Disaster Management Training and Education Centre for Africa, Faculty of Natural and Agricultural Sciences, University of the Free State, P. O. Box 339, Bloemfontein, 9300, Free State, South Africa.
Environ Sci Pollut Res Int. 2023 Jun;30(29):73425-73450. doi: 10.1007/s11356-023-27048-4. Epub 2023 May 16.
Evidence from increasing mineralization, micropollutant concentrations, waterborne epidemics, an algal boom, and dissolved organic matter has provided substantial evidence that climate change impacts water quality. While the impact of the extreme hydrological event (EHE) on water quality (WQ) has aroused considerable research interest, research uncertainty has been premised on WQ data scarcity, a short time frame, data non-linearity, data structure, and environmental biases on WQ. This study conceptualized a categorical and periodic correlation using confusion matrices and wavelet coherence for varying standard hydrological drought index (SHDI; 1971-2010) and daily WQ series (1977-2011) of four spatially distinct basins. By condensing the WQ variables using chemometric analyses, confusion matrices were assessed by cascading the SHDI series into 2-, 3-, and 5-phase scenarios. 2-phase revealed an overall accuracy (0.43-0.73), sensitivity analysis (0.52-1.00), and Kappa coefficient (- 0.13 to 0.14), which declines substantially with the phase increase, suggesting the disruptive impact of EHE on WQ. Wavelet coherence depicted the substantial ([Formula: see text]) mid- and long-term (8-32 days; 6-128 days) co-movement of streamflow over WQ, confirming the varying sensitivity of WQ variables. Land use/land cover mapping and the Gibbs diagram corroborate the eventful WQ evolution by EHE and their spatial variability concerning landscape transformation. Overall, the study deduced that hydrologic extreme triggers substantial WQ disruption with dissimilar WQ sensitivity. Consequently, suitable chemometric indicators of EHE impacts such as WQ index, nitrate-nitrogen, and Larson index at designated landscapes were identified for extreme chemodynamics impact assessment. This study proffers a recommendation for monitoring and managing the impact of climate change, floods, and drought on water quality.
证据表明,气候变化正在对水质产生影响,包括矿化作用增强、微量污染物浓度上升、水媒传染病、藻类爆发和溶解有机物增加等。虽然极端水文事件(EHE)对水质(WQ)的影响引起了相当多的研究兴趣,但研究不确定性主要基于 WQ 数据的稀缺性、时间框架较短、数据非线性、数据结构以及 EHE 对 WQ 的环境偏差。本研究使用混淆矩阵和小波相干性对四个空间上不同的流域的变化标准水文干旱指数(SHDI;1971-2010 年)和每日 WQ 序列(1977-2011 年)进行了分类和周期性关联。通过使用化学计量分析对 WQ 变量进行压缩,然后将 SHDI 系列级联到 2-、3-和 5 个阶段场景中,对混淆矩阵进行了评估。2 个阶段的整体准确性为 0.43-0.73,敏感性分析为 0.52-1.00,Kappa 系数为-0.13 至 0.14,随着阶段的增加而大幅下降,表明 EHE 对 WQ 的破坏性影响。小波相干性描述了流量与 WQ 之间的大量[公式:见正文]中短期(8-32 天;6-128 天)共同运动,证实了 WQ 变量的变化敏感性。土地利用/土地覆被制图和 Gibbs 图证实了 EHE 引起的 WQ 演变及其与景观转化有关的空间变异性。总体而言,本研究推断,水文极端事件会引发 WQ 的重大破坏,并导致 WQ 敏感性的不同。因此,需要在指定的景观中确定 WQ 指数、硝酸盐氮和 Larson 指数等适合的 EHE 影响化学计量指标,以评估极端化学动力学的影响。本研究为监测和管理气候变化、洪水和干旱对水质的影响提供了建议。