Frontiers in Water最新文献

{"title":"Recent streamflow trends across permafrost basins of North America","authors":"K. Bennett, J. Schwenk, Claire L. Bachand, Eve I. Gasarch, Jemma Stachelek, W. Bolton, J. Rowland","doi":"10.3389/frwa.2023.1099660","DOIUrl":"https://doi.org/10.3389/frwa.2023.1099660","url":null,"abstract":"Introduction Climate change impacts, including changing temperatures, precipitation, and vegetation, are widely anticipated to cause major shifts to the permafrost with resulting impacts to hydro-ecosystems across the high latitudes of the globe. However, it is challenging to examine streamflow shifts in these regions owing to a paucity of data, discontinuity of records, and other issues related to data consistency and accuracy. Methods Recent trends for long-term periods (1990–2021, 1976–2021) in observed minimum, mean, and maximum seasonal and annual streamflow were analyzed for a range of watersheds across North America affected by varying degrees of permafrost coverage. Results Streamflow trend analysis revealed that areas affected by permafrost are changing variably over the periods in terms of maximum, mean, and minimum seasonal and annual streamflow. These changes indicate a significant shift occurring in the most recent 46 years towards increasing mean streamflow for the dominant (> 50%) permafrost systems. Meanwhile, minimum streamflow increases for all permafrost-dominant systems and many of the other permafrost-affected systems across the seasons and annual periods considered, with the greatest number of significant changes in streamflow over other metrics. Maximum streamflow is shifting variably with significant increases in the permafrost-dominant systems in winter and fall over longer time periods of analysis. Our analysis suggests that streamflow trends are driven by climate (precipitation, followed by temperature), while variables such as permafrost coverage only appear important in the most recent 32-year period. Discussion The increases in streamflow trends observed in this study are reflective of deepening active layers and thawing permafrost, indicating that the entire hydrograph is undergoing change within permafrost-dominant streamflow systems as the Arctic moves towards a warmer future under climate change. Despite the many challenges to understanding changing streamflow in cold regions, there are new products and datasets in development that are increasingly allowing researchers to better understand the patterns of change in Arctic and subarctic systems affected by permafrost, offering a range of new tools, which, along with continued observational records, may help in improved understanding of changing Arctic streamflow patterns.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47990141","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":"Evaluating deep learning architecture and data assimilation for improving water temperature forecasts at unmonitored locations","authors":"J. Zwart, Jeremy Diaz, Scott D. Hamshaw, S. Oliver, Jesse C. Ross, Margaux Sleckman, A. Appling, Hayley Corson-Dosch, X. Jia, J. Read, J. Sadler, Theodore Thompson, David W. Watkins, Elaheh White","doi":"10.3389/frwa.2023.1184992","DOIUrl":"https://doi.org/10.3389/frwa.2023.1184992","url":null,"abstract":"Deep learning (DL) models are increasingly used to forecast water quality variables for use in decision making. Ingesting recent observations of the forecasted variable has been shown to greatly increase model performance at monitored locations; however, observations are not collected at all locations, and methods are not yet well developed for DL models for optimally ingesting recent observations from other sites to inform focal sites. In this paper, we evaluate two different DL model structures, a long short-term memory neural network (LSTM) and a recurrent graph convolutional neural network (RGCN), both with and without data assimilation for forecasting daily maximum stream temperature 7 days into the future at monitored and unmonitored locations in a 70-segment stream network. All our DL models performed well when forecasting stream temperature as the root mean squared error (RMSE) across all models ranged from 2.03 to 2.11°C for 1-day lead times in the validation period, with substantially better performance at gaged locations (RMSE = 1.45–1.52°C) compared to ungaged locations (RMSE = 3.18–3.27°C). Forecast uncertainty characterization was near-perfect for gaged locations but all DL models were overconfident (i.e., uncertainty bounds too narrow) for ungaged locations. Our results show that the RGCN with data assimilation performed best for ungaged locations and especially at higher temperatures (>18°C) which is important for management decisions in our study location. This indicates that the networked model structure and data assimilation techniques may help borrow information from nearby monitored sites to improve forecasts at unmonitored locations. Results from this study can help guide DL modeling decisions when forecasting other important environmental variables.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49296348","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":"Socio-hydrological dynamics and water conflicts in the upper Huasco valley, Chile","authors":"Juliane Dame, M. Nüsser, S. Schmidt, C. Zang","doi":"10.3389/frwa.2023.1100977","DOIUrl":"https://doi.org/10.3389/frwa.2023.1100977","url":null,"abstract":"In arid regions of north-central Chile, mining activities and agricultural land use changes lead to competing water demands, water insecurity, and related conflicts. Different local and external user groups rely on the scarce water resources. This case study investigates socio-hydrological transformations in the upper Huasco valley. It builds on a mixed method approach that combines remote sensing assessments (Corona, Landsat, Sentinel-2) with a set of social science methods including interviews and an analysis of Twitter tweets. Against the backdrop of the recent mega drought, results show that the upper Huasco valley faces adverse environmental impacts and conflicts over mining activities as well as an expansion of export-oriented agriculture. While water availability largely depends on the cryosphere, remote sensing analyses show a drastic glacier decrease in the vicinity of the mining project, where three glaciers completely disappeared since 2000. Furthermore, an expansion of the cultivated area from 2,000 ha in the 1990s to about 3,210 ha occurred in the 2000s. Agricultural expansion has come to a halt and only a slight increase of 100 ha can be detected over the last decade. Interview and social media data show local concerns and discourses on issues of water scarcity and quality related to these land use changes. The study stresses the necessity of integrative assessments for a better understanding of water scarcity and water-related conflicts. Equitable water governance in climate-sensitive areas requires contextualizing land use changes and the precarious drinking water situation from a socio-hydrological perspective.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48270901","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":"Dissolution rate variability at carbonate surfaces: 4D X-ray micro-tomography and stochastic modeling investigations","authors":"M. Guren, François Renard, C. Noiriel","doi":"10.3389/frwa.2023.1185608","DOIUrl":"https://doi.org/10.3389/frwa.2023.1185608","url":null,"abstract":"We provide a detailed 3D characterization of the geometry evolution and dissolution rate mapping at the surface of four carbonate samples, namely a calcite spar crystal, two limestone rock fragments, and an aragonite ooid, using time-lapse X-ray micro-tomography during dissolution experiments at pH 4.0. Evaluation of the retreat and mapping of the reaction rates at the whole surface of the samples reveals a large spatial variability in the dissolution rates, reflecting the composition and the specific contributions of the different regions of the samples. While crystal edges and convex topographies record the highest dissolution rates, the retreat is slower for flat surfaces and in topographic lows (i.e., concave areas), suggesting surface-energy related and/or diffusion-limited reactions. Microcrystalline aragonite has the highest rate of dissolution compared to calcite. Surprisingly, rough microcrystalline calcite surface dissolves globally more slowly than the {101̄4} faces of the calcite spar crystal. The presence of mineral impurities in rocks, through the development of a rough interface that may affect the transport of species across the surface, may explain the slight decrease in reactivity with time. Finally, a macroscopic stochastic model using the set of detachment probabilities at corner, edge, and face (terrace) sites obtained from kinetic Monte Carlo simulations is applied at the spar crystal scale to account for the effect of site coordination onto reactivity. Application of the model to the three other carbonate samples is discussed regarding their geometry and composition. The results suggest that the global dissolution process of carbonate rocks does not reflect only the individual behavior of their forming minerals, but also the geometry of the crystals and the shape of the fluid-mineral interface.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46672325","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":"Assessment of solid and liquid wastes management and health impacts along the failed sewerage systems in capital cities of African countries: case of Abidjan, Côte d'Ivoire","authors":"Z. Ouattara, K. Dongo, Komlavi Akpoti, A. T. Kabo-bah, F. Attiogbe, E. K. Siabi, Chu Donatus Iweh, Guemegbo Hypolithe Gogo","doi":"10.3389/frwa.2023.1071686","DOIUrl":"https://doi.org/10.3389/frwa.2023.1071686","url":null,"abstract":"The management of domestic wastewater and rainwater is a major concern for the population of Yopougon. The study presents the causes of wastewater discharge from dysfunctional sewers and their health impacts on the population. It also highlights the environmental and health risk associated with poor solid and liquid waste management. This was based on literature search, semi-participatory workshop, physicochemical and bacteriological characterization of wastewater and finally through a household survey. The field survey was conducted on 245 household heads obtained using the Canadian statistical guidelines. The results obtained indicated that all main pollution indicators were; total nitrogen (TN, 525 ± 0.02 to 3077 ± 0.3 mg/l), nitrates (NO3, 146 ± 0.01 to 1347 ± 0.12 mg/l), biochemical oxygen demand (BOD, 278 ± 195.16 to 645 ± 391.74 mg/l), chemical oxygen demand (COD, 940 ± 650.54 to 4050.5 ± 71.42 mg/l) and total dissolved solids (TDS, 151 ± 9.9 to 766 ± 237.59 mg/l) which were above the values recommended by the World Health Organization (WHO) and Cote d'Ivoire national policy guidelines standards for the discharge of effluents into the environment. The analysis of the bacterial flora of the effluents revealed that the concentrations of Total Coliforms and fecal streptococci exceeded the values recommended by the WHO and national policy guidelines standards. This means that the populations of this area are prone to infectious diseases. Diseases such as malaria (84.53%), respiratory infections (61%), diarrhea (48.66%), intestinal diseases (44.5%), and typhoid fever (28.84%) were prevalent in the surveyed households.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44154575","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":"Urban flood regulating ecosystem services under climate change: how can Nature-based Solutions contribute?","authors":"Thea Wübbelmann, Kristian Förster, L. Bouwer, C. Dworczyk, Steffen Bender, Benjamin Burkhard","doi":"10.3389/frwa.2023.1081850","DOIUrl":"https://doi.org/10.3389/frwa.2023.1081850","url":null,"abstract":"Urban areas are mostly highly sealed spaces, which often leads to large proportions of surface runoff. At the same time, heavy rainfall events are projected to increase in frequency and intensity with anthropogenic climate change. Consequently, higher risks and damages from pluvial flooding are expected. The analysis of Flood Regulating Ecosystem Services (FRES) can help to determine the benefits from nature to people by reducing surface runoff and runoff peaks. However, urban FRES are rarely studied for heavy rainfall events under changing climate conditions. Therefore, we first estimate the functionality of current urban FRES-supply and demand under changing climate conditions. Second, we identify the effects of Nature-based Solutions (NbS) on FRES-supply and demand and their potential future functionality and benefits concerning more intensive rainfall events. A district of the city of Rostock in northeastern Germany serves as the case study area. In addition to the reference conditions based on the current land use, we investigate two potential NbS: (1) increasing the number of trees; and (2) unsealing and soil improvement. Both NbS and a combination of both are applied for three heavy rainfall scenarios. In addition to a reference scenario, two future scenarios were developed to investigate the FRES functionality, based on 21 and 28% more intense rainfall. While the potential FRES-demand was held constant, we assessed the FRES-supply and actual demand for all scenario combinations, using the hydrological model LEAFlood. The comparison between the actual demand and supply indicates the changes in FRES-supply surplus and unmet demand increase. Existing land use structures reached a FRES capacity and cannot buffer more intense rainfall events. Whereas, the NbS serve FRES benefits by increasing the supply and reducing the actual demand. Using FRES indicators, based on hydrological models to estimate future functionality under changing climate conditions and the benefits of NbS, can serve as an analysis and decision-support tool for decision-makers to reduce future urban flood risk.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49144244","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":"Ecosystem services produced by groundwater dependent ecosystems: a framework and case study in California","authors":"J. Howard, Katherine E Dooley, K. Brauman, Kirk R. Klausmeyer, M. M. Rohde","doi":"10.3389/frwa.2023.1115416","DOIUrl":"https://doi.org/10.3389/frwa.2023.1115416","url":null,"abstract":"Groundwater is an important freshwater supply for agricultural, domestic, and environmental uses and critical buffer against a warming climate, particularly in semi-arid and arid regions of the world. Groundwater dependent ecosystems (GDEs), which rely on groundwater for some or all of their water requirements, include terrestrial vegetation, rivers, springs, wetlands, and riparian zones. These GDEs provide benefits to people ranging from habitat for pollinators to carbon sequestration. Accounting for these benefits, called ecosystem services, can inform management by expanding the potential group of groundwater users to include groundwater dependent ecosystems. Here we develop an approach to inventory the ecosystem services of GDEs by identifying the ecosystem functions of a range of GDEs and assessing how they are linked to a wide range of ecosystem services. We apply this approach as a case study in California, USA, where we found ecosystem services from GDEs is widespread across the state; over 30% of California's pollinator dependent crops may benefit from GDEs, and carbon storage of GDEs is equivalent to 790 million tons, twice as much as California emits annually.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42924575","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":"Editorial: Impact of anthropogenic disturbances on agroforestry ecosystems","authors":"P. Nasta, Z. Adane, R. Baatz, S. Schönbrodt-Stitt, H. Bogena","doi":"10.3389/frwa.2023.1207654","DOIUrl":"https://doi.org/10.3389/frwa.2023.1207654","url":null,"abstract":"COPYRIGHT © 2023 Nasta, Adane, Baatz, Schönbrodt-Stitt and Bogena. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Editorial: Impact of anthropogenic disturbances on agroforestry ecosystems","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48855235","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":"Predicting streamflow with LSTM networks using global datasets","authors":"Katharina Wilbrand, Riccardo Taormina, Marie-claire ten Veldhuis, M. Visser, M. Hrachowitz, J. Nuttall, R. Dahm","doi":"10.3389/frwa.2023.1166124","DOIUrl":"https://doi.org/10.3389/frwa.2023.1166124","url":null,"abstract":"Streamflow predictions remain a challenge for poorly gauged and ungauged catchments. Recent research has shown that deep learning methods based on Long Short-Term Memory (LSTM) cells outperform process-based hydrological models for rainfall-runoff modeling, opening new possibilities for prediction in ungauged basins (PUB). These studies usually feature local datasets for model development, while predictions in ungauged basins at a global scale require training on global datasets. In this study, we develop LSTM models for over 500 catchments from the CAMELS-US data base using global ERA5 meteorological forcing and global catchment characteristics retrieved with the HydroMT tool. Comparison against an LSTM trained with local datasets shows that, while the latter generally yields superior performances due to the higher spatial resolution meteorological forcing (overall median daily NSE 0.54 vs. 0.71), training with ERA5 results in higher NSE in most catchments of Western and North-Western US (median daily NSE of 0.83 vs. 0.78). No significant changes in performance occur when substituting local with global data sources for deriving the catchment characteristics. These results encourage further research to develop LSTM models for worldwide predictions of streamflow in ungauged basins using available global datasets. Promising directions include training the models with streamflow data from different regions of the world and with higher quality meteorological forcing.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44396129","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":"Editorial: Data-driven machine learning for advancing hydrological and hydraulic predictability","authors":"Dan Lu, Tiantian Yang, Xiaofeng Liu","doi":"10.3389/frwa.2023.1215966","DOIUrl":"https://doi.org/10.3389/frwa.2023.1215966","url":null,"abstract":"COPYRIGHT © 2023 Lu, Yang and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Editorial: Data-driven machine learning for advancing hydrological and hydraulic predictability","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42181859","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}