This study compares the Canadian Council Water Quality Index (CCME WQI) and the Arithmetic Water Quality Index (WAWQI) methodologies for determining the quality of water in the city of Azogues (Ecuador). Additionally, a drinking water quality risk index (IRCA) was determined to evaluate the degree of risk of disease occurrence related to water consumption. The data generated came from the analyses of twelve physicochemical parameters (pH, turbidity, colour, total dissolved solids, electrical conductivity, total hardness, alkalinity, nitrates, phosphates, sulfates, chlorides, residual chlorine) from 172 samples of water over six months. The calculated average value of CCME WQI (97.59 ± 1.08) indicates that 100% of the drinking system was of ‘excellent’ quality. The WAWQI average value was calculated to be 26.36 ± 1.13 indicating that 16.67% of the distribution system was of ‘excellent’ quality and 83.33% of the distribution water was of ‘good’ quality. The IRCA calculated in all the distribution zones is between 0 and 5% and therefore, the distributed water is considered suitable for human consumption and is rated at the no-risk level. Furthermore, WAWQI is influenced by parameters with low maximum allowed concentration (for example, turbidity value 1 NTU in the Ecuadorian standard was used instead of 5 NTU recommended by the WHO); conversely, CCME-WQI is influenced by parameters with a high maximum allowed concentration (no parameter exceeded the norm in this study). The IRCA is a support instrument to guarantee that the water supplied by the provider companies complies with the characteristics established for drinking water. GRAPHICAL ABSTRACT

The cultivation of rice is one of the main sources of greenhouse gas (GHG) emissions due to continuously flooded irrigation (CF), which demands large volumes of water. As an alternative solution, alternate wetting and drying (AWD) irrigation has been developed as a water-saving strategy. This study was conducted at the Experimental Agricultural Station (EEA) in Vista, Florida, in the Lambayeque region located on the northern coast of Peru. Thus, it was analyzed the effect of AWD irrigation at different depths (5, 10, and less than 20 cm below the surface) compared to CF control on methane (CH₄) and nitrous oxide (N₂O) emissions and rice grain yield. AWD treatments reduced CH₄ emissions by 84% to 99% but increased N₂O emissions by 66% to 273%. In terms of Global Warming Potential (GWP), the AWD₁₀ treatment demonstrated a 77% reduction and a Water Use Efficiency (WUE) of 0.96, affecting only a 2% decrease in rice grain yield, which ranged between 11.85 and 14.01 ${\mathrm{t} \mathrm{ha}}^{-1}$. Likewise, this study provides sufficient evidence for the adoption of AWD irrigation as a strategy for the efficient use of water resources and the mitigation of GHG emissions in rice cultivation in the study area, compared to continuous flooded irrigation.

In the face of the climate change crisis, the increase in air temperature negatively impacts rice crop productivity due to stress from water scarcity. The objective of this study was to determine the rice crop water stress index (CWSI) and stomatal conductance (Gs) under different irrigation regimes, specifically continuous flood irrigation treatments (CF) and irrigations with alternating wetting and drying (AWD) at water levels of 5 cm, 10 cm, and 20 cm below the soil surface (${\mathrm{AWD}}_5{, \mathrm{AWD}}_{10}$, and ${\mathrm{AWD}}_{20}$) in an experimental area of INIA-Vista Florida and in six commercial areas of the Lambayeque region using thermal images captured with thermal sensors. The results indicated that AWD irrigation generated more water stress, with CWSI values between 0.4 and 1.0. Despite this, the yields were similar in CF and ${\mathrm{AWD}}_{20}.$In the commercial areas, CWSI values between 0.38 and 0.51 were obtained, with Santa Julia having the highest values. Furthermore, a strong Pearson correlation (R) of 0.91 was established between the CWSI and Gs, representing a reference scale based on Gs values for evaluating water stress levels.

Predicting rice yield accurately is crucial for enhancing farming practices and securing food supplies. This research aims to estimate rice yield in Peru’s Lambayeque region by utilizing spectral and textural indices derived from unmanned aerial vehicle (UAV) imagery, which offers a cost-effective alternative to traditional approaches. UAV data collection in commercial areas involved seven flights in 2022 and ten in 2023, focusing on key growth stages such as flowering, milk, and dough, each showing significant predictive capability. Vegetation indices like NDVI, SP, DVI, NDRE, GNDVI, and EVI2, along with textural features from the gray-level co-occurrence matrix (GLCM) such as ENE, ENT, COR, IDM, CON, SA, and VAR, were combined to form a comprehensive dataset for model training. Among the machine learning models tested, including Multiple Linear Regression (MLR), Support Vector Machines (SVR), and Random Forest (RF), MLR demonstrated high reliability for annual data with an R² of 0.69 during the flowering and milk stages, and an R² of 0.78 for the dough stage in 2022. The RF model excelled in the combined analysis of 2022–2023 data, achieving an R² of 0.58 for the dough stage, all confirmed through cross-validation. Integrating spectral and textural data from UAV imagery enhances early yield prediction, aiding precision agriculture and informed decision-making in rice management. These results emphasize the need to incorporate climate variables to refine predictions under diverse environmental conditions, offering a scalable solution to improve agricultural management and market planning.

This article presents data on corrosion and dissolved copper in copper tubes that transport drinking water in domiciles of the Azogues city, Ecuador. Corrosion tests were performed using copper coupons exposed to water with different concentrations of free chlorine for 30, 60, 90 and 180 days. The determination of the copper corrosion rate exposed in chlorine was carried out by means of gravimetric tests. With weight loss data, the corrosion rate was determined. By means of static immersion tests, copper release of coupon surface was determined. In the obtained data it was observed that the corrosion rate and the release of copper increases with the chlorine concentration. This data is beneficial for drinking water companies and building builders by providing information on the corrosion and leaching behavior of copper pipes when exposed to chlorine and is useful for predicting the service life copper pipes. In addition, it could allow assessing the health risk by consuming water with copper in solution.