Ståle Haaland
Research Scientist
Authors
Ståle Haaland Josef Hejzlar Bjørnar Eikebrokk Geir Orderud Ma. Cristina Paule‐Mercado Petr Porcal Jiří Sláma Rolf David VogtAbstract
Over the past four decades, an increase in Dissolved Natural Organic Matter (DNOM) and colour, commonly referred to as browning, has been noted in numerous watercourses in the northern hemisphere. Understanding the fluctuations in DNOM quality is a prerequisite for gaining insights into the biogeochemical processes governing DNOM fluxes. Such knowledge is also pivotal for water treatment plants to effectively tailor their strategies for removing DNOM from raw water. The specific ultraviolet absorbance (sUVa) index has been a widely applied measurement for assessing DNOM quality. The sUVa index is the UV absorbance (OD254) of water normalized for DNOM concentration. We have used a long-term dataset spanning from 2007 to 2022, taken from the Malše River in South Bohemia, to model DNOM and the sUVa index. We have applied regression models with a process-oriented perspective and have also considered the influence of climate change. Both DNOM and the sUVa index is positively related to temperature, runoff and pH, and negatively related to ionic strength over the studied period. Two distinct model approaches were employed, both explaining about 40% of the variation in sUVa over the studied period. Based on a moderate IPCC monthly climate scenario, simulations indicate that both DNOM and the sUVa index averages remain fairly stable, with a slight increase in winter season minima projected towards the year 2099. A slight decline in summer season maxima is simulated for DNOM, while the sUVa summer maximum remain stable. These findings suggest a robust resilience in both DNOM and the sUVa index against anticipated changes in temperature and runoff for the Malše River in South Bohemia.
Abstract
Light penetration plays a vital role in lakes and drinking water reservoirs, influencing fundamental processes such as primary production and thermal budgets. The Secchi depth (ZSD) and the compensation depth (ZCD) are commonly used measurements in this context. ZSD is determined through visual inspection using a Secchi disc, while ZCD represents the depth at which photosynthetic activity balances respiration and can be measured using a quantum irradiance sensor. Through in situ water-core samples from 23 lakes within a lake district in Southeastern Norway, we observed that DNOM exerts a diverse influence on these light irradiance measurements. If DNOM concentrations are reduced to half or a quarter of the current concentration, similar to what was measured during the 1980s, the median ZCD:ZSD ratios are estimated to have decreased by approximately 30 and 60% since then, respectively. Conversely, a plausible future climate-driven doubling or quadrupling of the present DNOM concentrations are estimated to further decrease the median ZCD:ZSD ratios in the lake district with approximately 10 and 25%, respectively. From this, the ZCD:ZSD ratios seem to have experienced a considerable long-term decline attributed to both climate change and the recovery from acid rain, and a further climate-driven decrease is expected.
Abstract
Levels of dissolved natural organic matter (DNOM) are increasing in our boreal watercourses. This is manifested by an apparent increase in its yellow to brown colour of the water, i.e., browning. Sound predictions of future changes in colour of our freshwaters is a prerequisite for predicting effects on aquatic fauna and a sustainable operation of drinking water facilities using surface waters as raw water sources. A model for the effect of climate on colour (mg Pt L-1) has been developed for two surface raw water sources in Scotland, i.e., at Bracadale and Port Charlotte. Both sites are situated far out on the Scottish west coast, without major impact of acid rain, with limited amounts of frost, and with limited recent land-use changes. The model was fitted to 15 years long data-series on colour measurements, provided by Scottish Water, at the two sites. Meteorological data were provided by UK Met. The models perform well for both sites in simulating the variation in monthly measured colour, explaining 89 and 90% of the variation at Bracadale and Port Charlotte, respectively. These well fitted models were used to predict future changes in colour due to changes in temperature and precipitation based on median climate data from a high emission climate RCP8.5 scenario from the HadCM3 climate model (UKCP18). The model predicted an increase in monthly average colour during growing season at both sites from about 150 mg Pt L-1 to about 200 mg Pt L-1 in 2050–2079. Temperature is found to be the most important positively driver for colour development at both sites.