Design of sampling locations for river water quality monitoring considering seasonal variation of point and diffuse pollution loads

Water quality monitoring with purpose: Using a novel framework and leveraging long-term data

Water quality monitoring programs are developed to meet goals including attaining regulatory compliance, evaluating long-term environmental changes, or quantifying the impact of an emergency event. Methods for developing these programs often fail to address multiple aspects of development (hazard identification, parameter selection, monitoring locations/frequency) simultaneously. We develop a framework for monitoring program development that is both versatile and systematic, the Hazard Based Water Quality Monitoring Planning framework, and apply it to the Quabbin watershed in Massachusetts, USA. We use a novel application of dataset deconstruction of long-term water quality datasets and the Seasonal Kendall test for trends to evaluate the effects of sampling frequency on long-term trend detection at several watershed sites. Results showed that when sampling frequency is decreased, ability to detect statistically significant trends often decreases. Absolute error in trend slopes between biweekly (twice monthly) and reduced sampling frequencies was relatively small for specific conductance and turbidity but was high for total coliform, likely due to interannual variation in rainfall and temperature We found that no one sampling reduction method resulted in a consistently lower absolute error compared to the "truth" (biweekly sampling), highlighting the importance of evaluating conditions that may affect water quality at sites in different parts of a watershed. We demonstrate the framework's usefulness, particularly for parameter and sampling frequency selection, using methods that can be readily applied to other watershed systems.

An integrated approach for prioritization of river water quality sampling points using modified Sanders, analytic network process, and hydrodynamic modeling

Determination of the water quality monitoring network (WQMN) is a vital stage for surveying ecosystem health. Studies have been done in determining the optimal number and location of sampling points, but seasonality of water quality, especially for heavy metals, has been rarely studied. For the first time, this study proposes a framework to determine the optimal location of sampling points to monitor lead (Pb). This study was conducted for the Karoun River, located in southwestern Iran. First, hydraulic characteristics of the river were simulated by implementing of MIKE11 software as well as water quality(variation of Pb concentration). Nash‑Sutcliffe coefficient were 0.91 and 0.91 for discharge calibration and validation, respectively. Second, 16 potential sampling points were proposed using modified Sanders' approach considering seasonality. For a better accuracy in the WQMN layout and a more efficient site selection of sampling points, a 1-km buffer is stretched along the river for determining non-point source pollution sources and prioritizing candidate points. This leads to considering different land uses in the study area, while GIS software has been employed. Seasonal changes and land use have a significant impact on the location of optimal sampling points. The presented framework can be used to improve water quality and support watershed protection efforts.

Rationalization of water quality monitoring locations under spatiotemporal heterogeneity of diffuse pollution using seasonal export coefficient

Water quality is continuously changing because of anthropogenic origin of point and diffuses (non-point) pollution sources. Most of the time diffuse sources are not considered for rationalization of sampling sites as their accurate estimation is tedious and data intensive. The estimation of diffuse pollution is conventionally carried out using observed water quality data. These conventional approaches are data intensive and demands detailed information for a considerably long-time horizon and hence becomes challenging to implement in data-scarce regions. Also, diffuse pollution sources are characterized by spatio-temporal heterogeneity as they depend upon seasonal behavior of precipitation. The present study proposes an innovative semi-empirical approach of Seasonal Export Coefficients (SECs) for estimation of diffuse pollution loads, especially for tropical countries like India. This approach takes into account the effect of seasonality on the estimation of diffuse pollution loads, by considering seasonal heterogeneity of terrain and precipitation impact factors and land use applications. This seasonal heterogeneity is then tested for its possible impact on rationalization of water quality monitoring locations for Kali River basin in India. The SECs are estimated for available water quality dataset of 1999-2000 and are further used for simulation of nutrient loading for experimental years 2004-2005, 2009-2010, and 2014-2015. The resulting SECs for Kali river basin are: 2.03 (agricultural), 1.44 (fallow), and 0.92 (settlement) for monsoonal nitrate; while for non-monsoonal nitrate, SECs are 0.51 (agricultural), 0.23 (fallow), and 0.10 (settlement). The monsoonal phosphate SECs for land use classes - agricultural, fallow and settlement are 1.01, 0.68, and 0.25, while non-monsoonal phosphate SECs are 0.27, 0.14 and, 0.03 respectively. The seasonal variation of diffuse pollution sources is effectively captured by SECs. The proposed approach, by considering both point and diffuse pollution, is found efficient in determining optimum locations and number of monitoring sites where seasonal variations are found evident during experimental years.

Assessment of spatial and temporal variations in water quality by the application of multivariate statistical methods in the Kali River, Uttar Pradesh, India

The Kali River is a significant source of surface water as well as the main tributary of River Hindon that flows through major cities of western Uttar Pradesh, India. It flows throughout the urban and industrial regions; hence, it carries various amounts of pollutant. Therefore, a study was conducted to examine spatial-temporal variations in river water quality by determining physicochemical variables and heavy metal concentrations at seventeen sampling stations (S₁-S₁₇) throughout the river stretch. Various physicochemical variables, namely pH, EC, TDS, turbidity, BOD, COD, TH, TA, Ca, Mg, Na, K, HCO₃^-, Cl^-, SO₄^2-, NO₃^-, and PO₄^3- were higher in summer than in winter. The order of mean metal concentrations was Fe > Pb > Mn > Ni > Zn > Cu > Cr > Cd. The relationships among measured physicochemical variables and pollution index were examined. Furthermore, multivariate statistical methods were used to assess spatial-temporal variation in water quality to identify current pollution sources and validate results. Water quality index and comprehensive pollution index indicated that the Kali River was less polluted from S₁ to S₈. However, downstream sampling sites were polluted. Pollution starts from S₉ and drastically increases at and beyond S₁₃ because of effluents from industries and sugar mills in Muzaffarnagar. The study suggests cleaning the downstream region of river to restore human health and flora and fauna in the river ecosystem.

Spatial and Temporal Variability of Water Quality in the Bystrzyca River Basin, Poland

The aim of the study was to analyze the results of surface water quality tests carried out in the Bystrzyca river basin. The study was conducted over four years in four seasons. The following chemometric techniques were used for the purposes of statistical analyses: the principal component analysis with factor analysis (PCA/FA), the hierarchical cluster analysis (HCA), and the discriminant analysis (DA). The analyses allowed for determining the temporal variability in water quality between the seasons. The best water quality was recorded in summer and the worst in autumn. The analyses did not provide a clear assessment of the spatial variability of water quality in the river basin. Pollution from wastewater treatment plants and soil tillage had a similar effect on water quality. The tested samples were characterized by very high electrolytic conductivity, suspended solids and P-PO4 concentrations and the water quality did not meet the standards of good ecological status.

Methodological proposal for the allocation of water quality monitoring stations using strategic decision analysis

In order to fill a gap in the monitoring of water quality in Brazil, the objective of this study was to propose a methodology to support the allocation of water quality monitoring stations in river basins. To achieve this goal, eight criteria were selected and weighted according to their degree of importance. It was taken into account the opinion of water resources management experts. In addition, a decision support system was designed so that the methodology could be used in the allocation of water quality monitoring stations by researchers and management bodies of water resources, to be fully implemented in geographic information system environment. In order to demonstrate the potential of the proposed methodology, which can be used in places that have or not existing monitoring networks, it has been applied in the Minas Gerais portion of the Doce river basin. Because the area already has a monitoring network with 65 stations in operation under the responsibility of the Minas Gerais Water Management Institute (IGAM), an expansion of the network was suggested and a simulation of a scenario was performed considering that the study area did not have an established network. The results of the analyses consisted of maps of suitability, indicating the locations with greater and lesser suitability for the establishment of the stations. With the application of the methodology, seven new sites were proposed so that the study area had the density recommended by the National Water Agency (ANA), and it was verified that the Caratinga River Water Resources Management Unit (UGRH5 Caratinga) has the most deficiency of stations among the six units evaluated in the Minas Gerais portion of the Doce river basin. In the simulated scenario considering the non-existence of a network, the adequacy map obtained was compared with the existing monitoring network and it was possible to classify the stations according to the purpose for which they were established, such as monitoring environments under anthropic activities or establishing benchmarks for the water bodies. Overall, the proposed methodology proved itself robust, and although the results were specific to one basin, the criteria and decision support system used are fully applicable to other areas of study.

Methods for Sample Collection, Storage, and Analysis of Freshwater Phosphorus

Although phosphorus (P) is an essential nutrient for biological productivity, it can cause freshwater degradation when present at fairly low concentrations. Monitoring studies using continuous sampling is crucial for documenting P dynamics in freshwater ecosystems and to reduce the risk of eutrophication. Despite literature updates of developments of the analytical methods for measurement of P species in natural waters, there has been no comprehensive review addressing freshwater sample collection, sample preparation, and sample treatment to fractionate and characterize different forms of P. Therefore, this paper aims to elaborate the different techniques for freshwater sampling and to introduce alternative laboratory methods for sample preservation and P fractionation. The advantages and disadvantages of various sampling techniques, including the traditional manual and the recently developed automatic and passive methods, are presented to highlight the importance of collecting representative freshwater samples. Furthermore, we provide suggestions for sample pretreatment, including filtration, transportation, and storage steps to minimize microbial activity and to maximize the accuracy of measurement of various P fractions. Finally, the most common laboratory methods to measure dissolved and particulate as well as the organic and inorganic freshwater P fractions are efficiently provided. Using this guide, a comprehensive monitoring program of P dynamics in freshwater ecosystems can be developed and applied to improve water quality, particularly of P-rich freshwaters.

Ecological and Economic Sustainability in Olive Groves with Different Irrigation Management and Levels of Erosion: A Case Study

In the last 50 years, both the agricultural labour force and irrigated land area have increased almost eightfold in Spain. The main objective of irrigation, in the short term, is to increase agricultural production. However, in the long term, the environmental externalities of irrigation and its direct relationship with soil erosion processes are more uncertain and still poorly studied. In this study, in an olive-growing region of Andalusia, Spain, the variation of several soil parameters related to irrigation and erosion levels was analysed. The results showed that irrigation, while increasing the productive level of the olive groves, entails a progressive alteration of the soil, modifying physical aspects (greater compaction and humidity of the soil together with lower gravel content, porosity and soil weight) and chemical aspects (reduction of the organic matter of the soil and the content of nitrates) that can aggravate the consequences of the erosive processes. In the long term, the productive benefit attributed to irrigation could be unsustainable from an ecological and, consequently, economic point of view. In addition, the lack of sustainability of olive irrigation agroecosystems could be exacerbated by the future restrictive impacts of climate change on water resources in Mediterranean environments. This situation demands spatial planning and alternative management based on soil conservation and rational and efficient forms of irrigation to ensure the sustainability of olive groves and their economic viability.

A Comparison Study of Runoff Characteristics of Non-Point Source Pollution from Three Watersheds in South Korea

Three watersheds in Korea (Dochoncheon, Gongjicheon, Seolseongcheon) with different land cover characteristics were selected for non-point source pollution monitoring. Event mean concentration (EMC) was calculated, and runoff characteristics were compared through first-flushing and statistical analyses. The mean of the water quality parameters was the highest in Seolseongcheon during dry days among the three watersheds. EMCs of biochemical oxygen demand (BOD) and total nitrogen (TN) were higher in Dochoncheon and Gongjicheon during rainy days, respectively. The upper Seolseongchun watershed showed overall greater values of chemical oxygen demand (COD), suspended solids (SS), total organic carbon (TOC), and total phosphorus (TP). First-flush analyses indicated that SS had the strongest and TN had the weakest effects on the first flush. BOD was the highest in Dochoncheon (urban watershed) and increased with increased number of antecedent dry days. Rainfall intensity appeared to affect SS runoff strongly in Gongjicheon and Seolseongcheon. COD showed strong correlation with SS and TOC in all watersheds, and organic matter (COD and TOC) demonstrated high factor loads during dry and rainy days. Thus, organic matter–related factors were classified as the major factors in pollutant loads. TP and TN were separately classified during dry days in Gongjicheon and Seolseongcheon, whereas these were the secondary factors during rainfall when the influence of non-point pollution was substantial. Cluster analyses showed that the monitoring sites in Dochoncheon and Gongjicheon watersheds were closer than Seolseongcheon. As a result of the comparison of non-point source pollution runoff in the three watersheds, it was difficult to explain the non-point source pollution runoff by specific characteristics such as land cover. For science-based management of non-point pollution, it is necessary to obtain additional survey data considering the climatic, geographical and major industries.

A cost-effective and efficient framework to determine water quality monitoring network locations

A crucial part in designing a robust water quality monitoring network is the selection of appropriate water quality sampling locations. Due to cost and time constraints, it is essential to identify and select these locations in an accurate and efficient manner. The main contribution of the present article is the development of a practical methodology for allocating critical sampling points in present and future conditions of the non-point sources under a case study of the Khoy watershed in northwest Iran, where financial resources and water quality data are limited. To achieve this purpose, the river mixing length method (RML) was applied to propose potential sampling points. A new non-point source potential pollution score (NPPS) was then proposed by the analytic network process (ANP) to classify the importance of each sampling point prior to selecting the most appropriate locations for a river system. In addition, an integrated cellular automata-Markov chain model (CA-Markov) was applied to simulate future change in non-point sources during the period 2026-2036. Finally, by considering anthropogenic activities through land-use mapping, the hierarchy value, the non-point source potential pollution score values and budget deficiency in the study area, the seven sampling points were identified for the present and the future. It is not expected, however, that the present location of the proposed sampling points will change in the future due to the forthcoming changes in non-point sources. The current study provides important insights into the design of a reliable water quality monitoring network with a high level of assurance under certain changes in non-point sources. Furthermore, the results of this study should be valuable for water quality monitoring agencies looking for a cost-effective approach for selecting sampling locations.

Multivariate analyses of the effect of an urban wastewater treatment plant on spatial and temporal variation of water quality and nutrient distribution of a tropical mid-order river

Freshwater resources are increasingly scarce due to human activities, and the understanding of water quality variations at different spatial and temporal scales is necessary for adequate management. Here, we analyze the hypotheses that (1) the presence of a wastewater treatment plant (WWTP) and (2) a polluted tributary that drains downstream from the WWTP change the spatial patterns of physicochemical variables (pH, turbidity, dissolved oxygen, and electrical conductivity) and nutrient concentrations (reactive soluble phosphorus, total phosphorus, nitrogen series, total nitrogen, and total dissolved carbon) along a mid-order river in SE Brazil and that these effects depend on rainfall regime. Six study sites were sampled along almost 4 years to evaluate the impacts of human activities, including sites upstream (1-3) and downstream (5-6) from the WWTP. The impacts were observed presenting an increasing trend from the source (site 1) towards Água Quente stream (site 4, the polluted tributary), with signs of attenuation at site 5 (downstream from both WWTP and site 4) and the river mouth (site 6). Input of nutrients by rural and urban runoff was observed mainly at sites 2 and 3, respectively. At sites 4 and 5, the inputs of both untreated and treated wastewaters increased nutrient concentrations and changed physicochemical variables, with significant impacts to Monjolinho River. Seasonal variations in the measured values were also observed, in agreement with the pluviometric indexes of the region. Univariate analyses suggested no effect of the WWTP for most variables, with continued impacts at sites downstream, but non-parametric multivariate analysis indicated that these sites were recovering to chemical characteristics similar to upstream sites, apparently due to autodepuration. Therefore, multivariate methods that allow rigorous tests of multifactor hypotheses can greatly contribute to determine effects of both point and non-point sources in river systems, thus contributing to freshwater monitoring and management.