Journal Description
Hydrology
Hydrology
is an international, peer-reviewed, open access journal on hydrology published monthly online by MDPI. The American Institute of Hydrology (AIH) and Japanese Society of Physical Hydrology (JSPH) are affiliated with Hydrology and their members receive discounts on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), PubAg, GeoRef, and other databases.
- Journal Rank: CiteScore - Q2 (Earth-Surface Processes)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.8 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.2 (2022);
5-Year Impact Factor:
3.1 (2022)
Latest Articles
Comparative Study of Low Flow Frequency Analysis Using Bivariate Copula Model at Soyanggang Dam and Chungju Dam
Hydrology 2024, 11(6), 79; https://doi.org/10.3390/hydrology11060079 - 31 May 2024
Abstract
A univariate analysis that relies solely on precipitation data in low flow frequency analysis is a technique to express meteorological drought, so it is limited to analyzing the characteristics of hydrological drought related to available water resources. In addition, if the data for
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A univariate analysis that relies solely on precipitation data in low flow frequency analysis is a technique to express meteorological drought, so it is limited to analyzing the characteristics of hydrological drought related to available water resources. In addition, if the data for the model calibration are insufficient, the uncertainty of a single variable limits the construction of a reliable model. To improve this problem, a frequency analysis was performed by constructing a bivariate copula model as a multivariate model with a high correlation between variables targeting reservoir inflows. The methodology utilizes the theory of runs to identify low flow events, establishing a threshold based on the mandatory regional water supply plan, and determining the low flow duration and cumulative water deficit. The Gumbel copula function, effective in capturing correlations between hydrological variables, was applied to derive a joint bivariate probability distribution, facilitating the calculation of combined low flow event return periods. This study compared low flow frequencies at Soyanggang dam (’74–’22) and Chungju dam (’86–‘22), which are in the same Han River basin but have different capacities and water demands, using a bivariate copula model. The top four extreme low flow events for the two adjacent dam basins did not occur in the same year and, in the years of the extreme low flow events at one of the two dam basins, there was an insignificant magnitude at the remaining dam basin. This result is noteworthy because it shows that the possibility of extreme low flow events appearing simultaneously in both watersheds is not as high as expected. The operational efficiency can be improved by setting the coordinated operation rules of the two reservoirs using the copula dependency structure.
Full article
(This article belongs to the Topic Hydrology and Water Resources Management)
Open AccessArticle
Land-Use–Land Cover Changes in the Urban River’s Buffer Zone and Variability of Discharge, Water, and Sediment Quality—A Case of Urban Catchment of the Ngerengere River in Tanzania
by
Silaji S. Mbonaga, Amina A. Hamad and Stelyus L. Mkoma
Hydrology 2024, 11(6), 78; https://doi.org/10.3390/hydrology11060078 - 31 May 2024
Abstract
The physical integrity of the Ngerengere River and its three tributaries drains within Morogoro Municipality were evaluated by assessing the variations in land-use–land cover (LULC) in the river’s buffer zone, the discharge, and the contamination of river water and sediment from nutrients and
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The physical integrity of the Ngerengere River and its three tributaries drains within Morogoro Municipality were evaluated by assessing the variations in land-use–land cover (LULC) in the river’s buffer zone, the discharge, and the contamination of river water and sediment from nutrients and heavy metals. Integrated geospatial techniques were used to classify the LULC in the river’s buffer zone. In contrast, the velocity area method and monitoring data from the Wami-Ruvu Basin were used for the discharge measurements. Furthermore, atomic absorption spectrophotometry was used during the laboratory analysis to determine the level of nutrients and heavy metals in the water and river sediment across the 13 sampling locations. The LULC assessment in the river’s buffer during the sampling year of 2023 showed that bare land and built-up areas dominate the river’s buffer, with a coverage of 28% and 38% of the area distribution. The higher discharge across the sampling stations was in the upstream reaches at 3.73 m3/s and 2.36 m3/s at the confluences. The highest concentrations of heavy metals in the water for the dry and wet seasons were 0.09 ± 0.01, 0.25 ± 0.01, 0.03 ± 0.02, 0.73 ± 0.04, 4.07 ± 0.08, and 3.07 ± 0.04 mg/L, respectively, for Pb, Cr, Cd, Cu, Zn, and Ni. The order of magnitude of the heavy metal concentration in the sediments was Zn > Ni > Cr > Cu > Cd > Pb, while the highest NO2−, NO3−, NH3, and PO43− in the water and sediment were 2.05 ± 0.01, 0.394 ± 0.527 0.66 ± 0.05, and 0.63 ± 0.01 mg/L, and 2.64 ± 0.03, 0.63 ± 0.01, 2.36 ± 0.01, and 48.16 ± 0.01 mg/kg, respectively, across all sampling seasons. This study highlights the significant impact of urbanization on river integrity, revealing elevated levels of heavy metal contamination in both water and sediment, the variability of discharge, and alterations in the LULC in the rivers’ buffer. This study recommends the continuous monitoring of the river water quality and quantity of the urban rivers, and the overall land-use plans for conserving river ecosystems.
Full article
(This article belongs to the Special Issue Advances in Catchments Hydrology and Sediment Dynamics)
Open AccessArticle
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
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,
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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
Open AccessArticle
Hydrogeochemical Characterization of an Intermontane Aquifer Contaminated with Arsenic and Fluoride via Clustering Analysis
by
José Rafael Irigoyen-Campuzano, Diana Barraza-Barraza, Mélida Gutiérrez, Luis Arturo Torres-Castañón, Liliana Reynoso-Cuevas and María Teresa Alarcón-Herrera
Hydrology 2024, 11(6), 76; https://doi.org/10.3390/hydrology11060076 - 31 May 2024
Abstract
The controlling hydrogeochemical processes of an intermontane aquifer in central Mexico were identified through multivariate statistical analysis. Hierarchical cluster (HCA) and k-means clustering analyses were applied to Na+, K+, Ca2+, Mg2+, F−, Cl
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The controlling hydrogeochemical processes of an intermontane aquifer in central Mexico were identified through multivariate statistical analysis. Hierarchical cluster (HCA) and k-means clustering analyses were applied to Na+, K+, Ca2+, Mg2+, F−, Cl−, SO42−, NO3−, HCO3−, As, pH and electrical conductivity in 40 groundwater samples collected from shallow and deep wells, where As and F− are contaminants of concern. The effectiveness of each hierarchical and k-means clustering method in explaining solute concentrations within the aquifer and the co-occurrence of arsenic and fluoride was tested by comparing two datasets containing samples from 40 and 36 wells, the former including ionic balance outliers (>10%). When tested without outliers, cluster quality improved by about 5.4% for k-means and 7.3% for HCA, suggesting that HCA is more sensitive to ionic balance outliers. Both algorithms yielded similar clustering solutions in the outlier-free dataset, aligning with the k-means solution for all 40 samples, indicating that k-means was the more robust of the two methods. k-means clustering resolved fluoride and arsenic concentrations into four clusters (K1 to K4) based on variations in Na+, Ca2+, As, and F−. Cluster K2 was a Na-HCO3 water type with high concentrations of As and F. Clusters K1, K3, and K4 exhibited a Ca-HCO3, Na-Ca-HCO3, and Ca-Na-HCO3 water types, respectively, with decreasing As and F concentrations following the order K2 > K3 > K1 > K4. The weathering of evaporites and silicates and Na-Ca ion exchange with clays were the main processes controlling groundwater geochemistry. The dissolution of felsic rocks present in the aquifer fill is a likely source of As and F−, with evaporation acting as an important concentration factor.
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(This article belongs to the Topic Advances in Hydrogeological Research)
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Open AccessArticle
Evaluation of Gridded Rainfall Products in Three West African Basins
by
Omar Goudiaby, Ansoumana Bodian, Alain Dezetter, Ibrahima Diouf and Andrew Ogilvie
Hydrology 2024, 11(6), 75; https://doi.org/10.3390/hydrology11060075 - 29 May 2024
Abstract
In recent years, accessing rainfall data from ground observation networks maintained by national meteorological services in West Africa has become increasingly challenging. This is primarily due to high acquisition costs and the often sparse distribution of rainfall gauges across the region, which limits
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In recent years, accessing rainfall data from ground observation networks maintained by national meteorological services in West Africa has become increasingly challenging. This is primarily due to high acquisition costs and the often sparse distribution of rainfall gauges across the region, which limits their use in hydrological studies and related research. At the same time, the rising availability of precipitation products derived from satellite/earth observations, reanalysis datasets, and in situ measurements presents exciting prospects for hydrological applications. Nonetheless, these datasets constitute indirect measurements, necessitating rigorous validation against ground-based rainfall data. This study comprehensively assesses twenty-three gridded rainfall products, including sixteen from satellites, six from reanalysis data, and one from in situ measurements, across the Senegal, Gambia, and Casamance River basins. Performance evaluation is conducted across distinct climatic zones, both pre- and post-resampling against observed rainfall data gathered from forty-nine rainfall stations over a six-year period (2003–2008). Evaluation criteria include the Kling–Gupta Efficiency (KGE) and Percentage of Bias (PBIAS) metrics, assessed at daily, monthly, and seasonal time steps. The results reveal distinct performance levels among the evaluated rainfall products. RFE, ARC2, and CPC notably yield the highest KGE scores at the daily time step, while GPCP, CHIRP, CHIRPS, RFE, MSWEP, ARC2, CPC, TAMSAT, and CMORPHCRT demonstrate superior performance at the monthly time step. During the rainy season, these products generally exhibit robustness. However, rainfall estimates derived from reanalysis datasets (ERA5, EWEMBI, MERRA2, PGF, WFDEICRU, and WFDEIGPCC) perform poorly in the studied basins. Based on the PBIAS metric, most products tend to underestimate precipitation values, while only PERSIANN and PERSIANNCCS lead to significant overestimations. Spatially, optimal performance of the products is observed in the Casamance basin and the Sudanian and Sahelian climatic zones within the Gambia and Senegal basins. Conversely, in the Guinean zone of the Gambia and Senegal Rivers, the rainfall products displayed the poorest performance.
Full article
(This article belongs to the Topic Hydrology and Water Resources Management)
Open AccessArticle
Evaluation of Phosphate and E. coli Attenuation in a Natural Wetland Receiving Drainage from an Urbanized Catchment
by
Charles Humphrey, Jarrod Underwood, Guy Iverson, Randall Etheridge, Mike O’Driscoll and Avian White
Hydrology 2024, 11(6), 74; https://doi.org/10.3390/hydrology11060074 - 29 May 2024
Abstract
A natural wetland receiving drainage from a 24-ha urbanized catchment in the Falls Lake Watershed of North Carolina was evaluated to determine if it was providing ecosystem services with regards to phosphate and Escherichia coli (E. coli) attenuation. Inflow and outflow
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A natural wetland receiving drainage from a 24-ha urbanized catchment in the Falls Lake Watershed of North Carolina was evaluated to determine if it was providing ecosystem services with regards to phosphate and Escherichia coli (E. coli) attenuation. Inflow and outflow characteristics including nutrient and bacteria concentrations along with physicochemical properties (discharge, pH, oxidation reduction potential, temperature, and specific conductance) were assessed approximately monthly for over 2 years. The median exports of phosphate (0.03 mg/s) and E. coli (5807 MPN/s) leaving the wetland were 85% and 57% lower, respectively, relative to inflow loadings, and the differences were statistically significant (p < 0.05). Hydraulic head readings from three piezometers installed at different depths revealed the wetland was a recharge area. Phosphate and E. coli concentrations were significantly greater in the shallowest piezometer relative to the deepest one, suggesting treatment occurred during infiltration. However, severe erosion of the outlets is threatening the stability of the wetland. Upstream drainageway modifications were implemented to slow runoff, and septic system repairs and maintenance activities were implemented to improve water quality reaching the wetland and Lick Creek. However, more work will be needed to conserve the ecosystem services provided by the wetland.
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(This article belongs to the Special Issue Impacts of Climate Change and Human Activities on Wetland Hydrology)
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Open AccessArticle
Spatiotemporal Evaluation of Water Resources in Citarum Watershed during Weak La Nina and Weak El Nino
by
Armi Susandi, Arief Darmawan, Albertus Sulaiman, Mouli De Rizka Dewantoro, Aristyo Rahadian Wijaya, Agung Riyadi, Agus Salim, Rafif Rahman Darmawan and Angga Fauzan Pratama
Hydrology 2024, 11(6), 73; https://doi.org/10.3390/hydrology11060073 - 22 May 2024
Abstract
This study investigates the dynamics of water resources in the Citarum watershed during periods of weak La Niña, normal, and weak El Niño conditions occurring sequentially. The Citarum watershed serves various purposes, being utilized not only by seven (7) districts and two (2)
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This study investigates the dynamics of water resources in the Citarum watershed during periods of weak La Niña, normal, and weak El Niño conditions occurring sequentially. The Citarum watershed serves various purposes, being utilized not only by seven (7) districts and two (2) cities in West Java, Indonesia but also as a source of raw water for drinking in the City of Jakarta. Using a time-series analysis of surface water data, data-driven (machine learning) methods, and statistical analysis methods, spatiotemporal predictions of surface water have been made. The surface water time series data (2017–2021), obtained from in situ instruments, are used to assess water resources, predict groundwater recharge, and analyze seasonal patterns. The results indicate that surface water follows a seasonal pattern, particularly during the monsoon season, corresponding to the groundwater recharge pattern. In upstream areas, water resources exhibit an increasing trend during both weak La Nina and weak El Niño, except for Jatiluhur Dam, where a decline is observed in both seasons. Machine learning predictions suggest that water levels and groundwater recharge tend to decrease in both upstream and downstream areas.
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(This article belongs to the Topic Hydrology and Water Resources Management)
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A Systematic Review of Social Sustainability Indicators for Water Use along the Agricultural Value Chain
by
Pascalina Matohlang Pilane, Henry Jordaan and Yonas T. Bahta
Hydrology 2024, 11(5), 72; https://doi.org/10.3390/hydrology11050072 - 20 May 2024
Abstract
The concept of sustainable water use serves as an indicator of environmental, economic, and social pressure on freshwater resources globally; however, the social element of sustainability is not well researched within water-consumption studies. The objective of this paper is to consider the current
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The concept of sustainable water use serves as an indicator of environmental, economic, and social pressure on freshwater resources globally; however, the social element of sustainability is not well researched within water-consumption studies. The objective of this paper is to consider the current state of the literature on social sustainability indicators for water use in agriculture, as well as to describe the social (people) element of sustainability and establish water use as an element of society. By combining viewpoints, systematic literature reviews address research topics with a strength that no single work can have. From 314 papers published between 2013 and 2023, 42 papers were eligible for the review. This work employed a mixed-methods approach that included a systematic review following the (PRISMA) framework, scientific mapping through VOSviewer software (version 1.6.19), thematic reviews, and a review of the grey literature retrieved from artificial intelligence and deep learning technologies. The findings indicate that social sustainability indicators are based on environmental indicators. There are no set standards for what to consider as a social indicator of water use or for how these indictors can be measured. Life-cycle assessment and water-footprint assessment frameworks have shown progress with indicators that capture the social value of water such as productivity-reducing externalities, equity, and jobs per cubic metre of water.
Full article
(This article belongs to the Special Issue The Sustainable Water Management and Food Production Nexus for Global Development in the Past, Present and Future)
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Open AccessArticle
Integration of GIS and Water-Quality Index for Preliminary Assessment of Groundwater Suitability for Human Consumption and Irrigation in Semi-Arid Region
by
Kaddour Benmarce, Karim Zighmi, Riheb Hadji, Younes Hamed, Matteo Gentilucci, Maurizio Barbieri and Gilberto Pambianchi
Hydrology 2024, 11(5), 71; https://doi.org/10.3390/hydrology11050071 - 19 May 2024
Abstract
The Setifian high-plains region, Northeast of Algeria, grapples with challenges in water resource management. As the water demand intensifies across a diverse range of sectors, assessing groundwater quality becomes indispensable. This article responds to the critical need for a thorough assessment of groundwater
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The Setifian high-plains region, Northeast of Algeria, grapples with challenges in water resource management. As the water demand intensifies across a diverse range of sectors, assessing groundwater quality becomes indispensable. This article responds to the critical need for a thorough assessment of groundwater quality in the Wadi Boussellam sub-watershed. Employing a GIS-based method, we evaluate groundwater geochemistry by estimating the Water Quality Index (WQI), offering a comprehensive overview of water consumption. The analysis of groundwater samples reveals distinct facies, including calcic bicarbonate, calcic chloride, calcic sulfate, and magnesium sulfate, contributing to an enhanced understanding of the hydrochemical composition in the Setif region. Hydrochemical indices, specifically the WQI, Sodium Adsorption Ratio (SAR), and Na% are applied to assess groundwater suitability for various applications. The results indicate that most crops are generally suitable for irrigation, though they advise exercising caution with regard to human consumption. This study underscores the significance of regular monitoring to avert groundwater contamination and ensure sustainable use in the Setif region, providing insights that emphasize the ongoing necessity for efforts in water resource management and the preservation of this vital resource’s quality.
Full article
(This article belongs to the Special Issue The Sustainable Water Management and Food Production Nexus for Global Development in the Past, Present and Future)
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Open AccessArticle
Temporal Assessment of Phosphorus Speciation in a Model Ramsar Lake System in Asia
by
Anjali Venukumar, Abdugani M. Azimov, Gani M. Iztleuov, Vishnu S. Moorchilot, Usha K. Aravind, Marat I. Sataev, Valsamma J. Koshy and Charuvila T. Aravindakumar
Hydrology 2024, 11(5), 70; https://doi.org/10.3390/hydrology11050070 - 17 May 2024
Abstract
This study focused on monitoring phosphorus (P) concentrations in the water of the Ramsar site, Lake Vembanad, with a special focus on the mouths of the river bodies draining into the lake, a known hotspot for eutrophication. Four phosphorus fractions—total reactive phosphorus (TRP),
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This study focused on monitoring phosphorus (P) concentrations in the water of the Ramsar site, Lake Vembanad, with a special focus on the mouths of the river bodies draining into the lake, a known hotspot for eutrophication. Four phosphorus fractions—total reactive phosphorus (TRP), total acid hydrolysable phosphorus (TAHP), total organic phosphorus (TOP), and total phosphorus (TP)—were monitored during the pre-monsoon and post-monsoon seasons. The results revealed high levels of all monitored phosphorus fractions, with an average concentration exceeding 300 ppb P across both seasons, indicating a highly eutrophic state. Notably, TRP, TOP, and TP showed high concentrations in both the pre-monsoon and post-monsoon periods. These data suggest significant phosphorus input into the lake’s surface water, potentially triggering excessive algal growth and threatening the biodiversity of this rich wetland ecosystem.
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(This article belongs to the Section Surface Waters and Groundwaters)
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Open AccessArticle
Effects of Cascading Dams on Streamflow within the Downstream Areas of the Rufiji River Basin in Tanzania
by
Samson Stephen Mwitalemi, Sameh Ahmed Kantoush and Binh Quang Nguyen
Hydrology 2024, 11(5), 69; https://doi.org/10.3390/hydrology11050069 - 13 May 2024
Abstract
Despite their popularity, the construction and operation of hydropower reservoirs pose challenges to water resources. This study investigated the impacts of cascading dams on streamflow in Tanzania’s Rufiji River Basin. The SWAT model was developed to represent the entire Rufiji River Basin. The
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Despite their popularity, the construction and operation of hydropower reservoirs pose challenges to water resources. This study investigated the impacts of cascading dams on streamflow in Tanzania’s Rufiji River Basin. The SWAT model was developed to represent the entire Rufiji River Basin. The model simulated the streamflow for 41 years, from 1982 to 2022, and developed two main scenarios: with-dam and without-dam. To capture the influence of all dams, the results were emphasized from 2000 to 2022, when all three dams were operating. Calibration and validation were applied at the Rufiji-Stiegler and Kilombero-Swero stations with good performance. The results show that cascading dams annually decrease the streamflow by 1% at Rufiji-Stiegler station. In contrast, individually, the Mtera Dam displayed a 5% decrease while the Kidatu and Kihansi Dams exerted a 1% increase on the annual streamflow downstream at Rufiji-Stiegler. During 2000–2022, the Rufiji River Basin showed an annual reduction in streamflow contribution of 104.97 m3/s. Therefore, the reservoir’s operation significantly impacts the downstream streamflow. The findings are expected to guide policymakers, water resource managers, and environmentalists in mitigating potential adverse effects while optimizing the benefits of hydropower generation and water regulation within the region.
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(This article belongs to the Special Issue Advances in Catchments Hydrology and Sediment Dynamics)
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Open AccessArticle
Investigating the Morphometry and Hydrometeorological Variability of a Fragile Tropical Karstic Lake of the Yucatán Peninsula: Bacalar Lagoon
by
Laura Carrillo, Mario Yescas, Mario Oscar Nieto-Oropeza, Manuel Elías-Gutiérrez, Juan C. Alcérreca-Huerta, Emilio Palacios-Hernández and Oscar F. Reyes-Mendoza
Hydrology 2024, 11(5), 68; https://doi.org/10.3390/hydrology11050068 - 11 May 2024
Abstract
Comprehensive morphometric and hydrometeorological studies on Bacalar Lagoon, Mexico’s largest tropical karstic lake and a significant aquatic system of the Yucatán Peninsula, are lacking. This study provides a detailed analysis of its bathymetry, morphometry, and hydrometeorological characteristics. The lake’s main basin stretches more
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Comprehensive morphometric and hydrometeorological studies on Bacalar Lagoon, Mexico’s largest tropical karstic lake and a significant aquatic system of the Yucatán Peninsula, are lacking. This study provides a detailed analysis of its bathymetry, morphometry, and hydrometeorological characteristics. The lake’s main basin stretches more than 52.7 km in length, with widths varying from 0.18 km to 2.28 km. It has a volume of 554.4 million cubic meters, with an average depth of 8.85 m, reaching depths of up to 26 m in the north and featuring sub-lacustrine dolines in the south, with depths of 38 m, 48.5 m, and 63.6 m. The study reveals seasonal variations in surface water temperature, closely linked to air temperature (r = 0.89), and immediate responses of water levels to hydrometeorological events. Water level fluctuations also exhibit seasonal patterns that are correlated with regional aquifer conditions, with a lag of 2 months after seasonal rainfall. Interannual variability in rainfall and water levels was observed. From 2010 to 2012, rainfall consistently remained below its mean climatic value, due to a prolonged La Niña event, while the exceptionally wet conditions in 2020 were also associated with La Niña. Extreme and anomalous hydrometeorological events, such as those following tropical storm Cristobal in 2020, revealed the fragility of Bacalar Lagoon, causing a notable transformation in lake color and transparency, shifting it from its typical oligotrophic state to eutrophic conditions that lasted longer than a year. These color changes raise questions about the factors impacting ecological health in tropical karstic regions. Additional factors affecting water quality in the BL in 2020, such as deforestation, coastline changes, and urban growth, warrant further investigation. Our study can serve as a starting landmark.
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(This article belongs to the Topic Karst Environment and Global Change)
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Open AccessArticle
Reconstruction of a Long-Term, Reach-Scale Sediment Budget Using Lateral Channel Movement Data as a Proxy: A Case Study on the Lowland Section of the Tisza River, Hungary
by
Tímea Kiss, Marcell Tóth, Gergely T. Török and György Sipos
Hydrology 2024, 11(5), 67; https://doi.org/10.3390/hydrology11050067 - 9 May 2024
Abstract
Humans have influenced the sediment transport of rivers on a centurial scale. Our goal was to use the rate of lateral channel processes as a proxy to reconstruct sediment budget (SB) changes of a lowland river (Middle Tisza, Hungary) on a historical scale
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Humans have influenced the sediment transport of rivers on a centurial scale. Our goal was to use the rate of lateral channel processes as a proxy to reconstruct sediment budget (SB) changes of a lowland river (Middle Tisza, Hungary) on a historical scale (1838–2017). The gross sediment budget (GSB) refers to the total area of eroded and accumulated surfaces, and the net sediment budget (NSB) indicates the sediment sink or source characteristics. At the beginning (1838–1890), the artificial cut-offs increased the slope and channel erosion, but the eroded sediment deposited in the oxbows, so the reach acted as a sediment sink (NSB: +0.1–0.8 m2/m/y). Then (1890–1929), a quasi-equilibrium state developed (NSB: −0.2 m2/m/y to +0.4 m2/m/y). Later (1929–1976), the bank protections impeded lateral erosion, so the system became a sediment sink again (NSB: +0.1–0.7 m2/m/y). Finally (1976–2017), the erosional processes accelerated due to dam construction and revetment collapses, and now the river is a sediment source (NSB: −0.03 to −0.08 m2/m/y). This study proved that (1) the actual SB could not be projected in the long term, as it was heavily modified, and (2) lateral channel changes could be used as a proxy to estimate long-term SB.
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(This article belongs to the Special Issue Sediment Transport and Morphological Processes at the Watershed Scale)
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Open AccessArticle
Enhancing Monthly Streamflow Prediction Using Meteorological Factors and Machine Learning Models in the Upper Colorado River Basin
by
Saichand Thota, Ayman Nassar, Soukaina Filali Boubrahimi, Shah Muhammad Hamdi and Pouya Hosseinzadeh
Hydrology 2024, 11(5), 66; https://doi.org/10.3390/hydrology11050066 - 1 May 2024
Abstract
Streamflow prediction is crucial for planning future developments and safety measures along river basins, especially in the face of changing climate patterns. In this study, we utilized monthly streamflow data from the United States Bureau of Reclamation and meteorological data (snow water equivalent,
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Streamflow prediction is crucial for planning future developments and safety measures along river basins, especially in the face of changing climate patterns. In this study, we utilized monthly streamflow data from the United States Bureau of Reclamation and meteorological data (snow water equivalent, temperature, and precipitation) from the various weather monitoring stations of the Snow Telemetry Network within the Upper Colorado River Basin to forecast monthly streamflow at Lees Ferry, a specific location along the Colorado River in the basin. Four machine learning models—Random Forest Regression, Long short-term memory, Gated Recurrent Unit, and Seasonal AutoRegresive Integrated Moving Average—were trained using 30 years of monthly data (1991–2020), split into 80% for training (1991–2014) and 20% for testing (2015–2020). Initially, only historical streamflow data were used for predictions, followed by including meteorological factors to assess their impact on streamflow. Subsequently, sequence analysis was conducted to explore various input-output sequence window combinations. We then evaluated the influence of each factor on streamflow by testing all possible combinations to identify the optimal feature combination for prediction. Our results indicate that the Random Forest Regression model consistently outperformed others, especially after integrating all meteorological factors with historical streamflow data. The best performance was achieved with a 24-month look-back period to predict 12 months of streamflow, yielding a Root Mean Square Error of 2.25 and R-squared ( ) of 0.80. Finally, to assess model generalizability, we tested the best model at other locations—Greenwood Springs (Colorado River), Maybell (Yampa River), and Archuleta (San Juan) in the basin.
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(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Projecting Aleatoric Uncertainty of Temperature—Precipitation and Flows into the Future to Assess Climate Change Impacts and Deciding on Adaptation Measures)
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Open AccessArticle
Use of Soil Moisture as an Indicator of Climate Change in the SUPer System
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Josicleda Domiciano Galvincio, Rodrigo de Queiroga Miranda and Gabrielly Gregorio da Luz
Hydrology 2024, 11(5), 65; https://doi.org/10.3390/hydrology11050065 - 30 Apr 2024
Abstract
Soil moisture can be an important indicator of climate change in humid and semi-arid areas. This indicator can more efficiently propose different public policies related to climate change than just using precipitation and temperature data. Given the above, the objective of this study
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Soil moisture can be an important indicator of climate change in humid and semi-arid areas. This indicator can more efficiently propose different public policies related to climate change than just using precipitation and temperature data. Given the above, the objective of this study is to evaluate changes in soil moisture in the state of Pernambuco during the period 1961–2021, using the System of Hydrological Response Units for Pernambuco. In this study, two river basins in the state of Pernambuco that represent the different climatic conditions of the state were chosen. The results show that in the coastal region there is a tendency towards more saturated soils, and in the semi-arid region there is a tendency towards drier soils. With these results, it is possible to conclude that public policy decisions for the economy, environment, and society must consider this vital water balance variable. Leveraging soil moisture and precipitation data makes it possible to differentiate between flood risks and landslide vulnerabilities, particularly in regions characterized by higher levels of rainfall. Monitoring soil water content in humid and semi-arid areas can significantly enhance early warning systems, thereby preventing loss of life and minimizing the socio-economic impacts of such natural events. As such, this study provides a holistic understanding of the relationship between climatic patterns, soil moisture dynamics, and the occurrence of droughts and floods, ultimately contributing to more effective disaster preparedness and response measures in Pernambuco and similar regions.
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(This article belongs to the Topic Hydrology and Water Resources Management)
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Hydrologic Sensitivity of a Critical Turkish Watershed to Inform Water Resource Management in an Altered Climate
by
Furkan Yunus Emre Cevahir, Jennifer C. Adam, Mingliang Liu and Justin Sheffield
Hydrology 2024, 11(5), 64; https://doi.org/10.3390/hydrology11050064 - 30 Apr 2024
Abstract
This study introduces a novel sensitivity analysis approach to assess the resilience and susceptibility of hydrologic systems to the stresses of climate change, moving away from conventional top-down methodologies. By exploring the hydrological sensitivity of the upper Kızılırmak River basin using the Variable
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This study introduces a novel sensitivity analysis approach to assess the resilience and susceptibility of hydrologic systems to the stresses of climate change, moving away from conventional top-down methodologies. By exploring the hydrological sensitivity of the upper Kızılırmak River basin using the Variable Infiltration Capacity (VIC) hydrologic model, we employed a sensitivity-based approach as an alternative to the traditional Global Climate Model (GCM)-based methods, providing more insightful information for water managers. Considering the consistent projections of increasing temperature over this region in GCMs, the hydrologic system was perturbed to examine gradients of a more challenging climate characterized by warming and drying conditions. The sensitivity of streamflow, snow water equivalent, and evapotranspiration to temperature (T) and precipitation (P) variations under each perturbation or “reference” climate was quantified. Results indicate that streamflow responds to T negatively under all warming scenarios. As the reference climates become drier, streamflow sensitivity to P increases, indicating that meteorological drought impacts on water availability could be exacerbated. These results suggest that there will be heightened difficulty in managing water resources in the region if it undergoes both warming and drying due to the following setbacks: (1) water availability will shift away from the summer season of peak water demand due to the warming effects on the snowpack, (2) annual water availability will likely decrease due to a combination of warming and lower precipitation, and (3) streamflow sensitivity to hydroclimatic variability will increase, meaning that there will be more extreme impacts to water availability. Water managers will need to plan for a larger set of extreme conditions.
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(This article belongs to the Special Issue Runoff Modelling under Climate Change)
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A Comparative Analysis of Sediment Concentration Using Artificial Intelligence and Empirical Equations
by
Muhammad Ashraf Khalid, Abdul Razzaq Ghumman and Ghufran Ahmed Pasha
Hydrology 2024, 11(5), 63; https://doi.org/10.3390/hydrology11050063 - 27 Apr 2024
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Morphological changes in canals are greatly influenced by sediment load dynamics, whose estimation is a challenging task because of the non-linear behavior of the sediment concentration variables. This study aims to compare different techniques including Artificial Intelligence Models (AIM) and empirical equations for
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Morphological changes in canals are greatly influenced by sediment load dynamics, whose estimation is a challenging task because of the non-linear behavior of the sediment concentration variables. This study aims to compare different techniques including Artificial Intelligence Models (AIM) and empirical equations for estimating sediment load in Upper Chenab Canal based on 10 years of sediment data from 2012 to 2022. The methodology involves utilization of a newly developed empirical equation, the Ackers and White formula and AIM including 20 neural networks with 10 training functions for both Double and Triple Layers, two Artificial Neuro-Fuzzy Inference System (ANFIS), Particle Swarm Optimization, and Ensemble Learning Random Forest models. Sensitivity analysis of sediment concentration variables has also been performed using various scenarios of input combinations in AIM. A state-of-the-art optimization technique has been used to identify the parameters of the empirical equation, and its performance is tested against AIM and the Ackers and White equation. To compare the performance of various models, four types of errors—correlation coefficient (R), T-Test, Analysis of Variance (ANOVA), and Taylor’s Diagram—have been used. The results of the study show successful application of Artificial Intelligence (AI) and empirical equations to capture the non-linear behavior of sediment concentration variables and indicate that, among all models, the ANFIS outperformed in simulating the total sediment load with a high R-value of 0.958. The performance of various models in simulating sediment concentration was assessed, with notable accuracy achieved by models AIM11 and AIM21. Moreover, the newly developed equation performed better (R = 0.92) compared to the Ackers and White formula (R = 0.88). In conclusion, the study provides valuable insights into sediment concentration dynamics in canals, highlighting the effectiveness of AI models and optimization techniques. It is suggested to incorporate other AI techniques and use multiple canals data in modeling for the future.
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Open AccessArticle
Hydropedological Characterization of a Coal Mining Waste Deposition Area Affected by Self-Burning
by
Jorge Espinha Marques, Aracelis Narayan, Patrícia Santos, Joana Ribeiro, Sara C. Antunes, Armindo Melo, Fernando Rocha, Deolinda Flores and Catarina Mansilha
Hydrology 2024, 11(5), 62; https://doi.org/10.3390/hydrology11050062 - 25 Apr 2024
Abstract
Coal mining often produces severe environmental effects, including impacts on the soil system and, specifically, on hydropedological conditions that control the leaching of significant ions and Potentially Toxic Elements (PTEs). The research objective is to assess changes in the hydropedological conditions in an
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Coal mining often produces severe environmental effects, including impacts on the soil system and, specifically, on hydropedological conditions that control the leaching of significant ions and Potentially Toxic Elements (PTEs). The research objective is to assess changes in the hydropedological conditions in an area with a coal mining waste pile that underwent self-burning. An integrative approach was implemented, starting with the definition of hydropedological zoning based on field observations of soil formation factors (namely, parent material, relief, biological activity, anthropic influence, and time). The soil profile in each hydropedological zone was characterized regarding morphological features. The upper mineral horizons were sampled and characterized in terms of mineralogy and PTE geochemistry. Field measurements of unsaturated hydraulic conductivity, soil water content, and hydrophobicity were performed. Afterwards, the hydrogeochemistry of leachates was determined, and the soil leaching potential was evaluated. The research outcomes express substantial differences regarding the hydropedological zones: development of different soil profiles, diverse mineralogy and PTE geochemistry, higher unsaturated hydraulic conductivity and leaching of major ions, and PTEs in soils affected by coal mining activities. Finally, a Principal Component Analysis confirmed the existence of significant contrasts according to hydropedological zoning.
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(This article belongs to the Special Issue Novel Approaches in Contaminant Hydrology and Groundwater Remediation)
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Perspective of Hydrodynamics in Microbial-Induced Carbonate Precipitation: A Bibliometric Analysis and Review of Research Evolution
by
Armstrong Ighodalo Omoregie, Tariq Ouahbi, Dominic Ek Leong Ong, Hazlami Fikri Basri, Lin Sze Wong and Jibril Adewale Bamgbade
Hydrology 2024, 11(5), 61; https://doi.org/10.3390/hydrology11050061 - 25 Apr 2024
Abstract
Microbial-induced carbonate precipitation (MICP) is a promising process with applications in various industries, including soil improvement, bioremediation, and concrete repair. However, comprehensive bibliometric analyses focusing on MICP research in hydrodynamics are lacking. This study analyses 1098 articles from the Scopus database (1999–2024) using
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Microbial-induced carbonate precipitation (MICP) is a promising process with applications in various industries, including soil improvement, bioremediation, and concrete repair. However, comprehensive bibliometric analyses focusing on MICP research in hydrodynamics are lacking. This study analyses 1098 articles from the Scopus database (1999–2024) using VOSviewer and R Studio, identifying information on publications, citations, authors, countries, journals, keyword hotspots, and research terms. Global participation from 66 countries is noted, with China and the United States leading in terms of contributions. The top-cited papers discuss the utilisation of ureolytic microorganisms to enhance soil properties, MICP mechanisms, concrete deterioration mitigation, soil and groundwater flow enhancement, biomineral distribution, and MICP treatment effects on soil hydraulic properties under varying conditions. Keywords like calcium carbonate, permeability, and Sporosarcina pasteurii are pivotal in MICP research. The co-occurrence analysis reveals thematic clusters like microbial cementation and geological properties, advancing our understanding of MICP’s interdisciplinary nature and its role in addressing environmental challenges.
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(This article belongs to the Section Soil and Hydrology)
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A Simulation–Optimization Model for Optimal Aquifer Remediation, Using Genetic Algorithms and MODFLOW
by
Yiannis Ν. Kontos
Hydrology 2024, 11(5), 60; https://doi.org/10.3390/hydrology11050060 - 24 Apr 2024
Abstract
This paper investigates the optimal remediation process in an aquifer using Modflow 6 software and genetic algorithms. A theoretical confined aquifer has been polluted over a long period of time by unnoticed leakage in a pipeline conveying leachate from an adjacent landfill to
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This paper investigates the optimal remediation process in an aquifer using Modflow 6 software and genetic algorithms. A theoretical confined aquifer has been polluted over a long period of time by unnoticed leakage in a pipeline conveying leachate from an adjacent landfill to a wastewater treatment plant. When the extended leakage and groundwater pollution are discovered, the optimal planning of the remediation strategy is investigated using the pump-and-treat method or/and hydrodynamic control of the pollution. The practical goal is to find the optimal locations and flow rates of two additional pumping wells, which will pump the polluted water or/and control pollution, protecting an existing drinking water pumping well, securing its fully operational mode even during the remediation process with the minimum possible cost, simply represented by the pumped water volume of the additional wells. The remediation process is considered complete when the maximum concentration in the aquifer drops below a certain limit. The Modflow software (handled by the Flopy Python package) simulates the flow field and advective–dispersive mass transport, and a genetic algorithm is used as the optimization tool. The coupled simulation–optimization model, Modflow-GA, complemented by a sophisticated post-processing results analysis, provides optimal and alternate sub-optimal remediation strategies for the decision makers to select from.
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(This article belongs to the Special Issue Groundwater Pollution: Sources, Mechanisms, and Prevention)
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