN-Based Predictors of ASR Well Recovery Effectiveness in Unconfined Aquifers

by Saeid Masoudiashtiani and Richard C. Peralta

Hydrology 2023, 10(7), 151; https://doi.org/10.3390/hydrology10070151 - 19 Jul 2023

Cited by 1 | Viewed by 1965

Abstract

In this study, we present artificial neural networks (ANNs) to aid in a reconnaissance evaluation of an aquifer storage and recovery (ASR) well. Recovery effectiveness (REN) is the proportion of ASR-injected water recovered during subsequent extraction from the same well. ANN-based predictors allow [...] Read more.

In this study, we present artificial neural networks (ANNs) to aid in a reconnaissance evaluation of an aquifer storage and recovery (ASR) well. Recovery effectiveness (REN) is the proportion of ASR-injected water recovered during subsequent extraction from the same well. ANN-based predictors allow rapid REN prediction without requiring preparation for and execution of solute transport simulations. REN helps estimate blended water quality resulting from a conservative solute in an aquifer, extraction for environmental protection, and other uses, respectively. Assume that into an isotropic homogenous portion of an unconfined, one-layer aquifer, extra surface water is injected at a steady rate during two wet months (61 days) through a fully penetrating ASR well. And then, water is extracted from the well at the same steady rate during three dry months (91-day period of high demand). The presented dimensionless input parameters were designed to be calibrated within the ANNs to match REN values. The values result from groundwater flow and solute transport simulations for ranges of impact factors of unconfined aquifers. The ANNs calibrated the weighting coefficients associated with the input parameters to predict the achievable REN of an ASR well. The ASR steadily injects extra surface water during periods of water availability and, subsequently, steadily extracts groundwater for use. The total extraction volume equaled the total injection volume at the end of extraction day 61. Subsequently, continuing extraction presumes a pre-existing groundwater right. Full article

(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Integrated Surface Water and Groundwater Resources Management)

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23 pages, 5268 KiB

Open AccessEditor’s ChoiceArticle

Smart Data Blending Framework to Enhance Precipitation Estimation through Interconnected Atmospheric, Satellite, and Surface Variables

by Niloufar Beikahmadi, Antonio Francipane and Leonardo Valerio Noto

Hydrology 2023, 10(6), 128; https://doi.org/10.3390/hydrology10060128 - 5 Jun 2023

Cited by 4 | Viewed by 3257

Abstract

Accurate precipitation estimation remains a challenge, though it is fundamental for most hydrological analyses. In this regard, this study aims to achieve two objectives. Firstly, we evaluate the performance of two precipitation products from the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM-IMERG) [...] Read more.

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

(This article belongs to the Special Issue UAS and Satellite-Based Remote Sensing for Hydrological Observations and Applications)

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32 pages, 8254 KiB

Open AccessEditor’s ChoiceArticle

Impacts of Max-Stable Process Areal Exceedance Calculations to Study Area Sampling Density, Surface Network Precipitation Gage Extent and Density, and Model Fitting Method

by Brian Skahill, Cole Haden Smith, Brook T. Russell and John F. England

Hydrology 2023, 10(6), 121; https://doi.org/10.3390/hydrology10060121 - 28 May 2023

Cited by 7 | Viewed by 2578

Abstract

Max-stable process (MSP) models can be fit to data collected over a spatial domain to estimate areal-based exceedances while accounting for spatial dependence in extremes. They have theoretical grounding within the framework of extreme value theory (EVT). In this work, we fit MSP [...] Read more.

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

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25 pages, 5667 KiB

Open AccessEditor’s ChoiceArticle

Examination of Measured to Predicted Hydraulic Properties for Low Impact Development Substrates

by Satbir Guram and Rashid Bashir

Hydrology 2023, 10(5), 105; https://doi.org/10.3390/hydrology10050105 - 8 May 2023

Cited by 1 | Viewed by 2853

Abstract

To counter the impacts of climate change and urbanization, engineers have developed ingenious solutions to reduce flooding and capture stormwater contaminants through the use of Low Impact Developments (LIDs). The soil is generally considered to be completely saturated when designing for the LIDs. [...] Read more.

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

(This article belongs to the Special Issue Green Infrastructure and Advances in Urban Hydrology)

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17 pages, 3656 KiB

Open AccessEditor’s ChoiceArticle

Fuzzy Analytical Solution of Horizontal Diffusion Equation into the Vadose Zone

by Christos Tzimopoulos, Nikiforos Samarinas, Basil Papadopoulos and Christos Evangelides

Hydrology 2023, 10(5), 107; https://doi.org/10.3390/hydrology10050107 - 8 May 2023

Viewed by 2668

Abstract

The process of how soil moisture profiles evolve into the soil and reach the root zone could be estimated by solving the appropriate strong nonlinear Richards’ equation. The nonlinearity of the equation occurs because diffusivity D is generally an exponential function of water [...] Read more.

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

(This article belongs to the Topic Groundwater Pollution Control and Groundwater Management)

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19 pages, 7546 KiB

Open AccessEditor’s ChoiceArticle

Application of Running Water-Type Retarding Basin to Old Kinu River Floodplain, Japan

by Tadaharu Ishikawa and Ryosuke Akoh

Hydrology 2023, 10(4), 94; https://doi.org/10.3390/hydrology10040094 - 15 Apr 2023

Cited by 2 | Viewed by 2474

Abstract

In the upper and middle reaches of rivers in Japan, river channels used to meander in a comparatively narrow floodplain and heavy rain runoff used to naturally expand over the entire floodplain, retarding floods toward the downstream. Recent continuous levee building to prevent [...] Read more.

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

(This article belongs to the Special Issue Flood Inundation Mapping in Hydrological Systems)

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27 pages, 16811 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Evaluation of Various Resolution DEMs in Flood Risk Assessment and Practical Rules for Flood Mapping in Data-Scarce Geospatial Areas: A Case Study in Thessaly, Greece

by Nikolaos Xafoulis, Yiannis Kontos, Evangelia Farsirotou, Spyridon Kotsopoulos, Konstantinos Perifanos, Nikolaos Alamanis, Dimitrios Dedousis and Konstantinos Katsifarakis

Hydrology 2023, 10(4), 91; https://doi.org/10.3390/hydrology10040091 - 12 Apr 2023

Cited by 20 | Viewed by 4649

Abstract

Floods are lethal and destructive natural hazards. The Mediterranean, including Greece, has recently experienced many flood events (e.g., Medicanes Zorbas and Ianos), while climate change results in more frequent and intense flood events. Accurate flood mapping in river areas is crucial for flood [...] Read more.

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

(This article belongs to the Special Issue Modern Developments in Flood Modelling)

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18 pages, 6697 KiB

Open AccessEditor’s ChoiceArticle

Development of Multi-Inflow Prediction Ensemble Model Based on Auto-Sklearn Using Combined Approach: Case Study of Soyang River Dam

by Seoro Lee, Jonggun Kim, Joo Hyun Bae, Gwanjae Lee, Dongseok Yang, Jiyeong Hong and Kyoung Jae Lim

Hydrology 2023, 10(4), 90; https://doi.org/10.3390/hydrology10040090 - 11 Apr 2023

Cited by 8 | Viewed by 2453

Abstract

Accurate prediction of dam inflows is essential for effective water resource management and dam operation. In this study, we developed a multi-inflow prediction ensemble (MPE) model for dam inflow prediction using auto-sklearn (AS). The MPE model is designed to combine ensemble models for [...] Read more.

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

(This article belongs to the Section Water Resources and Risk Management)

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16 pages, 3843 KiB

Open AccessEditor’s ChoiceArticle

Modeling a Metamorphic Aquifer through a Hydro-Geophysical Approach: The Gap between Field Data and System Complexity

by Francesco Chidichimo, Michele De Biase, Francesco Muto and Salvatore Straface

Hydrology 2023, 10(4), 80; https://doi.org/10.3390/hydrology10040080 - 31 Mar 2023

Cited by 3 | Viewed by 2181

Abstract

The productivity of metamorphic aquifers is generally lower than that of the more common alluvial and carbonates ones. However, in some Mediterranean areas, such as the Calabria region (Italy), water scarcity combined with the presence of extensive metamorphic water bodies requires the development [...] Read more.

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

(This article belongs to the Topic Groundwater Pollution Control and Groundwater Management)

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23 pages, 4720 KiB

Open AccessEditor’s ChoiceArticle

IWRM Incorporating Water Use and Productivity Indicators of Economic Clusters Using a Hydro-Economic SDSS

by Gerald Norbert Souza da Silva, Márcia M. G. Alcoforado de Moraes, Laíse Alves Candido, Carlos Alberto G. de Amorim Filho, Nilena B. M. Dias, Marcelo Pereira da Cunha and Lourdinha Florêncio

Hydrology 2023, 10(3), 72; https://doi.org/10.3390/hydrology10030072 - 22 Mar 2023

Viewed by 2418

Abstract

IWRM should include the integration of management instruments towards intersectoral efficient water allocation. A platform linking economywide and network-based models, available from a Spatial Decision Support System (SDSS), was used to analyze allocation decisions in 4-interlinked basins in Northeastern Brazil during a period [...] Read more.

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

(This article belongs to the Special Issue Coupling of Human and Hydrological Systems)

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16 pages, 4082 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Compound Climate Risk: Diagnosing Clustered Regional Flooding at Inter-Annual and Longer Time Scales

by Yash Amonkar, James Doss-Gollin and Upmanu Lall

Hydrology 2023, 10(3), 67; https://doi.org/10.3390/hydrology10030067 - 16 Mar 2023

Cited by 2 | Viewed by 2586

Abstract

The potential for extreme climate events to cluster in space and time has driven increased interest in understanding and predicting compound climate risks. Through a case study on floods in the Ohio River Basin, we demonstrated that low-frequency climate variability could drive spatial [...] Read more.

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

(This article belongs to the Special Issue Water Resources Management under Uncertainty and Climate Change)

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13 pages, 2613 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

On the Sensitivity of Standardized-Precipitation-Evapotranspiration and Aridity Indexes Using Alternative Potential Evapotranspiration Models

by Aristoteles Tegos, Stefanos Stefanidis, John Cody and Demetris Koutsoyiannis

Hydrology 2023, 10(3), 64; https://doi.org/10.3390/hydrology10030064 - 6 Mar 2023

Cited by 24 | Viewed by 4038

Abstract

This paper examines the impacts of three different potential evapotranspiration (PET) models on drought severity and frequencies indicated by the standardized precipitation index (SPEI). The standardized precipitation-evapotranspiration index is a recent approach to operational monitoring and analysis of drought severity. The standardized precipitation-evapotranspiration [...] Read more.

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

(This article belongs to the Special Issue Advances in Evaporation and Evaporative Demand: Part II)

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14 pages, 1670 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Probabilistic Approach to Tank Design in Rainwater Harvesting Systems

by Maria Gloria Di Chiano, Mariana Marchioni, Anita Raimondi, Umberto Sanfilippo and Gianfranco Becciu

Hydrology 2023, 10(3), 59; https://doi.org/10.3390/hydrology10030059 - 27 Feb 2023

Cited by 12 | Viewed by 7307

Abstract

Storage tanks from rainwater harvesting systems (RWHs) are designed to provide flow equalization between rainfall and water demand. The minimum storage capacity required to take into account the maximum variations of stored water volumes, i.e., the active storage, depends basically on the magnitude [...] Read more.

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

(This article belongs to the Special Issue Soil–Water–City Nexus in Urban Environment: Experimental Investigations and Numerical Analysis in Urban Hydrology Science)

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18 pages, 23403 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

A Novel Multipurpose Self-Irrigated Green Roof with Innovative Drainage Layer

by Behrouz Pirouz, Stefania Anna Palermo, Gianfranco Becciu, Umberto Sanfilippo, Hana Javadi Nejad, Patrizia Piro and Michele Turco

Hydrology 2023, 10(3), 57; https://doi.org/10.3390/hydrology10030057 - 25 Feb 2023

Cited by 6 | Viewed by 3318

Abstract

Climate change is a significant problem that many countries are currently facing, and green roofs (GRs) are one of the suitable choices to confront it and decrease its impacts. The advantages of GRs are numerous, such as stormwater management, thermal need reduction, runoff [...] Read more.

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

(This article belongs to the Special Issue Soil–Water–City Nexus in Urban Environment: Experimental Investigations and Numerical Analysis in Urban Hydrology Science)

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18 pages, 4054 KiB

Open AccessEditor’s ChoiceArticle

Spatial Evaluation of a Hydrological Model on Dominant Runoff Generation Processes Using Soil Hydrologic Maps

by Hadis Mohajerani, Mathias Jackel, Zoé Salm, Tobias Schütz and Markus C. Casper

Hydrology 2023, 10(3), 55; https://doi.org/10.3390/hydrology10030055 - 22 Feb 2023

Cited by 1 | Viewed by 3225

Abstract

The aim of this study was to simulate dominant runoff generation processes (DRPs) in a mesoscale catchment in southwestern Germany with the physically-based distributed hydrological model WaSiM-ETH and to compare the resulting DRP patterns with a data-mining-based digital soil map. The model was [...] Read more.

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

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26 pages, 6225 KiB

Open AccessEditor’s ChoiceArticle

Use of UAV Monitoring to Identify Factors Limiting the Sustainability of Stream Restoration Projects

by Jakub Langhammer, Theodora Lendzioch and Jakub Šolc

Hydrology 2023, 10(2), 48; https://doi.org/10.3390/hydrology10020048 - 10 Feb 2023

Cited by 5 | Viewed by 2844

Abstract

The detection and mapping of riverscapes with Unmanned Aerial Vehicles (UAVs, drones) provide detailed, reliable, and operable spatial information in hydrological sciences, enhancing conventional field survey techniques. In this study, we present the results of long-term, optical RGB (red, green, blue) UAV monitoring [...] Read more.

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

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21 pages, 2973 KiB

Open AccessEditor’s ChoiceArticle

Fuzzy Unsteady-State Drainage Solution for Land Reclamation

by Christos Tzimopoulos, Nikiforos Samarinas, Kyriakos Papadopoulos and Christos Evangelides

Hydrology 2023, 10(2), 34; https://doi.org/10.3390/hydrology10020034 - 24 Jan 2023

Cited by 4 | Viewed by 2600

Abstract

Very well-drained lands could have a positive impact in various soil health indicators such as soil erosion and soil texture. A drainage system is responsible for properly aerated soil. Until today, in order to design a drainage system, a big challenge remained to [...] Read more.

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

(This article belongs to the Special Issue Groundwater Management)

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32 pages, 6796 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Determination of Environmental Flows in Data-Poor Estuaries—Wami River Estuary in Saadani National Park, Tanzania

by Amartya K. Saha, Japhet Kashaigili, Fredrick Mashingia, Halima Kiwango, Mercy Asha Mohamed, Michael Kimaro, Mathias Msafiri Igulu, Patroba Matiku, Rosemary Masikini, Rashid Tamatamah, Ismail Omary, Tumaini Magesa, Pendo Hyera, Roman Evarist and Maria C. Donoso

Hydrology 2023, 10(2), 33; https://doi.org/10.3390/hydrology10020033 - 23 Jan 2023

Cited by 5 | Viewed by 3006

Abstract

Land use changes and mounting water demands reduce freshwater inflows into estuaries, impairing estuarine ecosystems and accelerating coastal seawater intrusion. However, determining minimum river inflows for management guidelines is hampered by a lack of ecosystem-flow link data. This study describes the development of [...] Read more.

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

(This article belongs to the Special Issue Aquatic Ecosystems and Water Resources)

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19 pages, 2533 KiB

Open AccessEditor’s ChoiceArticle

Iron and Manganese Oxidation States, Bonding Environments, and Mobility in the Mining-Impacted Sediments of Coeur d’Alene Lake, Idaho: Core Experiments

by Gaige Swanson, Jeff B. Langman, Andrew W. Child, Frank M. Wilhelm and James G. Moberly

Hydrology 2023, 10(1), 23; https://doi.org/10.3390/hydrology10010023 - 16 Jan 2023

Cited by 2 | Viewed by 3345

Abstract

The mobility of a metal in mining-impacted sediments is determined by the environmental conditions that influence the metal’s oxidation state and bonding environment. Coeur d’Alene Lake, USA, has been impacted by legacy mining practices that allowed the hydrologic transport of mining waste to [...] Read more.

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

(This article belongs to the Section Ecohydrology)

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15 pages, 16352 KiB

Open AccessEditor’s ChoiceArticle

Assessment of a Smartphone App for Open Channel Flow Measurement in Data Scarce Irrigation Schemes

by Menwagaw T. Damtie, Marshet B. Jumber, Fasikaw A. Zimale and Seifu A. Tilahun

Hydrology 2023, 10(1), 22; https://doi.org/10.3390/hydrology10010022 - 15 Jan 2023

Cited by 4 | Viewed by 3326

Abstract

Accurate water flow measurement ensures proper irrigation water management by allocating the desired amount of water to the irrigation fields. The present study evaluated whether the non-intrusive smartphone application “DischargeApp” could be applicable and precise to measure small canal flow rates in the [...] Read more.

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

(This article belongs to the Topic Hydrology and Water Resources Management)

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