Biochar, a carbon-rich by-product of organic matter pyrolysis, has a variety of physiochemical properties beside a variety of applications. This review highlights some physical and chemical characteristics of herbaceous, woody, and sewage waste biochar under different pyrolysis conditions, as well as soil and foliar applications of biochar. The controlling role of pyrolysis temperature was the reason for selecting the discussed biochar types in the study. This review concludes that increasing pyrolysis temperature mainly raised the values of some chemical properties of the biochar, such as pH, electrical conductivity (EC), ash content, total phosphorus (TP), and a few values of physical properties like porosity and specific surface area (SSA). On the other hand, yield and total nitrogen (TN) decreased with rising pyrolysis temperature. Among biochar application methods to soil, mixing biochar with soil before planting is one of the best methods of application, and in most cases, biochar reapplication improved soil properties, while foliar application of biochar has positive effects on plant growth and yield parameters, ranging from low rates to the highest ones.

A field experiment was conducted with soybean to observe evapotranspiration (ET) and crop water stress index (CWSI) with three watering levels at Keszthely, Hungary, during the growing seasons 2017–2020. The three different watering levels were rainfed, unlimited, and water stress in flowering. Traditional and converted evapotranspirometers documented water stress levels in two soybean varieties (Sinara, Sigalia), with differing water demands. ET totals with no significant differences between varieties varied from 291.9 to 694.9 mm in dry, and from 205.5 to 615.6 mm in wet seasons. Theoretical CWSI, CWSI_t was computed using the method of Jackson. One of the seasons, the wet 2020 had to be excluded from the CWSI_t analysis because of uncertain canopy temperature, T_c data. Seasonal mean CWSI_t and T_c were inversely related to water use efficiency. An unsupervised Kohonen self-organizing map (K-SOM) was developed to predict the CWSI, CWSI_p based on easily accessible meteorological variables and T_c. In the prediction, the CWSI_p of three watering levels and two varieties covered a wide range of index values. The results suggest that CWSI_p modelling with the minimum amount of input data provided opportunity for reliable CWSI_p predictions in every water treatment (R² = 0.935–0.953; RMSE = 0.033–0.068 mm, MAE = 0.026–0.158, NSE = 0.336–0.901, SI = 0.095–0.182) that could be useful in water stress management of soybean. However, highly variable weather conditions in the mild continental climate of Hungary might limit the potential of CWSI application. The results in the study suggest that a less than 450 mm seasonal precipitation caused yield reduction. Therefore, a 100–160 mm additional water use could be recommended during the dry growing seasons of the country. The 150 year-long local meteorological data indicated that 6 growing seasons out of 10 are short of precipitation in rainfed soybean.

The five-year mean yield of five Hungarian wheat production counties was 5.59 t ha⁻¹ with a 7.02% average coefficient of variation. There was a regional effect on yield when progressing from south to north with a 1–2 °C higher mean winter air temperature, meaning that the T_a in southern counties increased the five-season mean yield by 15.9% (p = 0.002) compared to the yield of northern counties. Logistic regression models developed to assess the FHB risk driven by a few meteorological variables (T_a; RH) provided proper predictive performance. The results in the regression model were validated against the measured infection rates (P%) provided by the NÉBIH 30 days before and after heading. The FHB pressure was comparatively higher in Zala County, probably due to its special topological and growing conditions, irrespective of the season. Across all areas studied, two of the five identified counties (Pest and Somogy) provided the best classification for FHB infection. In the remaining three counties, the seasonal mean prediction accuracy (differences) exceeded 10% in only 6 out of 30 model outputs. The modeled five-season P% values averaged 70.4% and 93.2% of the measured infection rates for models 1 and 2, respectively. The coincidence of wet and warm weather around the time of wheat flowering enhanced the risk of FHB.

Leaf-litter input constitutes a major load in natural waters; therefore, to achieve and maintain high water quality, it is important to thoroughly examine and understand the litter decomposition process. The widespread Solidago canadensis exerts a negative effect on the composition of the ecosystem, causes extinction of species, and modifies the function of the system. In Hungary, goldenrod constantly spreads to newer areas, which can also be observed around Lake Balaton and at the bank of the Hévíz canal. In our investigation, we examined the decomposition rate of the leaves and stems of the goldenrod with the commonly applied method of leaf litter bags. As water temperature, ranging from 24.0 °C to 13.7 °C, decreases in Hévíz canal away from Lake Hévíz (−0.32 °C/100 m), we chose three different sampling sites with different water temperatures along the canal to determine how water temperature influences the rate of decomposition. For both leaves and stems, the fastest decomposition rate was observed at the first site, closest to the lake. At further sites with lower water temperatures, leaf litter decomposition rates decreased. Results observed through Hévíz canal demonstrated that higher water temperature accelerated the goldenrod decomposition dynamics, while the drift also impacted its efficiency.

When examining the water balance of lakes, the measurement and determination of evaporation and transpiration are the biggest problems. Evapotranspiration - as an output parameter of water balance- is very important in case of our largest lake, Lake Balaton and the associated Kis-Balaton Protection System. The evapotranspiration of the common reed (Phragmites australis) plays a decisive ecological role in the wildlife of the marshes. In case of Kis-Balaton, common reed is a significant factor due to the extent of its stands, which exceed 2,000 hectares. The latest solutions in evapotranspiration models are remote sensing models. We have tried to estimate the areal evapotranspiration with the red and near-infrared bands (NDVI, Normalized Difference Vegetation Index) of Landsat-8 satellite images using two different approaches: the use of FAO-56 potential evapotranspiration equation with local crop coefficients and the SEBAL model.