Pub Date : 2024-12-12DOI: 10.1016/j.jhydrol.2024.132492
Yining Ma, Jiawei Ren, Shaozhong Kang, Jun Niu, Ling Tong
Conventional drought studies have predominantly focused on elucidating the temporal-spatial evolution of drought while neglecting research on drought propagation. Various degrees of correspondence exist within the same drought propagation mode. This study utilized the Standardized Precipitation Evapotranspiration Index (SPEI) and Vegetation Condition Index (VCI) to characterize meteorological drought (MD) and agricultural drought (AD). The temporal-spatial characteristics of drought in Northwest China (NWC) from 1982 to 2020 were examined. Subsequently, the interaction between AD and MD was investigated, encompassing correlation, time-lag, propagation characteristics, and primary modes of propagation. Then, the impacts of climate change (CC) and human activities (HA) on AD were individually assessed and quantified. Finally, the probability and return period of drought propagation in different degrees were predicted. The findings reveal that: (1) MD exhibited short duration, high frequency, and low severity, whereas AD was less frequent but endured longer and caused greater harm. In recent 40 years, MD has shown a decrease, while AD has worsened. (2) AD typically lagged behind MD by 1–3 months, with about 33.72 % of regions experiencing a time-lag of approximately 1 month. Generally, AD displayed a positive correlation with MD, although the adverse impact of MD on AD has lessened in the last decade. (3) The primary mode of drought propagation in NWC was “one-to-one,” while in Ningxia, Gansu, and southern Xinjiang, it was “multiple-to-one.” (4) The sensitivity of AD to different climatic environmental factors exhibited noteworthy geographical variations, with SPEI, soil moisture, and maximum temperature exerting a more substantial impact on AD. CC predominantly had a positive contribution with AD, whereas HA exhibited a negative contribution in 54.24 % of the regions. (5) Future MD was projected to mainly consist of light drought, with AD dominated by no, light, and severe drought. AD was more serious in Qinghai, Ningxia and northern Xinjiang. Different degree of MD can easily lead to the same degree or more severe AD. Analyses of the return period of drought revealed that severe AD may have a greater adverse impact on the agricultural development of NWC in the future.
传统的干旱研究主要侧重于阐明干旱的时空演变，而忽视了对干旱传播的研究。在同一种干旱传播模式下，存在不同程度的对应关系。本研究利用标准化降水蒸散指数（SPEI）和植被状况指数（VCI）来描述气象干旱（MD）和农业干旱（AD）的特征。研究了中国西北地区（NWC）1982-2020 年干旱的时空特征。随后，研究了 AD 和 MD 之间的相互作用，包括相关性、时滞、传播特征和主要传播模式。然后，分别评估和量化了气候变化（CC）和人类活动（HA）对 AD 的影响。最后，预测了不同程度干旱传播的概率和回归期。研究结果表明(1) MD 表现为持续时间短、频率高、严重程度低，而 AD 频率较低，但持续时间较长，造成的危害较大。近 40 年来，MD 呈下降趋势，而 AD 呈恶化趋势。(2) 急性心肌梗死通常比急性心肌梗死滞后 1-3 个月，约 33.72% 的地区滞后约 1 个月。一般情况下，旱情与墒情呈正相关，但近十年来墒情对旱情的不利影响有所减弱。(3) 干旱在西北干旱区的主要传播方式是 "一对一"，而在宁夏、甘肃和新疆南部则是 "多对一"。(4) 干旱对不同气候环境因子的敏感性表现出显著的地域差异，SPEI、土壤水分和最高气温对干旱的影响更大。在 54.24% 的地区，CC 对平均日产量的影响主要为正，而 HA 对平均日产量的影响为负。(5) 预计未来MD以轻旱为主，AD以无旱、轻旱和重旱为主。青海、宁夏和新疆北部的 AD 更为严重。不同程度的 MD 很容易导致相同程度或更严重的 AD。对干旱重现期的分析表明，严重干旱对未来西北干旱带农业发展的不利影响可能更大。
{"title":"Spatial-temporal dynamics of meteorological and agricultural drought in Northwest China: Propagation, drivers and prediction","authors":"Yining Ma, Jiawei Ren, Shaozhong Kang, Jun Niu, Ling Tong","doi":"10.1016/j.jhydrol.2024.132492","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2024.132492","url":null,"abstract":"Conventional drought studies have predominantly focused on elucidating the temporal-spatial evolution of drought while neglecting research on drought propagation. Various degrees of correspondence exist within the same drought propagation mode. This study utilized the Standardized Precipitation Evapotranspiration Index (SPEI) and Vegetation Condition Index (VCI) to characterize meteorological drought (MD) and agricultural drought (AD). The temporal-spatial characteristics of drought in Northwest China (NWC) from 1982 to 2020 were examined. Subsequently, the interaction between AD and MD was investigated, encompassing correlation, time-lag, propagation characteristics, and primary modes of propagation. Then, the impacts of climate change (CC) and human activities (HA) on AD were individually assessed and quantified. Finally, the probability and return period of drought propagation in different degrees were predicted. The findings reveal that: (1) MD exhibited short duration, high frequency, and low severity, whereas AD was less frequent but endured longer and caused greater harm. In recent 40 years, MD has shown a decrease, while AD has worsened. (2) AD typically lagged behind MD by 1–3 months, with about 33.72 % of regions experiencing a time-lag of approximately 1 month. Generally, AD displayed a positive correlation with MD, although the adverse impact of MD on AD has lessened in the last decade. (3) The primary mode of drought propagation in NWC was “one-to-one,” while in Ningxia, Gansu, and southern Xinjiang, it was “multiple-to-one.” (4) The sensitivity of AD to different climatic environmental factors exhibited noteworthy geographical variations, with SPEI, soil moisture, and maximum temperature exerting a more substantial impact on AD. CC predominantly had a positive contribution with AD, whereas HA exhibited a negative contribution in 54.24 % of the regions. (5) Future MD was projected to mainly consist of light drought, with AD dominated by no, light, and severe drought. AD was more serious in Qinghai, Ningxia and northern Xinjiang. Different degree of MD can easily lead to the same degree or more severe AD. Analyses of the return period of drought revealed that severe AD may have a greater adverse impact on the agricultural development of NWC in the future.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"43 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825416","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 : 2024-12-12DOI: 10.1016/j.jhydrol.2024.132509
Junna Ning, Kunfu Pi, Xianjun Xie, Qianyong Liang, Philippe Van Cappellen, Yanxin Wang
Geogenic contaminants and emerging contaminants co-occur frequently in disturbed aquifer environments, complicating the evolution of geogenic contaminated groundwater and resultant health risk posed to human beings. The development of antimicrobial resistance (AMR) was found to affect critical microbial activities responsible for arsenic (As) mobilization, yet the underlying processes and mechanism remain undervalued from limited field investigation. By virtue of joint field campaign, molecular biological analysis, and hydrogeochemical modeling, this research provides novel insights into influence of cross-resistance between As and antibiotics on As biotransformation and enrichment in groundwater. Our basin-scale hydrogeological investigation reveals that lithological characteristics of Quaternary formations and associated regional groundwater flow regime led to gradual co-increase of antibiotic and As concentrations from recharge area to discharge area. While antibiotic resistance genes (ARGs) in groundwater exhibited spotty distribution pattern in the recharge area, they tended to accumulate in the discharge area. Consequently, microbially-mediated Fe(III)-oxide reduction was inhibited in groundwater subject to high-level antibiotics, whereas microbial SO42- reduction was sustained under high-antibiotic environmental stress. Moreover, cross-resistance was likely to develop after the accumulation of ARGs, thereby enhancing As biotransformation and re-migration. Hence, primary mechanism underlying As enrichment probably shifted from microbial dissolution of Fe(III) oxides to ARGs-driven As bio-migration in antibiotic-affected aquifers. These findings highlight the underestimated impact of AMR on evolution of geogenic As-contaminated groundwater in areas with significant antibiotic pollution. This research additionally warrants a careful re-assessment of in-situ groundwater remediation approaches in disturbed aquifer environments.
{"title":"Interactions between antibiotic resistance and arsenic metabolizing genes in geogenic contaminated groundwater: Consequence for arsenic migration","authors":"Junna Ning, Kunfu Pi, Xianjun Xie, Qianyong Liang, Philippe Van Cappellen, Yanxin Wang","doi":"10.1016/j.jhydrol.2024.132509","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2024.132509","url":null,"abstract":"Geogenic contaminants and emerging contaminants co-occur frequently in disturbed aquifer environments, complicating the evolution of geogenic contaminated groundwater and resultant health risk posed to human beings. The development of antimicrobial resistance (AMR) was found to affect critical microbial activities responsible for arsenic (As) mobilization, yet the underlying processes and mechanism remain undervalued from limited field investigation. By virtue of joint field campaign, molecular biological analysis, and hydrogeochemical modeling, this research provides novel insights into influence of cross-resistance between As and antibiotics on As biotransformation and enrichment in groundwater. Our basin-scale hydrogeological investigation reveals that lithological characteristics of Quaternary formations and associated regional groundwater flow regime led to gradual co-increase of antibiotic and As concentrations from recharge area to discharge area. While antibiotic resistance genes (ARGs) in groundwater exhibited spotty distribution pattern in the recharge area, they tended to accumulate in the discharge area. Consequently, microbially-mediated Fe(III)-oxide reduction was inhibited in groundwater subject to high-level antibiotics, whereas microbial SO<ce:inf loc=\"post\">4</ce:inf><ce:sup loc=\"post\">2-</ce:sup> reduction was sustained under high-antibiotic environmental stress. Moreover, cross-resistance was likely to develop after the accumulation of ARGs, thereby enhancing As biotransformation and re-migration. Hence, primary mechanism underlying As enrichment probably shifted from microbial dissolution of Fe(III) oxides to ARGs-driven As bio-migration in antibiotic-affected aquifers. These findings highlight the underestimated impact of AMR on evolution of geogenic As-contaminated groundwater in areas with significant antibiotic pollution. This research additionally warrants a careful re-assessment of in-situ groundwater remediation approaches in disturbed aquifer environments.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"1 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825412","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 : 2024-12-11DOI: 10.1016/j.jhydrol.2024.132489
Ikechukwu Kalu, Christopher E. Ndehedehe, Vagner G. Ferreira, Sreekanth Janardhanan, Mark J. Kennard
Soil moisture data is essential for estimating groundwater storage anomalies (GWSA) from the Gravity Recovery and Climate Experiment (GRACE) data, but the general lack of direct in-situ root-zone soil moisture observations has typically resulted in a reliance on modelled soil moisture estimates instead. These model-simulated soil moisture profiles – upper (0 to 10 cm), lower (10 to 100 cm), and deep layers (100 to 200 cm), are characterized by large uncertainties due to the simplification and parameterization of soil moisture processes in hydrological models. It is thus crucial to account for these uncertainties and understand how they affect the estimation of groundwater storage changes based on GRACE data. In this study, we evaluated the contributions and impacts of different soil moisture profiles on GRACE-derived groundwater storage (between 2002 and 2016) modelling uncertainties over the Murray Darling Basin (MDB) using statistical and machine learning regression. We observed that the lower layer exhibited the strongest correlation with base GWSA, particularly during 2006 to 2009 (r = 0.99, RMSE = 7.50 mm). Bootstrap analysis indicated that the lower layer consistently had the largest absolute coefficient weights, signifying its predominant influence on GWSA predictions. The deep layer contributed the least during 2010 to 2013, while the upper layer was highly dynamic and introduced a 26.8 % more uncertainty rating when compared to the lower layer. Regression analysis showed the lower layer maintained the smallest confidence interval widths, confirming its reliability. The Monte Carlo resampling corroborated these findings, with the lower layer maintaining the most consistent relationship with base GWSA across all periods. The lower layer’s steadier state and lower susceptibility to surface disturbances provided more accurate predictions than other layers. This study advances the modelling of groundwater storage from space by improving our understanding of the uncertainties introduced by the different soil moisture layers. It will be helpful for better and accurate freshwater reporting and management.
{"title":"Unravelling soil moisture uncertainties in GRACE groundwater modelling","authors":"Ikechukwu Kalu, Christopher E. Ndehedehe, Vagner G. Ferreira, Sreekanth Janardhanan, Mark J. Kennard","doi":"10.1016/j.jhydrol.2024.132489","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2024.132489","url":null,"abstract":"Soil moisture data is essential for estimating groundwater storage anomalies (GWSA) from the Gravity Recovery and Climate Experiment (GRACE) data, but the general lack of direct in-situ root-zone soil moisture observations has typically resulted in a reliance on modelled soil moisture estimates instead. These model-simulated soil moisture profiles – upper (0 to 10 cm), lower (10 to 100 cm), and deep layers (100 to 200 cm), are characterized by large uncertainties due to the simplification and parameterization of soil moisture processes in hydrological models. It is thus crucial to account for these uncertainties and understand how they affect the estimation of groundwater storage changes based on GRACE data. In this study, we evaluated the contributions and impacts of different soil moisture profiles on GRACE-derived groundwater storage (between 2002 and 2016) modelling uncertainties over the Murray Darling Basin (MDB) using statistical and machine learning regression. We observed that the lower layer exhibited the strongest correlation with base GWSA, particularly during 2006 to 2009 (r = 0.99, RMSE = 7.50 mm). Bootstrap analysis indicated that the lower layer consistently had the largest absolute coefficient weights, signifying its predominant influence on GWSA predictions. The deep layer contributed the least during 2010 to 2013, while the upper layer was highly dynamic and introduced a 26.8 % more uncertainty rating when compared to the lower layer. Regression analysis showed the lower layer maintained the smallest confidence interval widths, confirming its reliability. The Monte Carlo resampling corroborated these findings, with the lower layer maintaining the most consistent relationship with base GWSA across all periods. The lower layer’s steadier state and lower susceptibility to surface disturbances provided more accurate predictions than other layers. This study advances the modelling of groundwater storage from space by improving our understanding of the uncertainties introduced by the different soil moisture layers. It will be helpful for better and accurate freshwater reporting and management.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"23 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825417","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}
As the intensity and frequency of droughts increase, the vegetation community structure and terrestrial ecosystem are therefore threatened. However, the terrestrial ecosystem resilience under drought stress or its underlying drivers, remains poorly understood, hindering effective ecological protection and sustainable development efforts. Taking the Yellow River Basin (YRB) as an example, we constructed a resilience evaluation function by integrating the entropy weight method with the stability, resistance and recovery metrics. In general, the proposed resilience metric of terrestrial ecosystem under drought stress was proved to be reliable, highlighting a spatial pattern characterized by higher resilience in the southern regions and lower resilience in the northern areas. The forests exhibited greater resistance but slower recovery compared to grasslands, emerging as the most resilient vegetation type among the local ecosystems. The resilience pattern was largely dominated by precipitation (P), temperature (T) and plant biodiversity (PB), while P and T could have also indirect effects on resilience through PB. Moreover, we also found a significant threshold effect of PB on resilience. This study provides new insights into quantifying drought resilience and dominant drivers, which can help ecological protection and restoration of the YRB.
{"title":"Terrestrial ecosystem resilience to drought stress and driving mechanisms thereof in the Yellow River Basin, China","authors":"Xueying Zhu, Shengzhi Huang, Vijay P. Singh, Qiang Huang, Hongbo Zhang, Guoyong Leng, Liang Gao, Pei Li, Wenwen Guo, Jian Peng","doi":"10.1016/j.jhydrol.2024.132480","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2024.132480","url":null,"abstract":"As the intensity and frequency of droughts increase, the vegetation community structure and terrestrial ecosystem are therefore threatened. However, the terrestrial ecosystem resilience under drought stress or its underlying drivers, remains poorly understood, hindering effective ecological protection and sustainable development efforts. Taking the Yellow River Basin (YRB) as an example, we constructed a resilience evaluation function by integrating the entropy weight method with the stability, resistance and recovery metrics. In general, the proposed resilience metric of terrestrial ecosystem under drought stress was proved to be reliable, highlighting a spatial pattern characterized by higher resilience in the southern regions and lower resilience in the northern areas. The forests exhibited greater resistance but slower recovery compared to grasslands, emerging as the most resilient vegetation type among the local ecosystems. The resilience pattern was largely dominated by precipitation (P), temperature (T) and plant biodiversity (PB), while P and T could have also indirect effects on resilience through PB. Moreover, we also found a significant threshold effect of PB on resilience. This study provides new insights into quantifying drought resilience and dominant drivers, which can help ecological protection and restoration of the YRB.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"1 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825414","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 : 2024-12-11DOI: 10.1016/j.jhydrol.2024.132510
Cheng Sun, Shibo Chen, Qingqing Zuo, Lei Chen, Zhenyao Shen
Ditches and ponds are widely used in rural landscapes, forming integrated adaptation systems that play a pivotal role in reducing non-point source (NPS) pollution. However, existing semi-distributed models are not capable of accurately simulating pollution removals of ditches and ponds, resulting in a critical gap in integrating simulation, optimization, and spatial configuration for effective pollution control. To address this issue, the newly developed SWAT-DPS model was integrated with multi-objective optimization to construct an integrated framework for optimizing the layouts of ditches and ponds while effectively balancing environmental and economic benefits. This framework enables more accurate grid-scale simulation of pollution reduction of measures, offering more practical layout solutions. Results showed that implementing vegetated ditches, multiple ponds, and vegetation filter strips could reduce NPS pollutants by 20–60 %. Comparative analysis revealed the costs ranging from 0 to 6.28 × 10⁶ yuan, with all cost levels achieving required reductions in total nitrogen (TN) and total phosphorus (TP). Specifically, TN reductions exceeded 60 % in the medium-cost scheme, while TP reductions reached 60 % similarly in the high-cost scheme. This study provides a flexible framework for evaluating the removal efficiencies of NPS pollution, with fully consideration of the spatial configuration of ditch-pond system.
{"title":"Integration of SWAT-DPS and optimization algorithm for spatial design of ditch-pond systems in small agricultural catchments","authors":"Cheng Sun, Shibo Chen, Qingqing Zuo, Lei Chen, Zhenyao Shen","doi":"10.1016/j.jhydrol.2024.132510","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2024.132510","url":null,"abstract":"Ditches and ponds are widely used in rural landscapes, forming integrated adaptation systems that play a pivotal role in reducing non-point source (NPS) pollution. However, existing semi-distributed models are not capable of accurately simulating pollution removals of ditches and ponds, resulting in a critical gap in integrating simulation, optimization, and spatial configuration for effective pollution control. To address this issue, the newly developed SWAT-DPS model was integrated with multi-objective optimization to construct an integrated framework for optimizing the layouts of ditches and ponds while effectively balancing environmental and economic benefits. This framework enables more accurate grid-scale simulation of pollution reduction of measures, offering more practical layout solutions. Results showed that implementing vegetated ditches, multiple ponds, and vegetation filter strips could reduce NPS pollutants by 20–60 %. Comparative analysis revealed the costs ranging from 0 to 6.28 × 10⁶ yuan, with all cost levels achieving required reductions in total nitrogen (TN) and total phosphorus (TP). Specifically, TN reductions exceeded 60 % in the medium-cost scheme, while TP reductions reached 60 % similarly in the high-cost scheme. This study provides a flexible framework for evaluating the removal efficiencies of NPS pollution, with fully consideration of the spatial configuration of ditch-pond system.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"63 5 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825413","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 : 2024-12-11DOI: 10.1016/j.jhydrol.2024.132484
Vikas Kumar Das, Koustuv Debnath
The loss of land due to riverbank erosion is a crucial factor in shaping landforms and plays a significant role in fluvial geomorphology. Understanding and the quantification of the movement and the initiation of sediment particles are the key elements in various engineering and environmental studies. The entrainment and the transportation of sediment particles are controlled by many different physical processes in the sediment water interface. Among such processes, the characteristics of turbulence and the associated coherent structures within the flow are of utmost importance. Riverbank erosion is one of the major natural disasters and an issue of major concern. Flow turbulence plays an important role in riverbank erosion and in the shaping of the river planform. Eddies are pivotal in turbulence generation that sustain the random velocity fluctuations and continually distribute energy and exchange momentum through the eddy breakdown process, a feature absent in laminar flow. In this review paper a precise articulation of the characterization of turbulence parameters on riverbank erosion mechanism is presented together with different available river turbulence measurement techniques that are in use. Further, the investigations that explored the bank erosion process mechanisms both on natural riverbanks as well as in laboratory flumes in context of turbulence has also been discussed. Key insights include the impact of varying turbulence intensities on erosion rates, and the effectiveness of different turbulence parameters in the characterization of bank erosion. The review also identifies the gaps in the existing methodologies, emphasizing the need for standardizing the available techniques to enable cross-comparisons among studies. This paper provides a comprehensive summary of current measurement techniques for turbulence in riverbank regions, offering recommendations for future research and contributing valuable insights to the broader understanding of sediment transport and riverbank dynamics. Additionally, the discussion also outlines potential directions for future developments. This review paper in indented to discuss the characterisation of the turbulence parameters at the near bank region.
{"title":"Understanding riverbank erosion through the Lens of Turbulence: A review","authors":"Vikas Kumar Das, Koustuv Debnath","doi":"10.1016/j.jhydrol.2024.132484","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2024.132484","url":null,"abstract":"The loss of land due to riverbank erosion is a crucial factor in shaping landforms and plays a significant role in fluvial geomorphology. Understanding and the quantification of the movement and the initiation of sediment particles are the key elements in various engineering and environmental studies. The entrainment and the transportation of sediment particles are controlled by many different physical processes in the sediment water interface. Among such processes, the characteristics of turbulence and the associated coherent structures within the flow are of utmost importance. Riverbank erosion is one of the major natural disasters and an issue of major concern. Flow turbulence plays an important role in riverbank erosion and in the shaping of the river planform. Eddies are pivotal in turbulence generation that sustain the random velocity fluctuations and continually distribute energy and exchange momentum through the eddy breakdown process, a feature absent in laminar flow. In this review paper a precise articulation of the characterization of turbulence parameters on riverbank erosion mechanism is presented together with different available river turbulence measurement techniques that are in use. Further, the investigations that explored the bank erosion process mechanisms both on natural riverbanks as well as in laboratory flumes in context of turbulence has also been discussed. Key insights include the impact of varying turbulence intensities on erosion rates, and the effectiveness of different turbulence parameters in the characterization of bank erosion. The review also identifies the gaps in the existing methodologies, emphasizing the need for standardizing the available techniques to enable cross-comparisons among studies. This paper provides a comprehensive summary of current measurement techniques for turbulence in riverbank regions, offering recommendations for future research and contributing valuable insights to the broader understanding of sediment transport and riverbank dynamics. Additionally, the discussion also outlines potential directions for future developments. This review paper in indented to discuss the characterisation of the turbulence parameters at the near bank region.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"252 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825419","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 : 2024-12-11DOI: 10.1016/j.jhydrol.2024.132504
M. Girons Lopez, T. Bosshard, L. Crochemore, I.G. Pechlivanidis
Seasonal hydrological forecasts are vital for managing water resources and adapting to climate change, aiding in diverse planning and decision-making processes. Currently it is unknown how different forecasting methods, considering initial hydrological conditions and dynamic meteorological forcing, perform across the Swedish river systems, despite the significant socio-economic implications. Here we explore the drivers that mostly impact streamflow predictions and attribute the added quality of these predictions to local hydrological regimes. We compare the accuracy of seasonal streamflow forecasts driven by dynamic GCM-based meteorological forecasts with those generated by the Ensemble Streamflow Prediction (ESP) method. The analysis spans across about 39,500 sub-catchments in Sweden encompassing various climatic, geographical and human-influenced factors. Results show that the streamflow predictability varies in space due to the country’s diverse hydrological regimes. Regardless of the regime, updating the models to achieve the best possible initial conditions is crucial for enhancing forecast skill across all seasons for up to 4 months. GCM-based meteorological forcing notably improves short-term streamflow accuracy, showing significant impact particularly up to 4–8 weeks lead time depending on the local hydrological regime. In the snow-driven northern regions, ESP demonstrates superior performance over GCM-based streamflow forecasts in winter. Conversely, in the southern regions, where conditions are predominantly influenced by rainfall, GCM-based forecasts show higher performance up to 4–6 weeks ahead, regardless of the season. In river systems with high human influences, streamflow climatology outperforms ESP and GCM-based forecasts underscoring the challenges of accurately modelling artificial reservoir management and the need for better access to management data. These insights guide the development of an advanced national seasonal hydrological forecasting service, and highlight the need for region-specific forecasting strategies indicating areas where predictability is enhanced by improved monitoring, hence initial conditions, and/or meteorological forcings. Finally, we discuss the applicability of these forecasting methods to other regions worldwide, thereby placing our new insights within a global context.
{"title":"Leveraging GCM-based forecasts for enhanced seasonal streamflow prediction in diverse hydrological regimes","authors":"M. Girons Lopez, T. Bosshard, L. Crochemore, I.G. Pechlivanidis","doi":"10.1016/j.jhydrol.2024.132504","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2024.132504","url":null,"abstract":"Seasonal hydrological forecasts are vital for managing water resources and adapting to climate change, aiding in diverse planning and decision-making processes. Currently it is unknown how different forecasting methods, considering initial hydrological conditions and dynamic meteorological forcing, perform across the Swedish river systems, despite the significant socio-economic implications. Here we explore the drivers that mostly impact streamflow predictions and attribute the added quality of these predictions to local hydrological regimes. We compare the accuracy of seasonal streamflow forecasts driven by dynamic GCM-based meteorological forecasts with those generated by the Ensemble Streamflow Prediction (ESP) method. The analysis spans across about 39,500 sub-catchments in Sweden encompassing various climatic, geographical and human-influenced factors. Results show that the streamflow predictability varies in space due to the country’s diverse hydrological regimes. Regardless of the regime, updating the models to achieve the best possible initial conditions is crucial for enhancing forecast skill across all seasons for up to 4 months. GCM-based meteorological forcing notably improves short-term streamflow accuracy, showing significant impact particularly up to 4–8 weeks lead time depending on the local hydrological regime. In the snow-driven northern regions, ESP demonstrates superior performance over GCM-based streamflow forecasts in winter. Conversely, in the southern regions, where conditions are predominantly influenced by rainfall, GCM-based forecasts show higher performance up to 4–6 weeks ahead, regardless of the season. In river systems with high human influences, streamflow climatology outperforms ESP and GCM-based forecasts underscoring the challenges of accurately modelling artificial reservoir management and the need for better access to management data. These insights guide the development of an advanced national seasonal hydrological forecasting service, and highlight the need for region-specific forecasting strategies indicating areas where predictability is enhanced by improved monitoring, hence initial conditions, and/or meteorological forcings. Finally, we discuss the applicability of these forecasting methods to other regions worldwide, thereby placing our new insights within a global context.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"63 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825415","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 : 2024-12-11DOI: 10.1016/j.jhydrol.2024.132508
Kewei Lyu, Yihan Dong, Wensheng Lyu, Yan Zhou, Sufen Wang, Zhaomeng Wang, Weizhe Cui, Yaobin Zhang, Qiulan Zhang, Yali Cui
Ecological water replenishment (EWR) integrates surface and groundwater regulation to promote riverine baseflows and support groundwater recovery, affecting their interactions. This study introduces SWAT-LSTM-MODFLOW, an advanced SWAT-MODFLOW model incorporating LSTM networks to improve predictive accuracy in data-scarce watersheds. Applied to the Beijing section of the Yongding River Basin, the model evaluates the impact of EWR via reservoir and reclaimed water releases on groundwater recovery and SW-GW interactions. Results show that EWR enhanced groundwater levels in the short term, particularly at the mountain-plain boundary, with increases up to 5 m during high-volume replenishments. Repeated replenishments from 2019 to 2022 shifted dynamics from river seepage to increased groundwater recharge, particularly near replenishment zones. These findings highlight EWR’s role in transforming SW-GW dynamics and enhancing hydrological connectivity. This study provides a quantitative framework for assessing artificial recharge effects on groundwater and SW-GW interactions, offering a scalable methodology for similar hydrogeological conditions.
{"title":"Data-driven and numerical simulation coupling to quantify the impact of ecological water replenishment on surface water-groundwater interactions","authors":"Kewei Lyu, Yihan Dong, Wensheng Lyu, Yan Zhou, Sufen Wang, Zhaomeng Wang, Weizhe Cui, Yaobin Zhang, Qiulan Zhang, Yali Cui","doi":"10.1016/j.jhydrol.2024.132508","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2024.132508","url":null,"abstract":"Ecological water replenishment (EWR) integrates surface and groundwater regulation to promote riverine baseflows and support groundwater recovery, affecting their interactions. This study introduces SWAT-LSTM-MODFLOW, an advanced SWAT-MODFLOW model incorporating LSTM networks to improve predictive accuracy in data-scarce watersheds. Applied to the Beijing section of the Yongding River Basin, the model evaluates the impact of EWR via reservoir and reclaimed water releases on groundwater recovery and SW-GW interactions. Results show that EWR enhanced groundwater levels in the short term, particularly at the mountain-plain boundary, with increases up to 5 m during high-volume replenishments. Repeated replenishments from 2019 to 2022 shifted dynamics from river seepage to increased groundwater recharge, particularly near replenishment zones. These findings highlight EWR’s role in transforming SW-GW dynamics and enhancing hydrological connectivity. This study provides a quantitative framework for assessing artificial recharge effects on groundwater and SW-GW interactions, offering a scalable methodology for similar hydrogeological conditions.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"77 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825418","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 : 2024-12-09DOI: 10.1016/j.jhydrol.2024.132487
Cui Gan, Zhaobo Luo, Chengyuan Su, Caixi Hu, Lei Tong, Jianbo Shi
The hyporheic zone is a crucial ecohydrological interface that plays a substantial role in the biogeochemical activity of iron and its mediated pollutant conversion. It is significantly influenced by dissolved oxygen and temperature fluctuations, but the combined effects and mechanisms are unknown. In this study, the co-transport behavior of goethite colloid (Goe), aqueous Fe2+ and oxytetracycline (OTC) in groundwater discharge was simulated by column experiments. Our findings reveal that compared with room temperature (25 °C), the penetration rates of these compounds were generally promoted (0.1–7.0 % Goe, 14.1–43.1 % Fe2+, 0–19.6 % OTC) at low temperature (10 °C) but inhibited (0–5.0 % Goe, 0–51.0 % Fe2+, 0–3.8 % OTC) at high temperature (35 °C). At room temperature (25 °C), only 5 % of the Goe can penetrate the triadic transport system, where the Fe-OTC complex decreased the Zeta potential of Goe, hence improving its transport capacity. Compared with the penetration of individual Fe2+, the Fe2+ transport was increased by 13.2 % due to the promoting effect of OTC on Fe redox cycling, whereas the electron transfer effect between Goe and Fe2+ inhibited the transport by 46.6 %. The impact of μg/L OTC on the migration of Fe and Goe was dramatically diminished compared to the mg/L level. OTC was eliminated mainly by complex internal oxidation with Fe, weak adsorption, chemisorption, and hydroxyl degradation effects, but these were diminished at low temperatures while intensified at high temperatures. This study provides a deeper understanding of the intricate mechanisms of Fe and antibiotic transport in hyporheic zones, highlighting the significant roles of temperature and chemical interactions, particularly during seasonal changes.
{"title":"Temperature-dependent co-transport behavior of goethite, Fe2+, and antibiotic in the hyporheic zone","authors":"Cui Gan, Zhaobo Luo, Chengyuan Su, Caixi Hu, Lei Tong, Jianbo Shi","doi":"10.1016/j.jhydrol.2024.132487","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2024.132487","url":null,"abstract":"The hyporheic zone is a crucial ecohydrological interface that plays a substantial role in the biogeochemical activity of iron and its mediated pollutant conversion. It is significantly influenced by dissolved oxygen and temperature fluctuations, but the combined effects and mechanisms are unknown. In this study, the co-transport behavior of goethite colloid (Goe), aqueous Fe<ce:sup loc=\"post\">2+</ce:sup> and oxytetracycline (OTC) in groundwater discharge was simulated by column experiments. Our findings reveal that compared with room temperature (25 °C), the penetration rates of these compounds were generally promoted (0.1–7.0 % Goe, 14.1–43.1 % Fe<ce:sup loc=\"post\">2+</ce:sup>, 0–19.6 % OTC) at low temperature (10 °C) but inhibited (0–5.0 % Goe, 0–51.0 % Fe<ce:sup loc=\"post\">2+</ce:sup>, 0–3.8 % OTC) at high temperature (35 °C). At room temperature (25 °C), only 5 % of the Goe can penetrate the triadic transport system, where the Fe-OTC complex decreased the Zeta potential of Goe, hence improving its transport capacity. Compared with the penetration of individual Fe<ce:sup loc=\"post\">2+</ce:sup>, the Fe<ce:sup loc=\"post\">2+</ce:sup> transport was increased by 13.2 % due to the promoting effect of OTC on Fe redox cycling, whereas the electron transfer effect between Goe and Fe<ce:sup loc=\"post\">2+</ce:sup> inhibited the transport by 46.6 %. The impact of μg/L OTC on the migration of Fe and Goe was dramatically diminished compared to the mg/L level. OTC was eliminated mainly by complex internal oxidation with Fe, weak adsorption, chemisorption, and hydroxyl degradation effects, but these were diminished at low temperatures while intensified at high temperatures. This study provides a deeper understanding of the intricate mechanisms of Fe and antibiotic transport in hyporheic zones, highlighting the significant roles of temperature and chemical interactions, particularly during seasonal changes.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"39 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825421","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 : 2024-12-09DOI: 10.1016/j.jhydrol.2024.132478
Vitor Recacho, Márcio P. Laurini
Due to the significant influence of climate change and human activities on the water cycle, accurately estimating short- and long-term water availability has become imperative. This study introduces a time series model specifically crafted to decompose river flow time series, enabling estimation of trends, seasonality, and long memory components. This decomposition is interesting as it allows to separate permanent patterns, which can be associated with climate change processes, from transient effects on flow patterns. Additionally, this decomposition is incorporated into the quantile regression in quantile regression framework using a gamma function link. The estimation of this model is based on Bayesian inference, exploring the computational efficiency and accuracy of Integrated Nested Laplace Approximations. This methodology is applied to the principal rivers within the Araguaia River basin in Brazil and compared with other alternative time series decompositions with results indicating a remarkable alignment between the model and observed data.
{"title":"Bayesian structural decomposition of streamflow time series","authors":"Vitor Recacho, Márcio P. Laurini","doi":"10.1016/j.jhydrol.2024.132478","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2024.132478","url":null,"abstract":"Due to the significant influence of climate change and human activities on the water cycle, accurately estimating short- and long-term water availability has become imperative. This study introduces a time series model specifically crafted to decompose river flow time series, enabling estimation of trends, seasonality, and long memory components. This decomposition is interesting as it allows to separate permanent patterns, which can be associated with climate change processes, from transient effects on flow patterns. Additionally, this decomposition is incorporated into the quantile regression in quantile regression framework using a gamma function link. The estimation of this model is based on Bayesian inference, exploring the computational efficiency and accuracy of Integrated Nested Laplace Approximations. This methodology is applied to the principal rivers within the Araguaia River basin in Brazil and compared with other alternative time series decompositions with results indicating a remarkable alignment between the model and observed data.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"31 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825423","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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