Pub Date : 2023-11-07DOI: 10.5194/hess-27-3935-2023
Antonin Prijac, Laure Gandois, Pierre Taillardat, Marc-André Bourgault, Khawla Riahi, Alex Ponçot, Alain Tremblay, Michelle Garneau
Abstract. The magnitudes of dissolved organic carbon (DOC) exports from boreal peatlands to streams through lateral subsurface flow vary during the ice-free season. Peatland water table depth and the alternation of low and high flow in peat-draining streams are thought to drive this DOC export variability. However, calculation of the specific DOC exports from a peatland can be challenging considering the multiple potential DOC sources within the catchment. A calculation approach based on the hydrological connectivity between the peat and the stream could help to solve this issue, which is the approach used in the present research. This study took place from June 2018 to October 2019 in a boreal catchment in northeastern Canada, with 76.7 % of the catchment being covered by ombrotrophic peatland. The objectives were to (1) establish relationships between DOC exports from a headwater stream and the peatland hydrology; (2) quantify, at the catchment scale, the amount of DOC laterally exported to the draining stream; and (3) define the patterns of DOC mobilization during high-river-flow events. At the peatland headwater stream outlet, the DOC concentrations were monitored at a high frequency (hourly) using a fluorescent dissolved organic matter (fDOM) sensor, a proxy for DOC concentration. Hydrological variables, such as stream outlet discharge and peatland water table depth (WTD), were continuously monitored at hourly intervals for 2 years. Our results highlight the direct and delayed control of subsurface flow from peat to the stream and associated DOC exports. Rain events raised the peatland WTD, which increased hydrological connectivity between the peatland and the stream. This led to increased stream discharge (Q) and a delayed DOC concentration increase, typical of lateral subsurface flow. The magnitude of the WTD increase played a crucial role in influencing the quantity of DOC exported. Based on the observations that the peatland is the most important contributor to DOC exports at the catchment scale and that other DOC sources were negligible during high-flow periods, we propose a new approach to estimate the specific DOC exports attributable to the peatland by distinguishing between the surfaces used for calculation during high-flow and low-flow periods. In 2018–2019, 92.6 % of DOC was exported during flood events despite the fact that these flood events accounted for 59.1 % of the period. In 2019–2020, 93.8 % of DOC was exported during flood events, which represented 44.1 % of the period. Our analysis of individual flood events revealed three types of events and DOC mobilization patterns. The first type is characterized by high rainfall, leading to an important WTD increase that favours the connection between the peatland and the stream and leading to high DOC exports. The second is characterized by a large WTD increase succeeding a previous event that had depleted DOC available to be transferred to the stream, leading to low DOC exports. T
{"title":"Hydrological connectivity controls dissolved organic carbon exports in a peatland-dominated boreal catchment stream","authors":"Antonin Prijac, Laure Gandois, Pierre Taillardat, Marc-André Bourgault, Khawla Riahi, Alex Ponçot, Alain Tremblay, Michelle Garneau","doi":"10.5194/hess-27-3935-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3935-2023","url":null,"abstract":"Abstract. The magnitudes of dissolved organic carbon (DOC) exports from boreal peatlands to streams through lateral subsurface flow vary during the ice-free season. Peatland water table depth and the alternation of low and high flow in peat-draining streams are thought to drive this DOC export variability. However, calculation of the specific DOC exports from a peatland can be challenging considering the multiple potential DOC sources within the catchment. A calculation approach based on the hydrological connectivity between the peat and the stream could help to solve this issue, which is the approach used in the present research. This study took place from June 2018 to October 2019 in a boreal catchment in northeastern Canada, with 76.7 % of the catchment being covered by ombrotrophic peatland. The objectives were to (1) establish relationships between DOC exports from a headwater stream and the peatland hydrology; (2) quantify, at the catchment scale, the amount of DOC laterally exported to the draining stream; and (3) define the patterns of DOC mobilization during high-river-flow events. At the peatland headwater stream outlet, the DOC concentrations were monitored at a high frequency (hourly) using a fluorescent dissolved organic matter (fDOM) sensor, a proxy for DOC concentration. Hydrological variables, such as stream outlet discharge and peatland water table depth (WTD), were continuously monitored at hourly intervals for 2 years. Our results highlight the direct and delayed control of subsurface flow from peat to the stream and associated DOC exports. Rain events raised the peatland WTD, which increased hydrological connectivity between the peatland and the stream. This led to increased stream discharge (Q) and a delayed DOC concentration increase, typical of lateral subsurface flow. The magnitude of the WTD increase played a crucial role in influencing the quantity of DOC exported. Based on the observations that the peatland is the most important contributor to DOC exports at the catchment scale and that other DOC sources were negligible during high-flow periods, we propose a new approach to estimate the specific DOC exports attributable to the peatland by distinguishing between the surfaces used for calculation during high-flow and low-flow periods. In 2018–2019, 92.6 % of DOC was exported during flood events despite the fact that these flood events accounted for 59.1 % of the period. In 2019–2020, 93.8 % of DOC was exported during flood events, which represented 44.1 % of the period. Our analysis of individual flood events revealed three types of events and DOC mobilization patterns. The first type is characterized by high rainfall, leading to an important WTD increase that favours the connection between the peatland and the stream and leading to high DOC exports. The second is characterized by a large WTD increase succeeding a previous event that had depleted DOC available to be transferred to the stream, leading to low DOC exports. T","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"102 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135539805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-06DOI: 10.5194/hess-27-3911-2023
Dongyu Feng, Zeli Tan, Donghui Xu, L. Ruby Leung
Abstract. Compound flooding is a type of flood event caused by multiple flood drivers. The associated risk has usually been assessed using statistics-based analyses or hydrodynamics-based numerical models. This study proposes a compound flood (CF) risk assessment (CFRA) framework for coastal regions in the contiguous United States (CONUS). In this framework, a large-scale river model is coupled with a global ocean reanalysis dataset to (a) evaluate the CF exposure related to the coastal backwater effects on river basins, and (b) generate spatially distributed data for analyzing the CF hazard using a bivariate statistical model of river discharge and storm surge. The two kinds of risk are also combined to achieve a holistic understanding of the continental-scale CF risk. The estimated CF risk shows remarkable inter- and intra-basin variabilities along the CONUS coast with more variabilities in the CF hazard over the US west and Gulf coastal basins. Different risk assessment methods present significantly different patterns in a few key regions such as the San Francisco Bay area, the lower Mississippi River, and Puget Sound. Our results highlight the need to weigh different CF risk measures and avoid using single statistics-based or hydrodynamics-based CFRAs. Uncertainty sources in these CFRAs include the use of gauge observations, which cannot account for the flow physics or resolve the spatial variability of risks, and underestimations of the flood extremes and the dependence of CF drivers in large-scale models, highlighting the importance of understanding the CF risks for developing a more robust CFRA.
{"title":"Understanding the compound flood risk along the coast of the contiguous United States","authors":"Dongyu Feng, Zeli Tan, Donghui Xu, L. Ruby Leung","doi":"10.5194/hess-27-3911-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3911-2023","url":null,"abstract":"Abstract. Compound flooding is a type of flood event caused by multiple flood drivers. The associated risk has usually been assessed using statistics-based analyses or hydrodynamics-based numerical models. This study proposes a compound flood (CF) risk assessment (CFRA) framework for coastal regions in the contiguous United States (CONUS). In this framework, a large-scale river model is coupled with a global ocean reanalysis dataset to (a) evaluate the CF exposure related to the coastal backwater effects on river basins, and (b) generate spatially distributed data for analyzing the CF hazard using a bivariate statistical model of river discharge and storm surge. The two kinds of risk are also combined to achieve a holistic understanding of the continental-scale CF risk. The estimated CF risk shows remarkable inter- and intra-basin variabilities along the CONUS coast with more variabilities in the CF hazard over the US west and Gulf coastal basins. Different risk assessment methods present significantly different patterns in a few key regions such as the San Francisco Bay area, the lower Mississippi River, and Puget Sound. Our results highlight the need to weigh different CF risk measures and avoid using single statistics-based or hydrodynamics-based CFRAs. Uncertainty sources in these CFRAs include the use of gauge observations, which cannot account for the flow physics or resolve the spatial variability of risks, and underestimations of the flood extremes and the dependence of CF drivers in large-scale models, highlighting the importance of understanding the CF risks for developing a more robust CFRA.","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"30 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135679490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-03DOI: 10.5194/hess-27-3895-2023
Wenqian Mao, Wenyu Zhang, Menggang Kou
Abstract. In order to improve our understanding of the characteristics of raindrop size distribution (DSD) over complex mountainous terrain, the differences in DSD over the southern slopes, northern slopes, and interior of the Qilian Mountains were analyzed using 6 months of observations. For all rainfall events, the number concentrations of small and large raindrops in the interior and on the southern slopes were greater than on the northern slopes, but midsize raindrops were less. The DSD spectrum of the interior was more variable and differed significantly from that of the northern slopes. The differences in the normalized intercept parameters of the DSD for stratiform and convective rainfall were 8.3 % and 10.4 %, respectively, and those of the mass-weighted mean diameters were 10.0 % and 23.4 %, respectively, while the standard deviations of DSD parameters at interior sites were larger. The differences in the coefficient and exponent of the Z–R relationship were 2.5 % and 10.7 %, respectively, with an increasing value of the coefficient from the southern to the northern slopes for stratiform rainfall but the opposite for convective rainfall. In addition, the DSD characteristics and Z–R relationships were more similar at the ipsilateral sites and had smaller differences between the southern slopes and interior of the mountains.
{"title":"Statistical characteristics of raindrop size distribution during rainy seasons in complicated mountain terrain","authors":"Wenqian Mao, Wenyu Zhang, Menggang Kou","doi":"10.5194/hess-27-3895-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3895-2023","url":null,"abstract":"Abstract. In order to improve our understanding of the characteristics of raindrop size distribution (DSD) over complex mountainous terrain, the differences in DSD over the southern slopes, northern slopes, and interior of the Qilian Mountains were analyzed using 6 months of observations. For all rainfall events, the number concentrations of small and large raindrops in the interior and on the southern slopes were greater than on the northern slopes, but midsize raindrops were less. The DSD spectrum of the interior was more variable and differed significantly from that of the northern slopes. The differences in the normalized intercept parameters of the DSD for stratiform and convective rainfall were 8.3 % and 10.4 %, respectively, and those of the mass-weighted mean diameters were 10.0 % and 23.4 %, respectively, while the standard deviations of DSD parameters at interior sites were larger. The differences in the coefficient and exponent of the Z–R relationship were 2.5 % and 10.7 %, respectively, with an increasing value of the coefficient from the southern to the northern slopes for stratiform rainfall but the opposite for convective rainfall. In addition, the DSD characteristics and Z–R relationships were more similar at the ipsilateral sites and had smaller differences between the southern slopes and interior of the mountains.","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"13 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135873910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-02DOI: 10.5194/hess-27-3875-2023
Ana Ramos Oliveira, Tiago Brito Ramos, Lígia Pinto, Ramiro Neves
Abstract. Knowledge about streamflow regimes and values is essential for different activities and situations in which justified decisions must be made. However, streamflow behavior is commonly assumed to be non-linear, being controlled by various mechanisms that act on different temporal and spatial scales, making its estimation challenging. An example is the construction and operation of infrastructures such as dams and reservoirs in rivers. The challenges faced by modelers to correctly describe the impact of dams on hydrological systems are considerable. In this study, an already implemented solution of the MOHID-Land (where MOHID stands for HYDrodinamic MOdel, or MOdelo HIDrodinâmico in Portuguese) model for a natural flow regime in the Ulla River basin was considered as a baseline. The watershed referred to includes three reservoirs. Outflow values were estimated considering a basic operation rule for two of them (run-of-the-river dams) and considering a data-driven model of a convolutional long short-term memory (CLSTM) type for the other (high-capacity dam). The outflow values obtained with the CLSTM model were imposed in the hydrological model, while the hydrological model fed the CLSTM model with the level and the inflow of the reservoir. This coupled system was evaluated daily using two hydrometric stations located downstream of the reservoirs, resulting in an improved performance compared with the baseline application. The analysis of the modeled values with and without reservoirs further demonstrated that considering dams' operations in the hydrological model resulted in an increase in the streamflow during the dry season and a decrease during the wet season but with no differences in the average streamflow. The coupled system is thus a promising solution for improving streamflow estimates in modified catchments.
摘要在不同的活动和情况下，必须做出合理的决定，关于水流状况和价值的知识至关重要。然而，水流行为通常被认为是非线性的，受到各种作用于不同时间和空间尺度的机制的控制，这使得其估计具有挑战性。例如，河流中的水坝和水库等基础设施的建设和运营。建模者在正确描述大坝对水文系统的影响方面面临着相当大的挑战。在这项研究中，已经实施的MOHID- land (MOHID代表水力模型，或葡萄牙语MOdelo hidrodin mico)模型解决方案被认为是乌拉河流域自然流动状况的基线。这里所说的分水岭包括三个水库。考虑其中两个(河流大坝)的基本操作规则和考虑另一个(高容量大坝)的卷积长短期记忆(CLSTM)类型的数据驱动模型，估算流出值。利用CLSTM模型得到的流出量被施加到水文模型中，而水文模型将水库的水位和流入量馈送到CLSTM模型中。该耦合系统每天使用位于水库下游的两个水文测量站进行评估，结果与基线应用相比，性能有所提高。对有水库和无水库模型值的分析进一步表明，在水文模型中考虑大坝的运行导致旱季流量增加，雨季流量减少，但平均流量没有差异。因此，耦合系统是一种有希望的解决方案，可以改善改良集水区的流量估算。
{"title":"Direct integration of reservoirs' operations in a hydrological model for streamflow estimation: coupling a CLSTM model with MOHID-Land","authors":"Ana Ramos Oliveira, Tiago Brito Ramos, Lígia Pinto, Ramiro Neves","doi":"10.5194/hess-27-3875-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3875-2023","url":null,"abstract":"Abstract. Knowledge about streamflow regimes and values is essential for different activities and situations in which justified decisions must be made. However, streamflow behavior is commonly assumed to be non-linear, being controlled by various mechanisms that act on different temporal and spatial scales, making its estimation challenging. An example is the construction and operation of infrastructures such as dams and reservoirs in rivers. The challenges faced by modelers to correctly describe the impact of dams on hydrological systems are considerable. In this study, an already implemented solution of the MOHID-Land (where MOHID stands for HYDrodinamic MOdel, or MOdelo HIDrodinâmico in Portuguese) model for a natural flow regime in the Ulla River basin was considered as a baseline. The watershed referred to includes three reservoirs. Outflow values were estimated considering a basic operation rule for two of them (run-of-the-river dams) and considering a data-driven model of a convolutional long short-term memory (CLSTM) type for the other (high-capacity dam). The outflow values obtained with the CLSTM model were imposed in the hydrological model, while the hydrological model fed the CLSTM model with the level and the inflow of the reservoir. This coupled system was evaluated daily using two hydrometric stations located downstream of the reservoirs, resulting in an improved performance compared with the baseline application. The analysis of the modeled values with and without reservoirs further demonstrated that considering dams' operations in the hydrological model resulted in an increase in the streamflow during the dry season and a decrease during the wet season but with no differences in the average streamflow. The coupled system is thus a promising solution for improving streamflow estimates in modified catchments.","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"15 15","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135973204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-01DOI: 10.5194/hess-27-3851-2023
Adrian Dahlmann, Mathias Hoffmann, Gernot Verch, Marten Schmidt, Michael Sommer, Jürgen Augustin, Maren Dubbert
Abstract. In the light of the ongoing global climate crisis and the related increases in extreme hydrological events, it is crucial to assess ecosystem resilience and – in agricultural systems – to ensure sustainable management and food security. For this purpose, a comprehensive understanding of ecosystem water cycle budgets and spatiotemporal dynamics is indispensable. Evapotranspiration (ET) plays a pivotal role in returning up to 90 % of incoming precipitation back to the atmosphere. Here, we studied the impacts of soil types and management on an agroecosystem's seasonal cumulative ET (ETsum) and agronomic water use efficiency (WUEagro, the dry matter per unit of water used by the crop). To do so, a plot experiment with winter rye (17 September 2020 to 30 June 2021) was conducted in an eroded cropland which is located in the hilly and dry ground moraine landscape of the Uckermark region in northeastern Germany. Along the experimental plot (110 m × 16 m), two closed chambers were mounted on a robotic gantry crane system (FluxCrane as part of the AgroFlux platform) and used to determine ET. Three soil types representing the full soil erosion gradient related to the hummocky ground moraine landscape (extremely eroded: Calcaric Regosol; strongly eroded: Nudiargic Luvisol; non-eroded: Calcic Luvisol) and additional topsoil dilution (topsoil removal and subsoil admixture) were investigated (randomized block design, three replicates per treatment). Five different modeling approaches were used and compared in the light of their potential for reliable ETsum over the entire crop cultivation period and to reproduce short-term (e.g., diurnal) water flux dynamics. While machine-learning approaches such as support vector machines (SVMs) and artificial neural networks (with Bayesian regularization; ANN_BR) generally performed well during calibration, SVMs also provided a satisfactory prediction of measured ET during validation (k-fold cross-validation, k=5). We found significant differences in dry biomass (DM) and small trends in ETsum between soil types, resulting in different WUEagro. The extremely eroded Calcaric Regosol showed an up to 46 % lower ETsum and up to 54 % lower WUEagro compared to the non-eroded Calcic Luvisol. The key period contributing to 70 % of ETsum spanned the beginning of stem elongation in April to the harvest in June. However, differences in the ETsum between soil types and topsoil dilution resulted predominantly from small differences between the treatments throughout the cultivation rather than only during this short period of time.
摘要鉴于持续的全球气候危机和与之相关的极端水文事件的增加，评估生态系统的复原力以及在农业系统中确保可持续管理和粮食安全至关重要。为此，全面了解生态系统水循环收支和时空动态是必不可少的。蒸散发(ET)在将90%的降水返回大气中起着关键作用。本文研究了土壤类型和管理对农业生态系统季节累积ET (ETsum)和作物单位水分利用效率(WUEagro)的影响。为此，在位于德国东北部乌克尔马克地区丘陵和干地冰碛地貌的侵蚀农田中进行了冬季黑麦的地块试验(2020年9月17日至2021年6月30日)。沿着实验地块(110 m × 16 m)，两个封闭的室安装在机器人龙门起重机系统(FluxCrane作为AgroFlux平台的一部分)上，用于确定ET。三种土壤类型代表与丘状地面冰碛景观相关的完整土壤侵蚀梯度(严重侵蚀:Calcaric Regosol;强烈侵蚀:Nudiargic Luvisol;研究了非侵蚀:钙Luvisol)和额外的表土稀释(表土去除和底土外加剂)(随机区组设计，每个处理3个重复)。使用了五种不同的建模方法，并根据它们在整个作物种植期间可靠的ETsum的潜力和再现短期(如昼夜)水通量动态的潜力进行了比较。而机器学习方法，如支持向量机(svm)和人工神经网络(与贝叶斯正则化;ANN_BR)在校准期间通常表现良好，支持向量机在验证期间也提供了令人满意的预测测量ET (k-fold交叉验证，k=5)。我们发现不同土壤类型的干生物量(DM)差异显著，ETsum趋势较小，导致不同的WUEagro。与未被侵蚀的钙质露露醇相比，极度侵蚀的钙质露露醇的ETsum降低了46%，wuegro降低了54%。4月茎秆开始伸长至6月收获，是占总产量70%的关键时期。然而，土壤类型和表土稀释度之间的ETsum差异主要是由于整个栽培过程中处理之间的微小差异造成的，而不仅仅是在这短时间内。
{"title":"Benefits of a robotic chamber system for determining evapotranspiration in an erosion-affected, heterogeneous cropland","authors":"Adrian Dahlmann, Mathias Hoffmann, Gernot Verch, Marten Schmidt, Michael Sommer, Jürgen Augustin, Maren Dubbert","doi":"10.5194/hess-27-3851-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3851-2023","url":null,"abstract":"Abstract. In the light of the ongoing global climate crisis and the related increases in extreme hydrological events, it is crucial to assess ecosystem resilience and – in agricultural systems – to ensure sustainable management and food security. For this purpose, a comprehensive understanding of ecosystem water cycle budgets and spatiotemporal dynamics is indispensable. Evapotranspiration (ET) plays a pivotal role in returning up to 90 % of incoming precipitation back to the atmosphere. Here, we studied the impacts of soil types and management on an agroecosystem's seasonal cumulative ET (ETsum) and agronomic water use efficiency (WUEagro, the dry matter per unit of water used by the crop). To do so, a plot experiment with winter rye (17 September 2020 to 30 June 2021) was conducted in an eroded cropland which is located in the hilly and dry ground moraine landscape of the Uckermark region in northeastern Germany. Along the experimental plot (110 m × 16 m), two closed chambers were mounted on a robotic gantry crane system (FluxCrane as part of the AgroFlux platform) and used to determine ET. Three soil types representing the full soil erosion gradient related to the hummocky ground moraine landscape (extremely eroded: Calcaric Regosol; strongly eroded: Nudiargic Luvisol; non-eroded: Calcic Luvisol) and additional topsoil dilution (topsoil removal and subsoil admixture) were investigated (randomized block design, three replicates per treatment). Five different modeling approaches were used and compared in the light of their potential for reliable ETsum over the entire crop cultivation period and to reproduce short-term (e.g., diurnal) water flux dynamics. While machine-learning approaches such as support vector machines (SVMs) and artificial neural networks (with Bayesian regularization; ANN_BR) generally performed well during calibration, SVMs also provided a satisfactory prediction of measured ET during validation (k-fold cross-validation, k=5). We found significant differences in dry biomass (DM) and small trends in ETsum between soil types, resulting in different WUEagro. The extremely eroded Calcaric Regosol showed an up to 46 % lower ETsum and up to 54 % lower WUEagro compared to the non-eroded Calcic Luvisol. The key period contributing to 70 % of ETsum spanned the beginning of stem elongation in April to the harvest in June. However, differences in the ETsum between soil types and topsoil dilution resulted predominantly from small differences between the treatments throughout the cultivation rather than only during this short period of time.","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"162 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135325494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-27DOI: 10.5194/hess-27-3803-2023
Xiangfu Kong, Jiawen Yang, Ke Xu, Bo Dong, Shan Jiang
Abstract. Hydrological parameters should pass through a careful calibration procedure before being used in a hydrological model that aids decision making. However, significant difficulty is encountered when applying existing calibration methods to regions in which runoff data are inadequate. To achieve accurate hydrological calibration for ungauged road networks, we propose a Bayesian updating framework that calibrates hydrological parameters based on taxi GPS data. Hydrological parameters were calibrated by adjusting their values such that the runoff generated by acceptable parameter sets corresponded to the road disruption periods during which no taxi points are observed. The proposed method was validated on 10 flood-prone roads in Shenzhen and the results revealed that the trends of runoff could be correctly predicted for 8 of 10 roads. This study demonstrates that the integration of hydrological models and taxi GPS data can provide viable alternative measures for model calibration to derive actionable insights for flood hazard mitigation.
{"title":"A Bayesian updating framework for calibrating the hydrological parameters of road networks using taxi GPS data","authors":"Xiangfu Kong, Jiawen Yang, Ke Xu, Bo Dong, Shan Jiang","doi":"10.5194/hess-27-3803-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3803-2023","url":null,"abstract":"Abstract. Hydrological parameters should pass through a careful calibration procedure before being used in a hydrological model that aids decision making. However, significant difficulty is encountered when applying existing calibration methods to regions in which runoff data are inadequate. To achieve accurate hydrological calibration for ungauged road networks, we propose a Bayesian updating framework that calibrates hydrological parameters based on taxi GPS data. Hydrological parameters were calibrated by adjusting their values such that the runoff generated by acceptable parameter sets corresponded to the road disruption periods during which no taxi points are observed. The proposed method was validated on 10 flood-prone roads in Shenzhen and the results revealed that the trends of runoff could be correctly predicted for 8 of 10 roads. This study demonstrates that the integration of hydrological models and taxi GPS data can provide viable alternative measures for model calibration to derive actionable insights for flood hazard mitigation.","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136262438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-27DOI: 10.5194/hess-27-3823-2023
Bas J. M. Wullems, Claudia C. Brauer, Fedor Baart, Albrecht H. Weerts
Abstract. Estuarine salt intrusion causes problems with freshwater availability in many deltas. Water managers require timely and accurate forecasts to be able to mitigate and adapt to salt intrusion. Data-driven models derived with machine learning are ideally suited for this, as they can mimic complex non-linear systems and are computationally efficient. We set up a long short-term memory (LSTM) model to forecast salt intrusion in the Rhine–Meuse delta, the Netherlands. Inputs for this model are chloride concentrations, water levels, discharges and wind speed, measured at nine locations. It forecasts daily minimum, mean and maximum chloride concentrations up to 7 d ahead at Krimpen aan den IJssel, an important location for freshwater provision. The model forecasts baseline concentrations and peak timing well but peak height is underestimated, a problem that becomes worse with increasing lead time. Between lead times of 1 and 7 d, forecast precision declines from 0.9 to 0.7 and forecast recall declines from 0.7 to 0.5 on average. Given these results, we aim to extend the model to other locations in the delta. We expect that a similar setup can work in other deltas, especially those with a similar or simpler channel network.
{"title":"Forecasting estuarine salt intrusion in the Rhine–Meuse delta using an LSTM model","authors":"Bas J. M. Wullems, Claudia C. Brauer, Fedor Baart, Albrecht H. Weerts","doi":"10.5194/hess-27-3823-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3823-2023","url":null,"abstract":"Abstract. Estuarine salt intrusion causes problems with freshwater availability in many deltas. Water managers require timely and accurate forecasts to be able to mitigate and adapt to salt intrusion. Data-driven models derived with machine learning are ideally suited for this, as they can mimic complex non-linear systems and are computationally efficient. We set up a long short-term memory (LSTM) model to forecast salt intrusion in the Rhine–Meuse delta, the Netherlands. Inputs for this model are chloride concentrations, water levels, discharges and wind speed, measured at nine locations. It forecasts daily minimum, mean and maximum chloride concentrations up to 7 d ahead at Krimpen aan den IJssel, an important location for freshwater provision. The model forecasts baseline concentrations and peak timing well but peak height is underestimated, a problem that becomes worse with increasing lead time. Between lead times of 1 and 7 d, forecast precision declines from 0.9 to 0.7 and forecast recall declines from 0.7 to 0.5 on average. Given these results, we aim to extend the model to other locations in the delta. We expect that a similar setup can work in other deltas, especially those with a similar or simpler channel network.","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136318300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. Seasonal variation and influencing factors of river water isotopes were investigated in the Xiangjiang River basin located in the East Asian monsoon region. This investigation involved comprehensive sampling of daily precipitation and river water with a 5 d interval as well as observing hydrometeorological factors spanning 13 hydrological years from January 2010 to December 2022, combined with the temporal and spatial correlation analyses based on linear regression and the isotopic Atmospheric Water Balance Model. Key findings are as follows: river water δ2H (δ2HR) exhibited significant seasonal variation, with the most positive and negative values occurring in the spring flood period and summer drought period, respectively, in alignment with those observed in precipitation. The correlations of the δ2HR with corresponding hydrometeorological factors with a 5 d interval were commonly weak due to the seasonality of precipitation isotopes and mixing of various water bodies within the basin, but the changes in the runoff (ΔR) and δ2HR (Δδ2HR) between two contiguous samplings with 5 d or higher intervals showed significant responses to the corresponding accumulated precipitation and evaporation. Prolonged rainless intervals with high evaporation rates in 2013 and 2022 as well as significant precipitation events in major flood periods in 2011 and 2017 had a significant impact on the δ2HR and runoff discharge. However, the most positive δ2HR values were primarily influenced by precipitation input with the most enriched isotopes in the spring flood period, while the moderately isotope-depleted precipitation during limited wetness conditions led to the most negative δ2HR. The spatial correlation analysis between water isotopes and hydrometeorological factors at the observing site and in the surrounding regions supported the representation of the Changsha site in the Xiangjiang River basin. These results underscore the potential of Δδ2HR as a proxy that reflects the seasonal variations in local environments, while caution is advised when interpreting extreme isotopic signals in river water. Overall, this study provides insights into the seasonal variation, extreme signal interpreting, and controlling factors of δ2HR in the study area, which was valuable for paleoclimate reconstruction and establishment of isotope hydrologic models.
{"title":"Seasonal variation and influence factors of river water isotopes in the East Asian monsoon region: a case study in the Xiangjiang River basin spanning 13 hydrological years","authors":"Xiong Xiao, Xinping Zhang, Zhuoyong Xiao, Zhiguo Rao, Xinguang He, Cicheng Zhang","doi":"10.5194/hess-27-3783-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3783-2023","url":null,"abstract":"Abstract. Seasonal variation and influencing factors of river water isotopes were investigated in the Xiangjiang River basin located in the East Asian monsoon region. This investigation involved comprehensive sampling of daily precipitation and river water with a 5 d interval as well as observing hydrometeorological factors spanning 13 hydrological years from January 2010 to December 2022, combined with the temporal and spatial correlation analyses based on linear regression and the isotopic Atmospheric Water Balance Model. Key findings are as follows: river water δ2H (δ2HR) exhibited significant seasonal variation, with the most positive and negative values occurring in the spring flood period and summer drought period, respectively, in alignment with those observed in precipitation. The correlations of the δ2HR with corresponding hydrometeorological factors with a 5 d interval were commonly weak due to the seasonality of precipitation isotopes and mixing of various water bodies within the basin, but the changes in the runoff (ΔR) and δ2HR (Δδ2HR) between two contiguous samplings with 5 d or higher intervals showed significant responses to the corresponding accumulated precipitation and evaporation. Prolonged rainless intervals with high evaporation rates in 2013 and 2022 as well as significant precipitation events in major flood periods in 2011 and 2017 had a significant impact on the δ2HR and runoff discharge. However, the most positive δ2HR values were primarily influenced by precipitation input with the most enriched isotopes in the spring flood period, while the moderately isotope-depleted precipitation during limited wetness conditions led to the most negative δ2HR. The spatial correlation analysis between water isotopes and hydrometeorological factors at the observing site and in the surrounding regions supported the representation of the Changsha site in the Xiangjiang River basin. These results underscore the potential of Δδ2HR as a proxy that reflects the seasonal variations in local environments, while caution is advised when interpreting extreme isotopic signals in river water. Overall, this study provides insights into the seasonal variation, extreme signal interpreting, and controlling factors of δ2HR in the study area, which was valuable for paleoclimate reconstruction and establishment of isotope hydrologic models.","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"22 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134908749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-25DOI: 10.5194/hess-27-3743-2023
Julia Pfeffer, Anny Cazenave, Alejandro Blazquez, Bertrand Decharme, Simon Munier, Anne Barnoud
Abstract. The GRACE (Gravity Recovery And Climate Experiment) satellite gravity mission enables global monitoring of the mass transport within the Earth's system, leading to unprecedented advances in our understanding of the global water cycle in a changing climate. This study focuses on the quantification of changes in terrestrial water storage with respect to the temporal average based on an ensemble of GRACE solutions and two global hydrological models. Significant changes in terrestrial water storage are detected at pluri-annual and decadal timescales in GRACE satellite gravity data that are generally underestimated by global hydrological models though consistent with precipitation. The largest differences (more than 20 cm in equivalent water height) are observed in South America (Amazon, São Francisco and Paraná River basins) and tropical Africa (Congo, Zambezi and Okavango River basins). Smaller but significant (a few centimetres) differences are observed worldwide. While the origin of such differences is unknown, part of it is likely to be climate-related and at least partially due to inaccurate predictions of hydrological models. Pluri-annual to decadal changes in the terrestrial water cycle may indeed be overlooked in global hydrological models due to inaccurate meteorological forcing (e.g. precipitation), unresolved groundwater processes, anthropogenic influences, changing vegetation cover and limited calibration/validation datasets. Significant differences between GRACE satellite measurements and hydrological model predictions have been identified, quantified and characterised in the present study. Efforts must be made to better understand the gap between methods at both pluri-annual and decadal timescales, which challenges the use of global hydrological models for the prediction of the evolution of water resources in changing climate conditions.
{"title":"Assessment of pluri-annual and decadal changes in terrestrial water storage predicted by global hydrological models in comparison with the GRACE satellite gravity mission","authors":"Julia Pfeffer, Anny Cazenave, Alejandro Blazquez, Bertrand Decharme, Simon Munier, Anne Barnoud","doi":"10.5194/hess-27-3743-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3743-2023","url":null,"abstract":"Abstract. The GRACE (Gravity Recovery And Climate Experiment) satellite gravity mission enables global monitoring of the mass transport within the Earth's system, leading to unprecedented advances in our understanding of the global water cycle in a changing climate. This study focuses on the quantification of changes in terrestrial water storage with respect to the temporal average based on an ensemble of GRACE solutions and two global hydrological models. Significant changes in terrestrial water storage are detected at pluri-annual and decadal timescales in GRACE satellite gravity data that are generally underestimated by global hydrological models though consistent with precipitation. The largest differences (more than 20 cm in equivalent water height) are observed in South America (Amazon, São Francisco and Paraná River basins) and tropical Africa (Congo, Zambezi and Okavango River basins). Smaller but significant (a few centimetres) differences are observed worldwide. While the origin of such differences is unknown, part of it is likely to be climate-related and at least partially due to inaccurate predictions of hydrological models. Pluri-annual to decadal changes in the terrestrial water cycle may indeed be overlooked in global hydrological models due to inaccurate meteorological forcing (e.g. precipitation), unresolved groundwater processes, anthropogenic influences, changing vegetation cover and limited calibration/validation datasets. Significant differences between GRACE satellite measurements and hydrological model predictions have been identified, quantified and characterised in the present study. Efforts must be made to better understand the gap between methods at both pluri-annual and decadal timescales, which challenges the use of global hydrological models for the prediction of the evolution of water resources in changing climate conditions.","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135169079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-25DOI: 10.5194/hess-27-3769-2023
Tamara Michaelis, Anja Wunderlich, Thomas Baumann, Juergen Geist, Florian Einsiedl
Abstract. The hyporheic zone (HZ) is of major importance for carbon and nutrient cycling as well as for the ecological health of stream ecosystems, but it is also a hot spot of greenhouse gas production. Biogeochemical observations in this ecotone are complicated by a very high spatial heterogeneity and temporal dynamics. It is especially difficult to monitor changes in gas concentrations over time because this requires pore-water extraction, which may negatively affect the quality of gas analyses through gas losses or other sampling artifacts. In this field study, we wanted to test the effect of different pumping rates on gas measurements and installed Rhizon samplers for repeated pore-water extraction in the HZ of a small stream. Pore-water sampling at different pumping rates was combined with an optical sensor unit for in situ measurements of dissolved oxygen and a depth-resolved temperature monitoring system. While Rhizon samplers were found to be highly suitable for pore-water sampling of dissolved solutes, measured gas concentrations, here CH4, showed a strong dependency of the pumping rate during sample extraction, and an isotopic shift in gas samples became evident. This was presumably caused by a different behavior of water and gas phase in the pore space. The manufactured oxygen sensor could locate the oxic–anoxic interface with very high precision. This is ecologically important and allows us to distinguish between aerobic and anaerobic processes. Temperature data could not only be used to estimate vertical hyporheic exchange but also depicted sedimentation and erosion processes. Overall, the combined approach was found to be a promising and effective tool to acquire time-resolved data for the quantification of biogeochemical processes in the HZ with high spatial resolution.
{"title":"Technical note: Testing the effect of different pumping rates on pore-water sampling for ions, stable isotopes, and gas concentrations in the hyporheic zone","authors":"Tamara Michaelis, Anja Wunderlich, Thomas Baumann, Juergen Geist, Florian Einsiedl","doi":"10.5194/hess-27-3769-2023","DOIUrl":"https://doi.org/10.5194/hess-27-3769-2023","url":null,"abstract":"Abstract. The hyporheic zone (HZ) is of major importance for carbon and nutrient cycling as well as for the ecological health of stream ecosystems, but it is also a hot spot of greenhouse gas production. Biogeochemical observations in this ecotone are complicated by a very high spatial heterogeneity and temporal dynamics. It is especially difficult to monitor changes in gas concentrations over time because this requires pore-water extraction, which may negatively affect the quality of gas analyses through gas losses or other sampling artifacts. In this field study, we wanted to test the effect of different pumping rates on gas measurements and installed Rhizon samplers for repeated pore-water extraction in the HZ of a small stream. Pore-water sampling at different pumping rates was combined with an optical sensor unit for in situ measurements of dissolved oxygen and a depth-resolved temperature monitoring system. While Rhizon samplers were found to be highly suitable for pore-water sampling of dissolved solutes, measured gas concentrations, here CH4, showed a strong dependency of the pumping rate during sample extraction, and an isotopic shift in gas samples became evident. This was presumably caused by a different behavior of water and gas phase in the pore space. The manufactured oxygen sensor could locate the oxic–anoxic interface with very high precision. This is ecologically important and allows us to distinguish between aerobic and anaerobic processes. Temperature data could not only be used to estimate vertical hyporheic exchange but also depicted sedimentation and erosion processes. Overall, the combined approach was found to be a promising and effective tool to acquire time-resolved data for the quantification of biogeochemical processes in the HZ with high spatial resolution.","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"31 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135218802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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