Pub Date : 2023-11-15DOI: 10.3390/hydrology10110213
Hajar Lazar, Meryem Ayach, A. Barry, Ismail Mohsine, Abdessamad Touiouine, F. Huneau, Christophe Mori, É. Garel, I. Kacimi, Vincent Valles, L. Barbiero
The cross-referencing of two databases, namely the compartmentalization into groundwater bodies (GWB) and the quality monitoring (2830 observations including 15 physico-chemical and bacteriological parameters, on 662 collection points and over a period of 27 years) is applied to better understand the diversity of the waters of the island of Corsica (France) and to facilitate the surveillance and quality monitoring of the groundwater resource. Data conditioning (log-transformation), dimensional reduction (PCA), classification (AHC) and then quantification of the information lost during grouping (ANOVA), highlight the need to sub-divide the groundwater bodies in the crystalline part of the island in order to take better account of lithological diversity and other environmental factors (slope, altitude, soil thickness, etc.). The compartmentalization into 15 units, mainly based on structural geology, provides less information than the grouping into 12 units after subdivision of the crystalline region. The diversity of the waters in terms of chemical and bacteriological composition is discussed, and the results encourage a review of the compartmentalization of the island’s GWBs, with a view to more targeted monitoring based on this diversity.
{"title":"Groundwater Bodies Subdivision in Corsica: A Critical Approach Based on Multivariate Water Quality Criteria Using Large Database","authors":"Hajar Lazar, Meryem Ayach, A. Barry, Ismail Mohsine, Abdessamad Touiouine, F. Huneau, Christophe Mori, É. Garel, I. Kacimi, Vincent Valles, L. Barbiero","doi":"10.3390/hydrology10110213","DOIUrl":"https://doi.org/10.3390/hydrology10110213","url":null,"abstract":"The cross-referencing of two databases, namely the compartmentalization into groundwater bodies (GWB) and the quality monitoring (2830 observations including 15 physico-chemical and bacteriological parameters, on 662 collection points and over a period of 27 years) is applied to better understand the diversity of the waters of the island of Corsica (France) and to facilitate the surveillance and quality monitoring of the groundwater resource. Data conditioning (log-transformation), dimensional reduction (PCA), classification (AHC) and then quantification of the information lost during grouping (ANOVA), highlight the need to sub-divide the groundwater bodies in the crystalline part of the island in order to take better account of lithological diversity and other environmental factors (slope, altitude, soil thickness, etc.). The compartmentalization into 15 units, mainly based on structural geology, provides less information than the grouping into 12 units after subdivision of the crystalline region. The diversity of the waters in terms of chemical and bacteriological composition is discussed, and the results encourage a review of the compartmentalization of the island’s GWBs, with a view to more targeted monitoring based on this diversity.","PeriodicalId":37372,"journal":{"name":"Hydrology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139271125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-14DOI: 10.3390/hydrology10110212
B. Tom, Minxue He, Prabhjot Sandhu
Hydrodynamic models are widely used in simulating water dynamics in riverine and estuarine systems. A reasonably realistic representation of the geometry (e.g., channel length, junctions, cross-sections, etc.) of the study area is imperative for any successful hydrodynamic modeling application. Typically, hydrodynamic models do not digest these data directly but rely on pre-processing tools to convert the data to a readable format. This study presents a parsimonious open-source and user-friendly Java software tool, the Cross-Section Development Program (CSDP), that is developed by the authors to prepare geometric inputs for hydrodynamic models. The CSDP allows the user to select bathymetry data collected in different years by different agencies and create cross-sections and computational points in a channel automatically. This study further illustrates the application of this tool to the Delta Simulation Model II, which is the operational forecasting and planning hydrodynamic and water quality model developed for the Sacramento–San Joaquin Delta in California, United States. Model simulations on water levels and flow rates at key stations are evaluated against corresponding observations. The simulations mimic the patterns of the corresponding observations very well. The square of the correlation coefficient is generally over 0.95 during the calibration period and over 0.80 during the validation period. The absolute bias is generally less than 5% and 10% during the calibration and validation periods, respectively. The Kling–Gupta efficiency index is generally over 0.70 during both calibration and validation periods. The results illustrate that CSDP can be efficiently applied to generate geometric inputs for hydrodynamic models.
{"title":"An Open-Source Cross-Section Tool for Hydrodynamic Model Geometric Input Development","authors":"B. Tom, Minxue He, Prabhjot Sandhu","doi":"10.3390/hydrology10110212","DOIUrl":"https://doi.org/10.3390/hydrology10110212","url":null,"abstract":"Hydrodynamic models are widely used in simulating water dynamics in riverine and estuarine systems. A reasonably realistic representation of the geometry (e.g., channel length, junctions, cross-sections, etc.) of the study area is imperative for any successful hydrodynamic modeling application. Typically, hydrodynamic models do not digest these data directly but rely on pre-processing tools to convert the data to a readable format. This study presents a parsimonious open-source and user-friendly Java software tool, the Cross-Section Development Program (CSDP), that is developed by the authors to prepare geometric inputs for hydrodynamic models. The CSDP allows the user to select bathymetry data collected in different years by different agencies and create cross-sections and computational points in a channel automatically. This study further illustrates the application of this tool to the Delta Simulation Model II, which is the operational forecasting and planning hydrodynamic and water quality model developed for the Sacramento–San Joaquin Delta in California, United States. Model simulations on water levels and flow rates at key stations are evaluated against corresponding observations. The simulations mimic the patterns of the corresponding observations very well. The square of the correlation coefficient is generally over 0.95 during the calibration period and over 0.80 during the validation period. The absolute bias is generally less than 5% and 10% during the calibration and validation periods, respectively. The Kling–Gupta efficiency index is generally over 0.70 during both calibration and validation periods. The results illustrate that CSDP can be efficiently applied to generate geometric inputs for hydrodynamic models.","PeriodicalId":37372,"journal":{"name":"Hydrology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139277791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-13DOI: 10.3390/hydrology10110211
Francis Proteau-Bedard, Paul Baudron, Nicolas Benoit, Miroslav Nastev, Ryan Post, Janie Masse-Dufresne
Geochemical tracers have the potential to provide valuable insights for constructing conceptual models of groundwater flow, especially in complex geological contexts. Nevertheless, the reliability of tracer interpretation hinges on its integration into a robust geological framework. In our research, we concentrated on delineating the groundwater flow dynamics in the Innisfil Creek watershed, located in Ontario, Canada. We amalgamated extensive hydrogeological data derived from a comprehensive 3D geological model with the analysis of 61 groundwater samples, encompassing major ions, stable water isotopes, tritium, and radiocarbon. By seamlessly incorporating regional physiographic characteristics, flow pathways, and confinement attributes, we bolstered the efficiency of these tracers, resulting in several notable findings. Firstly, we identified prominent recharge and discharge zones within the watershed. Secondly, we observed the coexistence of relatively shallow and fast-flowing paths with deeper, slower-flowing channels, responsible for transporting groundwater from ancient glacial events. Thirdly, we determined that cation exchange stands as the predominant mechanism governing the geochemical evolution of contemporary water as it migrates toward confined aquifers situated at the base of the Quaternary sequence. Fourthly, we provided evidence of the mixing of modern, low-mineralized water originating from unconfined aquifer units with deep, highly mineralized water within soil–bedrock interface aquifers. These findings not only contribute significantly to the development a conceptual flow model for the sustainable management of groundwater in the Innisfil watershed, but also offer practical insights that hold relevance for analogous geological complexities encountered in other regions.
{"title":"Investigating Multilayer Aquifer Dynamics by Combining Geochemistry, Isotopes and Hydrogeological Context Analysis","authors":"Francis Proteau-Bedard, Paul Baudron, Nicolas Benoit, Miroslav Nastev, Ryan Post, Janie Masse-Dufresne","doi":"10.3390/hydrology10110211","DOIUrl":"https://doi.org/10.3390/hydrology10110211","url":null,"abstract":"Geochemical tracers have the potential to provide valuable insights for constructing conceptual models of groundwater flow, especially in complex geological contexts. Nevertheless, the reliability of tracer interpretation hinges on its integration into a robust geological framework. In our research, we concentrated on delineating the groundwater flow dynamics in the Innisfil Creek watershed, located in Ontario, Canada. We amalgamated extensive hydrogeological data derived from a comprehensive 3D geological model with the analysis of 61 groundwater samples, encompassing major ions, stable water isotopes, tritium, and radiocarbon. By seamlessly incorporating regional physiographic characteristics, flow pathways, and confinement attributes, we bolstered the efficiency of these tracers, resulting in several notable findings. Firstly, we identified prominent recharge and discharge zones within the watershed. Secondly, we observed the coexistence of relatively shallow and fast-flowing paths with deeper, slower-flowing channels, responsible for transporting groundwater from ancient glacial events. Thirdly, we determined that cation exchange stands as the predominant mechanism governing the geochemical evolution of contemporary water as it migrates toward confined aquifers situated at the base of the Quaternary sequence. Fourthly, we provided evidence of the mixing of modern, low-mineralized water originating from unconfined aquifer units with deep, highly mineralized water within soil–bedrock interface aquifers. These findings not only contribute significantly to the development a conceptual flow model for the sustainable management of groundwater in the Innisfil watershed, but also offer practical insights that hold relevance for analogous geological complexities encountered in other regions.","PeriodicalId":37372,"journal":{"name":"Hydrology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136282861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-09DOI: 10.3390/hydrology10110210
Justin T. Telfer, Mitchell M. Brown, Gustavious P. Williams, Kaylee B. Tanner, A. Woodruff Miller, Robert B. Sowby, Theron G. Miller
Atmospheric deposition (AD) is a significant source of nutrient loading to waterbodies around the world. However, the sources and loading rates are poorly understood for major waterbodies and even less understood for local waterbodies. Utah Lake is a eutrophic lake located in central Utah, USA, and has high-nutrient levels. Recent research has identified AD as a significant source of nutrient loading to the lake, though contributions from dust particles make up 10% of total AD. To better understand the dust AD sources, we sampled suspected source locations and collected deposition samples around the lake. We analyzed these samples using Inductively Coupled Plasma (ICP) for 25 metals to characterize their elemental fingerprints. We then compared the lake samples to the source samples to determine likely source locations. We computed spectral angle, coefficient of determination, multi-dimensional scaling, and radar plots to characterize the similarity of the samples. We found that samples from local dust sources were more similar to dust in lake AD samples than samples from distant sources. This suggests that the major source of the dust portion of AD onto Utah Lake is the local empty fields south and west of the lake, and not the farther playa and desert sources as previously suggested. Preliminary data suggest that dust AD is associated with dry, windy conditions and is episodic in nature. We show that AD from dust particles is likely a small portion of the overall AD nutrient loading on Utah Lake, with the dry and precipitation sources contributing most of the load. This case identifies AD sources to Utah Lake and provides an example of data and methods that can be used to assess similarity or perform attribution for dust, soil, and other environmental data. While we use ICP metals, any number of features can be used with these methods if normalized.
{"title":"Source Attribution of Atmospheric Dust Deposition to Utah Lake","authors":"Justin T. Telfer, Mitchell M. Brown, Gustavious P. Williams, Kaylee B. Tanner, A. Woodruff Miller, Robert B. Sowby, Theron G. Miller","doi":"10.3390/hydrology10110210","DOIUrl":"https://doi.org/10.3390/hydrology10110210","url":null,"abstract":"Atmospheric deposition (AD) is a significant source of nutrient loading to waterbodies around the world. However, the sources and loading rates are poorly understood for major waterbodies and even less understood for local waterbodies. Utah Lake is a eutrophic lake located in central Utah, USA, and has high-nutrient levels. Recent research has identified AD as a significant source of nutrient loading to the lake, though contributions from dust particles make up 10% of total AD. To better understand the dust AD sources, we sampled suspected source locations and collected deposition samples around the lake. We analyzed these samples using Inductively Coupled Plasma (ICP) for 25 metals to characterize their elemental fingerprints. We then compared the lake samples to the source samples to determine likely source locations. We computed spectral angle, coefficient of determination, multi-dimensional scaling, and radar plots to characterize the similarity of the samples. We found that samples from local dust sources were more similar to dust in lake AD samples than samples from distant sources. This suggests that the major source of the dust portion of AD onto Utah Lake is the local empty fields south and west of the lake, and not the farther playa and desert sources as previously suggested. Preliminary data suggest that dust AD is associated with dry, windy conditions and is episodic in nature. We show that AD from dust particles is likely a small portion of the overall AD nutrient loading on Utah Lake, with the dry and precipitation sources contributing most of the load. This case identifies AD sources to Utah Lake and provides an example of data and methods that can be used to assess similarity or perform attribution for dust, soil, and other environmental data. While we use ICP metals, any number of features can be used with these methods if normalized.","PeriodicalId":37372,"journal":{"name":"Hydrology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135242712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-09DOI: 10.3390/hydrology10110209
Alejandra Correa-González, Joel Hernández-Bedolla, Marco Antonio Martínez-Cinco, Sonia Tatiana Sánchez-Quispe, Mario Alberto Hernández-Hernández
In recent years, due to various anthropogenic activities, such as agriculture and livestock, the presence of nitrogen-associated contaminants has been increasing in surface- and groundwater resources. Among these, the main compounds present in groundwater are ammonia, nitrite, and nitrate. However, it is sometimes difficult to assess such effects given the scarcity or lack of information and the complexity of the system. In the current study, a methodology is proposed to assess nitrate in groundwater from diffuse sources considering spatiotemporal patterns of hydrological systems using a coupled SWAT/MODFLOW/MT3DMS model. The application of the model is carried out using a simplified simulation scheme of hydrological and agricultural systems because of the limited spatial and temporal data. The study area includes the Cuitzeo Lake basin in superficial flow form and the Morelia–Querendaro aquifer in groundwater flow form. The results within the methodology are surface runoff, groundwater levels, and nitrate concentrations present in surface- and groundwater systems. The results indicate that the historical and simulated nitrate concentrations were obtained within acceptable values of the statistical parameters and, therefore, are considered adequate.
{"title":"Assessment of Nitrate in Groundwater from Diffuse Sources Considering Spatiotemporal Patterns of Hydrological Systems Using a Coupled SWAT/MODFLOW/MT3DMS Model","authors":"Alejandra Correa-González, Joel Hernández-Bedolla, Marco Antonio Martínez-Cinco, Sonia Tatiana Sánchez-Quispe, Mario Alberto Hernández-Hernández","doi":"10.3390/hydrology10110209","DOIUrl":"https://doi.org/10.3390/hydrology10110209","url":null,"abstract":"In recent years, due to various anthropogenic activities, such as agriculture and livestock, the presence of nitrogen-associated contaminants has been increasing in surface- and groundwater resources. Among these, the main compounds present in groundwater are ammonia, nitrite, and nitrate. However, it is sometimes difficult to assess such effects given the scarcity or lack of information and the complexity of the system. In the current study, a methodology is proposed to assess nitrate in groundwater from diffuse sources considering spatiotemporal patterns of hydrological systems using a coupled SWAT/MODFLOW/MT3DMS model. The application of the model is carried out using a simplified simulation scheme of hydrological and agricultural systems because of the limited spatial and temporal data. The study area includes the Cuitzeo Lake basin in superficial flow form and the Morelia–Querendaro aquifer in groundwater flow form. The results within the methodology are surface runoff, groundwater levels, and nitrate concentrations present in surface- and groundwater systems. The results indicate that the historical and simulated nitrate concentrations were obtained within acceptable values of the statistical parameters and, therefore, are considered adequate.","PeriodicalId":37372,"journal":{"name":"Hydrology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135242386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-08DOI: 10.3390/hydrology10110207
Abel Andrés Ramírez Molina, Nejc Bezak, Glenn Tootle, Chen Wang, Jiaqi Gong
The Sava River Basin (SRB) includes six countries (Slovenia, Croatia, Bosnia and Herzegovina, Serbia, Albania, and Montenegro), with the Sava River (SR) being a major tributary of the Danube River. The SR originates in the mountains (European Alps) of Slovenia and, because of a recent Slovenian government initiative to increase clean, sustainable energy, multiple hydropower facilities have been constructed within the past ~20 years. Given the importance of this river system for varying demands, including hydropower (energy production), information about past (paleo) dry (drought) and wet (pluvial) periods would provide important information to water managers and planners. Recent research applying traditional regression techniques and methods developed skillful reconstructions of seasonal (April–May–June–July–August–September or AMJJAS) streamflow using tree-ring-based proxies. The current research intends to expand upon these recent research efforts and investigate developing reconstructions of seasonal (AMJJAS) precipitation applying novel Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) techniques. When comparing the reconstructed AMJJAS precipitation datasets, the AI/ML/DL techniques statistically outperformed traditional regression techniques. When comparing the SRB AMJJAS precipitation reconstruction developed in this research to the SRB AMJJAS streamflow reconstruction developed in previous research, the temporal variability of the two reconstructions compared favorably. However, pluvial magnitudes of extreme periods differed, while drought magnitudes of extreme periods were similar, confirming drought is likely better captured in tree-ring-based proxy reconstructions of hydrologic variables.
{"title":"Machine-Learning-Based Precipitation Reconstructions: A Study on Slovenia’s Sava River Basin","authors":"Abel Andrés Ramírez Molina, Nejc Bezak, Glenn Tootle, Chen Wang, Jiaqi Gong","doi":"10.3390/hydrology10110207","DOIUrl":"https://doi.org/10.3390/hydrology10110207","url":null,"abstract":"The Sava River Basin (SRB) includes six countries (Slovenia, Croatia, Bosnia and Herzegovina, Serbia, Albania, and Montenegro), with the Sava River (SR) being a major tributary of the Danube River. The SR originates in the mountains (European Alps) of Slovenia and, because of a recent Slovenian government initiative to increase clean, sustainable energy, multiple hydropower facilities have been constructed within the past ~20 years. Given the importance of this river system for varying demands, including hydropower (energy production), information about past (paleo) dry (drought) and wet (pluvial) periods would provide important information to water managers and planners. Recent research applying traditional regression techniques and methods developed skillful reconstructions of seasonal (April–May–June–July–August–September or AMJJAS) streamflow using tree-ring-based proxies. The current research intends to expand upon these recent research efforts and investigate developing reconstructions of seasonal (AMJJAS) precipitation applying novel Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) techniques. When comparing the reconstructed AMJJAS precipitation datasets, the AI/ML/DL techniques statistically outperformed traditional regression techniques. When comparing the SRB AMJJAS precipitation reconstruction developed in this research to the SRB AMJJAS streamflow reconstruction developed in previous research, the temporal variability of the two reconstructions compared favorably. However, pluvial magnitudes of extreme periods differed, while drought magnitudes of extreme periods were similar, confirming drought is likely better captured in tree-ring-based proxy reconstructions of hydrologic variables.","PeriodicalId":37372,"journal":{"name":"Hydrology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135391882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-08DOI: 10.3390/hydrology10110208
Gabriela Emiliana de Melo e Costa, Frederico Carlos M. de Menezes Filho, Fausto A. Canales, Maria Clara Fava, Abderraman R. Amorim Brandão, Rafael Pedrollo de Paes
Stochastic modeling to forecast hydrological variables under changing climatic conditions is essential for water resource management and adaptation planning. This study explores the applicability of stochastic models, specifically SARIMA and SARIMAX, to forecast monthly average river discharge in a sub-basin of the Paranaíba River near Patos de Minas, MG, Brazil. The Paranaíba River is a vital water source for the Alto Paranaíba region, serving industrial supply, drinking water effluent dilution for urban communities, agriculture, fishing, and tourism. The study evaluates the performance of SARIMA and SARIMAX models in long-term discharge modeling and forecasting, demonstrating the SARIMAX model’s superior performance in various metrics, including the Nash–Sutcliffe coefficient (NSE), the root mean square error (RMSE), and the mean absolute percentage error (MAPE). The inclusion of precipitation as a regressor variable considerably improves the forecasting accuracy, and can be attributed to the multivariate structure of the SARIMAX model. While stochastic models like SARIMAX offer valuable decision-making tools for water resource management, the study underscores the significance of employing long-term time series encompassing flood and drought periods and including model uncertainty analysis to enhance the robustness of forecasts. In this study, the SARIMAX model provides a better fit for extreme values, overestimating peaks by around 11.6% and troughs by about 5.0%, compared with the SARIMA model, which tends to underestimate peaks by an average of 6.5% and overestimate troughs by approximately 76.0%. The findings contribute to the literature on water management strategies and mitigating risks associated with extreme hydrological events.
{"title":"Assessment of Time Series Models for Mean Discharge Modeling and Forecasting in a Sub-Basin of the Paranaíba River, Brazil","authors":"Gabriela Emiliana de Melo e Costa, Frederico Carlos M. de Menezes Filho, Fausto A. Canales, Maria Clara Fava, Abderraman R. Amorim Brandão, Rafael Pedrollo de Paes","doi":"10.3390/hydrology10110208","DOIUrl":"https://doi.org/10.3390/hydrology10110208","url":null,"abstract":"Stochastic modeling to forecast hydrological variables under changing climatic conditions is essential for water resource management and adaptation planning. This study explores the applicability of stochastic models, specifically SARIMA and SARIMAX, to forecast monthly average river discharge in a sub-basin of the Paranaíba River near Patos de Minas, MG, Brazil. The Paranaíba River is a vital water source for the Alto Paranaíba region, serving industrial supply, drinking water effluent dilution for urban communities, agriculture, fishing, and tourism. The study evaluates the performance of SARIMA and SARIMAX models in long-term discharge modeling and forecasting, demonstrating the SARIMAX model’s superior performance in various metrics, including the Nash–Sutcliffe coefficient (NSE), the root mean square error (RMSE), and the mean absolute percentage error (MAPE). The inclusion of precipitation as a regressor variable considerably improves the forecasting accuracy, and can be attributed to the multivariate structure of the SARIMAX model. While stochastic models like SARIMAX offer valuable decision-making tools for water resource management, the study underscores the significance of employing long-term time series encompassing flood and drought periods and including model uncertainty analysis to enhance the robustness of forecasts. In this study, the SARIMAX model provides a better fit for extreme values, overestimating peaks by around 11.6% and troughs by about 5.0%, compared with the SARIMA model, which tends to underestimate peaks by an average of 6.5% and overestimate troughs by approximately 76.0%. The findings contribute to the literature on water management strategies and mitigating risks associated with extreme hydrological events.","PeriodicalId":37372,"journal":{"name":"Hydrology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135391875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analysis of Electrical Resistivity Survey Data for Aquifer Potential and Protective Capacity at Mararaba Dan-Daudu Minna, North Central Nigeria","authors":"Alfa Idris Alhaji, Salako Kazeem Adeyinka, Rafiu Abdulwaheed Adewuyi, Udensi Emmanuel Emeka, Adetona Abbas Adebayo, Jamilu Shehu","doi":"10.11648/j.hyd.20231104.12","DOIUrl":"https://doi.org/10.11648/j.hyd.20231104.12","url":null,"abstract":"","PeriodicalId":37372,"journal":{"name":"Hydrology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139312032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-25DOI: 10.3390/hydrology10110205
Jennifer H. Weeks, Syeda Nadra Ahmed, Joseph D. Daron, Benjamin J. Harrison, Peter Hogarth, Tariq Ibrahim, Asif Inam, Arshi Khan, Faisal Ahmed Khan, Tariq Masood Ali Khan, Ghulam Rasul, Nadia Rehman, Akhlaque A. Qureshi, Sardar Sarfaraz
Pakistan is vulnerable to a range of climate hazards, including sea-level rise. The Indus Delta region, situated in the coastal Sindh province, is particularly at risk of sea-level rise due to low-lying land and fragile ecosystems. In this article, expertise is drawn together from the newly established Pakistan Sea-Level Working Group, consisting of policy experts, scientists, and practitioners, to provide recommendations for future research, investment, and coastal risk management. An assessment of the current scientific understanding of sea-level change and coastal climate risks in Pakistan highlights an urgent need to improve the availability and access to sea-level data and other coastal measurements. In addition, reflecting on the policy environment and the enablers needed to facilitate effective responses to future sea-level change, recommendations are made to integrate coastal climate services into the National Adaptation Plan and develop a National Framework for Climate Services. Such a framework, alongside collaboration, co-production, and capacity development, could help support required improvements in coastal observations and monitoring and continuously deliver useful, usable, and accessible sea-level information for use by practitioners and decision-makers.
{"title":"Sea-Level Rise in Pakistan: Recommendations for Strengthening Evidence-Based Coastal Decision-Making","authors":"Jennifer H. Weeks, Syeda Nadra Ahmed, Joseph D. Daron, Benjamin J. Harrison, Peter Hogarth, Tariq Ibrahim, Asif Inam, Arshi Khan, Faisal Ahmed Khan, Tariq Masood Ali Khan, Ghulam Rasul, Nadia Rehman, Akhlaque A. Qureshi, Sardar Sarfaraz","doi":"10.3390/hydrology10110205","DOIUrl":"https://doi.org/10.3390/hydrology10110205","url":null,"abstract":"Pakistan is vulnerable to a range of climate hazards, including sea-level rise. The Indus Delta region, situated in the coastal Sindh province, is particularly at risk of sea-level rise due to low-lying land and fragile ecosystems. In this article, expertise is drawn together from the newly established Pakistan Sea-Level Working Group, consisting of policy experts, scientists, and practitioners, to provide recommendations for future research, investment, and coastal risk management. An assessment of the current scientific understanding of sea-level change and coastal climate risks in Pakistan highlights an urgent need to improve the availability and access to sea-level data and other coastal measurements. In addition, reflecting on the policy environment and the enablers needed to facilitate effective responses to future sea-level change, recommendations are made to integrate coastal climate services into the National Adaptation Plan and develop a National Framework for Climate Services. Such a framework, alongside collaboration, co-production, and capacity development, could help support required improvements in coastal observations and monitoring and continuously deliver useful, usable, and accessible sea-level information for use by practitioners and decision-makers.","PeriodicalId":37372,"journal":{"name":"Hydrology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135112645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-25DOI: 10.3390/hydrology10110206
Matthew W. Becker, Francine M. Cason, Benjamin Hagedorn
Groundwater discharge from high tropical islands can have a significant influence on the biochemistry of reef ecosystems. Recent studies have suggested that a portion of groundwater may underflow the reefs to be discharged, either through the reef flat or toward the periphery of the reef system. Understanding of this potential discharge process is limited by the characterization of subsurface reef structures in these environments. A geophysical method was used in this study to profile the reef surrounding the high volcanic island of Mo’orea, French Polynesia. Boat-towed continuous resistivity profiling (CRP) revealed electrically resistive features at about 10–15 m depth, ranging in width from 30 to 200 m. These features were repeatable in duplicate survey lines, but resolution was limited by current-channeling through the seawater column. Anomalous resistivity could represent the occurrence of freshened porewater confined within the reef, but a change in porosity due to secondary cementation cannot be ruled out. Groundwater-freshened reef porewater has been observed near-shore on Mo’orea and suggested elsewhere using similar geophysical surveys, but synthetic models conducted as part of this study demonstrate that CRP alone is insufficient to draw these conclusions. These CRP surveys suggest reefs surrounding high islands may harbor pathways for terrestrial groundwater flow, but invasive sampling is required to demonstrate the role of groundwater in terrestrial runoff.
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