The growing global water shortage is an increasing challenge for the agricultural sector, which aims to produce sufficient quantity and quality of food and animal feed. In our study, effluent water from an intensive African catfish farm was irrigated on grain sorghum plants in four consecutive years. In our study the effects of the effluent on the N, P, K, Na content of the seeds, on the phenological parameters (plant height, relative chlorophyll content), the green mass, and on the grain yield of three varieties (‘Alföldi 1’, ‘Farmsugro 180’ and ‘GK Emese’) were investigated. Five treatments (Körös River (K) water and effluent (E) water: 30 and 45 mm weekly irrigation water dose; non-irrigated control) were applied with micro-spray irrigation. Compared to non-irrigated plants, effluent water did not negatively affect the N, P, K and Na contents of the grain crop. In terms of phenological parameters, the quality of the irrigation water (150–230 cm) had no negative effect on any of the measured parameters compared to the control (133–187 cm) values. In terms of biomass in 2020, grain yields were 89–109 g/plant with variety Alföldi 1, 64–91 g/plant with variety Farmsugro 180, and 86–110 g/plant with GK Emese.

In this study, a special rice-energy willow/poplar agroforestry system was used to analyze the effects of reused water irrigation and mulching on soil salinity, earthworm biomass and abundance, soil organic matter (SOM) content and weed coverage in treerow-dependent habitats. After three-year-irrigation, we investigated the woody line (WL), the buffer zone (BZ) and the crop line habitats (CL). Between 2019 and 2021, we collected data on the distribution of soil-specific electrical conductivity (EC), ammonium-lactate soluble sodium (AL-Na) and exchangeable cations (Na⁺, K⁺, Ca²⁺, Mg²⁺) and soil NO₂⁻ + NO₃⁻-N contents from CL habitats irrigated with effluent water from an intensive catfish farm. Based on our results, significantly greater earthworm abundance (274 pc m⁻²) and earthworm biomass (54.0 g m⁻²) values were measured in WL than in BZ or CL habitats. There was no significant difference in weed coverage between the CL (0.61%) and BZ (1.91%), but weeds were significantly denser on the WL (12.3%). In the third year, the EC, AL-Na and ESP values were lower, but the SOM was higher in mulched soil (183.1 mS cm⁻¹, 253.1 mg kg⁻¹, 4.4 ESP% and 4.597%, respectively) than in un-mulched soil.

Efficient utilization, treatment, and disposal of agricultural wastewater and sewage sludge are important environmental risks. In our research, effluent water from intensive aquaculture was evaluated for the irrigation of short rotation energy willow in a lysimeter experiment. Two different water types and their combinations were applied with weekly doses of 15, 30, and 60 mm, respectively. Our results revealed that implementing effluent water instead of fresh water could potentially increase the yield of the willow due to its higher nitrogen content (29 N mg/L). The biomass of irrigated short rotation coppice (SRC) willow plants were between 493–864 g/plant, 226–482 g/plant, and 268–553 g/plant dry weight during experiment period (2015–2017), respectively. However, due to the chemical properties (Na concentration, SAR value) of effluent water, the increase of the soil exchangeable sodium percentage (ESP) was significant and it can lead to soil degradation in the long term. The current study also investigated the relationship between chemical composition of the plant tissue and the irrigation water. In the case of K-levels of willow clones, an increasing trend was observed year-by-year. In terms of N and Na content was localized in leaf parts, especially in samples irrigated with effluent. Less N and Na values were detected in the stem and in the samples irrigated with surface water. In SRC willow plants, phosphorus was mostly localized in the stem, to a lower extent in the leaf part. The difference is mostly observed in the case of the amount of irrigation water, where the P content of the examined plant parts decreased with the increase of the amount of irrigation water. In the case of phenological observations, higher values of plant height were measured during diluted and effluent irrigation. Moreover, the SPAD of the plants irrigated with effluent water exceeded the irrigated ones with surface water.

Nowadays, climate change not only leads to riverine floods and flash floods but also to inland excess water (IEW) inundations and drought due to extreme hydrological processes. The Carpathian Basin is extremely affected by fast-changing weather conditions during the year. IEW (sometimes referred to as water logging) is formed when, due to limited runoff, infiltration, and evaporation, surplus water remains on the surface or in places where groundwater flowing to lower areas appears on the surface by leaking through porous soil. In this study, eight different machine learning approaches were applied to derive IEW inundations on three different dates in 2021 (23 February, 7 March, 20 March). Index-based approaches are simple and provide relatively good results, but they need to be adapted to specific circumstances for each area and date. With an overall accuracy of 0.98, a Kappa of 0.65, and a QADI score of 0.020, the deep learning method Convolutional Neural Network (CNN) gave the best results, compared to the more traditional machine learning approaches Maximum Likelihood (ML), Random Forest (RF), Support Vector Machine (SVM) and artificial neural network (ANN) that were evaluated. The CNN-based IEW maps can be used in operational inland excess water control by water management authorities.

Regularly, large parts of the agricultural areas of the Great Hungarian Plain are inundated due to excessive rainfall and insufficient evaporation and infiltration. Climate change is expected to lead to increasingly extreme weather conditions, which may even increase the frequency and extent of these inundations. Shallow “floods”, also defined as inland excess water, are phenomena that occur due to a complex set of interrelated factors. Our research presents a workflow based on active and passive satellite data from Sentinel-1 and -2, combined with a large auxiliary data set to detect and predict these floods. The workflow uses convolutional neural networks to classify water bodies based on Sentinel-1 and Sentinel-2 satellite data. The inundation data were complimented with meteorological, soil, land use, and GIS data to form 24 features that were used to train an XGBoost model and a deep neural network to predict future inundations, with a daily interval. The best prediction was reached with the XGBoost model, with an overall accuracy of 86%, a Kappa value of 0.71, and an F1 score of 0.86. The SHAP explainable AI method showed that the most important input features were the amount of water detected in the satellite imagery during the week before the forecast and during the period two weeks earlier, the number of water pixels in the surroundings on the day before the forecast, and the potential evapotranspiration on the day of the forecast. The resulting inland excess water inundation time series can be used for operational action, planning, and prevention.

Irrigation determines the success of water-intensive beet cultivation in Hungary. Taking into account the guidelines of the circular economy; the aim of our study was to investigate the effect of high sodium effluent from fish farms on the yield and sugar content of fodder and sugar beet in two-year-lysimeter experiment and to calculate the possibility of phytoremediation and the potential to use saline effluent water to mitigate drought effects of root biomass reduction According to our results, irrigation with effluent water did not cause yield depression in the root biomass compared to irrigation with fresh water. The effect of irrigation water quality was seen in the sodium (Na) concentration values of the roots in both years, because it was the lowest in the treatments irrigated with Körös River fresh water. The highest estimated extracted sodium amount was 83.1 kg Na/ha in case of fodder beet variety ‘Rózsaszínű Beta’ in treatment irrigated with effluent water from catfish farm (EW) in 2021, which means 7.2% of the Na applied through the effluent water. All cultivars produced higher root fresh weight when irrigated with river Körös, effluent, or diluted waters compared to control crops irrigated by scarce rain water.