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- Predictive modeling of terrestrial radiation for optimizing solar-powered irrigation under limited data in Adrar Region (Algeria)Publication . Meziani, Assia; Mega, Nabil; Miloudi, Abdelmonen; Duarte, A.C.An accurate estimation of the radiation is a prerequisite for the net radiation balance, evapotranspiration modeling, and optimal scheduling of water extraction by solar-powered irrigation, especially in the water-scarce Saharan zone. In this study, we developed a predictive model to estimate daily terrestrial radiation at the surface of the Adrar region in Algeria. We used a training set of 25 years of data (2000–2025) from 10 stations (Adrar, Tamantit, Sidi Ahmed Timmi, Fenoughil, Zaouiet Kounta, Reggane, Gharmianou, Tittaf, Ikiss, Kassbet Lahrar) with only three features: soil temperature (0–7 cm), air temperature (2 m), and vapor pressure deficit. The robustness of the models was ensured by a time-based split. The random forest (RF), gradient boosting (GB), and extra trees (ET) tree-based models were evaluated on the generalization set. RF and ET exhibited the best performance (R = 0.92, rootean square error—RMSE = 31.85 W/m2, Nash–Sutcliffe efficiency—NSE = 0.84 for RF; R = 0.92, RMSE = 32.33 W/m2, NSE = 0.84 for ET), whereas GB exhibited poor performance (R = 0.90, RMSE = 36.67 W/m2, NSE = 0.79). Finally, we proposed a map for solar-powered irrigation optimization. In particular, we demonstrated that the southern part of the Adrar region (Reggane, Zaouiet Kounta) has high potential for solar-powered irrigation (more than 350 W/m2). This study contributes to hyper-arid agricultural regions in Algeria through water conservation and the utilization of renewable energy.
- Spatiotemporal analysis and machine learning prediction of reference evapotranspiration in Khenchela, Algeria: Comparison of MLR, GRNN, and LSTM modelsPublication . Meziani, Assia; Mega, Nabil; Miloudi, Abdelmonen; Duarte, A.C.; Khechekhouche, AbderahamaneReference evapotranspiration (ET₀) is a key parameter for water management in semi-arid regions with variable climates. This study analyzed the spatiotemporal dynamics of annual ET₀ in the Khenchela region of north-eastern Algeria (2000–2024). ET₀ was computed using the FAO-56 Penman–Monteith (PM) method. Spatial patterns were mapped using Inverse Distance Weighting (IDW). Meteorological data from 16 stations were used to train three models: Multiple Linear Regression (MLR), Generalized Regression Neural Network (GRNN), and Long Short-Term Memory (LSTM) to predict ET₀. The regional mean annual ET₀ increased by 7.2% from 2010 to 2019 decadal average (1 490 mm/year) to the 2020-2024 period (1597 mm/year), contributing to a cumulative 25-year increase of 7% from 2000 to 2009 baseline with hotspots in Babar 2 reaching ~2194 mm/year. The Mann–Kendall test confirmed significant upward trends (p < 0.05) driven by rising temperatures and declining relative humidity. All models performed well (R² > 0.965, RMSE < 0.49 mm/day, RSR < 0.20), with LSTM showing superior accuracy (R² > 0.987, RMSE < 0.232 mm/day, NSE ≈ 0.991, WI > 0.909). The superior performance of LSTM is attributed to its inherent capability to capture temporal autocorrelation and long-term dependencies in climatic time-series data. These findings support adaptive irrigation and drought mitigation in semi-arid regions of northern Africa.
- Neural network approximation based on ANFIS and Geographic Information System mapping for reliable evapotranspiration prediction in Khenchela, AlgeriaPublication . Meziani, Assia; Mega, Nabil; Miloudi, Abdelmonen; Duarte, A.C.; Khechekhouche, AbderahamaneAccurate estimation of reference evapotranspiration (ET0) is critical for sustainable water resource management, irrigation scheduling, and climate adaptation in heterogeneous semi-arid regions. This study presents a streamlined neural network (NN) approximation inspired by the Adaptive Neuro-Fuzzy Inference System (ANFIS) for predicting daily ET0 in Khenchela province, northeastern Algeria. Utilizing meteorological and soil data from 2000 to 2024 at 16 representative stations (Babar (1), Babar (2), Babar (3), Baghai, Bouhmama, Chechar, Djellal, El Hamma, Kais, Khenchela, Khirane, M’sara, Remila, Tamza, Taouzient, and Zaoui), sourced from the Open-Meteo Historical Weather API, the model employs inputs including air temperature, relative humidity, precipitation, wind speed, sunshine duration, terrestrial radiation, soil temperature, and soil moisture. The NN was trained to closely approximate the FAO-56 Penman-Monteith reference ET0 values computed directly by the API. Performance evaluation yielded strong agreement across stations: R2 > 0.96, RMSE 0.22 - 0.46 mm/day, NSE > 0.95, RSR < 0.13, and Willmott’s index 0.88 - 0.93, with peak accuracy (R2 > 0.99, RMSE < 0.24 mm/day) at high-elevation sites. Spatial patterns, mapped via GIS-based inverse distance weighting interpolation, revealed pronounced topographic and aridity-driven variability, confirmed by Emberger and De Martonne indices. This computationally efficient NN offers a scalable surrogate for FAO-56 calculations in data-limited, heterogeneous environments, supporting precision irrigation, drought monitoring, and adaptive strategies in semi-arid North Africa and Mediterranean regions.
- Effects of DEM Resolution on the characterization of a small agroforestry basin for hydrological modelling: The case of Idanha—PortugalPublication . Duarte, A.C.; Ferreira, Carla; Vitali, GiulianoDigital elevation models (DEMs) are key fundamental inputs in hydrological modelling, yet the influence of spatial resolution on basin delineation and process representation remains insufficiently understood, particularly in small catchments. This study investigates the influence of DEM resolution on topographic characterization and hydrological response in a small agroforestry basin in central Portugal. Three DEMs with resolutions of 5 m, 10 m, and 30 m were generated from contour data and satellite sources and processed using the TOPAZ-based TopAGNPS delineation framework. The sensitivity of basin structure to delineation parameters—critical source area (CSA) and minimum source channel length (MSCL)—was assessed, and the resulting configurations were used as inputs to the AnnAGNPS model. Results show that DEM resolution strongly influences the representation of hydrological cells and stream reaches. Increasing resolution from 30 m to 5 m leads to a nearly doubling of average cell slope and increases reach slope by more than four times, with corresponding changes in drainage network density and connectivity. Loglinear relationships were identified between slope and contributing area, as well as between slope and reach length, consistent with established geomorphic scaling laws. Hydrological simulations further indicate that resolution-dependent delineation significantly influences runoff, erosion, and peak discharge estimates, with finer resolutions increasing sensitivity to parametrization. Among land-cover scenarios, desertified conditions generate substantially higher runoff and peak flows compared to naturalized and forested conditions. Overall, the findings demonstrate that DEM resolution, together with preprocessing and delineation choices, exerts a critical control on hydrological model outputs. These effects are particularly pronounced in low-relief, human-influenced catchments, where coarse-resolution DEMs may lead to systematic underestimation of hydrological responses. The study highlights the need for resolution-aware modelling strategies and careful parametrization to improve the reliability and transferability of hydrological simulations.
- Emerging contaminants in water resources: Monitoring gaps, treatment limitations and governance challenges with insights from PortugalPublication . Esperanço, Pedro; Leal, Teresa; Almeida, André; Duarte, A.C.; Lopes, Luísa Cruz; Gonçalves, José Manuel; Oliveira, MargaridaThis study provides a comprehensive overview of emerging contaminants in water resources. It includes a global perspective with specific insights from Portugal. Following PRISMA 2020 guidelines, peer-reviewed studies published between 2020 and 2025 were critically assessed to identify patterns of contamination, monitoring gaps and technological readiness levels. Results indicate frequently detected emerging contaminants including pesticides, antibiotics and antidepressants in surface water, groundwater and wastewater systems. Advanced analytical methods, particularly liquid chromatography coupled with high-resolution mass spectrometry, stands out as the main detection technique, allowing the identification of trace levels of contaminants. These techniques also support the identification of pollution patterns associated with agriculture, urban and industrial effluents. However, significant asymmetries persist between international and Portuguese research. Particularly evident in systematic monitoring networks and integrated risk assessment approaches. Conventional water/wastewater treatment plants show limited removal efficiency, while advanced oxidation processes, adsorption technologies and microalgae-based systems demonstrate promising but variable performance depending on scale and operational maturity. The findings highlight gaps between scientific advances and regulatory implementation, emphasizing the need for strengthened monitoring frameworks and technology scale-up strategies. They also call for improved integration between science, governance, and sustainability policies to ensure resilient water resource management in line with the Sustainable Development Goals.
- Machine learning models for simulating daily reference evapotranspiration in a semi-arid environment using four meteorological variables: A multi-station study in Northwestern Algeria (Tlemcen Region)Publication . Meziani, Assia; Duarte, A.C.In this study, we evaluated the use of five different ML algorithms (CatBoost, XGBoost, random forest, gradient boosting, and support vector regression [SVR]) to estimate daily ET0 based only on four independent variables: 2 m air temperature, vapor pressure deficit, 10 m wind speed, and sunshine duration. We used a total of 9132 daily values (2000–2025) from the Open-Meteo Historical Weather API (2000–2025) at 10 stations in the Tlemcen province of northwest Algeria. The dataset was divided into training, validation, and testing sets using a chronological split of 70/15/15. We estimated the performance of each algorithm by using several statistics (RMSE, MAE, R2, NSE, RSR, andWillmott Index) as well as some statistics to evaluate the potential of overfitting and the ability to reproduce the behavior observed during the training phase. CatBoost had the highest overall accuracy and the most generalized performance, with an RMSE of approximately 0.292 mm day−1, MAE of approximately 0.208 mm day−1, R2 of 0.971, and NSE of 0.971 in the test set, suggesting an extremely low risk of overfitting. The optimal CatBoost model was also used to estimate the spatial and temporal variations of monthly ET0. The results showed high interannual variability (changes from year to year from −12.815 to +8.707 mm month−1) in the semi-arid region of Tlemcen but no significant long-term trends (cumulative net change of approximately −0.021 mm month−1 over 2000–2025). Therefore, the use of CatBoost is recommended as a robust, efficient, and reliable emulator of the FAO-56 Penman–Monteith equation (ET0) for estimating ET0 in semi-arid environments with limited climate data availability, and could be particularly useful in northwestern Algeria and other semi-arid Mediterranean regions.
- Use of cactus pear (Opuntia ficus-indica) as forage in the diet of small ruminantsPublication . Pitacas, F.I.; Reis, C.M.G.; Rodrigues, A.M.The use of cactus pear (Opuntia ficus-indica (L.) Miller) has proven to be a viable alternative for feeding small ruminants, particularly in arid and semi-arid regions. It serves as an accessible source of water and nutrients, partially replacing more expensive and less available feeds, especially during periods of feed scarcity. This review examines the nutritional value and chemical composition of cactus pear cladodes and their application in small ruminant feeding. Additionally, general aspects related to planting systems, biomass production, and cladode storage are discussed. Three examples of diets incorporating Opuntia ficus-indica cladodes in small ruminant feeding are presented: Assaf sheep breed, fattening lamb, and Saanen goat breed. In these diets, the proportion of fresh O. ficus-indica cladodes varied between 51.3% and 79.2%. A literature review was conducted to evaluate the impact of cactus pear cladodes on meat and milk production and quality. In general, O. ficus-indica cladodes exhibit low levels of dry matter (DM), crude protein (CP), and neutral detergent fibre (NDF). However, they are an excellent source of energy, rich in non-fibrous arbohydrates, and have a high DM digestibility. Given the importance of DM, CP, and NDF in ruminant nutrition and the high-water content of cladodes, O. ficus-indica can be effectively integrated into diets when animals have access to dry forage and a high-CP feed source. The use of O. ficus-indica represents a promising option for feeding small ruminants, offering a sustainable solution to reduce dependence on imported feeds and contributing to a lower carbon footprint, without compromising meat and milk production or quality.
- Animal-origin food waste across global supply chains: Trends, upcycling strategies, and circular economy solutionsPublication . Gonçalves, Joana; Guiné, Raquel P.F.; Ribeiro, Paulo; Florença, Sofia G.; Lopes, Luísa Cruz; Anjos, O.; Sun, Da-WenRecently, the problem of food waste management has attracted the attention of producers, processors, retailers, and consumers due to economic, environmental, food safety, and sustainability consequences, affecting the entire food supply chain. This article reviews data on food waste of animal origin at different stages along the production and transformation systems, from an environmental, economic, or social perspective. Results show differences between developed and developing countries. While in developed countries, most waste occurs at the end of the food chain, in developing countries, most waste occurs in primary production and transportation. Food waste is very expressive in production and retail, but also in final consumption in households and food services. Mitigating measures include upcycling, i.e., recovering valuable food components for industrial use with economic and environmental benefits, and alternatives for food waste reutilization. The role of the consumer is unquestionable, particularly when shopping for food for the household or when consuming food in restaurants or canteens. Hence, it is crucial to understand the behaviours leading to food waste as a way to reduce it and implement strategies to effectively reduce food waste at various levels. The role of education, regulation, and policies is pivotal in achieving minimal food waste.
- Selección de sustrato de emergencia por Cordulegaster boltonii (Donovan, 1807) (Odonata: Cordulegastridae) en un río del centro de la Península IbéricaPublication . Casanueva, Patricia; Campos, Francisco; Velasco, Tatiana; Sanz, Germán; Nunes, LuisaSe analizan los sustratos de emergencia de Cordulegaster boltonii en un río del centro de la Península Ibérica. Para ello se recogieron exuvias en un tramo de 60 m de longitud. El 86% de las exuvias estaban sobre vegetales y las restantes sobre rocas del cauce. En la zona analizada las larvas seleccionaron positivamente para emerger plantas de la familia Cyperaceae, principalmente Carex y Eleocharis. Ninguna exuvia se localizó en árboles, tanto troncos como raíces fuera del agua.
- Altitudinal variation of wing length and wing area in Libellula quadrimaculata (Odonata: Libellulidae)Publication . Casanueva, Patricia; Sanz Requena, José-Francisco; Hernández, M. Ángeles; Ortega, Silvia; Nunes, Luisa; Campos, FranciscoThe area and length of the right fore and hind wings and the abdomen length were analysed in specimens from two Iberian populations of Libellula quadrimaculata Linnaeus, 1758, one on a plateau (782 m a.s.l.) and another in the mountains (1 909 m a.s.l.), with a view to ascertaining whether their morphometric characteristics vary with altitude. Allometric relationships in terms of length and area of the fore and hind wings of both populations were found. The wings are longer and have a greater area in plateau specimens whereas the length of the abdomen did not vary between populations. Between the populations there was an overlap in the wing length measurements. The significance of these parameters in aiding the dragonflies’ flight capacity and hence the effects on their lifestyle under different environmental conditions is discussed.