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Hydrology, Volume 10, Issue 3 (March 2023) – 20 articles

Cover Story (view full-size image): In this work, a sensitivity analysis for the standardized precipitation-evapotranspiration and aridity indexes was carried out using three different PET models, namely the Penman–Monteith model, a temperature-based parametric model, and the Thornthwaite model. The analysis was undertaken in six gauge stations in the California region where long-term drought events have occurred. Having used the Penman–Monteith model as the PET model for estimating the standardized precipitation-evapotranspiration index, our findings highlight the presence of uncertainty in defining the severity of drought, especially for large timescales (12 months to 48 months), and that the PET parametric model is a preferable model to the Thornthwaite model for both the standardized precipitation-evapotranspiration index and the aridity indexes. View this paper
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17 pages, 5109 KiB  
Article
Experimental and Artificial Neural Network (ANN) Modeling of Instream Vegetation Hydrodynamic Resistance
by Afzal Ahmed, Manousos Valyrakis, Abdul Razzaq Ghumman, Rashid Farooq, Ghufran Ahmed Pasha, Shahmir Janjua and Ali Raza
Hydrology 2023, 10(3), 73; https://doi.org/10.3390/hydrology10030073 - 22 Mar 2023
Viewed by 1353
Abstract
This study examines the impact of upstream structures on the bulk drag coefficient of vegetation through experimental means, which has not been previously conducted. An embankment model was placed upstream of the vegetation, both with and without a moat/depression. The results showed that [...] Read more.
This study examines the impact of upstream structures on the bulk drag coefficient of vegetation through experimental means, which has not been previously conducted. An embankment model was placed upstream of the vegetation, both with and without a moat/depression. The results showed that the presence of an upstream structure reduced the bulk drag coefficient of vegetation as the structure shared the drag. When only the embankment was placed upstream, a maximum decrease of 11% in the bulk drag coefficient was observed. However, when both the embankment and moat models were placed upstream, a 20% decrease in the bulk drag coefficient was observed. Regression models and artificial neural network (ANN) models were developed to predict the bulk drag coefficient based on the variables affecting it. Five ANN models with different training functions were compared to find the best possible training function, with performance indicators such as coefficient of determination (R2), root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE), sum of square error (SSE), mean absolute error (MAE), and Taylor’s diagrams used to evaluate the model performance. The ANN model with nine neurons in each hidden layer performed the best, achieving the highest R2 and NSE values and the lowest RMSE, SSE, and MAE values. Finally, the comparison between the regression model and the ANN model showed that the best ANN model outperformed the regression models, achieving R2 values of 0.99 and 0.98 for the training and validation subsets, respectively. Full article
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23 pages, 4720 KiB  
Article
IWRM Incorporating Water Use and Productivity Indicators of Economic Clusters Using a Hydro-Economic SDSS
by Gerald Norbert Souza da Silva, Márcia M. G. Alcoforado de Moraes, Laíse Alves Candido, Carlos Alberto G. de Amorim Filho, Nilena B. M. Dias, Marcelo Pereira da Cunha and Lourdinha Florêncio
Hydrology 2023, 10(3), 72; https://doi.org/10.3390/hydrology10030072 - 22 Mar 2023
Viewed by 1527
Abstract
IWRM should include the integration of management instruments towards intersectoral efficient water allocation. A platform linking economywide and network-based models, available from a Spatial Decision Support System (SDSS), was used to analyze allocation decisions in 4-interlinked basins in Northeastern Brazil during a period [...] Read more.
IWRM should include the integration of management instruments towards intersectoral efficient water allocation. A platform linking economywide and network-based models, available from a Spatial Decision Support System (SDSS), was used to analyze allocation decisions in 4-interlinked basins in Northeastern Brazil during a period of water scarcity. The SDSS can integrate water allocation issues considering hydrologic and socioeconomic aspects. In this study, we applied a normalized concentration index and exploratory spatial data analysis to socioeconomic data to identify job hotspots in economic sectors. Hydro-economic indicators were determined and used as economic weights of those hotspots and individual users for water allocation. This innovative method of allocation simulates the use of economic instruments. Removing the weights, the use of non-economic instruments is also simulated. The economic allocation transfers water from agriculture and industry to the services sector compared to the non-economic. This is justified given the low indicators of the main sectors of agriculture and industry in the region: sugarcane cultivation and the sugar–alcohol industry. Moreover, regional transfer results show that without using economic criteria and maintaining the current distribution network, there is a transfer of water stored in drier to humid regions. These results can support the decision-making process by defining effective management instruments. Full article
(This article belongs to the Special Issue Coupling of Human and Hydrological Systems)
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17 pages, 7929 KiB  
Article
Assessing the Impacts of Land Use and Land Cover Changes on the Water Quality of River Hooghly, West Bengal, India: A Case Study
by Ghritartha Goswami, Sameer Mandal, Sudip Basack, Rishika Mukherjee and Moses Karakouzian
Hydrology 2023, 10(3), 71; https://doi.org/10.3390/hydrology10030071 - 22 Mar 2023
Cited by 1 | Viewed by 2131
Abstract
Rivers are crucial components of human civilization, as they provide water for domestic, agricultural, and industrial use. Additionally, they transport domestic and industrial waste to the sea. The Ganga River is a major river in India, originating from Gangotri in the north, flowing [...] Read more.
Rivers are crucial components of human civilization, as they provide water for domestic, agricultural, and industrial use. Additionally, they transport domestic and industrial waste to the sea. The Ganga River is a major river in India, originating from Gangotri in the north, flowing through five provinces, and discharging into the Bay of Bengal. This study examined the impact of land use and land cover changes (LULC) on water quality along the River Hooghly in India. The research involved collecting water samples from different locations and analyzing them in the laboratory to estimate various parameters. The findings indicate that the expansion of built-up and agricultural lands is causing a reduction in tree cover and water bodies, leading to deteriorating water quality. The study highlights the need for sustainable land use practices and improved water management to preserve the river’s ecosystem and maintain water quality. Specifically, the study identified localities in the vicinity of Dakshineshwar, Shibpur, and Garden Reach as particularly vulnerable to water quality deterioration due to LULC changes and population growth. The study’s results provide valuable insights for policymakers and stakeholders in implementing strategies to address the challenges posed by land use changes and population growth. Full article
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25 pages, 6175 KiB  
Article
Utilizing NDWI, MNDWI, SAVI, WRI, and AWEI for Estimating Erosion and Deposition in Ping River in Thailand
by Jeerapong Laonamsai, Phongthorn Julphunthong, Thanat Saprathet, Bounhome Kimmany, Tammarat Ganchanasuragit, Phornsuda Chomcheawchan and Nattapong Tomun
Hydrology 2023, 10(3), 70; https://doi.org/10.3390/hydrology10030070 - 19 Mar 2023
Cited by 9 | Viewed by 7055
Abstract
The Ping River, located in northern Thailand, is facing various challenges due to the impacts of climate change, dam operations, and sand mining, leading to riverbank erosion and deposition. To monitor the riverbank erosion and accretion, this study employs remote sensing and GIS [...] Read more.
The Ping River, located in northern Thailand, is facing various challenges due to the impacts of climate change, dam operations, and sand mining, leading to riverbank erosion and deposition. To monitor the riverbank erosion and accretion, this study employs remote sensing and GIS technology, utilizing five water indices: the Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), Soil-Adjusted Vegetation Index (SAVI), Water Ratio Index (WRI), and Automated Water Extraction Index (AWEI). The results from each water index were comparable, with an accuracy ranging from 79.10 to 94.53 percent and analytical precision between 96.05 and 100 percent. The AWEI and WRI streams showed the highest precision out of the five indices due to their larger total surface water area. Between 2015 and 2022, the riverbank of the Ping River saw 5.18 km2 of erosion. Conversely, the morphological analysis revealed 5.55 km2 of accretion in low-lying river areas. The presence of riverbank stabilizing structures has resulted in accretion being greater than erosion, leading to the formation of riverbars along the Ping River. The presence of water hyacinth, narrow river width, and different water levels between the given periods may impact the accuracy of retrieved river areas. Full article
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15 pages, 1256 KiB  
Article
Promoting Water Efficiency in a Municipal Market Building: A Case Study
by Ana M. Antão-Geraldes, Matheus Pinto, Maria João Afonso, António Albuquerque, Cristina Sousa Coutinho Calheiros and Flora Silva
Hydrology 2023, 10(3), 69; https://doi.org/10.3390/hydrology10030069 - 18 Mar 2023
Cited by 1 | Viewed by 1738
Abstract
This study aimed to determine the water demand of a Municipal Market building to propose water use efficiency measures. The flushing cisterns have the highest water consumption (63.15%), followed by washbasins, restaurant and coffee shop taps, and hairdresser’s showerhead (31.64%). Therefore, the implementation [...] Read more.
This study aimed to determine the water demand of a Municipal Market building to propose water use efficiency measures. The flushing cisterns have the highest water consumption (63.15%), followed by washbasins, restaurant and coffee shop taps, and hairdresser’s showerhead (31.64%). Therefore, the implementation of two main categories of solutions: reducing water consumption through the adoption of efficient devices and installing a rainwater harvesting system (RWHS) when drinking water quality is not required, was evaluated. These solutions were organized in four distinct scenarios: (1) Flushing cistern replacement by dual-flush ones; (2) washbasins, restaurant, coffee shop taps, and hairdresser showerhead replacement; (3) scenario 1 combined to a RWHS for recharging the replaced flushing cisterns and (4) combining scenarios 3 and 4. Under scenarios 1, 2, 3, and 4, the expected water consumption reduction was 28.36%, 17.06%, 57.36%, and 74.41%, respectively. As a result, the annual water bill reduction was €3835.81 (scenario 1), €2307.07 (scenario 2), €7757.65 (scenario 3), and €10,064.73 (scenario 4). Furthermore, to ensure the harvested rainwater attains the required standard for recharge flushing cisterns, it is advisable to dispose of the first-flush rainwater collected after a long dry period. Full article
(This article belongs to the Special Issue Coupling of Human and Hydrological Systems)
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20 pages, 5701 KiB  
Article
Development of Groundwater Flow Models for the Integrated Management of the Alluvial Aquifer Systems of Dravsko polje and Ptujsko polje, Slovenia
by Ada Vengust, Anja Koroša, Janko Urbanc and Nina Mali
Hydrology 2023, 10(3), 68; https://doi.org/10.3390/hydrology10030068 - 16 Mar 2023
Cited by 1 | Viewed by 1618
Abstract
With increasing exploitation of groundwater resources and implementation of various activities in their recharge areas, it is vital to conduct a comprehensive assessment of aquifers to ensure their conservation and sustainable management. In the present study, we used a comprehensive approach to conceptualise [...] Read more.
With increasing exploitation of groundwater resources and implementation of various activities in their recharge areas, it is vital to conduct a comprehensive assessment of aquifers to ensure their conservation and sustainable management. In the present study, we used a comprehensive approach to conceptualise and identify the functioning of two connected aquifer systems in north-eastern Slovenia: the Quaternary porous aquifers Dravsko polje and Ptujsko polje. The study presents the conceptual models of both aquifers and their interconnectedness using separate mathematical-numerical models with the aim of ensuring an integrated management of these alluvial aquifer systems. It also highlights the importance of understanding connections between such systems for simulating groundwater flow and transport of different contaminants. To describe the entire aquifer system, the study defines its three essential elements: the geometry of the aquifers, their recharge by precipitation, and other boundary conditions. The geometry of the Quaternary aquifers was defined using Sequential Indicator Simulation (SIS) with the ESRI’s ArcMap software. Next, LIDAR was used for determining their surface geometry. The hydrogeologic model was designed using the Groundwater Modelling System (GMS) developed by AQUAVEO. We used the MODFLOW 2000 calculation method based on the finite difference method (FDM). The model was calibrated with the PEST module, which was used to calibrate hydraulic conductivity and hydraulic heads between the measured and modelled data. Finally, the model was validated using the Nash–Sutcliffe (NSE) efficiency coefficient. In addition, the model results estimated using the PEST tool were validated with the hydraulic conductivities determined at the pumping sites (pumping tests), each belonging to water protection zones that define the maximum travel time of the particles. This was performed using the MODPATH method. The paper also presents the possibility of modelling heterogeneous but interdependent aquifers in a groundwater body. Modelling the connection between the two aquifers, which are the most important ones in the region, is essential for a comprehensive management of the entire system of water resources. The models allow for a better understanding of groundwater flow in both aquifers. Moreover, their interconnectedness will be used for further studies in this field, as well as for integrated water management. Full article
(This article belongs to the Topic Groundwater Pollution Control and Groundwater Management)
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16 pages, 4082 KiB  
Article
Compound Climate Risk: Diagnosing Clustered Regional Flooding at Inter-Annual and Longer Time Scales
by Yash Amonkar, James Doss-Gollin and Upmanu Lall
Hydrology 2023, 10(3), 67; https://doi.org/10.3390/hydrology10030067 - 16 Mar 2023
Viewed by 1573
Abstract
The potential for extreme climate events to cluster in space and time has driven increased interest in understanding and predicting compound climate risks. Through a case study on floods in the Ohio River Basin, we demonstrated that low-frequency climate variability could drive spatial [...] Read more.
The potential for extreme climate events to cluster in space and time has driven increased interest in understanding and predicting compound climate risks. Through a case study on floods in the Ohio River Basin, we demonstrated that low-frequency climate variability could drive spatial and temporal clustering of the risk of regional climate extremes. Long records of annual maximum streamflow from 24 USGS gauges were used to explore the regional spatiotemporal patterns of flooding and their associated large-scale climate modes. We found that the dominant time scales of flood risk in this basin were in the interannual (6–7 years), decadal (11–13 years), and secular bands and that different sub-regions within the Ohio River Basin responded differently to large-scale forcing. We showed that the leading modes of streamflow variability were associated with ENSO and secular trends. The low-frequency climate modes translated into epochs of increased and decreased flood risk with multiple extreme floods or the absence of extreme floods, thus informing the nature of compound climate-induced flood risk. A notable finding is that the secular trend was associated with an east-to-west shift in the flood incidence and the associated storm track. This is consistent with some expectations of climate change projections. Full article
(This article belongs to the Special Issue Water Resources Management under Uncertainty and Climate Change)
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17 pages, 2957 KiB  
Article
Support Vector Regression Models of Stormwater Quality for a Mixed Urban Land Use
by Mugdha P. Kshirsagar and Kanchan C. Khare
Hydrology 2023, 10(3), 66; https://doi.org/10.3390/hydrology10030066 - 13 Mar 2023
Cited by 2 | Viewed by 1681
Abstract
The present study is an attempt to model the stormwater quality of a stream located in Pune, India. The city is split up into twenty-three basins (named A to W) by the Pune Municipal Corporation. The selected stream lies in the haphazardly expanded [...] Read more.
The present study is an attempt to model the stormwater quality of a stream located in Pune, India. The city is split up into twenty-three basins (named A to W) by the Pune Municipal Corporation. The selected stream lies in the haphazardly expanded peri-urban G basin. The G basin has constructed stormwater drains which open up in this selected open stream. The runoff over the regions picks up the non-point source pollutants which are also added to the selected stream. The study becomes more complex as the stream is misused to dump trash materials, garbage and roadside litter, which adds to the stormwater pollution. Experimental investigations include eleven distinct locations on a naturally occurring stream in the G basin. Stormwater samples were collected for twenty-two storm events, for the monsoon season over four years from 2018–2021, during and after rainfall. The physicochemical characteristics were analyzed for twelve water quality parameters, including pH, Conductivity, Turbidity, Total solids (TS), Total Suspended Solids (TSS), Total Dissolved Solids (TDS), Bio-chemical Oxygen Demand (BOD5), Chemical Oxygen Demand (COD), Dissolved Oxygen (DO), Phosphate, Ammonia and Nitrate. The Water Quality Index (WQI) ranged from 46.9 to 153.9 and from 41.20 to 87.70 for samples collected during and immediately after the rainfall, respectively. Principal Component Analysis was used to extract the most significant stormwater quality parameters. To understand the non-linear complex relationship of rainfall characteristics with significant stormwater pollutant parameters, a Support Vector Regression (SVR) model with Radial Basis Kernel Function (RBF) was developed. The Support Vector Machine is a powerful supervised algorithm that works best on smaller datasets but on complex ones with the help of kernel tricks. The accuracy of the model was evaluated based on normalized root-mean-square error (NRMSE), coefficient of determination (R2) and the ratio of performance to the interquartile range (RPIQ). The SVR model depicted the best performance for parameter TS with NRMSE (0.17), R2 (0.82) and RPIQ (2.91). The unit increase or decrease in the coefficients of rainfall characteristics displays the weighted deviation in the values of pollutant parameters. Non-linear Support Vector Regression models confirmed that both antecedent dry days and rainfall are correlated with significant stormwater quality parameters. The conclusions drawn can provide effective information to decision-makers to employ an appropriate treatment train approach of varied source control measures (SCM) to be proposed to treat and mitigate runoff in an open stream. This holistic approach serves the stakeholder’s objectives to manage stormwater efficiently. The research can be further extended by selecting a multi-criteria decision-making tool to adopt the best SCM and its multiple potential combinations. Full article
(This article belongs to the Special Issue Stormwater/Drainage Systems and Wastewater Management)
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27 pages, 76507 KiB  
Article
Simulating Groundwater Potential Zones in Mountainous Indian Himalayas—A Case Study of Himachal Pradesh
by Anshul Sud, Rahul Kanga, Suraj Kumar Singh, Gowhar Meraj, Shruti Kanga, Pankaj Kumar, AL. Ramanathan, Sudhanshu and Vinay Bhardwaj
Hydrology 2023, 10(3), 65; https://doi.org/10.3390/hydrology10030065 - 10 Mar 2023
Cited by 9 | Viewed by 2696
Abstract
Groundwater resources are increasingly important as the main supply of fresh water for household, industrial, and agricultural activities. However, overuse and depletion of these resources can lead to water scarcity and resource deterioration. Therefore, assessing groundwater availability is essential for sustainable water management. [...] Read more.
Groundwater resources are increasingly important as the main supply of fresh water for household, industrial, and agricultural activities. However, overuse and depletion of these resources can lead to water scarcity and resource deterioration. Therefore, assessing groundwater availability is essential for sustainable water management. This study aims to identify potential groundwater zones in the Bilaspur district of Himachal Pradesh using the Multi Influencing Factor (MIF) technique, a modern decision-making method widely used in various sectors. Geospatial models were integrated with the MIF technique to evaluate prospective groundwater areas. Grid layouts of all underground water influencing variables were given a predetermined score and weight in this decision-making strategy. The potential groundwater areas were then statistically assessed using graded data maps of slope, lithology, land-use, lineament, aspect, elevation, soil, drainage, geomorphology, and rainfall. These maps were converted into raster data using the raster converter tool in ArcGIS software, utilizing Survey of India toposheets, SRTM DEM data, and Resourcesat-2A satellite imageries. The prospective groundwater zones obtained were classified into five categories: nil–very low, covering 0.34% of the total area; very low–low (51.64%); low–moderate (4.92%); moderate–high (18%) and high–very high (25%). Scholars and policymakers can collaborate to develop systematic exploration plans for future developments and implement preservative and protective strategies by identifying groundwater recharge zones to reduce groundwater levels. This study provides valuable insights for long-term planning and management of water resources in the region. Full article
(This article belongs to the Special Issue Groundwater Decline and Depletion)
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13 pages, 2613 KiB  
Article
On the Sensitivity of Standardized-Precipitation-Evapotranspiration and Aridity Indexes Using Alternative Potential Evapotranspiration Models
by Aristoteles Tegos, Stefanos Stefanidis, John Cody and Demetris Koutsoyiannis
Hydrology 2023, 10(3), 64; https://doi.org/10.3390/hydrology10030064 - 06 Mar 2023
Cited by 11 | Viewed by 2394
Abstract
This paper examines the impacts of three different potential evapotranspiration (PET) models on drought severity and frequencies indicated by the standardized precipitation index (SPEI). The standardized precipitation-evapotranspiration index is a recent approach to operational monitoring and analysis of drought severity. The standardized precipitation-evapotranspiration [...] Read more.
This paper examines the impacts of three different potential evapotranspiration (PET) models on drought severity and frequencies indicated by the standardized precipitation index (SPEI). The standardized precipitation-evapotranspiration index is a recent approach to operational monitoring and analysis of drought severity. The standardized precipitation-evapotranspiration index combines precipitation and temperature data, quantifying the severity of a drought as the difference in a timestep as the difference between precipitation and PET. The standardized precipitation-evapotranspiration index thus represents the hydrological processes that drive drought events more realistically than the standardized precipitation index at the expense of additional computational complexity and increased data demands. The additional computational complexity is principally due to the need to estimate PET within each time step. The standardized precipitation-evapotranspiration index was originally defined using the Thornthwaite PET model. However, numerous researchers have demonstrated the standardized precipitation-evapotranspiration index is sensitive to the PET model adopted. PET models requiring sparse meteorological inputs, such as the Thornthwaite model, have particular utility for drought monitoring in data scarce environments. The aridity index (AI) investigates the spatiotemporal changes in the hydroclimatic system. It is defined as the ratio between potential evapotranspiration and precipitation. It is used to characterize wet (humid) and dry (arid) regions. In this study, a sensitivity analysis for the standardized precipitation-evapotranspiration and aridity indexes was carried out using three different PET models; namely, the Penman–Monteith model, a temperature-based parametric model and the Thornthwaite model. The analysis was undertaken in six gauge stations in California region where long-term drought events have occurred. Having used the Penman–Monteith model as the PET model for estimating the standardized precipitation-evapotranspiration index, our findings highlight the presence of uncertainty in defining the severity of drought, especially for large timescales (12 months to 48 months), and that the PET parametric model is a preferable model to the Thornthwaite model for both the standardized precipitation-evapotranspiration index and the aridity indexes. The latter outcome is worth further consideration for when climatic studies are under development in data scarce areas where full required meteorological variables for Penman–Monteith assessment are not available. Full article
(This article belongs to the Special Issue Advances in Evaporation and Evaporative Demand: Part II)
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15 pages, 17378 KiB  
Article
Estimation of Nitrate Background Value in Groundwater under the Long-Term Human Impact
by Patricia Buškulić, Jelena Parlov, Zoran Kovač and Zoran Nakić
Hydrology 2023, 10(3), 63; https://doi.org/10.3390/hydrology10030063 - 04 Mar 2023
Cited by 2 | Viewed by 1415
Abstract
This study demonstrates an approach to estimate the background value of nitrate as a basis for better groundwater management and protection in areas under long-term human impact. The aim was to determine the ambient background value (ABV) of nitrate in the catchment area [...] Read more.
This study demonstrates an approach to estimate the background value of nitrate as a basis for better groundwater management and protection in areas under long-term human impact. The aim was to determine the ambient background value (ABV) of nitrate in the catchment area of the Velika Gorica well field, a hydrogeologically homogeneous area within the Zagreb aquifer. ABVs are determined using four well-known model-based objective methods (the iterative 2-σ technique, IT; the calculated distribution function, CDF; the cumulative frequency curve, CFC; and the probability plot, PP), while simultaneously testing the reliability of the results of each method. If the results are not statistically significant, data selection is performed. The results show that using data without selection can lead to statistically non-significant ABVs, but with the additional selection of data, a statistically non-significant result became a statistically significant one. In summary, all final ABVs must be statistically significant and determined using as large a data set as possible. Reducing the size of the data set is acceptable only in the case of a statistically non-significant result. Full article
(This article belongs to the Topic Human Impact on Groundwater Environment)
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13 pages, 1184 KiB  
Article
Assessing the Effect of Spatial Variation in Soils on Sediment Loads in Yazoo River Watershed
by Vivek Venishetty, Prem B. Parajuli and Filip To
Hydrology 2023, 10(3), 62; https://doi.org/10.3390/hydrology10030062 - 02 Mar 2023
Cited by 1 | Viewed by 1747
Abstract
Sediment deposition in river channels from various topographic conditions has been one of the major contributors to water quality impairment through non-point sources. Soil is one of the key components in sediment loadings, during runoff. Yazoo River Watershed (YRW) is the largest watershed [...] Read more.
Sediment deposition in river channels from various topographic conditions has been one of the major contributors to water quality impairment through non-point sources. Soil is one of the key components in sediment loadings, during runoff. Yazoo River Watershed (YRW) is the largest watershed in Mississippi. Topography in the watershed has been classified into two types based on land-use and slope conditions: Delta region with a slope ranging from 0% to 3% and Bluff hills with a slope exceeding 10%. YRW spans over 50,000 km2; the Soil and Water Assessment Tool (SWAT) was used to estimate soil-specific sediment loss in the watershed. Soil predominance was based on spatial coverage; a total of 14 soil types were identified, and the sediment contributed by those soils was quantified. The SWAT model was calibrated and validated for streamflow, sediment, Total Nitrogen (TN), Total Phosphorus (TP), and Crop yield for soybeans. Model performance was evaluated using the Coefficient of determination (R2), Nash and Sutcliffe Efficiency index (NSE), and Mean Absolute Percentage Error (MAPE). The performance was good for streamflow, ranging between 0.34 and 0.83, and 0.33 and 0.81, for both R2 and NSE, respectively. Model performance for sediment and nutrient was low-satisfactory as R2 and NSE ranged between 0.14 and 0.40, and 0.14 and 0.35, respectively. In the case of crop yield, model performance was satisfactory during calibration and good for validation with an R2 of 0.56 and 0.76 and with a MAPE of 11.21% and 10.79%, respectively. Throughout YRW, soil type Smithdale predicted the highest sediment loads with 115.45 tons/ha/year. Sediment loss in agricultural fields with a soybean crop was also analyzed, where soil type Alligator predicted the highest with 8.37 tons/ha/year. Results from this study demonstrate a novel addition to the scientific community in understanding sediment loads based on soil types, which can help stakeholders in decision-making toward soil conservation and improving the environment. Full article
(This article belongs to the Special Issue Advances in Catchments Hydrology and Sediment Dynamics)
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17 pages, 3863 KiB  
Article
Cultural Heritage in the Light of Flood Hazard: The Case of the “Ancient” Olympia, Greece
by Kleomenis Kalogeropoulos, Konstantinos Tsanakas, Nikolaos Stathopoulos, Demetrios E. Tsesmelis and Andreas Tsatsaris
Hydrology 2023, 10(3), 61; https://doi.org/10.3390/hydrology10030061 - 01 Mar 2023
Cited by 3 | Viewed by 1850
Abstract
Floods are natural hazards with negative environmental and socioeconomic impacts at a local and regional level. In addition to human lives, facilities, and infrastructure, flooding is a potential threat to archaeological sites, with all the implications for the cultural heritage of each country. [...] Read more.
Floods are natural hazards with negative environmental and socioeconomic impacts at a local and regional level. In addition to human lives, facilities, and infrastructure, flooding is a potential threat to archaeological sites, with all the implications for the cultural heritage of each country. Technological developments of recent years, particularly concerning geospatial technologies (GIS, Remote Sensing, etc.), have brought novel advantages to hydrological modelling. This study uses geoinformatics to quantify flood hazard assessment. The study area is the ungauged torrent of Kladeos River, located in Peloponnese, Greece. Geomorphological analysis combined with hydrological modelling were performed in a GIS-based environment in order to study the hydrological behavior of the Kladeos River basin. The hydrological analysis was carried out with rainfall data and hypothetical storms using a 5 × 5 m digital terrain model. The quantitative features of the catchment were calculated in order to determine its susceptibility to flooding. The hydro-morphometric analysis revealed stream order anomalies in the drainage network which, combined with the morphology of its upper and lower parts, enhance the possibility of flood events. The primary results indicated that there is an increased possibility of extensive flooding in the archaeological site, depending on the severity of the rainfall, since the basic geomorphological characteristics favor it. The proposed methodology calculates parameters such as flow rate, flow velocity, etc., in order to measure and quantify flood hazard and risks in the area of interest. Full article
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17 pages, 4622 KiB  
Article
Reconstruction of Recharge and Discharge Pattern in the Polder Drainage Canal Network
by Gordon Gilja, Neven Kuspilić, Martina Lacko and Davor Romić
Hydrology 2023, 10(3), 60; https://doi.org/10.3390/hydrology10030060 - 28 Feb 2023
Viewed by 1869
Abstract
Rainfed agriculture is dependent on rainfall and runoff patterns, especially in lowland areas that rely on pumping operation to remove excess water from the drainage network. Polder areas are extremely vulnerable to saltwater intrusion and subsequent soil salinization driven by rising sea levels [...] Read more.
Rainfed agriculture is dependent on rainfall and runoff patterns, especially in lowland areas that rely on pumping operation to remove excess water from the drainage network. Polder areas are extremely vulnerable to saltwater intrusion and subsequent soil salinization driven by rising sea levels and accelerated by climate change. The aim of this paper is to reconstruct the recharge and discharge pattern in the Vidrice polder, a drainage canal network within the Neretva River Delta agroecosystem used to collect the surface and subsurface runoff from the agricultural land and saltwater infiltration through the aquifer. Water regime data are collected over an 18-month period of real-time monitoring at 15 min intervals on three stations along the primary drainage canal and one station at the secondary canal. Analysis of water level flashiness in the Vidrice polder using the Richards-Baker flashiness index (R-Bindex) indicates that daily pumping of water infiltrated in the canal network is sub-optimal: discharge fluctuates significantly more than recharge, by 46% on average, resulting in unnecessary lowering of the water level in the drainage network. The results show that the correlation between the intensive rainfall events (>10 mm/day) and the recharge rates can be used to modify the daily pumping operation and maintain high freshwater levels in the canal network to increase the resistance to infiltration and reduce saltwater intrusion into the polder. Full article
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14 pages, 1670 KiB  
Article
Probabilistic Approach to Tank Design in Rainwater Harvesting Systems
by Maria Gloria Di Chiano, Mariana Marchioni, Anita Raimondi, Umberto Sanfilippo and Gianfranco Becciu
Hydrology 2023, 10(3), 59; https://doi.org/10.3390/hydrology10030059 - 27 Feb 2023
Cited by 4 | Viewed by 4260
Abstract
Storage tanks from rainwater harvesting systems (RWHs) are designed to provide flow equalization between rainfall and water demand. The minimum storage capacity required to take into account the maximum variations of stored water volumes, i.e., the active storage, depends basically on the magnitude [...] Read more.
Storage tanks from rainwater harvesting systems (RWHs) are designed to provide flow equalization between rainfall and water demand. The minimum storage capacity required to take into account the maximum variations of stored water volumes, i.e., the active storage, depends basically on the magnitude and the variability of rainfall profiles and the size of the demand. Given the random nature of the variables involved in the hydrological process, probability theory is a suitable technique for active storage estimation. This research proposes a probabilistic approach to determine an analytical expression for the cumulative distribution function (CDF) of the active storage as a function of rainfall moments, water demand and the mean number of consecutive storm events in a deficit sub-period. The equation can be used by developers to decide on the storage capacity required at a desired non-exceedance probability and under a preset water demand. The model is validated through a continuous simulation of the tank behavior using rainfall time series from Milan (Northern Italy). Full article
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14 pages, 2421 KiB  
Article
Modeling Various Drought Time Scales via a Merged Artificial Neural Network with a Firefly Algorithm
by Babak Mohammadi
Hydrology 2023, 10(3), 58; https://doi.org/10.3390/hydrology10030058 - 27 Feb 2023
Cited by 30 | Viewed by 2447
Abstract
Drought monitoring and prediction have important roles in various aspects of hydrological studies. In the current research, the standardized precipitation index (SPI) was monitored and predicted in Peru between 1990 and 2015. The current study proposed a hybrid model, called ANN-FA, for SPI [...] Read more.
Drought monitoring and prediction have important roles in various aspects of hydrological studies. In the current research, the standardized precipitation index (SPI) was monitored and predicted in Peru between 1990 and 2015. The current study proposed a hybrid model, called ANN-FA, for SPI prediction in various time scales (SPI3, SPI6, SPI18, and SPI24). A state-of-the-art firefly algorithm (FA) has been documented as a powerful tool to support hydrological modeling issues. The ANN-FA uses an artificial neural network (ANN) which is coupled with FA for Lima SPI prediction via other stations. Through the intelligent utilization of SPI series from neighbors’ stations as model inputs, the suggested approach might be used to forecast SPI at various time scales in a meteorological station with insufficient data. To conduct this, the SPI3, SPI6, SPI18, and SPI24 were modeled in Lima meteorological station using other meteorological stations’ datasets in Peru. Various error criteria were employed to investigate the performance of the ANN-FA model. Results showed that the ANN-FA is an effective and promising approach for drought prediction and also a multi-station strategy is an effective strategy for SPI prediction in the meteorological station with a lack of data. The results of the current study showed that the ANN-FA approach can help to predict drought with the mean absolute error = 0.22, root mean square error = 0.29, the Pearson correlation coefficient = 0.94, and index of agreement = 0.97 at the testing phase of best estimation (SPI3). Full article
(This article belongs to the Section Hydrological and Hydrodynamic Processes and Modelling)
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18 pages, 23403 KiB  
Article
A Novel Multipurpose Self-Irrigated Green Roof with Innovative Drainage Layer
by Behrouz Pirouz, Stefania Anna Palermo, Gianfranco Becciu, Umberto Sanfilippo, Hana Javadi Nejad, Patrizia Piro and Michele Turco
Hydrology 2023, 10(3), 57; https://doi.org/10.3390/hydrology10030057 - 25 Feb 2023
Cited by 1 | Viewed by 1995
Abstract
Climate change is a significant problem that many countries are currently facing, and green roofs (GRs) are one of the suitable choices to confront it and decrease its impacts. The advantages of GRs are numerous, such as stormwater management, thermal need reduction, runoff [...] Read more.
Climate change is a significant problem that many countries are currently facing, and green roofs (GRs) are one of the suitable choices to confront it and decrease its impacts. The advantages of GRs are numerous, such as stormwater management, thermal need reduction, runoff quality, and life quality improvement. However, there are some limitations, including the weight, limits in water retention, irrigation in the drought period, suitability of harvested water for building usages, installation on sloped roofs, and high cost. Therefore, developing a novel system and design for GRs with higher efficiency and fewer negative points seems necessary and is the main scope of this research. In this regard, a novel multipurpose self-irrigated green roof with an innovative drainage layer combined with specific multilayer filters has been developed. The application of the proposed system in terms of water retention capacity, water storage volume, runoff treatment performance, irrigation system, drainage layer, application of the harvested water for domestic purposes, and some other aspects has been analyzed and compared with the conventional systems with a focus on extensive green roofs. The results demonstrate that this novel green roof would have many advantages including less weight due to the replacement of the gravel drainage layer with a pipeline network for water storage, higher water retention capacity due to the specific design, higher impacts on runoff treatment due to the existence of multilayer filters that can be changed periodically, easier installation on flat and sloped roofs, the possibility of using the collected rainfall for domestic use, and fewer irrigation water demands due to the sub-surface self-irrigation system. Full article
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14 pages, 1840 KiB  
Article
Evaluating Optimum Limited Irrigation and Integrated Nutrient Management Strategies for Wheat Growth, Yield and Quality
by Usman Zulfiqar, Muhammad Ahmad, Mohammad Valipour, Muhammad Ishfaq, Muhammad Faisal Maqsood, Rashid Iqbal, Muhammad Fraz Ali, Rana Roy and Ayman El Sabagh
Hydrology 2023, 10(3), 56; https://doi.org/10.3390/hydrology10030056 - 25 Feb 2023
Cited by 3 | Viewed by 1631
Abstract
Agricultural productivity is significantly influenced by the restricted availability of irrigation water and poor soil health. To assess the influence of different potential soil moisture deficit (PSMD) regimes and integrated nutrient levels on the growth, yield, and quality of wheat, an experiment was [...] Read more.
Agricultural productivity is significantly influenced by the restricted availability of irrigation water and poor soil health. To assess the influence of different potential soil moisture deficit (PSMD) regimes and integrated nutrient levels on the growth, yield, and quality of wheat, an experiment was carried out at the research area of the University of Agriculture, Faisalabad. The experiment includes three levels of PSMD (I1: 25 mm PSMD, I2: 50 mm PSMD, and I3: 75 mm PSMD) and four integrated nutrition levels (N1: 50% organic manure + 50% Inorganic NPK, N2: 75% organic manure + 25% inorganic NPK, N3: 100% application of organic manure, and N4: 100% application of inorganic NPK). Results of the experiment revealed that maximum grain yield (4.78 t ha−1) was obtained as a result of irrigation at 50 mm PSMD with the combined use of organic and inorganic sources in equal proportions. In contrast, the minimum yield was observed at I3: 75 mm PSMD with 100% application of organic manure. The highest plant height (99.11 cm), fertile tillers (284.4), 1000-grain weight (44.48 g), biological yield (14.82 t ha−1), radiation use efficiency for grain yield (RUEGY) (5.71 g MJ−1), and radiation use efficiency for total dry matter (RUETDM) (2.15 g MJ−1) were observed under N1: 50% organic manure with 50% inorganic NPK treatment. The highest value of these parameters was also observed in I2 (50 mm PSMD). The results of this study can be extended to arid and semi-arid regions, where deficit irrigation is a key strategy to address water crises and to meet sustainable development goals. Full article
(This article belongs to the Special Issue Advances in Soil Moisture Dynamics across Scales)
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18 pages, 4054 KiB  
Article
Spatial Evaluation of a Hydrological Model on Dominant Runoff Generation Processes Using Soil Hydrologic Maps
by Hadis Mohajerani, Mathias Jackel, Zoé Salm, Tobias Schütz and Markus C. Casper
Hydrology 2023, 10(3), 55; https://doi.org/10.3390/hydrology10030055 - 22 Feb 2023
Cited by 1 | Viewed by 1912
Abstract
The aim of this study was to simulate dominant runoff generation processes (DRPs) in a mesoscale catchment in southwestern Germany with the physically-based distributed hydrological model WaSiM-ETH and to compare the resulting DRP patterns with a data-mining-based digital soil map. The model was [...] Read more.
The aim of this study was to simulate dominant runoff generation processes (DRPs) in a mesoscale catchment in southwestern Germany with the physically-based distributed hydrological model WaSiM-ETH and to compare the resulting DRP patterns with a data-mining-based digital soil map. The model was parameterized by using 11 Pedo-transfer functions (PTFs) and driven by multiple synthetic rainfall events. For the pattern comparison, a multiple-component spatial performance metric (SPAEF) was applied. The simulated DRPs showed a large variability in terms of land use, applied rainfall rates, and the different PTFs, which highly influence the rapid runoff generation under wet conditions. Full article
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23 pages, 7994 KiB  
Article
Water Cycles and Geothermal Processes in a Volcanic Crater Lake
by Kazuhisa A. Chikita, Akio Goto, Jun Okada, Takashi Yamaguchi and Hideo Oyagi
Hydrology 2023, 10(3), 54; https://doi.org/10.3390/hydrology10030054 - 22 Feb 2023
Viewed by 1732
Abstract
Exploring how the hydrological and thermal conditions of a volcanic lake change in response to volcanic activity is important to identify the signs of a volcanic eruption. A water cycle system and a geothermal process in a crater lake, Okama, in the active [...] Read more.
Exploring how the hydrological and thermal conditions of a volcanic lake change in response to volcanic activity is important to identify the signs of a volcanic eruption. A water cycle system and a geothermal process in a crater lake, Okama, in the active Zao Volcano, Japan, were explored by estimating the hydrological and chemical budgets of the lake, and analyzing the time series of lake water temperature, respectively. In 2021, the lake level consistently increased by snowmelt plus rainfall in May–June, and then stayed nearly constant in the rainfall season of July–September. The hydrological budget estimated during the increasing lake level indicated that the net groundwater inflow is at any time positive. This suggests that the groundwater inflow to the lake is controlled by the water percolation into volcanic debris from the melting of snow that remained in the catchment. Solving the simultaneous equation from the hydrological and chemical budgets evaluated the groundwater inflow, Gin, at 0.012–0.040 m3/s, and the groundwater outflow, Gout, at 0.012–0.027 m3/s in May–September 2021. By adding the 2020 values of Gin and Gout evaluated at the relatively high lake level, it was found that Gin and Gout exhibit highly negative and positive correlations (R2 = 0.661 and 0.848; p < 0.01) with the lake level, respectively. In the completely ice-covered season of 15 December 2021–28 February 2022, the lake water temperature increased between the bottom and 15 m above the bottom at the deepest point, which reflects the geothermal heat input at the bottom. The heat storage change during the increasing water temperature was evaluated at a range of −0.4–5.5 W/m2 as the 10-day moving average heat flux. By accumulating the daily heat storage change for the calculated period, the water temperature averaged over the heated layer increased from 1.08 to 1.56 °C. The small temperature increase reflects a stagnant state of volcanic activity in the Zao Volcano. The present study could be useful to investigate how an active volcano responds to water percolation and geothermal heat. Full article
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