Pub Date : 2024-01-08DOI: 10.3389/frwa.2023.1220146
H. Wainwright, B. Dafflon, E. Siirila‐Woodburn, Nicola Falco, Yuxin Wu, Ian Breckheimer, Rosemary W. H. Carroll
In this study, we develop a machine-learning (ML)-enabled strategy for selecting hillslope-scale ecohydrological monitoring sites within snow-dominated mountainous watersheds, with a particular focus on snow-soil–plant interactions. Data layers rely on spatial data layers from both remote sensing and hydrological model simulations. Specifically, a Landsat-based foresummer drought sensitivity index is used to define the dependency of the annual peak plant productivity on the Palmer drought severity index in the early growing season. Hydrological simulations provide the spatiotemporal dynamics of near-surface soil moisture and snow depth. In this framework, a regression analysis identifies the key hydrological variables relevant to the spatial heterogeneity of drought sensitivity. We then apply unsupervised clustering to these key variables, using the Gaussian mixture model, to group hillslopes into several zones that have divergent relationships regarding soil moisture, snow dynamics, and drought sensitivity. Using the datasets collected in the East River Watershed (Crested Butte, Colorado, United States), results show that drought sensitivity is significantly correlated with model-derived soil moisture and snow-free timing over space and time. The relationship is, however, non-linear, such that the correlation decreases above a threshold elevation and in a heavy snow year due to large snowpacks, lateral flow, and soil storage limitations. Clustering is then able to define the zones that have high or low sensitivity to drought, as well as the mid-elevation regions where sensitivity is associated with the topographic aspect and net potential radiation. In addition, the algorithm identifies the most representative hillslopes with road/trail access within each zone for installing monitoring sites. Our method also aims to significantly increase the use of ML and model-simulation results to guide critical zone and watershed monitoring activities.
{"title":"Model and remote-sensing-guided experimental design and hypothesis generation for monitoring snow-soil–plant interactions","authors":"H. Wainwright, B. Dafflon, E. Siirila‐Woodburn, Nicola Falco, Yuxin Wu, Ian Breckheimer, Rosemary W. H. Carroll","doi":"10.3389/frwa.2023.1220146","DOIUrl":"https://doi.org/10.3389/frwa.2023.1220146","url":null,"abstract":"In this study, we develop a machine-learning (ML)-enabled strategy for selecting hillslope-scale ecohydrological monitoring sites within snow-dominated mountainous watersheds, with a particular focus on snow-soil–plant interactions. Data layers rely on spatial data layers from both remote sensing and hydrological model simulations. Specifically, a Landsat-based foresummer drought sensitivity index is used to define the dependency of the annual peak plant productivity on the Palmer drought severity index in the early growing season. Hydrological simulations provide the spatiotemporal dynamics of near-surface soil moisture and snow depth. In this framework, a regression analysis identifies the key hydrological variables relevant to the spatial heterogeneity of drought sensitivity. We then apply unsupervised clustering to these key variables, using the Gaussian mixture model, to group hillslopes into several zones that have divergent relationships regarding soil moisture, snow dynamics, and drought sensitivity. Using the datasets collected in the East River Watershed (Crested Butte, Colorado, United States), results show that drought sensitivity is significantly correlated with model-derived soil moisture and snow-free timing over space and time. The relationship is, however, non-linear, such that the correlation decreases above a threshold elevation and in a heavy snow year due to large snowpacks, lateral flow, and soil storage limitations. Clustering is then able to define the zones that have high or low sensitivity to drought, as well as the mid-elevation regions where sensitivity is associated with the topographic aspect and net potential radiation. In addition, the algorithm identifies the most representative hillslopes with road/trail access within each zone for installing monitoring sites. Our method also aims to significantly increase the use of ML and model-simulation results to guide critical zone and watershed monitoring activities.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139447413","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 : 2024-01-08DOI: 10.3389/frwa.2023.1321137
David R. Piatka, Raphaela L. Nánási, R. Mwanake, Florian Engelsberger, Georg Willibald, Frank Neidl, Ralf Kiese
Stream ecosystems are actively involved in the biogeochemical cycling of carbon (C) and nitrogen (N) from terrestrial and aquatic sources. Streams hydrologically connected to peatland soils are suggested to receive significant quantities of particulate, dissolved, and gaseous C and N species, which directly enhance losses of greenhouse gases (GHGs), i.e., carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), and fuel in-stream GHG production. However, riverine GHG concentrations and emissions are highly dynamic due to temporally and spatially variable hydrological, meteorological, and biogeochemical conditions. In this study, we present a complete GHG monitoring system in a peatland stream, which can continuously measure dissolved GHG concentrations and allows to infer gaseous fluxes between the stream and the atmosphere and discuss the results from March 31 to August 25 at variable hydrological conditions during a cool spring and warm summer period. Stream water was continuously pumped into a water-air equilibration chamber, with the equilibrated and actively dried gas phase being measured with two GHG analyzers for CO2 and N2O and CH4 based on Off-Axis Integrated Cavity Output Spectroscopy (OA-ICOS) and Non-Dispersive Infra-Red (NDIR) spectroscopy, respectively. GHG measurements were performed continuously with only shorter measurement interruptions, mostly following a regular maintenance program. The results showed strong dynamics of GHGs with hourly mean concentrations up to 9959.1, 1478.6, and 9.9 parts per million (ppm) and emissions up to 313.89, 1.17, and 0.40 mg C or N m−2h−1 for CO2, CH4, and N2O, respectively. Significantly higher GHG concentrations and emissions were observed shortly after intense precipitation events at increasing stream water levels, contributing 59% to the total GHG budget of 762.2 g m−2 CO2-equivalents (CO2-eq). The GHG data indicated a constantly strong terrestrial signal from peatland pore waters, with high concentrations of dissolved GHGs being flushed into the stream water after precipitation. During drier periods, CO2 and CH4 dynamics were strongly influenced by in-stream metabolism. Continuous and high-frequency GHG data are needed to assess short- and long-term dynamics in stream ecosystems and for improved source partitioning between in-situ and ex-situ production.
{"title":"Precipitation fuels dissolved greenhouse gas (CO2, CH4, N2O) dynamics in a peatland-dominated headwater stream: results from a continuous monitoring setup","authors":"David R. Piatka, Raphaela L. Nánási, R. Mwanake, Florian Engelsberger, Georg Willibald, Frank Neidl, Ralf Kiese","doi":"10.3389/frwa.2023.1321137","DOIUrl":"https://doi.org/10.3389/frwa.2023.1321137","url":null,"abstract":"Stream ecosystems are actively involved in the biogeochemical cycling of carbon (C) and nitrogen (N) from terrestrial and aquatic sources. Streams hydrologically connected to peatland soils are suggested to receive significant quantities of particulate, dissolved, and gaseous C and N species, which directly enhance losses of greenhouse gases (GHGs), i.e., carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), and fuel in-stream GHG production. However, riverine GHG concentrations and emissions are highly dynamic due to temporally and spatially variable hydrological, meteorological, and biogeochemical conditions. In this study, we present a complete GHG monitoring system in a peatland stream, which can continuously measure dissolved GHG concentrations and allows to infer gaseous fluxes between the stream and the atmosphere and discuss the results from March 31 to August 25 at variable hydrological conditions during a cool spring and warm summer period. Stream water was continuously pumped into a water-air equilibration chamber, with the equilibrated and actively dried gas phase being measured with two GHG analyzers for CO2 and N2O and CH4 based on Off-Axis Integrated Cavity Output Spectroscopy (OA-ICOS) and Non-Dispersive Infra-Red (NDIR) spectroscopy, respectively. GHG measurements were performed continuously with only shorter measurement interruptions, mostly following a regular maintenance program. The results showed strong dynamics of GHGs with hourly mean concentrations up to 9959.1, 1478.6, and 9.9 parts per million (ppm) and emissions up to 313.89, 1.17, and 0.40 mg C or N m−2h−1 for CO2, CH4, and N2O, respectively. Significantly higher GHG concentrations and emissions were observed shortly after intense precipitation events at increasing stream water levels, contributing 59% to the total GHG budget of 762.2 g m−2 CO2-equivalents (CO2-eq). The GHG data indicated a constantly strong terrestrial signal from peatland pore waters, with high concentrations of dissolved GHGs being flushed into the stream water after precipitation. During drier periods, CO2 and CH4 dynamics were strongly influenced by in-stream metabolism. Continuous and high-frequency GHG data are needed to assess short- and long-term dynamics in stream ecosystems and for improved source partitioning between in-situ and ex-situ production.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139447727","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 : 2024-01-08DOI: 10.3389/frwa.2023.1306481
N. Tull, A. Moodie, Paola Passalacqua
The morphology of river levees and floodplains is an important control on river-floodplain connectivity within a river system under sub-bankfull conditions, and this morphology changes as a river approaches the coast due to backwater influence. Floodplain width can also vary along a river, and floodplain constrictions in the form of bluffs adjacent to the river can influence inundation extent. However, the relative controls of backwater-influenced floodplain topography and bluff topography on river-floodplain connectivity have not been studied. We measure discharge along the lower Trinity River (Texas, USA) during high flow to determine which floodplain features are associated with major river-floodplain flow exchanges. We develop a numerical model representing the transition to backwater-dominated river hydraulics, and quantify downstream changes in levee channelization, inundation, and fluxes along the river-floodplain boundary. We model passive particle transport through the floodplain, and compute residence times as a function of location where particles enter the floodplain. We find that bluff topography controls flow from the floodplain back to the river, whereas levee topography facilitates flow to the floodplain through floodplain channels. Return flow to the river is limited to locations just upstream of bluffs, even under receding flood conditions, whereas outflow locations are numerous and occur all along the river. Residence times for particles entering the floodplain far upstream of bluffs are as much as two orders of magnitude longer than those for particles entering short distances upstream of bluffs. This study can benefit floodplain ecosystem management and restoration plans by informing on the key locations of lateral exchange and variable residence time distributions in river-floodplain systems.
{"title":"River-floodplain connectivity and residence times controlled by topographic bluffs along a backwater transition","authors":"N. Tull, A. Moodie, Paola Passalacqua","doi":"10.3389/frwa.2023.1306481","DOIUrl":"https://doi.org/10.3389/frwa.2023.1306481","url":null,"abstract":"The morphology of river levees and floodplains is an important control on river-floodplain connectivity within a river system under sub-bankfull conditions, and this morphology changes as a river approaches the coast due to backwater influence. Floodplain width can also vary along a river, and floodplain constrictions in the form of bluffs adjacent to the river can influence inundation extent. However, the relative controls of backwater-influenced floodplain topography and bluff topography on river-floodplain connectivity have not been studied. We measure discharge along the lower Trinity River (Texas, USA) during high flow to determine which floodplain features are associated with major river-floodplain flow exchanges. We develop a numerical model representing the transition to backwater-dominated river hydraulics, and quantify downstream changes in levee channelization, inundation, and fluxes along the river-floodplain boundary. We model passive particle transport through the floodplain, and compute residence times as a function of location where particles enter the floodplain. We find that bluff topography controls flow from the floodplain back to the river, whereas levee topography facilitates flow to the floodplain through floodplain channels. Return flow to the river is limited to locations just upstream of bluffs, even under receding flood conditions, whereas outflow locations are numerous and occur all along the river. Residence times for particles entering the floodplain far upstream of bluffs are as much as two orders of magnitude longer than those for particles entering short distances upstream of bluffs. This study can benefit floodplain ecosystem management and restoration plans by informing on the key locations of lateral exchange and variable residence time distributions in river-floodplain systems.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139444970","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 : 2024-01-08DOI: 10.3389/frwa.2023.1323139
Vikram Kumar, Sumit Sen
Accurate measurement of continuous stream discharge poses both excitement and challenges for hydrologists and water resource planners, particularly in mountainous watersheds. This study centers on the development of rating curves utilizing the power law at three headwaters of the lesser Himalayas—Aglar, Paligaad, and Balganga—through the installation of water level recorders for stage measurement and salt dilution for discharge measurement from 2014 to 2016. The stream stage–discharge relationship, crucially known as the rating curve, is susceptible to numerous factors in mountainous watersheds that are often challenging to comprehend or quantify. Despite significant errors introduced during the rating curve development, such as stemming from observations, modeling, and parameterization, they are frequently overlooked. In this study, acknowledging the inherent uncertainty, we employ the maximum-likelihood method to assess uncertainty in the developed rating curve. Our findings reveal substantial inconsistency in the stage–discharge relationship, particularly during high flows. A novel contribution of this study is introducing a weighing factor concept that correlates uncertainty with the morphological parameters of the watershed. The higher value of the weighting factor in Paligaad (0.37) as compared to Balganga (0.35) and less in the case of Aglar (0.27) will have more uncertainty. The authors contend that precise rating curves and comprehensive uncertainty analyses can mitigate construction costs, foster robust decision-making, and enhance the perceived credibility of decisions in hydrology and water resource management.
{"title":"Rating curve development and uncertainty analysis in mountainous watersheds for informed hydrology and resource management","authors":"Vikram Kumar, Sumit Sen","doi":"10.3389/frwa.2023.1323139","DOIUrl":"https://doi.org/10.3389/frwa.2023.1323139","url":null,"abstract":"Accurate measurement of continuous stream discharge poses both excitement and challenges for hydrologists and water resource planners, particularly in mountainous watersheds. This study centers on the development of rating curves utilizing the power law at three headwaters of the lesser Himalayas—Aglar, Paligaad, and Balganga—through the installation of water level recorders for stage measurement and salt dilution for discharge measurement from 2014 to 2016. The stream stage–discharge relationship, crucially known as the rating curve, is susceptible to numerous factors in mountainous watersheds that are often challenging to comprehend or quantify. Despite significant errors introduced during the rating curve development, such as stemming from observations, modeling, and parameterization, they are frequently overlooked. In this study, acknowledging the inherent uncertainty, we employ the maximum-likelihood method to assess uncertainty in the developed rating curve. Our findings reveal substantial inconsistency in the stage–discharge relationship, particularly during high flows. A novel contribution of this study is introducing a weighing factor concept that correlates uncertainty with the morphological parameters of the watershed. The higher value of the weighting factor in Paligaad (0.37) as compared to Balganga (0.35) and less in the case of Aglar (0.27) will have more uncertainty. The authors contend that precise rating curves and comprehensive uncertainty analyses can mitigate construction costs, foster robust decision-making, and enhance the perceived credibility of decisions in hydrology and water resource management.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139446550","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 : 2024-01-08DOI: 10.3389/frwa.2023.1278336
Ping Song, Yiwei Li, Huiru Chen, Likai Li, Haibo Xia, Yeyuan Xiao, Bingjie Fang, Yue Guo, Zhongrui Bai, Lu Ma, Jiawen Wang, Lei Yang, Yanxia Le
The domestic sewage in rural areas of South China is characterized by a relatively low concentration of organic pollutants; however, the factors causing this have not been carefully examined. This study conducted a comprehensive survey on two sewer networks in a small town of Eastern Guangdong, China, via grab water sampling at a frequency of once every 2 weeks lasting for 1 year. The sewage quality showed significant variations across the systems, while a gradual decrease in the concentrations of chemical oxygen demand (COD), total nitrogen (TN) and phosphorus (TP) from the upper to lower reaches of sewers could be observed. Storm events could have a flushing effect on TP in the upper reach of sewers, but a dilution effect on COD and TN in flat terrains. The diurnal pattern of sewage was largely impacted by the position of the manholes and water consumption difference between holidays and normal days. Both COD/TN and TN/TP ratios of the sewage showed a lognormal distribution dominating in the range of 2.0–3.0 and ~10.0, respectively. The low ratio of COD/TN in the morning discharge peak could be attributed to the wide use of septic tanks in the area, while groundwater infiltration played more important roles in the basal flow conditions. This study could serve as a basic reference for designing and managing sewage infrastructure in rural areas of South China and highlights that prevention of groundwater infiltration is crucial to improve the efficiency of sewage infrastructure in high water table areas.
{"title":"Characterization of sewage quality and its spatiotemporal variations in a small town in Eastern Guangdong, China","authors":"Ping Song, Yiwei Li, Huiru Chen, Likai Li, Haibo Xia, Yeyuan Xiao, Bingjie Fang, Yue Guo, Zhongrui Bai, Lu Ma, Jiawen Wang, Lei Yang, Yanxia Le","doi":"10.3389/frwa.2023.1278336","DOIUrl":"https://doi.org/10.3389/frwa.2023.1278336","url":null,"abstract":"The domestic sewage in rural areas of South China is characterized by a relatively low concentration of organic pollutants; however, the factors causing this have not been carefully examined. This study conducted a comprehensive survey on two sewer networks in a small town of Eastern Guangdong, China, via grab water sampling at a frequency of once every 2 weeks lasting for 1 year. The sewage quality showed significant variations across the systems, while a gradual decrease in the concentrations of chemical oxygen demand (COD), total nitrogen (TN) and phosphorus (TP) from the upper to lower reaches of sewers could be observed. Storm events could have a flushing effect on TP in the upper reach of sewers, but a dilution effect on COD and TN in flat terrains. The diurnal pattern of sewage was largely impacted by the position of the manholes and water consumption difference between holidays and normal days. Both COD/TN and TN/TP ratios of the sewage showed a lognormal distribution dominating in the range of 2.0–3.0 and ~10.0, respectively. The low ratio of COD/TN in the morning discharge peak could be attributed to the wide use of septic tanks in the area, while groundwater infiltration played more important roles in the basal flow conditions. This study could serve as a basic reference for designing and managing sewage infrastructure in rural areas of South China and highlights that prevention of groundwater infiltration is crucial to improve the efficiency of sewage infrastructure in high water table areas.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139446611","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 : 2023-12-21DOI: 10.3389/frwa.2023.1287357
M. G. Eltarabily, Hany Abd-elhamid, Martina Zeleňáková, Mohamed Kamel Elshaarawy, Mohamed Elkiki, Tarek Selim
Efficient water resource management in irrigation systems relies on the accurate estimation of seepage loss from lined canals. This study utilized machine learning (ML) algorithms to tackle this challenge in seepage loss prediction.Firstly, seepage flow through irrigation canals was modeled numerically and experimentally using Slide2 and physical models, respectively. Then, the Slide2 model results were compared to the experimental tests. Thus, the model was used to conduct 600 simulation scenarios. A parametric analysis was performed to investigate the effect of canal geometry and liner properties on seepage loss. Based on the conducted scenarios, ML models were developed and evaluated to determine the best predictive model. The ML models included non-ensemble (regression-based, evolutionary, neural network) and ensemble models. Non-ensemble models (adaptive boosting, random forest, gradient boosting). There were four input ratios in these models: bed width to water depth, side slope, liner to soil hydraulic conductivity, and liner thickness to water depth. The output variable was the seepage loss ratio. Seven performance indices and k-fold cross-validation were employed to evaluate reliability and accuracy. Moreover, a sensitivity analysis was conducted to investigate the significance of each input in predicting seepage loss.The findings revealed that the Artificial Neural Network (ANN) model was the most dependable predictor, achieving the highest determination-coefficient (R2) value of 0.997 and root-mean-square-error (RMSE) of 0.201. The eXtreme Gradient Boosting (XGBoost) followed the ANN model closely, which achieved an R2 of 0.996 and RMSE of 0.246. Sensitivity analysis showed that liner hydraulic conductivity is the most significant parameter, contributing 62% predictive importance, while the side slope has the lowest significance. In conclusion, this study presented efficient and cost-effective models for predicting seepage loss, eliminating the need for resource-intensive experimental or field investigations.
灌溉系统中有效的水资源管理有赖于对衬砌渠道渗漏损失的准确估算。本研究利用机器学习（ML）算法来解决渗流损失预测中的这一难题。首先，使用 Slide2 和物理模型分别对灌溉渠道中的渗流进行了数值建模和实验建模。然后，将 Slide2 模型结果与实验测试结果进行比较。因此，该模型被用于进行 600 个模拟场景。通过参数分析，研究了运河几何形状和衬垫特性对渗流损失的影响。根据模拟场景，开发并评估了 ML 模型，以确定最佳预测模型。ML 模型包括非集合模型（基于回归的模型、进化模型、神经网络模型）和集合模型。非集合模型（自适应提升、随机森林、梯度提升）。这些模型有四个输入比率：床宽与水深的比率、边坡、衬垫与土壤的导水率以及衬垫厚度与水深的比率。输出变量是渗流损失率。采用了七个性能指标和 k 倍交叉验证来评估可靠性和准确性。研究结果表明，人工神经网络（ANN）模型是最可靠的预测模型，其确定系数（R2）值为 0.997，均方根误差（RMSE）为 0.201。最高梯度提升（XGBoost）紧随 ANN 模型之后，R2 值为 0.996，均方根误差为 0.246。敏感性分析表明，衬垫水导率是最重要的参数，其预测重要性占 62%，而边坡的重要性最低。总之，本研究提出了高效且经济的渗流损失预测模型，无需进行资源密集型实验或实地调查。
{"title":"Predicting seepage losses from lined irrigation canals using machine learning models","authors":"M. G. Eltarabily, Hany Abd-elhamid, Martina Zeleňáková, Mohamed Kamel Elshaarawy, Mohamed Elkiki, Tarek Selim","doi":"10.3389/frwa.2023.1287357","DOIUrl":"https://doi.org/10.3389/frwa.2023.1287357","url":null,"abstract":"Efficient water resource management in irrigation systems relies on the accurate estimation of seepage loss from lined canals. This study utilized machine learning (ML) algorithms to tackle this challenge in seepage loss prediction.Firstly, seepage flow through irrigation canals was modeled numerically and experimentally using Slide2 and physical models, respectively. Then, the Slide2 model results were compared to the experimental tests. Thus, the model was used to conduct 600 simulation scenarios. A parametric analysis was performed to investigate the effect of canal geometry and liner properties on seepage loss. Based on the conducted scenarios, ML models were developed and evaluated to determine the best predictive model. The ML models included non-ensemble (regression-based, evolutionary, neural network) and ensemble models. Non-ensemble models (adaptive boosting, random forest, gradient boosting). There were four input ratios in these models: bed width to water depth, side slope, liner to soil hydraulic conductivity, and liner thickness to water depth. The output variable was the seepage loss ratio. Seven performance indices and k-fold cross-validation were employed to evaluate reliability and accuracy. Moreover, a sensitivity analysis was conducted to investigate the significance of each input in predicting seepage loss.The findings revealed that the Artificial Neural Network (ANN) model was the most dependable predictor, achieving the highest determination-coefficient (R2) value of 0.997 and root-mean-square-error (RMSE) of 0.201. The eXtreme Gradient Boosting (XGBoost) followed the ANN model closely, which achieved an R2 of 0.996 and RMSE of 0.246. Sensitivity analysis showed that liner hydraulic conductivity is the most significant parameter, contributing 62% predictive importance, while the side slope has the lowest significance. In conclusion, this study presented efficient and cost-effective models for predicting seepage loss, eliminating the need for resource-intensive experimental or field investigations.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138949528","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 : 2023-12-21DOI: 10.3389/frwa.2023.1295286
Luiz Felipe Rezende, Lincoln Alves, Alexandre Augusto Barbosa, A. Sales, G. Pedra, Rômulo Simões Cézar Menezes, Gustavo Felipe Arcoverde, Jean Pierre Ometto
A discussion that has occurred in the scientific community is that despite the increase in the frequency of droughts, the semi-arid world may be increasing the density of vegetation due to fertilization by the increase in atmospheric CO2, a phenomenon called “greening.” Through this study, we sought to evaluate and discuss whether this “greening” would also be occurring in the Brazilian semiarid and what would be its contribution or counterpoint about droughts. Another topic covered was Water Use Efficiency (WUE), about its contribution to mitigating droughts. We chose eight study areas in which the native vegetation was preserved for periods of around 20 years or more. We used data from the Leaf Area Index (LAI), Gross Primary Productivity (GPP), precipitation, evaporation, transpiration, and soil moisture. We divided into two distinct periods to calculate the means of these variables. We applied the Standardized Precipitation Index (SPI) to identify the frequency of droughts for the period from 1961 to 2020. It was observed that between 2001 and 2020, there was an increase in the relative frequency of extreme and exceptional droughts around 19 and 11%, respectively. Our results showed evidence of “greening” for only two sites that were less impacted by droughts, and it seems that the CO2 fertilizer effect could not compensate for the scarcity of water in the other locations of our study. However, WUE was present in almost all sites, which may be a factor in mitigating the impacts of the high frequency of droughts.
{"title":"Greening and Water Use Efficiency during a period of high frequency of droughts in the Brazilian semi-arid","authors":"Luiz Felipe Rezende, Lincoln Alves, Alexandre Augusto Barbosa, A. Sales, G. Pedra, Rômulo Simões Cézar Menezes, Gustavo Felipe Arcoverde, Jean Pierre Ometto","doi":"10.3389/frwa.2023.1295286","DOIUrl":"https://doi.org/10.3389/frwa.2023.1295286","url":null,"abstract":"A discussion that has occurred in the scientific community is that despite the increase in the frequency of droughts, the semi-arid world may be increasing the density of vegetation due to fertilization by the increase in atmospheric CO2, a phenomenon called “greening.” Through this study, we sought to evaluate and discuss whether this “greening” would also be occurring in the Brazilian semiarid and what would be its contribution or counterpoint about droughts. Another topic covered was Water Use Efficiency (WUE), about its contribution to mitigating droughts. We chose eight study areas in which the native vegetation was preserved for periods of around 20 years or more. We used data from the Leaf Area Index (LAI), Gross Primary Productivity (GPP), precipitation, evaporation, transpiration, and soil moisture. We divided into two distinct periods to calculate the means of these variables. We applied the Standardized Precipitation Index (SPI) to identify the frequency of droughts for the period from 1961 to 2020. It was observed that between 2001 and 2020, there was an increase in the relative frequency of extreme and exceptional droughts around 19 and 11%, respectively. Our results showed evidence of “greening” for only two sites that were less impacted by droughts, and it seems that the CO2 fertilizer effect could not compensate for the scarcity of water in the other locations of our study. However, WUE was present in almost all sites, which may be a factor in mitigating the impacts of the high frequency of droughts.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138951758","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}
Following the final biological treatment, the oil wastewater is intended for reuse in factory floor cleaning. However, the presence of varying concentrations of oil-in-iron characteristic wastewater has led to a sudden surge in sludge SV to 90%, adversely affecting water treatment efficiency. In this study, we conducted an analysis of microbial community structure and selected pepA and 16S rRNA primers to assess the proportions of zoogloea and total bacteria in sludge bulking. Iron concentration plays a pivotal role, and it should be maintained at or 0.6 mgL−1. By selective discharging of sludge to maintain 1,700 mgL−1, we minimized iron enrichment, thereby enhancing the sludge settling performance. Maintaining dissolved oxygen (DO) at 3.5 mgL−1 supports the aerobic sludge's ability to replenish iron in its system, while the oil content should be controlled at 145.33 mgL−1 to reduce the release of iron into the water. The order of significance is as follows: sludge concentration > Fe amount > DO > oil content. Implementing this approach was applied in the field for 1 week and effectively reduced the SV from 90% to approximately 43%. The interaction between quorum sensing molecules related to sludge bulking and iron, leading to the formation of complexes, underscores the significance of controlling iron levels. This study offers a valuable case for practical application of quorum quenching technology in oil wastewater, presenting a rapid, efficient, and cost-effective solution to address the issue of sludge bulking.
{"title":"Fe controls the reproduction of zoogloea and sludge bulking in oil-in-iron wastewater","authors":"Xinfeng Shi, Zhibin Su, Xiaoxia Tao, Xin Zhou, Jinbo Zhao, Ruiqi Wang, Jinyi Qin","doi":"10.3389/frwa.2023.1289276","DOIUrl":"https://doi.org/10.3389/frwa.2023.1289276","url":null,"abstract":"Following the final biological treatment, the oil wastewater is intended for reuse in factory floor cleaning. However, the presence of varying concentrations of oil-in-iron characteristic wastewater has led to a sudden surge in sludge SV to 90%, adversely affecting water treatment efficiency. In this study, we conducted an analysis of microbial community structure and selected pepA and 16S rRNA primers to assess the proportions of zoogloea and total bacteria in sludge bulking. Iron concentration plays a pivotal role, and it should be maintained at or 0.6 mgL−1. By selective discharging of sludge to maintain 1,700 mgL−1, we minimized iron enrichment, thereby enhancing the sludge settling performance. Maintaining dissolved oxygen (DO) at 3.5 mgL−1 supports the aerobic sludge's ability to replenish iron in its system, while the oil content should be controlled at 145.33 mgL−1 to reduce the release of iron into the water. The order of significance is as follows: sludge concentration > Fe amount > DO > oil content. Implementing this approach was applied in the field for 1 week and effectively reduced the SV from 90% to approximately 43%. The interaction between quorum sensing molecules related to sludge bulking and iron, leading to the formation of complexes, underscores the significance of controlling iron levels. This study offers a valuable case for practical application of quorum quenching technology in oil wastewater, presenting a rapid, efficient, and cost-effective solution to address the issue of sludge bulking.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138954891","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 : 2023-12-20DOI: 10.3389/frwa.2023.1243251
El Mahdi El Khalki, Y. Tramblay, M. Saidi, A. Marchane, A. Chehbouni
In data-sparse regions and in developing countries such as Morocco, where flooding has serious socio-economic impacts, satellite-based precipitation products open new possibilities for monitoring and modelling water resources and floods. The objective of the study is to explore the possibility of using satellite precipitation products (SPPs) with hydrological models (CREST and MISDc) over 9 basins in Morocco. This work provides a hydrological assessment of three SPPs that have demonstrated good capabilities in reproducing precipitation over different basins in Morocco (GPM IMERG – PERSIANN CDR (PERCDR) and CHIRPS). The two hydrological models are coupled with a stochastic calibration method to provide the different ranges of uncertainties. In addition, we investigate the ability of SPPs on reproducing the November 2014 flood event that affected a large part of Morocco. The results indicated that, in calibration, both hydrological models provided similar performance to reproduce river discharge with observed precipitation or PERSIANN CDR. In validation, the combination of the MISDc model with PERSIANN CDR performed the best, notably allowing a good simulation of the flood hydrographs during the November 2014 event. Future analysis of relationships between SPPs, basin properties, and hydrological modelling technique will allow to find the appropriate combination for different application purposes.
{"title":"Hydrological assessment of different satellite precipitation products in semi-arid basins in Morocco","authors":"El Mahdi El Khalki, Y. Tramblay, M. Saidi, A. Marchane, A. Chehbouni","doi":"10.3389/frwa.2023.1243251","DOIUrl":"https://doi.org/10.3389/frwa.2023.1243251","url":null,"abstract":"In data-sparse regions and in developing countries such as Morocco, where flooding has serious socio-economic impacts, satellite-based precipitation products open new possibilities for monitoring and modelling water resources and floods. The objective of the study is to explore the possibility of using satellite precipitation products (SPPs) with hydrological models (CREST and MISDc) over 9 basins in Morocco. This work provides a hydrological assessment of three SPPs that have demonstrated good capabilities in reproducing precipitation over different basins in Morocco (GPM IMERG – PERSIANN CDR (PERCDR) and CHIRPS). The two hydrological models are coupled with a stochastic calibration method to provide the different ranges of uncertainties. In addition, we investigate the ability of SPPs on reproducing the November 2014 flood event that affected a large part of Morocco. The results indicated that, in calibration, both hydrological models provided similar performance to reproduce river discharge with observed precipitation or PERSIANN CDR. In validation, the combination of the MISDc model with PERSIANN CDR performed the best, notably allowing a good simulation of the flood hydrographs during the November 2014 event. Future analysis of relationships between SPPs, basin properties, and hydrological modelling technique will allow to find the appropriate combination for different application purposes.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138954468","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 : 2023-12-20DOI: 10.3389/frwa.2023.1296344
M. Pesci, Philipp Schulte Overberg, Thomas Bosshard, Kristian Förster
Coupled glacio-hydrological models have recently become a valuable method for predicting the hydrological response of catchments in mountainous regions under a changing climate. While hydrological models focus mostly on processes of the non-glacierized part of the catchment with a relatively simple glacier representation, the latest generation of standalone (global) glacier models tend to describe glacier processes more accurately by using new global datasets and explicitly modeling ice-flow dynamics. Yet, to the authors' knowledge, existing catchment-scale coupled glacio-hydrological models either do not include these most recent advances in glacier modeling or are simply not available to other users. By making use of the capabilities of the free, distributed, physically-based Water Flow and Balance Simulation Model (WaSiM) and the Open Global Glacier Model (OGGM), a coupling scheme is developed to bridge the gap between global glacier representation and local catchment hydrology. The WaSiM-OGGM coupling scheme is used to further assess the impacts under future climates on the glaciological and hydrological processes in the Gepatschalm catchment (Austria), by considering a combination of three climate projections under the Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5. Additionally, the results are compared to the original WaSiM model with the integrated Volume-Area (VA) scaling approach for modeling glaciers. Although both models (WaSiM with VA scaling and WaSiM-OGGM coupling scheme) perform very similar during the historical simulations (1971–2010), large discrepancies arise when looking into the future (2011–2100). In terms of runoff, the VA scaling model suggests a reduction of the mean monthly peak between 10–19%, whereas a reduction of 26–41% is computed by the coupling scheme. Similarly, results suggest that glaciers will continuously retreat until 2100. By the end of the century, between 20–43% of the 2010 glacier area will remain according to the VA scaling model, but only 1–23% is expected to remain with the coupling scheme. The results from the WaSiM-OGGM coupling scheme raises awareness of including more sophisticated glacier evolution models when performing hydrological simulations at the catchment scale in the future. As the WaSiM-OGGM coupling scheme is released as open-source software, it is accessible to any interested modeler with limited or even no glacier knowledge.
{"title":"From global glacier modeling to catchment hydrology: bridging the gap with the WaSiM-OGGM coupling scheme","authors":"M. Pesci, Philipp Schulte Overberg, Thomas Bosshard, Kristian Förster","doi":"10.3389/frwa.2023.1296344","DOIUrl":"https://doi.org/10.3389/frwa.2023.1296344","url":null,"abstract":"Coupled glacio-hydrological models have recently become a valuable method for predicting the hydrological response of catchments in mountainous regions under a changing climate. While hydrological models focus mostly on processes of the non-glacierized part of the catchment with a relatively simple glacier representation, the latest generation of standalone (global) glacier models tend to describe glacier processes more accurately by using new global datasets and explicitly modeling ice-flow dynamics. Yet, to the authors' knowledge, existing catchment-scale coupled glacio-hydrological models either do not include these most recent advances in glacier modeling or are simply not available to other users. By making use of the capabilities of the free, distributed, physically-based Water Flow and Balance Simulation Model (WaSiM) and the Open Global Glacier Model (OGGM), a coupling scheme is developed to bridge the gap between global glacier representation and local catchment hydrology. The WaSiM-OGGM coupling scheme is used to further assess the impacts under future climates on the glaciological and hydrological processes in the Gepatschalm catchment (Austria), by considering a combination of three climate projections under the Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5. Additionally, the results are compared to the original WaSiM model with the integrated Volume-Area (VA) scaling approach for modeling glaciers. Although both models (WaSiM with VA scaling and WaSiM-OGGM coupling scheme) perform very similar during the historical simulations (1971–2010), large discrepancies arise when looking into the future (2011–2100). In terms of runoff, the VA scaling model suggests a reduction of the mean monthly peak between 10–19%, whereas a reduction of 26–41% is computed by the coupling scheme. Similarly, results suggest that glaciers will continuously retreat until 2100. By the end of the century, between 20–43% of the 2010 glacier area will remain according to the VA scaling model, but only 1–23% is expected to remain with the coupling scheme. The results from the WaSiM-OGGM coupling scheme raises awareness of including more sophisticated glacier evolution models when performing hydrological simulations at the catchment scale in the future. As the WaSiM-OGGM coupling scheme is released as open-source software, it is accessible to any interested modeler with limited or even no glacier knowledge.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139170929","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}
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