Water, nergy and Environmental Engineering research unit, Faculty of Technology, 90014, University of Oulu, Finland.
Water, nergy and Environmental Engineering research unit, Faculty of Technology, 90014, University of Oulu, Finland.
J Environ Manage. 2022 Jan 15;302(Pt B):114107. doi: 10.1016/j.jenvman.2021.114107. Epub 2021 Nov 16.
Effective identification and quantification of groundwater (GW) infiltration into sewage collection networks represents an important step towards sustainable urban water management. In many countries, including northern regions, sewage networks are aging to the point where renovation is needed. This study focused on the utilization of stable water isotopes as tracer substances for GW infiltration detection. The main objectives were to investigate the validity of the method for quantifying GW infiltration in cold climate conditions and to test the robustness of this method under assumed low GW infiltration rates. In general, the stable water isotopes (δO) produced reliable results regarding origin identification and quantification of GW infiltration rates in winter conditions (continuous below zero temperatures and snow accumulation during preceding months). The 1.6‰ distinction between the δO isotope composition signals of the two water sources (drinking water from river and groundwater) in the studied network was sufficient to allow source separation. However, a larger distinction would reduce the uncertainties connected to GW-fraction identification in situations where low GW infiltration rates (<8%) are expected. Due to the climate conditions (no surface water inflow), GW infiltration to the network branch monitored represented the totality of I/I (infiltration/surface inflow) flows and was estimated to reach a maximum daily rate of 6.5%. This being substantially lower than the 29% yearly average I/I rate of ca 29% reported for the city's network. Overall, our study tested the stable water isotope method for GW infiltration detection in sewage networks successfully and proved the suitability of this method for network assessment in cold climate conditions. Isotope sampling could be part of frequent monitoring campaigns revealing potential infiltration and, consequently, the need for renovation.
有效识别和量化地下水（GW）渗入污水收集网络是实现可持续城市水资源管理的重要步骤。在许多国家，包括北方地区，污水管网已经老化，需要进行翻新。本研究侧重于利用稳定的水同位素作为示踪物质来检测 GW 渗入。主要目标是研究该方法在寒冷气候条件下量化 GW 渗入的有效性，并测试该方法在假定低 GW 渗入率下的稳健性。一般来说，稳定的水同位素（δO）在冬季条件下（连续低于零的温度和前几个月的积雪积累）对 GW 渗入率的来源识别和量化产生了可靠的结果。在所研究的网络中，两种水源（来自河流的饮用水和地下水）的δO 同位素组成信号之间 1.6‰的差异足以实现源分离。然而，如果预计 GW 渗入率较低（<8%），更大的差异将减少与 GW 分数识别相关的不确定性。由于气候条件（没有地表水流入），监测到的网络分支中的 GW 渗入量代表了 I/I（渗入/地表水流入）流量的全部，估计最大日流量达到 6.5%。这远低于该城市网络报告的 29%的年平均 I/I 率 29%。总的来说，我们的研究成功地测试了稳定水同位素法在污水网络中检测 GW 渗入的方法，并证明了该方法在寒冷气候条件下对网络评估的适用性。同位素采样可以成为频繁监测活动的一部分，揭示潜在的渗入，并因此需要进行翻新。
