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Volume 10
Issue 8
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Hydrology, Volume 10, Issue 8 (August 2023) – 20 articles

Cover Story (view full-size image): The agro-hydrologic VegET model simulates daily soil moisture, evapotranspiration, and runoff using inflow–outflow flux accounting and saturation excess principles in a control volume defined by the root zone. The updated VegET v2.0 includes snowpack and snowmelt processes by adapting an existing temperature-index approach. The evaluation results indicated a successful integration of remote sensing and gridded weather data to represent key hydrologic processes for various applications including drought monitoring. By connecting the land surface phenology parameter with land cover and using projected climatic variables, the VegET model can be used for scenario building of the effect of land cover and climate change on processes such as the timing and duration of snowmelt and quantify the severity and extent of drought around the world. View this paper
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33 pages, 8842 KiB  
Article
Assimilating Soil Moisture Information to Improve the Performance of SWAT Hydrological Model
by Maria Kofidou and Alexandra Gemitzi
Hydrology 2023, 10(8), 176; https://doi.org/10.3390/hydrology10080176 - 21 Aug 2023
Cited by 1 | Viewed by 2186
Abstract
The present work aims to highlight the possibility of improving model performance by assimilating soil moisture information in the calibration and validation process. The Soil and Water Assessment Tool (SWAT) within QGIS, i.e., QSWAT, was used to simulate the hydrological processes within the [...] Read more.
The present work aims to highlight the possibility of improving model performance by assimilating soil moisture information in the calibration and validation process. The Soil and Water Assessment Tool (SWAT) within QGIS, i.e., QSWAT, was used to simulate the hydrological processes within the test basin, i.e., Vosvozis River Basin (VRB) in NE Greece. The model calibration and validation were conducted via SWAT-CUP for a four-year period from 2019 to 2022, in three different ways, i.e., using the traditional calibration process with river flow measurements, using satellite-based soil moisture only in the calibration, and finally incorporating satellite-based soil moisture datasets and calibrating using simultaneously flow and soil moisture information. All modeling approaches used the same set of input data related to topography, land cover, and soil information. This study utilized the recently released global scale daily downscaled soil moisture at 1 km from the Soil Moisture Active Passive (SMAP) mission to generate soil moisture datasets. Two performance indicators were evaluated: Nash Sutcliffe (NS) and coefficient of determination (R2). Results showed that QSWAT successfully simulated river flow in VRB with NS = 0.61 and R2 = 0.69 for the calibration process using river flow measurements at the outlet of VRB. However, comparing satellite-based soil moisture, NS and R2 were considerably lower with an average derived from the 19 subbasins (NS = 0.55, R2 = 0.66), indicating lower performance related to the simulation of soil moisture regime. Subsequently, introducing satellite-derived soil moisture as an additional parameter in the calibration process along with flow improved the acquired average soil moisture results of the 19 subbasins (NS = 0.85, R2 = 0.91), while preserving the satisfactory performance related to flow simulation (NS = 0.57, R2 = 0.66). Our work thus demonstrates how assimilating available satellite-derived soil moisture information into the SWAT model may offer considerable improvement in the description of soil moisture conditions, keeping the satisfactory performance in flow simulation. Full article
(This article belongs to the Topic Hydrological Modeling and Engineering: Managing Risk and Uncertainties)
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13 pages, 2812 KiB  
Article
Simple and Complex Substrates (Sugar, Acetate and Milk Whey) for In Situ Bioremediation of Groundwater with Nitrate and Actinide Contamination
by Ivan Myasnikov, Grigory Artemiev, Elena Lavrinovich, Irina Kazinskaya, Alexander Novikov and Alexey Safonov
Hydrology 2023, 10(8), 175; https://doi.org/10.3390/hydrology10080175 - 18 Aug 2023
Cited by 1 | Viewed by 1152
Abstract
The complex contamination of groundwater near radioactive waste repositories by nitrates and actinides is a common problem for many nuclear fuel cycle facilities. One of the effective methods to remove nitrates and reduce actinide migration activity is bioremediation through the activation of native [...] Read more.
The complex contamination of groundwater near radioactive waste repositories by nitrates and actinides is a common problem for many nuclear fuel cycle facilities. One of the effective methods to remove nitrates and reduce actinide migration activity is bioremediation through the activation of native microbial communities by soluble electron donors and carbon sources. This work evaluated the effectiveness of using simple and complex electron donors to remove nitrate in the microbial community in an aquifer near the B2 storage of the Siberian Chemical Combine (Seversk, Siberia). The addition of sugar and milk whey led to the maximum efficiency of nitrate-ion removal and a decrease in the redox potential of the system, creating optimal conditions for the immobilization of actinide. Special attention was paid to the behavior of uranium, plutonium, neptunium, and americium under conditions simulating groundwater when sugar, acetate, and milk whey were added and when microbial metabolic products were formed. Neither microbial metabolites nor organic solutions were found to have a significant effect on the leaching of neptunium. At the same time, for plutonium, a decrease in yield was observed when rocks were treated with organic solutions were compared to groundwater treatment without them. Plutonium leaching is significantly affected by rock composition. In rocks with a low clay fraction content, its yield can reach 40%. At the same time, microbial metabolites can increase americium (Am) desorption from rocks with a low clay fraction content. Additionally, particle size analysis was performed using a step-by-step filtration approach, aiming to evaluate the risks that are associated with colloidal phase formation. It was shown that microbiological stimulation resulted in particle enlargement, substantially diminishing the presence of actinides in the form of dissolved or sub-50 nm nanoparticles. This outcome significantly reduced the potential for colloidal and pseudocolloidal transfer, thereby lowering associated risks. Full article
(This article belongs to the Special Issue Novel Approaches in Contaminant Hydrology and Groundwater Remediation)
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17 pages, 4230 KiB  
Article
A First Step towards Developing a Decision Support System Based on the Integration of Environmental Monitoring Activities for Regional Water Resource Protection
by Carmine Massarelli, Maria Silvia Binetti, Mariangela Triozzi and Vito Felice Uricchio
Hydrology 2023, 10(8), 174; https://doi.org/10.3390/hydrology10080174 - 18 Aug 2023
Cited by 1 | Viewed by 1196
Abstract
The topic of diffuse pollution is of particular interest from technical, scientific, and administrative management points of view. Diffuse pollution is defined as the contamination or chemical, physical, or biological alterations of environmental matrices caused by diffuse sources and not attributable to a [...] Read more.
The topic of diffuse pollution is of particular interest from technical, scientific, and administrative management points of view. Diffuse pollution is defined as the contamination or chemical, physical, or biological alterations of environmental matrices caused by diffuse sources and not attributable to a single origin. In this study, various sources of diffuse pollution such as nitrates, pesticides, metals, and plastics were analysed. This was aimed at the implementation of a decision support system able to represent the state of environmental matrices degradation, with particular attention to water resources, and to make decisions evaluating similar environmental contexts. The potential of the developed system makes it possible to identify areas with the same environmental characteristics, referring to the various activities that create diffuse pollution and areas with the same pressure values on the environmental matrices. The system provides the political decision-maker with greater awareness of the environmental state, thus enabling him to apply more accurate land management policies. The created system, based on open-source software, which can be implemented with additional available data sources, is characterised by a data processing workflow that provides output information at the municipal level, so that it can be managed both by mayors and regional managers who are able to share the same information with all. Full article
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18 pages, 13584 KiB  
Article
Applying Geophysical and Hydrogeochemical Methods to Evaluate Groundwater Potential and Quality in Middle Egypt
by Esam Ismail, Dimitrios E. Alexakis, Mohamed Abou Heleika, Mohamed Hashem, Mohamed S. Ahmed, Doha Hamdy and Ahmed Ali
Hydrology 2023, 10(8), 173; https://doi.org/10.3390/hydrology10080173 - 18 Aug 2023
Cited by 2 | Viewed by 1409
Abstract
The El-Minia district is a location of interest for future urban development. Using hydrochemistry and electrical resistivity studies, this work aimed to evaluate the groundwater potentiality and it’s suitable for various uses. The groundwater potential in the study area was evaluated based on [...] Read more.
The El-Minia district is a location of interest for future urban development. Using hydrochemistry and electrical resistivity studies, this work aimed to evaluate the groundwater potentiality and it’s suitable for various uses. The groundwater potential in the study area was evaluated based on 24 VESs (vertical electrical soundings), and its quality was determined based on the analyses of 57 groundwater samples. EC (salinity index), Na% (salt hazard), SAR (ratio of sodium adsorption), chloride risks, SSP (soluble sodium percentage), MH (magnesium hazard), and other indicators were used to determine whether the collected water samples were suitable for irrigation. Four layers in the study area are mentioned in the geoelectrical cross-sections that have been constructed. The first is made up of silt and clay from the Nile River, while the second is made up of sandy clay, which has a resistivity range of 15 to 32 Ohm.m and a range thickness of 2 to 68 m. Dry limestone makes up the third layer; its resistivity ranges from 1222 to 3000 Ohm.m and its thickness varies between 75 and 95 m. The Eocene aquifer in the research area is represented by the final layer, which has a thickness of more than 250 m and resistivity values that range from 602 to 860 Ohm.m. Most groundwater samples that were collected are safe for drinking; however, none of them are fit for home usage because of their extreme hardness. According to the SAR and US diagram, RSC, KR, and PI, most groundwater samples from the Pleistocene and Eocene aquifers are fit for irrigation. Full article
(This article belongs to the Special Issue Groundwater Pollution: Sources, Mechanisms, and Prevention)
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19 pages, 9333 KiB  
Article
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 5 | Viewed by 2609
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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13 pages, 4261 KiB  
Article
Identification of the Groundwater Quality and Potential Noncarcinogenic Health Risk Assessment of Nitrate in the Groundwater of El Milia Plain, Kebir Rhumel Basin, Algeria
by Djouhaina Brella, Lazhar Belkhiri, Ammar Tiri, Hichem Salhi, Fatma Elhadj Lakouas, Razki Nouibet, Adeltif Amrane, Ryma Merdoud and Lotfi Mouni
Hydrology 2023, 10(8), 171; https://doi.org/10.3390/hydrology10080171 - 14 Aug 2023
Cited by 2 | Viewed by 1555
Abstract
In this study, we analyzed the quality and the potential noncarcinogenic health risk of nitrate in groundwater in the El Milia plain, Kebir Rhumel Basin, Algeria. Moran’s I and the ordinary kriging (OK) interpolation technique were used to examine the spatial distribution pattern [...] Read more.
In this study, we analyzed the quality and the potential noncarcinogenic health risk of nitrate in groundwater in the El Milia plain, Kebir Rhumel Basin, Algeria. Moran’s I and the ordinary kriging (OK) interpolation technique were used to examine the spatial distribution pattern of the hydrochemical parameters in the groundwater. It was found that the hydrochemical parameters Ca, Cl, and HCO3 showed strong spatial autocorrelation in the El Milia plain, indicating a spatial dependence and clustering of these parameters in the groundwater. The groundwater quality was evaluated using the entropy water quality index (EWQI). The results showed that approximately 86% of the total groundwater samples in the study area fall within the moderate groundwater quality category. The spatial map of the EWQI values indicated an increasing trend from the south-west to the northeast, following the direction of groundwater flow. The highest EWQI values were observed near El Milia city in the center of the plain. This spatial pattern suggests variations in groundwater quality across the study area, with potentially higher risks near the city center. The potential noncarcinogenic health risks associated with nitrate contamination in groundwater for adults and children through the drinking water pathway were assessed using the hazard quotient (HQ). The results revealed that approximately 5.7% of the total groundwater samples exceeded the HQ limit for adults, indicating potential health risks. Moreover, a higher percentage, 14.28%, of the total groundwater samples exceeded the HQ limit for children, highlighting their increased vulnerability to noncarcinogenic health hazards associated with nitrate contamination in the study area. Taking timely action and ensuring strict compliance with regulations in groundwater management are crucial for protecting public health, preserving the environment, addressing water scarcity, and achieving sustainable development goals. Full article
(This article belongs to the Special Issue Groundwater Pollution: Sources, Mechanisms, and Prevention)
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22 pages, 9908 KiB  
Article
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 1 | Viewed by 2395
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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20 pages, 2498 KiB  
Article
Using Ensembles of Machine Learning Techniques to Predict Reference Evapotranspiration (ET0) Using Limited Meteorological Data
by Hamza Salahudin, Muhammad Shoaib, Raffaele Albano, Muhammad Azhar Inam Baig, Muhammad Hammad, Ali Raza, Alamgir Akhtar and Muhammad Usman Ali
Hydrology 2023, 10(8), 169; https://doi.org/10.3390/hydrology10080169 - 11 Aug 2023
Viewed by 1840
Abstract
To maximize crop production, reference evapotranspiration (ET0) measurement is crucial for managing water resources and planning crop water needs. The FAO-PM56 method is recommended globally for estimating ET0 and evaluating alternative methods due to its extensive theoretical foundation. Numerous meteorological [...] Read more.
To maximize crop production, reference evapotranspiration (ET0) measurement is crucial for managing water resources and planning crop water needs. The FAO-PM56 method is recommended globally for estimating ET0 and evaluating alternative methods due to its extensive theoretical foundation. Numerous meteorological parameters, needed for ET0 estimation, are difficult to obtain in developing countries. Therefore, alternative ways to estimate ET0 using fewer climatic data are of critical importance. To estimate ET0 with alternative methods, difference climatic parameters of temperatures, relative humidity (maximum and minimum), sunshine hours, and wind speed for a period of 20 years from 1996 to 2015 were used in the study. The data were recorded by 11 meteorological observatories situated in various climatic regions of Pakistan. The significance of the climatic parameters used was evaluated using sensitivity analysis. The machine learning techniques of single decision tree (SDT), tree boost (TB) and decision tree forest (DTF) were used to perform sensitivity analysis. The outcomes indicated that DTF-based models estimated ET0 with higher accuracy and fewer climatic variables as compared to other ML techniques used in the study. The DTF technique, with Model 15 as input, outperformed other techniques for the most part of the performance metrics (i.e., NSE = 0.93, R2 = 0.96 and RMSE = 0.48 mm/month). The results indicated that the DTF with fewer climatic variables of mean relative humidity, wind speed and minimum temperature could estimate ET0 accurately and outperformed other ML techniques. Additionally, a non-linear ensemble (NLE) of ML techniques was further used to estimate ET0 using the best input combination (i.e., Model 15). It was seen that the applied non-linear ensemble (NLE) approach enhanced modelling accuracy as compared to a stand-alone application of ML techniques (R2 Multan = 0.97, R2 Skardu = 0.99, R2 ISB = 0.98, R2 Bahawalpur = 0.98 etc.). The study results affirmed the use of an ensemble model for ET0 estimation and suggest applying it in other parts of the world to validate model performance. Full article
(This article belongs to the Special Issue Big Data and Machine Learning in Hydrology: Recent Advances and Trends)
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26 pages, 7730 KiB  
Article
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
Viewed by 1977
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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17 pages, 3666 KiB  
Article
Drought Severity and Trends in a Mediterranean Oak Forest
by Stefanos Stefanidis, Dimitra Rossiou and Nikolaos Proutsos
Hydrology 2023, 10(8), 167; https://doi.org/10.3390/hydrology10080167 - 10 Aug 2023
Cited by 15 | Viewed by 1536
Abstract
Drought is a significant natural hazard with widespread socioeconomic and environmental impacts. This study investigated the long-term drought characteristics in a Mediterranean oak forest ecosystem using the Standardized Precipitation Evapotranspiration Index (SPEI) at various time scales and seasons. The analysis was based on [...] Read more.
Drought is a significant natural hazard with widespread socioeconomic and environmental impacts. This study investigated the long-term drought characteristics in a Mediterranean oak forest ecosystem using the Standardized Precipitation Evapotranspiration Index (SPEI) at various time scales and seasons. The analysis was based on a long-term time series dataset obtained from a meteorological station located at the University Forest of Taxiarchis in Greece. The dataset encompassed a substantial time span of 47 years of continuous monitoring, from 1974 to 2020. To accomplish the goals of the current research, the SPEI was calculated for 3, 6, 12, and 24-month periods, and drought events were identified. The Mann-Kendall (M-K) test was used to analyze the trends in drought severity and evaluate the trends significance. The results showed that shorter time scales (SPEI3 and SPEI6) were more efficient for identifying short-term droughts, while longer time scales (SPEI12 and SPEI24) were better for identifying less frequent but longer-lasting drought episodes. The analysis consistently revealed positive trends across all seasons and time scales, indicating an overall transition towards wetter conditions. Nearly all the data series for SPEI12 and SPEI24 exhibited statistically significant upward trends (wetter conditions) at a 95% confidence level. However, more intense events were detected during the recent decade using the seasonal analysis. Additionally, as the time scale expanded, the magnitude of these trends increased. The findings contributed to a better understanding of drought dynamics in Mediterranean oak forests and provided valuable information for forest management and climate change adaptation planning. Full article
(This article belongs to the Special Issue Forest Hydrometeorology)
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15 pages, 3167 KiB  
Article
Development and Automation of a Photovoltaic-Powered Soil Moisture Sensor for Water Management
by Denilson Alves de Melo, Patrícia Costa Silva, Adriana Rodolfo da Costa, Josué Gomes Delmond, Ana Flávia Alves Ferreira, Johnny Alves de Souza, José Francisco de Oliveira-Júnior, Jhon Lennon Bezerra da Silva, Alexandre Maniçoba da Rosa Ferraz Jardim, Pedro Rogerio Giongo, Maria Beatriz Ferreira, Abelardo Antônio de Assunção Montenegro, Henrique Fonseca Elias de Oliveira, Thieres George Freire da Silva and Marcos Vinícius da Silva
Hydrology 2023, 10(8), 166; https://doi.org/10.3390/hydrology10080166 - 10 Aug 2023
Cited by 3 | Viewed by 1992
Abstract
The objective of this study was to develop and calibrate a photovoltaic-powered soil moisture sensor (SMS) for irrigation management. Soil moisture readings obtained from the sensor were compared with gravimetric measurements. An automated SMS was used in two trials: (i) okra crop ( [...] Read more.
The objective of this study was to develop and calibrate a photovoltaic-powered soil moisture sensor (SMS) for irrigation management. Soil moisture readings obtained from the sensor were compared with gravimetric measurements. An automated SMS was used in two trials: (i) okra crop (Abelmoschus esculentus) and (ii) chili pepper (Capsicum frutescens). All sensors were calibrated and automated using an Arduino Mega board with C++. The soil moisture data were subjected to descriptive statistical analysis. The data recorded by the equipment was correlated with the gravimetric method. The determination coefficient (R2), Pearson correlation (r), and root mean square error (RMSE) were adopted as criteria for equipment validation. The results show that our SMS achieved an R2 value of 0.70 and an r value of 0.84. Notably, there was a striking similarity observed between SMS and gravimetric data, with RMSE values of 3.95 and 4.01, respectively. The global model developed exhibited highly efficient outcomes with R2 (0.98) and r (0.99) values. The applicability of the developed SMS facilitates irrigation management with accuracy and real-time monitoring using digital data. The automation of the SMS emerges as a real-time and precise alternative for performing irrigation at the right moment and in the correct amount, thus avoiding water losses. Full article
(This article belongs to the Topic Hydrology and Water Resources in Agriculture and Ecology)
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13 pages, 1914 KiB  
Article
Hydrological Properties of Litter in Different Vegetation Types: Implications for Ecosystem Functioning
by Lara Castagnolli, Fernando Santos Boggiani, Jeferson Alberto de Lima, Marcelle Teodoro Lima and Kelly Cristina Tonello
Hydrology 2023, 10(8), 165; https://doi.org/10.3390/hydrology10080165 - 10 Aug 2023
Cited by 1 | Viewed by 1333
Abstract
This study investigated the hydrological properties of litter in different vegetation cover types, including Eucalyptus sp. plantation, Agroforestry, and Restoration Forest. The research focused on evaluating litter accumulation, composition, water holding capacity, and effective water retention. The results revealed variations in litter accumulation [...] Read more.
This study investigated the hydrological properties of litter in different vegetation cover types, including Eucalyptus sp. plantation, Agroforestry, and Restoration Forest. The research focused on evaluating litter accumulation, composition, water holding capacity, and effective water retention. The results revealed variations in litter accumulation among the stands, and especially Eucalyptus sp., which had a higher proportion of branches compared to leaves. The water holding capacity of the litter differed among the stands. Agroforest and Restoration Forest showed higher litter water capacities than Eucalyptus sp. The composition and decomposition stage of the litter fractions influenced their water retention capabilities, with leaves exhibiting superior water retention. In contrast, branches had lower water absorption due to their hydrophobic nature. Despite these differences, the effective water retention, which indicates the ability of litter to intercept precipitation, was similar among the stands. The findings highlight the importance of considering litter composition and species-specific characteristics in understanding the hydrological functions of litter. This knowledge contributes to effective conservation and management strategies for sustainable land use practices and water resource management. Further research is recommended to expand the study’s scope to include a wider range of forest types and natural field conditions, providing a more comprehensive understanding of litter hydrological functions and their implications for ecosystem processes. Full article
(This article belongs to the Topic Hydrology and Water Resources in Agriculture and Ecology)
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23 pages, 6733 KiB  
Article
Enhancing Flood Prediction Accuracy through Integration of Meteorological Parameters in River Flow Observations: A Case Study Ottawa River
by Clara Letessier, Jean Cardi, Antony Dussel, Isa Ebtehaj and Hossein Bonakdari
Hydrology 2023, 10(8), 164; https://doi.org/10.3390/hydrology10080164 - 10 Aug 2023
Cited by 3 | Viewed by 1501
Abstract
Given that the primary cause of flooding in Ontario, Canada, is attributed to spring floods, it is crucial to incorporate temperature as an input variable in flood prediction models with machine learning algorithms. This inclusion enables a comprehensive understanding of the intricate dynamics [...] Read more.
Given that the primary cause of flooding in Ontario, Canada, is attributed to spring floods, it is crucial to incorporate temperature as an input variable in flood prediction models with machine learning algorithms. This inclusion enables a comprehensive understanding of the intricate dynamics involved, particularly the impact of heatwaves on snowmelt, allowing for more accurate flood prediction. This paper presents a novel machine learning approach called the Adaptive Structure of the Group Method of Data Handling (ASGMDH) for predicting daily river flow rates, incorporating measured discharge from the previous day as a historical record summarizing watershed characteristics, along with real-time data on air temperature and precipitation. To propose a comprehensive machine learning model, four different scenarios with various input combinations were examined. The simplest model with three parameters (maximum temperature, precipitation, historical daily river flow discharge) achieves high accuracy, with an R2 value of 0.985 during training and 0.992 during testing, demonstrating its reliability and potential for practical application. The developed ASGMDH model demonstrates high accuracy for the study area, with a significant number of samples having a relative error of less than 15%. The final ASGMDH-based model has only a second-order polynomial (AICc = 19,648.71), while it is seven for the classical GMDH-based model (AICc = 19,701.56). The sensitivity analysis reveals that maximum temperature significantly impacts the prediction of daily river flow discharge. Full article
(This article belongs to the Special Issue Traditional Statistics vs. Modern Machine Learning Approaches in Hydrology)
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23 pages, 6358 KiB  
Article
Stream Barrier Removal: Are New Approaches Possible in Small Rivers? The Case of the Selho River (Northwestern Portugal)
by Francisco Costa and António Vieira
Hydrology 2023, 10(8), 163; https://doi.org/10.3390/hydrology10080163 - 09 Aug 2023
Viewed by 1603
Abstract
The identification and characterization of barriers to river continuity are essential for the preparation of an inventory of hydraulic infrastructure. To this end, it is necessary to define the main identifying and characterizing elements of hydraulic infrastructures and descriptors of ecological continuity, with [...] Read more.
The identification and characterization of barriers to river continuity are essential for the preparation of an inventory of hydraulic infrastructure. To this end, it is necessary to define the main identifying and characterizing elements of hydraulic infrastructures and descriptors of ecological continuity, with information that can characterize them from the point of view of their impact on the watercourse. Several authors have defined decision criteria for the removal of existing hydraulic structures in watercourses and their application, reinforcing the environmental benefits of the elimination of these hydraulic structures. In the present work, we proposed to develop a methodology for the evaluation of barriers in the Selho River (Guimarães Municipality, Northwest Portugal), elaborating an Environmental Condition Index (ECI) based on hydromorphological, socioeconomical, and ecological criteria, which allowed the identification of 43 weirs, of which 95% revealed quality inferior to Good. Following the application of a decision support methodology for the removal of hydraulic structures, it was possible to determine that 16 of the 43 weirs evaluated could be subject to removal, 26 would be under conditioned removal, and only 1 would be able to remain unchanged. Full article
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29 pages, 8625 KiB  
Article
Evaluation of BOLAM Fine Grid Weather Forecasts with Emphasis on Hydrological Applications
by Nikolaos Malamos, Dimitrios Koulouris, Ioannis L. Tsirogiannis and Demetris Koutsoyiannis
Hydrology 2023, 10(8), 162; https://doi.org/10.3390/hydrology10080162 - 03 Aug 2023
Viewed by 1159
Abstract
The evaluation of weather forecast accuracy is of major interest in decision making in almost every sector of the economy and in civil protection. To this, a detailed assessment of Bologna Limited-Area Model (BOLAM) seven days fine grid 3 h predictions is made [...] Read more.
The evaluation of weather forecast accuracy is of major interest in decision making in almost every sector of the economy and in civil protection. To this, a detailed assessment of Bologna Limited-Area Model (BOLAM) seven days fine grid 3 h predictions is made for precipitation, air temperature, relative humidity, and wind speed over a large lowland agricultural area of a Mediterranean-type climate, characterized by hot summers and rainy moderate winters (plain of Arta, NW Greece). Timeseries that cover a four-year period (2016–2019) from seven agro-meteorological stations located at the study area are used to run a range of contingency and accuracy measures as well as Taylor diagrams, and the results are thoroughly discussed. The overall results showed that the model failed to comply with the precipitation regime throughout the study area, while the results were mediocre for wind speed. Considering relative humidity, the results revealed acceptable performance and good correlation between the model output and the observed values, for the early days of forecast. Only in air temperature, the forecasts exhibited very good performance. Discussion is made on the ability of the model to predict major rainfall events and to estimate water budget components as rainfall and reference evapotranspiration. The need for skilled weather forecasts from improved versions of the examined model that may incorporate post-processing techniques to improve predictions or from other forecasting services is underlined. Full article
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19 pages, 4944 KiB  
Article
Quantification of Mountainous Hydrological Processes in the Aktash River Watershed of Uzbekistan, Central Asia, over the Past Two Decades
by Ying Ouyang, John A. Stanturf, Marcus D. Williams, Evgeniy Botmann and Palle Madsen
Hydrology 2023, 10(8), 161; https://doi.org/10.3390/hydrology10080161 - 02 Aug 2023
Viewed by 1266
Abstract
Estimation of hydrological processes is critical to water resource management, water supply planning, ecological protection, and climate change impact assessment. Mountains in Central Asia are the major source of water for rivers and agricultural practices. The disturbance of mountain forests in the region [...] Read more.
Estimation of hydrological processes is critical to water resource management, water supply planning, ecological protection, and climate change impact assessment. Mountains in Central Asia are the major source of water for rivers and agricultural practices. The disturbance of mountain forests in the region has altered the hydrological processes and accelerated soil erosion, mudflow, landslides, and flooding. We used the SWAT (Soil and Water Assessment Tool) model calibrated and validated with remote sensing data to quantify the mountainous hydrological processes in the Aktash River watershed (ARW) of Uzbekistan, Central Asia. Simulations showed that the daily surface runoff and streamflow closely responded to daily precipitation. Groundwater discharge reached its maximum in winter because of snowmelt. The wet months were from July to December, and the dry months were from January to June. The magnitudes of the seasonal hydrological processes were in the following order: fall > summer > winter > spring for precipitation and surface runoff; summer > spring > fall > winter for evapotranspiration (ET); winter > spring > fall > summer for snowmelt; fall > winter > summer > spring for water yield and streamflow; and winter > fall > spring > summer for groundwater discharge. The Mann–Kendall statistical test revealed a significant increasing trend for the annual precipitation (τ = 0.45, p < 0.01) and surface runoff (τ = 0.41, p < 0.02) over the past 17 years from 2003 to 2019. Compared to rangeland, forested land decreased monthly and annual average surface runoff by 20%, and increased monthly and annual average groundwater recharge by about 5%. Agricultural land had much higher unit-area values (mm/km2/y) of ET, groundwater recharge, and water yield than those of urban, forest, and range lands. Our research findings provide useful information to farmers, foresters, and decision makers for better water resource management in the ARW, Central Asia, and other mountain watersheds with similar conditions. Full article
(This article belongs to the Special Issue Forest Hydrometeorology)
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22 pages, 3247 KiB  
Article
Modeled Forest Conversion Influences Humid Tropical Watershed Hydrology More than Projected Climate Change
by Taylor Joyal, Alexander K. Fremier and Jan Boll
Hydrology 2023, 10(8), 160; https://doi.org/10.3390/hydrology10080160 - 31 Jul 2023
Viewed by 1332
Abstract
In the humid tropics, forest conversion and climate change threaten the hydrological function and stationarity of watersheds, particularly in steep terrain. As climate change intensifies, shifting precipitation patterns and expanding agricultural and pastoral land use may effectively reduce the resilience of headwater catchments. [...] Read more.
In the humid tropics, forest conversion and climate change threaten the hydrological function and stationarity of watersheds, particularly in steep terrain. As climate change intensifies, shifting precipitation patterns and expanding agricultural and pastoral land use may effectively reduce the resilience of headwater catchments. Compounding this problem is the limited long-term monitoring in developing countries for planning in an uncertain future. In this study, we asked which change, climate or land use, more greatly affects stream discharge in humid tropical mountain watersheds? To answer this question, we used the process-based, spatially distributed Soil Moisture Routing model. After first evaluating model performance (Ns = 0.73), we conducted a global sensitivity analysis to identify the model parameters that most strongly influence simulated watershed discharge. In particular, peak flows are most influenced by input model parameters that represent shallow subsurface soil pathways and saturation-excess runoff while low flows are most sensitive to macropore hydraulic conductivity, soil depth and porosity parameters. We then simulated a range of land use and climate scenarios in three mountain watersheds of central Costa Rica. Our results show that deforestation influences streamflow more than altered precipitation and temperature patterns through changes in first-order hydrologic hillslope processes. However, forest conversion coupled with intensifying precipitation events amplifies hydrological extremes, reducing the hydrological resilience to predicted climate shifts in mountain watersheds of the humid tropics. This finding suggests that reforestation can help mitigate the effects of climate change on streamflow dynamics in the tropics including impacts to water availability, flood pulses, channel geomorphology and aquatic habitat associated with altered flow regimes. Full article
(This article belongs to the Topic Hydrology and Water Resources Management)
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18 pages, 1340 KiB  
Article
Extreme Events Analysis Using LH-Moments Method and Quantile Function Family
by Cristian Gabriel Anghel, Stefan Ciprian Stanca and Cornel Ilinca
Hydrology 2023, 10(8), 159; https://doi.org/10.3390/hydrology10080159 - 30 Jul 2023
Viewed by 1701
Abstract
A direct way to estimate the likelihood and magnitude of extreme events is frequency analysis. This analysis is based on historical data and assumptions of stationarity, and is carried out with the help of probability distributions and different methods of estimating their parameters. [...] Read more.
A direct way to estimate the likelihood and magnitude of extreme events is frequency analysis. This analysis is based on historical data and assumptions of stationarity, and is carried out with the help of probability distributions and different methods of estimating their parameters. Thus, this article presents all the relations necessary to estimate the parameters with the LH-moments method for the family of distributions defined only by the quantile function, namely, the Wakeby distribution of 4 and 5 parameters, the Lambda distribution of 4 and 5 parameters, and the Davis distribution. The LH-moments method is a method commonly used in flood frequency analysis, and it uses the annual series of maximum flows. The frequency characteristics of the two analyzed methods, which are both involved in expressing the distributions used in the first two linear moments, as well as in determining the confidence interval, are presented. The performances of the analyzed distributions and the two presented methods are verified in the following maximum flows, with the Bahna river used as a case study. The results are presented in comparison with the L-moments method. Following the results obtained, the Wakeby and Lambda distributions have the best performances, and the LH-skewness and LH-kurtosis statistical indicators best model the indicators’ values of the sample (0.5769, 0.3781, 0.548 and 0.3451). Similar to the L-moments method, this represents the main selection criterion of the best fit distribution. Full article
(This article belongs to the Special Issue Climate Change Effects on Hydrology and Water Resources)
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24 pages, 10756 KiB  
Article
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
Viewed by 1957
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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16 pages, 4643 KiB  
Article
Hydroclimatic Trends and Drought Risk Assessment in the Ceyhan River Basin: Insights from SPI and STI Indices
by Hamid Darabi, Ali Danandeh Mehr, Gülşen Kum, Mehmet Emin Sönmez, Cristina Alina Dumitrache, Khadija Diani, Ahmet Celebi and Ali Torabi Haghighi
Hydrology 2023, 10(8), 157; https://doi.org/10.3390/hydrology10080157 - 26 Jul 2023
Cited by 2 | Viewed by 1252
Abstract
This study examined the spatiotemporal climate variability over the Ceyhan River basin in Southern Anatolia, Türkiye using historical rainfall and temperature observations recorded at 15 meteorology stations. Various statistical and geostatistical techniques were employed to determine the significance of trends for each climatic [...] Read more.
This study examined the spatiotemporal climate variability over the Ceyhan River basin in Southern Anatolia, Türkiye using historical rainfall and temperature observations recorded at 15 meteorology stations. Various statistical and geostatistical techniques were employed to determine the significance of trends for each climatic variable in the whole basin and its three sub-regions (northern, central, and southern regions). The results revealed that the recent years in the basin were generally warmer compared with previous years, with a temperature increase of approximately 4 °C. The standardized temperature index analysis indicated a shift towards hotter periods after 2005, while the coldest periods were observed in the early 1990s. The spatial distribution of temperature showed non-uniform patterns throughout the basin. The first decade of the study period (1975–1984) was characterized by relatively cold temperatures, followed by a transition period from cold to hot between 1985 and 2004, and a hotter period in the last decade (2005–2014). The rainfall analysis indicated a decreasing trend in annual rainfall, particularly in the northern and central regions of the basin. However, the southern region showed an increasing trend in annual rainfall during the study period. The spatial distribution of rainfall exhibited considerable variability across the basin, with different regions experiencing distinct patterns. The standardized precipitation index analysis revealed the occurrence of multiple drought events throughout the study period. The most severe and prolonged droughts were observed in the years 1992–1996 and 2007–2010. These drought events had significant impacts on water availability and agricultural productivity in the basin. Full article
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