A combined approach for the estimation of groundwater leaching potential and environmental impacts of pesticides for agricultural lands.

Pesticide pollution can degrade the quality of land, water, and air, and imposes risks on people, flora and fauna. Pesticides are frequently chosen based on their agricultural effectiveness and cost, rather than their potential environmental impacts. The aim of this study is to present a combined approach to estimate the leaching potential and environmental impacts of pesticides for agricultural lands. The pilot study area (PSA) is the agricultural plain of the Lower Aksu Stream Basin in Antalya - Turkey. The groundwater of the agricultural plain contributes to around half of the flow rate of the stream. The first phase of the combined approach involved pesticide monitoring to screen the target pesticides, the second phase involved evaluating the physicochemical properties of the target pesticides and estimating their leaching potential using several indices, and the third phase involved environmental impact analysis of the target pesticides using the Environmental Impact Quotient (EIQ) risk indicator. Additionally, Principal Component Analysis was conducted to examine the correlations between physicochemical parameters of pesticides and the leaching potential index results. By the application of the combined approach, 45 target pesticides were identified for the PSA and the indices were consistent to estimate similar leaching potentials for the same pesticides. Moreover, the computed EIQ-Field Use Rates provided valuable information to rank target pesticides according to their environmental impacts on consumer, farmworker and ecology. The applied methodology provided a practical approach to select pesticides with the least leaching potential and environmental impacts to protect water quality and ecosystem health.

Impacts of the protective measures taken for the COVID-19 pandemic on water consumption and post meter leakages in public places.

Adequate, secure, and sustainable water supply gained utmost importance as an essential public service during the COVID-19 pandemic. The aim of this research study is to investigate impacts of the protective measures taken for the COVID-19 pandemic on water consumption and post meter leakages in public places. A total of 22 pilot study sites (PSS) representing schools, graveyards, parks, mosques, public toilets, a university building, and a sport facility were chosen to apply this study. The PSS were equipped with smart meters with different sizes that were capable of measuring the flow rates at short intervals of 15 min. The flow rates were continuously monitored at the PSS for more than 1 year before and during the COVID-19 pandemic in 2019 and 2020. Post meter leakages were determined based on the minimum night flow (MNF). The monitoring results showed a considerable decrease (42%) in the total flow rates at public places because of the lockdown measures, but excessive post meter leakages (72% of total flow rates) were also observed. Additionally, the decrease in flow rates adversely affected measuring accuracy of the meters and thereby increased the apparent water losses. Control of post meter leakages and selection of appropriate size of meters are important for efficient use of urban water. Water and energy savings besides reduction in greenhouse gas emissions are the main environmental benefits of leakage control. The use of smart technologies contributes to efficient and sustainable management of urban water demand, but raising public awareness for conservation of water is essential.

Evaluation of different management scenarios for trout farm effluents using dynamic water quality modeling.

Trout farm effluents are among the important sources of water pollution by nutrients, organics, and suspended solids. This research study was conducted to investigate and manage the impacts of trout farm effluents on Esen Stream water quality, which is located at the southwest of Turkey. A water quality monitoring program was conducted for a period of 1 year at 21 stations to determine river hydraulics and water quality characteristics. Monthly water quality analyses were conducted for inflow and outflow of a number of selected farms to determine their characteristics and contribution to water pollution. About 1460 t of suspended solids, 230 t of nitrogen, and 46 t of phosphorus were annually discharged into Esen Stream from the farms. A dynamic water quality simulation model developed by the US-Environmental Protection Agency, WASP8, was applied to Esen Stream to predict and manage pollution from trout farms and the tributaries. The calibrated and verified model was used to evaluate the impacts of different management scenarios on stream water quality. Solid removal with a rotating micro-screen, establishment of a partially recirculated system and increasing production capacities of farms were among the simulated scenarios. The best management practice was the combined application of solids removal and reuse of treated farm effluents in a partially recirculated system, which provided significant improvements in the receiving stream water quality. This study showed that dynamic water quality models are powerful tools for basin-scale management of land-based aquaculture for capacity planning, assimilation capacity estimation, sustainable operation, and environmental impact assessment.

Significance of validation for karst aquifers' vulnerability assessments: Antalya Travertine Plateau (Turkey) application.

Vulnerability maps were generated for Altinova Region within the Antalya Travertine Plateau based on DRASTIC, SINTACS, EPIK, COP and PI methods. Majority of the study area is covered by productive karstic aquifer, which is composed of travertine. Travertine includes typical karstic features such as dolines, springs and caves where groundwater of travertine aquifer is the sole source for irrigation. Areal extends of low, medium, high and very high vulnerability classes and their areal extends were determined for all methods and compared with each other. High and very high vulnerable areas covered >74% of the study area as investigated by all methods, except PI. Although PI is a specific method for karstic aquifers, this method could not generate a reasonable vulnerability map based on the assigned parameter definitions and scores. Only areal extents were not sufficient to decide about the proper vulnerability method for the study area. Therefore, NO3- concentration based validation method was performed for all generated vulnerability maps. Consequently, the areas which had NO3- concentrations higher than 30 mg/L were matched with high-very high vulnerable areas. According to this validation method, application of SINTACS with "karstic aquifer" weights could validate 95% of the area with NO3- concentrations higher than the selected threshold level of 30 mg/L for Altinova region. This study showed that simulation performance of vulnerability methods was highly related to the defined parameter definitions, score ranges and weights of each method. Similar parameters with variable score ranges could create considerably distinct vulnerability maps. Validation is the essential interpretation step for taking decision on the proper vulnerability method. Additionally, site-specific contaminant observations are critical for validation of vulnerability maps. Validated vulnerability maps could be used as a valuable water resources management tool.

A fuzzy logic approach to assess groundwater pollution levels below agricultural fields.

A fuzzy logic approach has been developed to assess the groundwater pollution levels below agricultural fields. The data collected for Kumluca Plain of Turkey have been utilized to develop the approach. The plain is known with its intensive agricultural activities, which imply excessive application of fertilizers. The characteristics of the soils and underlying groundwater for this plain were monitored during the years 1999 and 2000. Additionally, an extensive field survey related to the types and yields of crops, fertilizer application and irrigation water was carried out. Both the soil and groundwater have exhibited high levels of nitrogen, phosphorus and salinity with considerable spatial and temporal variations. The pollution level of groundwater at several established stations within the plain were assessed using Fuzzy Logic. Water Pollution Index (WPI) values are calculated by Fuzzy Logic utilizing the most significant groundwater pollutants in the area namely nitrite, nitrate and orthophosphate together with the groundwater vulnerability to pollution. The results of the calculated WPI and the monitoring study have yielded good agreement. WPI indicated high to moderate water pollution levels at Kumluca plain depending on factors such as agricultural age, depth to groundwater, soil characteristics and vulnerability of groundwater to pollution. Fuzzy Logic approach has shown to be a practical, simple and useful tool to assess groundwater pollution levels.