Gilboa Yael, Friedler Eran, Talhami Firas, Gal Gideon
Faculty of Civil and Environmental Engineering, Technion - Israel Institute of Technology, Haifa 32000, Israel.
Water Authority of Israel, Zahar Industrial Area, POB 623, Rosh Pina 12000, Israel.
Water Res X. 2022 Jul 14;16:100149. doi: 10.1016/j.wroa.2022.100149. eCollection 2022 Aug 1.
Water residence time, which is affected by increasing water demands and climate change, plays a crucial role in lakes and reservoirs since it influences many natural physical and ecological processes that eventually impact the water quality of the waterbody. Thus, accurate quantification of the water residence time and its distribution is an important tool in lake management. In this study we present a novel approach for assessing the residence time in lakes and reservoirs. The approach is based on the that was originally developed for the analysis of age-structured biological population dynamics. In this approach the water in the lake is divided into different age classes each representing the time since the "parcel" of water entered the lake and provides an overall picture of the water age structure. The traditional approach for calculating residence times, which relies only on the lake volume and annual inflow or outflow volumes thereby disregarding any previous information, is very sensitive to large interannual variation. While the proposed approach produces the fraction and volume distribution curves of all age classes within the lake for each simulated timestep. Thus, in addition to mean residence time, the fraction of young water (FYW), quantifying the "young" fraction of water in the lake can be analyzed. The same is true for any other age class of water. The approach was applied to Lake Kinneret (Sea of Galilee) historical data collected over 32 years (1987-2018) and for prediction of long-term time series based on several future scenarios (inflows and outflows). It offers a more accurate quantification of the mean residence time of water in a lake and can easily be adapted to other waterbodies. Comparison of simulation results may serve as basis for determining the lake's management policy, by controlling the inflows and outflows, that will affect both the mean residence time and the fraction of "young/old" age classes of water.
受用水需求增加和气候变化影响的水停留时间，在湖泊和水库中起着至关重要的作用，因为它影响着许多自然物理和生态过程，最终影响水体的水质。因此，准确量化水停留时间及其分布是湖泊管理中的一项重要工具。在本研究中，我们提出了一种评估湖泊和水库停留时间的新方法。该方法基于最初为分析年龄结构生物种群动态而开发的方法。在这种方法中，湖泊中的水被分为不同的年龄类别，每个类别代表水“块”进入湖泊后的时间，并提供了水年龄结构的整体情况。传统的计算停留时间的方法仅依赖于湖泊体积和年流入或流出量，从而忽略了任何先前的信息，对年际间的大幅变化非常敏感。而所提出的方法在每个模拟时间步长内生成湖泊内所有年龄类别的分数和体积分布曲线。因此，除了平均停留时间外，还可以分析量化湖泊中“年轻”水分数的年轻水分数（FYW）。对于任何其他年龄类别的水也是如此。该方法应用于基尼烈湖（加利利海）32年（1987 - 2018年）收集的历史数据，并基于几种未来情景（流入和流出）对长期时间序列进行预测。它提供了对湖泊中水的平均停留时间更准确的量化，并且可以很容易地应用于其他水体。模拟结果的比较可作为通过控制流入和流出量来确定湖泊管理政策的基础，这将影响平均停留时间以及水的“年轻/年老”年龄类别的分数。
