Assessment of seasonal and spatial variation of surface water quality, identification of factors associated with water quality variability, and the modeling of critical nonpoint source pollution areas in an agricultural watershed

Abstract

Surface water quality impairment in agricultural watersheds is a major environmental concern in the United States. To assess seasonal and spatial variability of surface water quality and identify factors associated with surface water quality variability, we monitored surface water quality at seven locations in Bayou Plaquemine Brule Watershed in Louisiana twice monthly from March of 2002 to February of 2008 and performed multivariate analyses of the dataset. Using the Soil and Water Assessment Tool (SWAT) model, we identified critical areas of nonpoint source pollution in the watershed. While temperature, turbidity, dissolved oxygen (DO), conductivity and pH were determined in the field using YSI Sonde (YSI Incorporated, Yellow Springs, Ohio), surface water samples were analyzed for total nitrogen (TN), total phosphorus (TP), nitrate/nitrite-N (NO 3 /NO 2 -N), soluble reactive phosphate (SRP), total suspended solids (TSS), and five-day biological oxygen demand (BOD 5 ) in laboratory. The monthly water quality sampling included a regular sampling and an after-rain-event sampling. Average DO for the summer months, March through November, was 4.91 ± 0.08 mg L -1 (4.91 ± 0.08 ppm), while average DO for the winter months, December through February, was 8.32 ± 0.12 mg L -1 (8.32 ± 0.12 ppm). Dissolved oxygen was negatively correlated with TN (r = -0.22, p ≤ 0.001), SRP (r = -0.17, p ≤ 0.001), TP (r = -0.17, p ≤ 0.001), BOD 5 (r = -0.25, p ≤ 0.001), and surface water temperature (r = -0.70, p ≤ 0.001). Turbidity was strongly correlated with TSS (r = 0.59, p ≤ 0.001), suggesting that most turbidity in the water body comes from suspended solids. Similarly BOD 5 was significantly positively correlated with TN (r = 0.43, p ≤ 0.001), NO 3 /NO 2 -N (r = 0.26, p ≤ 0.001), TP (r = 0.25, p ≤ 0.001), and SRP (r = 0.18, p ≤ 0.001). Results of factor analyses showed sediment, phosphorus (P), nitrogen (N), surface water temperature, dissolved solids, and acidity/alkalinity as the most important factors associated with surface water quality variability in this watershed. Although relatively higher concentrations of sediments, TP, and TN were observed in the upper reaches of the watershed based on water quality monitoring, the SWAT simulation results showed the critical nonpoint source pollution areas of sediment, P, and N in the lower reaches of the watershed. Lower reaches of the watershed have mainly rice and crawfish production, while the upper reaches include primarily sugarcane, pasturelands, and soybean production. Information on seasonal variability of surface water quality, factors associated with surface water quality variability, and the critical areas for nonpoint source pollution will be valuable inputs for developing a watershed management plan for effective nonpoint source pollution control in an agricultural watershed.

Indicadores de qualidade da água e padrões de uso da terra em bacias hidrográficas no Estado do Paraná

“…A análise da correlação de padrões de uso das terras e indicadores de qualidade da água é complexa já que diversos fatores (multicolinearidade) estão simultaneamente influenciando os resultados ao longo do tempo (Poudel et al, 2013;Ekness & Randhir, 2015). Assim, no verão de 2009 foram observados os menores valores de IQA b para todas as bacias, o que coincide com o período de maior precipitação observado, mas também com uma alta ocorrida no preço da soja e aumento na área plantada em relação ao ano anterior (Cepea, 2011;.…”

Glebokie Lake in Szczecin after hydrotechnical regulations

“…The collected data can be analyzed descriptively, as performed in this study as well as in overall practice [45,46] and -with chemometric methods as presented in these paper.…”

“…Principal Component Analysis provides information on the most important water quality indices that describe the entire data set by performing data reduction with minimal loss of original information carried by the data [21,22,24,28,29,45].…”

Modelo de avaliação da qualidade da água utilizando geoquímica e bioindicadores

“…Ainda conforme Poudel et al (2013), devido à interação entre os parâmetros é possível explicar a variabilidade na qualidade da água de superfície utilizando alguns grupos de parâmetros.…”

“…It was collected water samples in the 12 spots, polyethylene bottle 1L, purified water were used to the experience and they had been washed with nitric acid 10% v/v by the Milliq system (resistivity procedure used by Poudel et al 2013;Zhang, et al 2013).…”