Assessment of ensemble data assimilation based heat tracer method for estimating surface water-groundwater interaction at seasonal timescale under complex field conditions

IF 5.9 1区 地球科学 Q1 ENGINEERING, CIVIL
Xuchen Zhai , Kewei Chen , Xiuyu Liang , Guoliang Wang , Xin Zhao , Zhilin Guo , Renjie Zhou , Chen Ding , Cancan Liu , Chunmiao Zheng
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引用次数: 0

Abstract

Quantifying fluid fluxes between surface water (SW) and groundwater (GW) is essential for understanding nutrient transport processes across the terrestrial-aquatic interface and river ecosystems. For highly dynamic rivers (e.g., dam-regulated river, tidal river), frequent fluctuations in river stages present challenges in the assessment of SW-GW interactions. To address this challenge, an ensemble smoother-multiple data assimilation (ES-MDA) based heat tracer method was proposed previously, which outperforms analytical heat tracer methods and is able to capture sub-daily fluxes accurately. However, the performance of this method under non-ideal conditions (e.g., unsaturated flow, heterogeneous sediment) has not been thoroughly investigated, especially at the seasonal time scale when the flow patterns vary distinctively. In this study, we examined the influences of seasonal flow patterns, riverbed heterogeneity, and unsaturated flow conditions on the performance of the ES-MDA method for flux estimation. Our findings indicate that the ES-MDA method yields robust results under saturated flow conditions with heterogeneous permeability fields across all seasons. Both long-term low fluxes (e.g., ± 1 m/day) and temporary flux peaks (e.g., 3 m/day) can be accurately captured. Temperature differences between different depths significantly affect the estimation uncertainty, and the co-occurrence of low temperature differences and high heterogeneity may weaken the method’s performance. In variably saturated zones, while the flow direction remains identifiable, the estimated fluxes may be unrealistic. Our work demonstrates that the ES-MDA method has the potential for application under complex field conditions for long-term monitoring of SW-GW interactions.
复杂野外条件下季节性时间尺度地表水-地下水相互作用综合同化热示踪估算方法的评价
地表水(SW)和地下水(GW)之间的流体通量的量化对于理解跨陆水界面和河流生态系统的养分运输过程至关重要。对于高度动态的河流(如水坝调节的河流、潮汐河),河流阶段的频繁波动对SW-GW相互作用的评估提出了挑战。为了解决这一挑战,先前提出了一种基于集合平滑-多重数据同化(ES-MDA)的热示踪方法,该方法优于分析热示踪方法,能够准确捕获亚日通量。然而,该方法在非理想条件下(如非饱和水流、非均质泥沙)的性能尚未得到充分研究,特别是在流动模式变化明显的季节时间尺度下。在本研究中,我们考察了季节流量模式、河床异质性和非饱和流量条件对ES-MDA方法通量估算性能的影响。我们的研究结果表明,ES-MDA方法在所有季节渗透率场均不均匀的饱和流条件下产生了可靠的结果。可以准确捕获长期低通量(例如,±1米/天)和临时通量峰值(例如,3米/天)。不同深度间的温差显著影响估计的不确定度,低温温差和高非均质共存会削弱方法的性能。在可变饱和区,虽然流动方向仍然可识别,但估计的通量可能是不现实的。我们的工作表明,ES-MDA方法具有在复杂野外条件下长期监测SW-GW相互作用的潜力。
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来源期刊
Journal of Hydrology
Journal of Hydrology 地学-地球科学综合
CiteScore
11.00
自引率
12.50%
发文量
1309
审稿时长
7.5 months
期刊介绍: The Journal of Hydrology publishes original research papers and comprehensive reviews in all the subfields of the hydrological sciences including water based management and policy issues that impact on economics and society. These comprise, but are not limited to the physical, chemical, biogeochemical, stochastic and systems aspects of surface and groundwater hydrology, hydrometeorology and hydrogeology. Relevant topics incorporating the insights and methodologies of disciplines such as climatology, water resource systems, hydraulics, agrohydrology, geomorphology, soil science, instrumentation and remote sensing, civil and environmental engineering are included. Social science perspectives on hydrological problems such as resource and ecological economics, environmental sociology, psychology and behavioural science, management and policy analysis are also invited. Multi-and interdisciplinary analyses of hydrological problems are within scope. The science published in the Journal of Hydrology is relevant to catchment scales rather than exclusively to a local scale or site.
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