Andrew R. Slaughter

A method to disaggregate monthly flows to daily using daily rainfall observations: model design and testing

Abstract A monthly to daily streamflow disaggregation method is presented as part of an emerging water quality model designed to link with established monthly hydrology and yield models. The daily time step is assumed necessary for simulating water quality dynamics. The method is tested on two catchments in South Africa where observed daily flow data are available. The model includes a volume correction process to ensure daily sums are equal to input monthly flows and this reduces the sensitivity of the results to some model parameters. The sequences of events in the input daily rainfall must be representative of the catchment. Model validation against observed flows achieved Nash-Sutcliffe efficiency values ranging from 0.75 to 0.94 and initial applications of a water quality component suggested little difference between using observed and disaggregated flows. The main practical advantages are simplicity and the fact that the method builds on the experience of existing monthly models. Editor D. Koutsoyiannis; Guest editor G. Mahé

A chronic toxicity test protocol using Caridina nilotica (Decapoda: Atyidae) and the generation of salinity toxicity data

Salinization of freshwater resources is an increasing global problem, yet there is a paucity of chronic salinity tolerance data linked to very few chronic toxicity test protocols. This research aimed to generate a chronic toxicity test protocol and protective salinity tolerance data for the indigenous South African freshwater shrimp Caridina nilotica. In addition, the theory that LC5s (concentration causing 5% lethality) are indicative of No Observed Effect Concentrations (NOECs) was tested. NaCl and Na2SO4 were used as toxicants as they are indicative of natural and industrial salinization, respectively. NOEC values of 1.9 g l–1 were calculated for both salts. Within the chronic toxicity tests, LC5s that were calculated using regression methods approximated the calculated NOEC values for both salts. Chronic NOECs calculated here are lower, by a factor of 3, than the acute LC50s calculated for the same species and salts. Although evidence exists to suggest that C. nilotica is generally sensitive to toxicants, it was found to be not particularly sensitive to salinity. However, the species was found to be a good chronic toxicity test organism for partial life-cycle toxicity tests where growth was measured as the test endpoint, and may yield valuable chronic toxicity data for other toxicants.

An assessment of two-step linear regression and multifactor probit analysis as alternatives to acute to chronic ratios in the estimation of chronic response from acute toxicity data to derive water quality guidelines

Abstract In aquatic ecotoxicology, acute to chronic ratios (ACRs) are often used to predict chronic responses from available acute data to derive water quality guidelines, despite many problems associated with this method. This paper explores the comparative protectiveness and accuracy of predicted guideline values derived from the ACR, linear regression analysis (LRA), and multifactor probit analysis (MPA) extrapolation methods applied to acute toxicity data for aquatic macroinvertebrates. Although the authors of the LRA and MPA methods advocate the use of extrapolated lethal effects in the 0.01% to 10% lethal concentration (LC0.01–LC10) range to predict safe chronic exposure levels to toxicants, the use of an extrapolated LC50 value divided by a safety factor of 5 was in addition explored here because of higher statistical confidence surrounding the LC50 value. The LRA LC50/5 method was found to compare most favorably with available experimental chronic toxicity data and was therefore most likely to be sufficiently protective, although further validation with the use of additional species is needed. Values derived by the ACR method were the least protective. It is suggested that there is an argument for the replacement of ACRs in developing water quality guidelines by the LRA LC50/5 method.

A management-oriented water quality model for data scarce catchments

Abstract Due to the degeneration of water quality globally, water quality models could increasingly be utilised within water resource management. However, a lack of observed data as well as financial resources often constrain the number of potential water quality models that could practically be utilised. This study presents the Water Quality Systems Assessment Model (WQSAM). WQSAM directly utilises flow data generated by systems models to drive water quality simulations. The model subscribes to requisite simplicity by constraining the number of variables simulated as well as the processes represented to only those most important to water quality management, in this case, nutrients and salinity. The model application to the upper Olifants River catchment in South Africa is described. WQSAM was able to use the limited observed data to simulate representative frequency distributions of water quality, and the approach used within WQSAM was shown to be suitable for application to data scarce catchments.

Accuracy assessment of time–concentration–effect models in predicting chronic lethality from acute toxicity data

Acute-to-chronic (ACE) models (accelerated life testing, ALT; linear regression analysis, LRA) are used to estimate chemical concentrations resulting in low levels of chronic mortality from acute toxicity data, thereby greatly increasing the inferential value of acute data. We applied the ACE models to test data from 72 chemicals and 14 aquatic species (131 acute and 97 chronic tests) and then compared the results with reported chronic no observed effect concentrations (NOEC) and lowest observed effect concentrations (LOEC), as determined by traditional analysis of variance techniques. Acute-to-chronic models produced highly accurate chronic lethality estimates compared with reported chronic NOEC and LOEC values. Lethality estimates fell within two times reported NOEC-LOEC values 71% of the time and within five times 98% of the time. Therefore, ACE models are very appropriate for estimating chronic lethality from acute toxicity data when chronic data are absent and have high applicability in probability-based hazard and risk assessments.