Pub Date : 2023-08-07DOI: 10.3389/frwa.2023.1236924
Atuey J. Martínez Durán, V. A. Rodríguez Núñez, José del C. Castillo Jáquez
The use of biosolids from wastewater treatment plants in agriculture is considered relevant for the promotion of sustainable agricultural practices, the improvement of soil fertility, and the reduction of dependence on synthetic chemical products. The Dominican Republic is today the world's largest producer of organic bananas and the main exporter of organic and fair-trade bananas to Europe. The biosolids generated in the wastewater treatment plants in the Dominican Republic currently have no use. In other countries, biosolids are used for agriculture, although biosolids have different characteristics in each place and their potential must be analyzed. In the Dominican Republic, there is no research that analyzes biosolids and their impact on agriculture. This research aims to compare the nutritional composition of bananas in plantations fertilized with different doses of biosolids and other organic fertilizers.For this test, five blocks were prepared with organic fertilization, another with potassium sulfate, and a control block. Laboratory analysis was used to determine the characteristics of the biosolids used and also to know the nutritional composition of bananas of the Williams variety.The results, when compared, show the impact that each of these fertilizers has or can have on the production of organic bananas in the Dominican Republic.The use of dose Y of the biosolid, characterized by the application of 16 kilograms of biosolid per plant, is the most recommended to fertilize the banana since the collected fruits presented the most optimal nutritional values.
{"title":"Use of biosolids from wastewater treatment plants and other organic fertilizers in agriculture—a preliminary results of a case study in banana cultivation in the Dominican Republic","authors":"Atuey J. Martínez Durán, V. A. Rodríguez Núñez, José del C. Castillo Jáquez","doi":"10.3389/frwa.2023.1236924","DOIUrl":"https://doi.org/10.3389/frwa.2023.1236924","url":null,"abstract":"The use of biosolids from wastewater treatment plants in agriculture is considered relevant for the promotion of sustainable agricultural practices, the improvement of soil fertility, and the reduction of dependence on synthetic chemical products. The Dominican Republic is today the world's largest producer of organic bananas and the main exporter of organic and fair-trade bananas to Europe. The biosolids generated in the wastewater treatment plants in the Dominican Republic currently have no use. In other countries, biosolids are used for agriculture, although biosolids have different characteristics in each place and their potential must be analyzed. In the Dominican Republic, there is no research that analyzes biosolids and their impact on agriculture. This research aims to compare the nutritional composition of bananas in plantations fertilized with different doses of biosolids and other organic fertilizers.For this test, five blocks were prepared with organic fertilization, another with potassium sulfate, and a control block. Laboratory analysis was used to determine the characteristics of the biosolids used and also to know the nutritional composition of bananas of the Williams variety.The results, when compared, show the impact that each of these fertilizers has or can have on the production of organic bananas in the Dominican Republic.The use of dose Y of the biosolid, characterized by the application of 16 kilograms of biosolid per plant, is the most recommended to fertilize the banana since the collected fruits presented the most optimal nutritional values.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43579995","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 : 2023-08-01DOI: 10.3389/frwa.2023.1188321
A. Pawley, David Moldoff, Joshua Brown, Stephanie Freed
Sacramento, the capital of California, has a population of over 2 million and is one of the most flood prone regions in the nation. Its problems exemplify those of many urban communities built near riverine and deltaic systems, that are subject to climate change. The city and its surrounding communities are protected by an elaborate system of levees and flood bypasses; but aging infrastructure, expected increases in extreme wet weather, and projected sea level rise are increasing the risk of levee failures. We explore how flood management approaches including social/institutional (non-structural), traditional structural, and ecological based approaches are being implemented in the Lower Sacramento/North Delta Region amid significant obstacles, to build resilient flood management systems. We review four case studies, one structural levee project and three multi-benefit projects that are only recently being implemented. We also examine the barriers, constraints, and challenges for implementing flood protection projects, and how project proponents are collectively working through these obstacles. We conclude that significant progress has been made in building flood resiliency since the 2008 Central Valley Flood Protection Act and the release of the 2012 Central Valley Flood Protection Plan. Informational tools and policies are being developed to educate the public and prepare for floods. Structural levee investments are substantial and are being implemented through partnerships. Statewide policies and investments are increasingly supporting multi-benefit projects that incorporate ecological restoration/enhancement while expanding flood volume capacity. Progress on implementing multi-benefit projects has been slow, due to land acquisition, easements, funding, regulatory and construction challenges; however, solutions to these impediments are emerging to facilitate more rapid progress. It is essential to continue and intensify the progress made in the last two decades, by learning from past projects, and improving on existing pathways to implement sustainable projects at a faster rate.
{"title":"Reducing flood risk and improving system resiliency in Sacramento, California: overcoming obstacles and emerging solutions","authors":"A. Pawley, David Moldoff, Joshua Brown, Stephanie Freed","doi":"10.3389/frwa.2023.1188321","DOIUrl":"https://doi.org/10.3389/frwa.2023.1188321","url":null,"abstract":"Sacramento, the capital of California, has a population of over 2 million and is one of the most flood prone regions in the nation. Its problems exemplify those of many urban communities built near riverine and deltaic systems, that are subject to climate change. The city and its surrounding communities are protected by an elaborate system of levees and flood bypasses; but aging infrastructure, expected increases in extreme wet weather, and projected sea level rise are increasing the risk of levee failures. We explore how flood management approaches including social/institutional (non-structural), traditional structural, and ecological based approaches are being implemented in the Lower Sacramento/North Delta Region amid significant obstacles, to build resilient flood management systems. We review four case studies, one structural levee project and three multi-benefit projects that are only recently being implemented. We also examine the barriers, constraints, and challenges for implementing flood protection projects, and how project proponents are collectively working through these obstacles. We conclude that significant progress has been made in building flood resiliency since the 2008 Central Valley Flood Protection Act and the release of the 2012 Central Valley Flood Protection Plan. Informational tools and policies are being developed to educate the public and prepare for floods. Structural levee investments are substantial and are being implemented through partnerships. Statewide policies and investments are increasingly supporting multi-benefit projects that incorporate ecological restoration/enhancement while expanding flood volume capacity. Progress on implementing multi-benefit projects has been slow, due to land acquisition, easements, funding, regulatory and construction challenges; however, solutions to these impediments are emerging to facilitate more rapid progress. It is essential to continue and intensify the progress made in the last two decades, by learning from past projects, and improving on existing pathways to implement sustainable projects at a faster rate.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41738726","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 : 2023-07-31DOI: 10.3389/frwa.2023.1243114
O. Schilling, L. J. Halloran, H. Delottier, Y. Sano, R. Therrien
{"title":"Editorial: Advances and emerging methods in tracer hydrogeology","authors":"O. Schilling, L. J. Halloran, H. Delottier, Y. Sano, R. Therrien","doi":"10.3389/frwa.2023.1243114","DOIUrl":"https://doi.org/10.3389/frwa.2023.1243114","url":null,"abstract":"","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46206683","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 : 2023-07-27DOI: 10.3389/frwa.2023.1195094
Grégoire Davignon, Julie Cagliero, L. Guentas, Emilie Bierque, P. Genthon, P. Gunkel-Grillon, F. Juillot, Malia Kainiu, C. Laporte-Magoni, M. Picardeau, Nazha Selmaoui-Folcher, Marie-Estelle Soupé-Gilbert, C. Tramier, Jessica Vilanova, K. Wijesuriya, Roman Thibeaux, C. Goarant
Leptospira is a complex bacterial genus which biodiversity has long been overlooked. In the recent years however, environmental studies have contributed to shed light on its original and current environmental habitat. Although very fragile bacteria in laboratories, Leptospira have been shown to successfully occupy a range of soil and freshwater habitats. Recent work has strongly suggested that biofilm formation, a multicellular lifestyle regulated by the second messenger c-di-GMP, might be one strategy developed to overcome the multiple challenges of environmental survival. Within the genus, a minority of pathogenic species have developed the ability to infect mammals and be responsible for leptospirosis. However, most of them have retained their environmental survival capacity, which is required to fulfill their epidemiological cycle. Indeed, susceptible hosts, such as human, suffer from various symptoms, while reservoir hosts stay asymptomatic and release bacteria in the environment. In this review, we discuss how c-di-GMP might be a central regulator allowing pathogenic Leptospira to fulfill this complex life cycle. We conclude by identifying knowledge gaps and propose some hypotheses that should be researched to gain a holistic vision of Leptospira biology.
{"title":"Leptospirosis: toward a better understanding of the environmental lifestyle of Leptospira","authors":"Grégoire Davignon, Julie Cagliero, L. Guentas, Emilie Bierque, P. Genthon, P. Gunkel-Grillon, F. Juillot, Malia Kainiu, C. Laporte-Magoni, M. Picardeau, Nazha Selmaoui-Folcher, Marie-Estelle Soupé-Gilbert, C. Tramier, Jessica Vilanova, K. Wijesuriya, Roman Thibeaux, C. Goarant","doi":"10.3389/frwa.2023.1195094","DOIUrl":"https://doi.org/10.3389/frwa.2023.1195094","url":null,"abstract":"Leptospira is a complex bacterial genus which biodiversity has long been overlooked. In the recent years however, environmental studies have contributed to shed light on its original and current environmental habitat. Although very fragile bacteria in laboratories, Leptospira have been shown to successfully occupy a range of soil and freshwater habitats. Recent work has strongly suggested that biofilm formation, a multicellular lifestyle regulated by the second messenger c-di-GMP, might be one strategy developed to overcome the multiple challenges of environmental survival. Within the genus, a minority of pathogenic species have developed the ability to infect mammals and be responsible for leptospirosis. However, most of them have retained their environmental survival capacity, which is required to fulfill their epidemiological cycle. Indeed, susceptible hosts, such as human, suffer from various symptoms, while reservoir hosts stay asymptomatic and release bacteria in the environment. In this review, we discuss how c-di-GMP might be a central regulator allowing pathogenic Leptospira to fulfill this complex life cycle. We conclude by identifying knowledge gaps and propose some hypotheses that should be researched to gain a holistic vision of Leptospira biology.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"1 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41611800","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 : 2023-07-24DOI: 10.3389/frwa.2023.1223338
P. Tunby, J. Nichols, Asmita Kaphle, A. Khandelwal, David Van Horn, R. González‐Pinzón
Anthropogenic and natural disasters (e.g., wildfires, oil spills, mine spills, sewage treatment facilities) cause water quality disturbances in fluvial networks. These disturbances are highly unpredictable in space-time, with the potential to propagate through multiple stream orders and impact human and environmental health over days to years. Due to challenges in monitoring and studying these events, we need methods to strategize the deployment of rapid response research teams on demand. Rapid response research has the potential to close the gap in available water quality data and process understanding through time-sensitive data collection efforts. This manuscript presents a protocol that can guide researchers in preparing for and researching water quality disturbance events. We tested and refined the protocol by assessing the longitudinal propagation of water quality disturbances from the 2022 Hermit's Peak—Calf Canyon, NM, USA, the largest in the state's recorded history. Our rapid response research allowed us to collect high-resolution water quality data with semi-continuous sensors and synoptic grab sampling. The data collected have been used for traditional peer-reviewed publications and pragmatically to inform water utilities, restoration, and outreach programs.
{"title":"Development of a general protocol for rapid response research on water quality disturbances and its application for monitoring the largest wildfire recorded in New Mexico, USA","authors":"P. Tunby, J. Nichols, Asmita Kaphle, A. Khandelwal, David Van Horn, R. González‐Pinzón","doi":"10.3389/frwa.2023.1223338","DOIUrl":"https://doi.org/10.3389/frwa.2023.1223338","url":null,"abstract":"Anthropogenic and natural disasters (e.g., wildfires, oil spills, mine spills, sewage treatment facilities) cause water quality disturbances in fluvial networks. These disturbances are highly unpredictable in space-time, with the potential to propagate through multiple stream orders and impact human and environmental health over days to years. Due to challenges in monitoring and studying these events, we need methods to strategize the deployment of rapid response research teams on demand. Rapid response research has the potential to close the gap in available water quality data and process understanding through time-sensitive data collection efforts. This manuscript presents a protocol that can guide researchers in preparing for and researching water quality disturbance events. We tested and refined the protocol by assessing the longitudinal propagation of water quality disturbances from the 2022 Hermit's Peak—Calf Canyon, NM, USA, the largest in the state's recorded history. Our rapid response research allowed us to collect high-resolution water quality data with semi-continuous sensors and synoptic grab sampling. The data collected have been used for traditional peer-reviewed publications and pragmatically to inform water utilities, restoration, and outreach programs.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49037889","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 : 2023-07-24DOI: 10.3389/frwa.2023.1141786
T. Milojevic, J. Blanchet, M. Lehning
Return level calculations are widely used to determine the risks that extreme events may pose to infrastructure, including hydropower site operations. Extreme events (e.g., extreme precipitation and droughts) are expected to increase in frequency and intensity in the future, but not necessarily in a homogenous way across regions. This makes localized assessment important for understanding risk changes to specific sites. However, for sites with relatively small datasets, selecting an applicable method for return level calculations is not straightforward. This study focuses on the application of traditional univariate extreme value approaches (Generalized Extreme Value and Generalized Pareto) as well as two more recent approaches (extended Generalized Pareto and Metastatistical Extreme Value distributions), that are specifically suited for application to small datasets. These methods are used to calculate return levels of extreme precipitation at six Alpine stations and high reservoir inflow events for a hydropower reservoir. In addition, return levels of meteorological drought and low inflow periods (dry spells) are determined using a non-parametric approach. Return levels for return periods of 10- and 20- years were calculated using 10-, 20-, and 40- years of data for each method. The results show that even shorter timeseries can give similar return levels as longer timeseries for most methods. However, the GEV has greater sensitivity to sparse data and tended to give lower estimates for precipitation return levels. The MEV is only to be preferred over GPD if the underlying distribution fits the data well. The result is used to assemble a profile of 10- and 20-year return levels estimated with various statistical approaches, for extreme high precipitation/inflow and low precipitation/inflow events. The findings of the study may be helpful to researchers and practitioners alike in deciding which statistical approach to use to assess local extreme precipitation and inflow risks to individual reservoirs.
{"title":"Determining return levels of extreme daily precipitation, reservoir inflow, and dry spells","authors":"T. Milojevic, J. Blanchet, M. Lehning","doi":"10.3389/frwa.2023.1141786","DOIUrl":"https://doi.org/10.3389/frwa.2023.1141786","url":null,"abstract":"Return level calculations are widely used to determine the risks that extreme events may pose to infrastructure, including hydropower site operations. Extreme events (e.g., extreme precipitation and droughts) are expected to increase in frequency and intensity in the future, but not necessarily in a homogenous way across regions. This makes localized assessment important for understanding risk changes to specific sites. However, for sites with relatively small datasets, selecting an applicable method for return level calculations is not straightforward. This study focuses on the application of traditional univariate extreme value approaches (Generalized Extreme Value and Generalized Pareto) as well as two more recent approaches (extended Generalized Pareto and Metastatistical Extreme Value distributions), that are specifically suited for application to small datasets. These methods are used to calculate return levels of extreme precipitation at six Alpine stations and high reservoir inflow events for a hydropower reservoir. In addition, return levels of meteorological drought and low inflow periods (dry spells) are determined using a non-parametric approach. Return levels for return periods of 10- and 20- years were calculated using 10-, 20-, and 40- years of data for each method. The results show that even shorter timeseries can give similar return levels as longer timeseries for most methods. However, the GEV has greater sensitivity to sparse data and tended to give lower estimates for precipitation return levels. The MEV is only to be preferred over GPD if the underlying distribution fits the data well. The result is used to assemble a profile of 10- and 20-year return levels estimated with various statistical approaches, for extreme high precipitation/inflow and low precipitation/inflow events. The findings of the study may be helpful to researchers and practitioners alike in deciding which statistical approach to use to assess local extreme precipitation and inflow risks to individual reservoirs.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46213825","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 : 2023-07-20DOI: 10.3389/frwa.2023.1115264
S. Dickerson‐Lange, Emily R. Howe, Kenna Patrick, R. Gersonde, J. Lundquist
Forest thinning and gap creation are being implemented across the western United States of America (USA) to reduce wildfire and forest mortality risk as the climate warms. The Eastern Cascades in Washington, USA, is in a transitional zone between maritime and continental climate conditions and represents a data gap in observations describing the relationship between forest density and snowpack. We collected 3 years of snow observations across a range of forest densities to characterize how forest management efforts in this region may influence the magnitude and duration of snow storage. Observations indicate that peak snow storage magnitude in small gaps ranges from the same to over twice that observed in unburned forest plots in the Eastern Cascades. However, differences in snow duration are generally small. Across all Eastern Cascade sites and years, we observed a median difference of snow storage lasting 7 days longer in gaps as compared to nearby forest plots. A notable exception to this pattern occurred at one north-facing site, where snow lasted 30 days longer in the gap. These observations of similar snow storage duration in the Eastern Cascades are attributed to minimal differences in canopy snow interception processes between forests and gaps at some sites, and to higher ablation rates that counterbalance the higher snow accumulation in the gaps at other sites. At the north-facing site, more snow accumulated in the gap, and ablation rates in the open gap were similar to the shaded forest due to the aspect of the site. Thus, snow storage duration was much longer in the gap. Together, these data suggest that prescriptions to reduce forest density through thinning and creating gaps may increase the overall amount of snow storage by reducing loss due to sublimation and melting of canopy-intercepted snow. However, reducing forest density in the Eastern Cascades is unlikely to buffer climate-induced shortening of snow storage duration, with the possible exception of gap creation in north-facing forests. Lastly, these observations fill a spatial and climatic data gap and can be used to support hydrological modeling at spatial and temporal scales that are relevant to forest management decisions.
{"title":"Forest gap effects on snow storage in the transitional climate of the Eastern Cascade Range, Washington, United States","authors":"S. Dickerson‐Lange, Emily R. Howe, Kenna Patrick, R. Gersonde, J. Lundquist","doi":"10.3389/frwa.2023.1115264","DOIUrl":"https://doi.org/10.3389/frwa.2023.1115264","url":null,"abstract":"Forest thinning and gap creation are being implemented across the western United States of America (USA) to reduce wildfire and forest mortality risk as the climate warms. The Eastern Cascades in Washington, USA, is in a transitional zone between maritime and continental climate conditions and represents a data gap in observations describing the relationship between forest density and snowpack. We collected 3 years of snow observations across a range of forest densities to characterize how forest management efforts in this region may influence the magnitude and duration of snow storage. Observations indicate that peak snow storage magnitude in small gaps ranges from the same to over twice that observed in unburned forest plots in the Eastern Cascades. However, differences in snow duration are generally small. Across all Eastern Cascade sites and years, we observed a median difference of snow storage lasting 7 days longer in gaps as compared to nearby forest plots. A notable exception to this pattern occurred at one north-facing site, where snow lasted 30 days longer in the gap. These observations of similar snow storage duration in the Eastern Cascades are attributed to minimal differences in canopy snow interception processes between forests and gaps at some sites, and to higher ablation rates that counterbalance the higher snow accumulation in the gaps at other sites. At the north-facing site, more snow accumulated in the gap, and ablation rates in the open gap were similar to the shaded forest due to the aspect of the site. Thus, snow storage duration was much longer in the gap. Together, these data suggest that prescriptions to reduce forest density through thinning and creating gaps may increase the overall amount of snow storage by reducing loss due to sublimation and melting of canopy-intercepted snow. However, reducing forest density in the Eastern Cascades is unlikely to buffer climate-induced shortening of snow storage duration, with the possible exception of gap creation in north-facing forests. Lastly, these observations fill a spatial and climatic data gap and can be used to support hydrological modeling at spatial and temporal scales that are relevant to forest management decisions.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46278683","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 : 2023-07-17DOI: 10.3389/frwa.2023.1220544
R. Mwanake, G. Gettel, E. Wangari, K. Butterbach‐Bahl, R. Kiese
Greenhouse gas emissions from headwater streams are linked to multiple sources influenced by terrestrial land use and hydrology, yet partitioning these sources at catchment scales remains highly unexplored. To address this gap, we sampled year-long stable water isotopes (δ18O and δ2H) from 17 headwater streams differing in catchment agricultural areas. We calculated mean residence times (MRT) and young water fractions (YWF) based on the seasonality of δ18O signals and linked these hydrological measures to catchment characteristics, mean annual water physico-chemical variables, and GHG % saturations. The MRT and the YWF ranged from 0.25 to 4.77 years and 3 to 53%, respectively. The MRT of stream water was significantly negatively correlated with stream slope (r2 = 0.58) but showed no relationship with the catchment area. Streams in agriculture-dominated catchments were annual hotspots of GHG oversaturation, which we attributed to precipitation-driven terrestrial inputs of dissolved GHGs for streams with shorter MRTs and nutrients and GHG inflows from groundwater for streams with longer MRTs. Based on our findings, future research should also consider water mean residence time estimates as indicators of integrated hydrological processes linking discharge and land use effects on annual GHG dynamics in headwater streams.
{"title":"Interactive effects of catchment mean water residence time and agricultural area on water physico-chemical variables and GHG saturations in headwater streams","authors":"R. Mwanake, G. Gettel, E. Wangari, K. Butterbach‐Bahl, R. Kiese","doi":"10.3389/frwa.2023.1220544","DOIUrl":"https://doi.org/10.3389/frwa.2023.1220544","url":null,"abstract":"Greenhouse gas emissions from headwater streams are linked to multiple sources influenced by terrestrial land use and hydrology, yet partitioning these sources at catchment scales remains highly unexplored. To address this gap, we sampled year-long stable water isotopes (δ18O and δ2H) from 17 headwater streams differing in catchment agricultural areas. We calculated mean residence times (MRT) and young water fractions (YWF) based on the seasonality of δ18O signals and linked these hydrological measures to catchment characteristics, mean annual water physico-chemical variables, and GHG % saturations. The MRT and the YWF ranged from 0.25 to 4.77 years and 3 to 53%, respectively. The MRT of stream water was significantly negatively correlated with stream slope (r2 = 0.58) but showed no relationship with the catchment area. Streams in agriculture-dominated catchments were annual hotspots of GHG oversaturation, which we attributed to precipitation-driven terrestrial inputs of dissolved GHGs for streams with shorter MRTs and nutrients and GHG inflows from groundwater for streams with longer MRTs. Based on our findings, future research should also consider water mean residence time estimates as indicators of integrated hydrological processes linking discharge and land use effects on annual GHG dynamics in headwater streams.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44689802","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 : 2023-07-17DOI: 10.3389/frwa.2023.1087076
E. Habib, B. Miles, L. Skilton, Mohamed Elsaadani, A. Osland, Emma Willis, Robert Miller, Trung Do, Stephen R. Barnes
The lack of community-relevant flood informational resources and tools often results in inadequate and divergent understandings of flood risk and can impede communities' ability to function cohesively in the face of increasing flood threats. The current study reports on a set of workshops that the authors conducted with various groups (citizens, city engineers and planners, realtors and builders, and media representatives) within a flood prone community to evaluate how novel hydroinformatic tools that include hydrodynamic modeling, geospatial visualization, and socioeconomic analysis can enhance understanding of flood risk and engagement in flood risk mitigation among diverse community members. The workshops were designed to help identify stakeholder preferences regarding key functionality needed for integrated hydroinformatic technologies and socioeconomic analyses for flood risk reduction. Workshop participants were asked to use and comment on examples of prototype flood risk informational tools, such as: (1) flood damage estimation tool, (2) drivability and emergency accessibility tool, and (3) community-scale social and economic metrics tool. Data gathered from workshops were analyzed using qualitative analysis based on a grounded-theory approach. Data were coded by hand based on themes identified by the research team and incorporated deviant case analysis to ensure minority opinions was represented. The study results are focused on the following main themes and how flood tools can address them: (1) improving the understanding of flood risk and engagement in flood risk mitigation, (2) reducing the gap between individual and community risk, (3) challenges in communicating flood risk information, (4) enhancing relevance to and engagement of the community, and (5) enabling actionable information. Our research demonstrates the need for community-anchored tools and technologies that can illustrate local context, include local historical and simulated events at multiple levels of community impact, enable analyses by flood professionals while also providing simplified tools of use by citizens, and allow individuals to expand their knowledge beyond their homes, businesses, and places of work.
{"title":"Anchoring tools to communities: insights into perceptions of flood informational tools from a flood-prone community in Louisiana, USA","authors":"E. Habib, B. Miles, L. Skilton, Mohamed Elsaadani, A. Osland, Emma Willis, Robert Miller, Trung Do, Stephen R. Barnes","doi":"10.3389/frwa.2023.1087076","DOIUrl":"https://doi.org/10.3389/frwa.2023.1087076","url":null,"abstract":"The lack of community-relevant flood informational resources and tools often results in inadequate and divergent understandings of flood risk and can impede communities' ability to function cohesively in the face of increasing flood threats. The current study reports on a set of workshops that the authors conducted with various groups (citizens, city engineers and planners, realtors and builders, and media representatives) within a flood prone community to evaluate how novel hydroinformatic tools that include hydrodynamic modeling, geospatial visualization, and socioeconomic analysis can enhance understanding of flood risk and engagement in flood risk mitigation among diverse community members. The workshops were designed to help identify stakeholder preferences regarding key functionality needed for integrated hydroinformatic technologies and socioeconomic analyses for flood risk reduction. Workshop participants were asked to use and comment on examples of prototype flood risk informational tools, such as: (1) flood damage estimation tool, (2) drivability and emergency accessibility tool, and (3) community-scale social and economic metrics tool. Data gathered from workshops were analyzed using qualitative analysis based on a grounded-theory approach. Data were coded by hand based on themes identified by the research team and incorporated deviant case analysis to ensure minority opinions was represented. The study results are focused on the following main themes and how flood tools can address them: (1) improving the understanding of flood risk and engagement in flood risk mitigation, (2) reducing the gap between individual and community risk, (3) challenges in communicating flood risk information, (4) enhancing relevance to and engagement of the community, and (5) enabling actionable information. Our research demonstrates the need for community-anchored tools and technologies that can illustrate local context, include local historical and simulated events at multiple levels of community impact, enable analyses by flood professionals while also providing simplified tools of use by citizens, and allow individuals to expand their knowledge beyond their homes, businesses, and places of work.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46464682","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 : 2023-07-13DOI: 10.3389/frwa.2023.1193142
D. Karimanzira, J. Weis, Andreas Wunsch, Linda Ritzau, T. Liesch, M. Ohmer
The prediction of groundwater nitrate concentration's response to geo-environmental and human-influenced factors is essential to better restore groundwater quality and improve land use management practices. In this paper, we regionalize groundwater nitrate concentration using different machine learning methods (Random forest (RF), unimodal 2D and 3D convolutional neural networks (CNN), and multi-stream early and late fusion 2D-CNNs) so that the nitrate situation in unobserved areas can be predicted. CNNs take into account not only the nitrate values of the grid cells of the observation wells but also the values around them. This has the added benefit of allowing them to learn directly about the influence of the surroundings. The predictive performance of the models was tested on a dataset from a pilot region in Germany, and the results show that, in general, all the machine learning models, after a Bayesian optimization hyperparameter search and training, achieve good spatial predictive performance compared to previous studies based on Kriging and numerical models. Based on the mean absolute error (MAE), the random forest model and the 2DCNN late fusion model performed best with an MAE (STD) of 9.55 (0.367) mg/l, R2 = 0.43 and 10.32 (0.27) mg/l, R2 = 0.27, respectively. The 3DCNN with an MAE (STD) of 11.66 (0.21) mg/l and largest resources consumption is the worst performing model. Feature importance learning from the models was used in conjunction with partial dependency analysis of the most important features to gain greater insight into the major factors explaining the nitrate spatial variability. Large uncertainties in nitrate prediction have been shown in previous studies. Therefore, the models were extended to quantify uncertainty using prediction intervals (PIs) derived from bootstrapping. Knowledge of uncertainty helps the water manager reduce risk and plan more reliably.
{"title":"Application of machine learning and deep neural networks for spatial prediction of groundwater nitrate concentration to improve land use management practices","authors":"D. Karimanzira, J. Weis, Andreas Wunsch, Linda Ritzau, T. Liesch, M. Ohmer","doi":"10.3389/frwa.2023.1193142","DOIUrl":"https://doi.org/10.3389/frwa.2023.1193142","url":null,"abstract":"The prediction of groundwater nitrate concentration's response to geo-environmental and human-influenced factors is essential to better restore groundwater quality and improve land use management practices. In this paper, we regionalize groundwater nitrate concentration using different machine learning methods (Random forest (RF), unimodal 2D and 3D convolutional neural networks (CNN), and multi-stream early and late fusion 2D-CNNs) so that the nitrate situation in unobserved areas can be predicted. CNNs take into account not only the nitrate values of the grid cells of the observation wells but also the values around them. This has the added benefit of allowing them to learn directly about the influence of the surroundings. The predictive performance of the models was tested on a dataset from a pilot region in Germany, and the results show that, in general, all the machine learning models, after a Bayesian optimization hyperparameter search and training, achieve good spatial predictive performance compared to previous studies based on Kriging and numerical models. Based on the mean absolute error (MAE), the random forest model and the 2DCNN late fusion model performed best with an MAE (STD) of 9.55 (0.367) mg/l, R2 = 0.43 and 10.32 (0.27) mg/l, R2 = 0.27, respectively. The 3DCNN with an MAE (STD) of 11.66 (0.21) mg/l and largest resources consumption is the worst performing model. Feature importance learning from the models was used in conjunction with partial dependency analysis of the most important features to gain greater insight into the major factors explaining the nitrate spatial variability. Large uncertainties in nitrate prediction have been shown in previous studies. Therefore, the models were extended to quantify uncertainty using prediction intervals (PIs) derived from bootstrapping. Knowledge of uncertainty helps the water manager reduce risk and plan more reliably.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47273625","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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