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Herbicides play a pivotal role in paddy rice cultivation by effectively controlling weeds, thus ensuring optimal resource utilisation and higher crop yields, making them indispensable for efficient rice production systems. However, herbicide applications could be related to potential environmental impacts such as water contamination and harm to non-target species, requiring special attention in their management to ensure the long-term sustainability of rice farming practices. The development and utilisation of robust risk assessment indicators for pesticides are essential tools in evaluating and mitigating potential environmental and human health hazards associated with pesticide use in agricultural practices. The Environmental Potential Risk Indicator for Pesticides (EPRIP) is not suitable for rice paddy cultivation due to its limitations in accurately assessing pesticide risk in this specific agricultural context. This is primarily attributed to the unique hydrological characteristics and ecosystem dynamics of paddy fields, which significantly differ from other agricultural systems. To address this issue and to enhance the accuracy of pesticide risk assessment in rice paddy fields, EPRIP has been improved and validated in two agricultural seasons. A synergistic approach involving field experiments and enhanced EPRIP model simulations was employed to assess the risk associated with the application of two herbicides in Italian paddy rice systems. The observed and model-predicted surface water (SW) concentrations exhibited a close alignment, though an overestimation was observed for groundwater (GW). In general, the estimated Risk Points (1 for SW and 4 for GW) were largely in accord with those derived from the field experiments (1 for SW and 3 for GW), suggesting that the refined EPRIP model holds promise for conducting reliable risk assessments following herbicide applications in such contexts.

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When river water quality fluctuates over relatively short periods of time with respect to the sampling frequency, the collection of grab samples may be inappropriate for characterising average water quality. This paper presents the results of a water quality monitoring study carried out on a stretch of the river Lambro (northern Italy) dominated by a periodically overloaded sewage treatment works (STW) located near its upstream end. Water quality was strongly influenced by a pronounced diurnal cycle in pollutant loads caused by the regular emission of untreated waste water during periods of high domestic flow (daytime). Two different sampling techniques were employed: grab sampling and 24-h composite sampling using automatic samplers. Samples were collected at the plant overflow and at several sites along the river and analysed for two common ingredients of household detergents, linear alkylbenzene sulphonate (LAS) and boron (B) and for routine water quality variables. The results obtained show that: (1) The diurnal variability of point-source-derived chemical concentrations in the river downstream of the undersized STW increased with increasing removal efficiency in sewage treatment. (2) The shape of the diurnal concentration signal remained relatively intact for a considerable distance downstream of the STW for several water quality variables, suggesting that hydrodynamic dispersion plays a relatively minor role in controlling concentration patterns in this river. (3) In-stream degradation of LAS was consistent with first order kinetics with a rate constant of 0.05-0.06 h(-1). (4) Grab sampling is a relatively inefficient methodology for capturing mean concentrations for rivers subjected to highly variable loads, especially when it is restricted to office hours. The inefficiency of grab sampling is more marked for substances (e.g. LAS) which are effectively removed during sewage treatment than for substances which are not. (5) For LAS, diurnal variability in the concentration signal decreases with distance downstream, making grab sampling an increasingly reliable methodology for estimating mean concentrations. (6) 24-h composite sampling is an efficient way of eliminating the effect of diurnal variations in load strength.

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The work presents the results of a comprehensive modelling study of surface and groundwater resources in the Muzza-Bassa Lodigiana irrigation district, in Northern Italy. It assesses the impact of changes in land use and irrigation water availability on the distribution of crop water consumption in space and time, as well as on the groundwater resources. A distributed, integrated surface water-groundwater simulation system was implemented and applied to the study area. The system is based on the coupling of a conceptual vadose zone model with the groundwater model MODFLOW. To assess the impact of land use and irrigation water availability on water deficit for crops as well as on groundwater system in the area, a number of management scenarios were identified and compared with a base scenario, reflecting the present conditions. Changes in land use may alter significantly both total crop water requirement and aquifer recharge. Water supply is sufficient to meet demand under present conditions and, from the crop water use viewpoint, a reduction of water availability has a positive effect on the overall irrigation system efficiency; however, evapotranspiration deficit increases, concentrated in July and August, when it may be critical for maize crops.

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Per capita boron loads reaching 48 sewage treatment works (STWs) in The Netherlands, Germany, Italy, and the UK have been determined from monitoring data. These have been compared with the per capita input predicted from boron in detergents, as determined from detergent product sales data. The resulting distribution of the ratios of measured boron to boron predicted from consumer usage has a 90th percentile of less than 1.5. Boron has previously been shown to be a good marker for substances contained in detergent products, as it cannot be biodegraded and is not substantially adsorbed in the sewer, and there is little or no removal during sewage treatment processes. The monitoring information on the distribution of boron loads found at the different STWs should thus be indicative of the distribution of other substances released to the environment by detergent products, as specified by the relevant industrial category (IC 5-personal/domestic) in the Technical Guidance Documents. Variation in detergent product consumption figures from 18 European countries is also low, with the country with the highest per capita detergent consumption having only 1.3 times the European average detergent use. Thus the present practice of determining a "reasonable worst case" by multiplying the average per capita consumption by a factor of four to account for geographic differences in distribution, is considered to be inappropriate. This should be replaced by a factor of less than two, which combines within country and between country variations to provide a reasonable worst case approximation of the load reaching the sewage treatment facility.

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