A Modeling Framework to Support Decision Making on the Precursors and Formation of Trihalomethanes (THMs) in Ireland and Sweden
Abstract
Water disinfection is an essential treatment phase for safeguarding drinking water quality. Harmful pathogens in water are eliminated by the use of disinfectants such as chlorine. However, some naturally occurring organic matter can contribute to the formation of disinfection by-products (DBPs). Dissolved organic matter (DOM) is therefore an important precursor of DBPs and is often quantified via dissolved organic carbon (DOC). In Ireland and Sweden, trihalomethanes (THMs) are one of the most prevailing DBPs. This represents an important threat for water users due to the negative human health implications of THMs in drinking water. The estimation of DOC loading into drinking water sources can then be of great importance for informing authorities of future DOM levels and ensuring safe water. In this study, we test a semi-distributed loading function hydrologic and water quality model in one Irish catchment (inflow to Lake Feagh) and 13 Swedish catchments (inflows to Lake Malaren) to (1) simulate historical levels of DOC, and (2) to estimate future DOC levels using representative concentration pathways scenarios (RCPs). Despite its relative simplicity, the model does simulate the range of DOC concentrations that have been measured over the historical record, and can reproduce historical trends of increasing DOC concentrations in the catchments. We were able to evaluate the potential for changes in DOC concentrations and loads in the study sites that can be expected to occur as a result of increasing rates of organic matter decomposition, which in turn will respond to changes in temperature and soil moisture that can be simulated using general circulation model (GCM) inputs. Furthermore, we test the assumptions of the model by varying the decomposition over a range based on published parameter values. This helps place the uncertainty of our predictions in context and provides relevance to the work done so that the potential for a modeling framework implementation increases. This modeling framework will aim to support decision making related to THMs precursors and formation in different drinking water supplies in (but not limited to) Ireland and Sweden.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFM.H16B..05P