Effect of Water Quality Sampling Approaches on Nitrate Load Predictions of a Prominent Regression-Based Model

Inconsistency of PCA-based water quality index - Does it reflect the quality?

The formalization of a stable water quality index (WQI) from measured hydrogeochemical parameters is essential for the identification and classification of water resources. In the principal component analysis (PCA) based WQI approach, the parameter weight is derived using either PC loading or rotated factor loading from a large number of samples pooled for WQI measurement. The PCA-based approach is paradoxical, as the calculated WQI rating of a sample would rather be dependent on the size, and composition of the population. Though this issue is well anticipated, no attempt has been made to regularize or measure the extent of WQI disagreement. In the present study, the WQI of 106 groundwater samples analyzed for 12 different hydrochemical parameters were modelled using PC loading or rotated factor loading (referred to as PCQ-1, PCQ-2, respectively) approach. Analysis reveals PCQ-1 to be positively biased in 78 % of samples and rating disagreements were evident in 9.43 % of samples. WQI of the data set was estimated using repeated (1000) random non-overlapping 2 to 5-fold data partitioning (containing 21 to 83 samples in each fold) adopting either an in-sample (test set) or out-sample (train set) modelling approach. The mean of WQI deviations in repeated resampling from the reference (i.e., using the entire dataset) has been positive in most of the samples using the PCQ-1 model, irrespective of the fold partition size. The median root mean square deviation values of the data set increased with the number of fold partitioning for in-sample calibration for both PCQ-1 and PCQ-2 approaches. The exclusion of a single water quality parameter from the PCA model can cause up to a 60 % deviation of the WQI score in some water samples. The cross-validation and Monte Carlo resampling approach can serve as a framework to test the stability of PCA-based WQI.

Evaluation of SEAWAVE-QEX in a high agricultural intensity catchment in Belgium

Pesticide surface water monitoring data have rarely been used as the only quantitative measure of exposure because the available monitoring data for most pesticides has not been considered robust enough for direct use in pesticide exposure assessments due to infrequent sampling. The cost of daily sample collection and analysis prohibits frequent sampling for most monitoring programs. In this context, a common question raised in assessments is how likely peak concentrations (i.e., annual maxima) may be missed if sampling intervals are longer than daily. The US Geological Survey developed the statistical model "seasonal wave with streamflow adjustment and extended capability" (SEAWAVE-QEX) to address the need to estimate infrequently occurring pesticide concentrations, such as annual maximum daily concentrations, for sites with nondaily monitoring data. This study compares the results of two postprocessing methods and evaluates the capability of SEAWAVE-QEX to estimate annual maximum concentrations of three commonly used herbicides and one metabolite in a catchment in Belgium. The study concludes that the appropriateness of using SEAWAVE-QEX to estimate annual maximum concentrations depends on pesticide characteristics and use and that the model can be particularly sensitive to nonflow correlated exposure events (e.g., point source contributions or drift). Integr Environ Assess Manag 2023;19:513-526. © 2022 Stone Environmental and Bayer AG Crop Science Division. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Dissolved phosphorus export through baseflow in an intensively cultivated agricultural watershed of eastern China

Inputs of phosphorus (P) during baseflow period usually come from groundwater, bed sediments, and some other sources. Baseflow P can have critical effects on nutrient enrichment of surface waters in some intensively cultivated agricultural watersheds. This study was conducted to estimate the baseflow dissolved phosphorus (DP) export in a typical rainy agricultural watershed of eastern China using a recursive tracing source algorithm (RTSA) and reveal the rules and trends of baseflow DP loads and concentrations. Results indicated that RTSA provided a satisfactory prediction for baseflow DP load (Nash-Sutcliffe efficiency (NSE) = 0.72, R2 = 0.74). From 2003 to 2012, the annual baseflow DP loads ranged from 0.159 (2004) to 0.771 (2012) kg/ha which contributed about 64.3% of the mean total annual DP export in stream (0.597 kg/ha). The annual flow-weighted DP concentrations in streamflow (0.076-0.125 mg/L) and baseflow (0.076-0.137 mg/L) far exceeded the eutrophication threshold of DP (0.01 mg/L). Significantly increasing trends were obtained in the streamflow and baseflow DP loads and the flow-weighted concentrations (Mann-Kendall test, Zs > 2.56, p < 0.01) because of the changes of hydro-meteorological conditions. This indicates that, in the context of global climate change, baseflow DP export would be one of key issues for nonpoint source pollution control in the intensive agricultural watershed.