The relative relationships “yield – evapotranspiration” were used long time ago. The well known linear relationship yi = 1 – ky (1 – ei), where yi is relative yield, ky – yield response factor and ei – relative evapotranspiration was proposed. It’s usually assumed that ky is constant for a given crop and climatic conditions. It was found, however, that ky for late variety of maize H 708 varied through the study years (1984–1990) in the Plovdiv region (South Bulgaria, altitude 150 m). During the dry years it was significantly higher than in the medium and humid years. The range of ky for maize in this location was 1.12–1.90, the average value being 1.50. The climate in the Sofia region (the ex-perimental field of Chelopechene, altitude 550 m) is comparatively more humid. The two regions approximately outlined the boundaries of the appropriate economical conditions for grain maize pro-duction. The experiments in the Sofia region were carried out in the years 1994–2000. The seven years results for mean variety maize showed that the relationships “yield – evapotranspiration” and, respectively, ky varied at these climatic conditions too. The highest ky value was 1.41 for the driest year (2000) and the lowest value – 1.05 for the most wet years (1995, 1999). The value of ky for av-erage years was 1.21. The yield response factor ky is of more significance when the relative evapotranspiration is less than 0.7–0.8. Thus, the extreme or the average values of ky could be used for the corresponding climatic regions. The relationships between ky and relative yield were estab-lished without considering irrigation.

Lublin Upland and Roztocze region are known for the occurrence of a large number of springs of high yield. These springs are fed mainly from Cretaceous or Tertiary water-bearing horizon. In order to determine variability of springs’ yield, 61 selected springs were analysed in spring periods of the years 1998–2008. Collected hydrometric materials allowed for comparing average and extreme yield values of springs in various physiographic regions within the period of 11 years. Average value was 76.1 dm3·s–1, while the mean of the minimal yields was 44.7 dm3·s–1 and of the maximal – 132.7 dm3·s–1. Coefficient of irregularity of the springs’ yield ranged from 1.5 to 5.0, which may lead to the conclusion that the springs’ yield is constant or varies slightly. In some cases the irregularity was higher but it was determined by hydrogeological, meteorological and local factors.

Lignite still plays a key role in the production of electricity in Poland. About one-third of domestic electric energy comes from lignite burned in large power plants that produce megatons (Mt) of bottom ash and fly ash annually. Nearly 11 wt% of the total ash generated by the lignite-fired power industry in Poland comes from lignite extracted from the Konin Lignite Mine. Part of the ash escapes into the atmosphere, and the rest is utilized, which is expensive and often harmful to the environment; hence, geochemical studies of these ashes are fully justified and increasingly carried out. The lignite samples examined in this paper represent the entire vertical section of the first Mid-Polish lignite seam (MPLS-1) mined in opencasts at Jóźwin IIB, Drzewce, and Tomisławice. First, the samples were oxidized (burnt) at one of three temperatures: 100, 850, and 950°C; then the chemical composition of oxides and trace elements was determined according to the ASTM D6349-13 standard. The ashes were rich in SiO2 and CaO; Ba, Sr, and Cu dominated the trace element content. Among the harmful elements found, Pb is of most concern. Only a few elements (Ba, Cu, Pb, Sb) reached values higher than their corresponding Clarke values. Based on the results obtained, it can be concluded that the examined ashes are approximately as harmful to the environment as ashes from other lignite used to generate electricity. Moreover, the increased amount of CaCO3 in the MPLS-1 is beneficial in the process of natural desulphurization.

The aim of any industrial plant, which is dealing in the energy sector, is to maximise the revenue generation at the lowest production cost. It can be carried out either by optimizing the manpower or by improving the performance index of the overall unit. This paper focuses on the optimisation of a biomass power plant which is powered by G50 hardwood chips (Austrian standard for biomass chips). The experiments are conducted at different operating conditions. The overall effect of the enhanced abilities of a reactor on the power generation is examined. The output enthalpy of a generated gas, the gas yield of a reactor and the driving mechanism of the pyrolysis are examined in this analysis. The thermal efficiency of the plant is found to vary from 44 to 47% at 400◦C, whereas it is 44 to 48% for running the same unit at 600 ◦C. The transient thermal condition is solved with the help of the lumped capacitance method. The thermal efficiency of the same design, within the constraint limit, is enhanced by 5.5%, whereas the enthalpy of the produced gas is magnified by 49.49% through nonlinear optimisation. The temperature of biomass should be homogenous, and the ramping rate must be very high. The 16% rise in temperature of the reactor is required to reduce the mass yield by 20.17%. The gas yield of the reactor is increased by up to 85%. The thermal assessment indicates that the bed is thermally thin, thus the exterior heat transfer rate is a deciding factor of the pyrolysis in the reactor.

This study was conducted to predict the yield and biomass of lentil (Lens culinaris L.) affected by weeds using artificial neural network and multiple regression models. Systematic sampling was done at 184 sampling points at the 8-leaf to early-flowering and at lentil maturity. The weed density and height as well as canopy cover of the weeds and lentil were measured in the first sampling stage. In addition, weed species richness, diversity and evenness were calculated. The measured variables in the first sampling stage were considered as predictive variables. In the second sampling stage, lentil yield and biomass dry weight were recorded at the same sampling points as the first sampling stage. The lentil yield and biomass were considered as dependent variables. The model input data included the total raw and standardized variables of the first sampling stage, as well as the raw and standardized variables with a significant relationship to the lentil yield and biomass extracted from stepwise regression and correlation methods. The results showed that neural network prediction accuracy was significantly more than multiple regression. The best network in predicting yield of lentil was the principal component analysis network (PCA), made from total standardized data, with a correlation coefficient of 80% and normalized root mean square error of 5.85%. These values in the best network (a PCA neural network made from standardized data with significant relationship to lentil biomass) were 79% and 11.36% for lentil biomass prediction, respectively. Our results generally showed that the neural network approach could be used effectively in lentil yield prediction under weed interference conditions.

Scarcity of fresh water resources is the major constraint for agricultural development in Iran as in many other regions with arid and semi-arid climate. With the pressure on fresh water resources, the use of un-conventional water resources including brackish, saline and sewage water has received greater attentions in recent years. The objective of this study was to assess the impact of farmers' practices using saline groundwater on wheat yield and soil salinity in a Mediterranean cli-mate of Fars province in southern Iran. The study was carried out in several commercial wheat production regions for two years. Chemical analysis of irrigation waters, volume of applied irrigation water, electrical conductivity of soil saturation extract (ECe) and yield were measured in each field. General information on agronomic practices was also collected using a questionnaire. Results demonstrate that waters with salinities higher than what has been classified as “suitable for irriga-tion” are being used for the production of wheat crop. Analysis of wheat yield response to saline irrigation water showed that for water salinities up to 10.7 mS∙cm–1 (threshold value) variation in yield was relatively minor, above which wheat yield decreased at a greater rate. Root zone salinity profiles showed the effect of winter rainfall in reducing soil salinity. It is concluded that although acceptable yields are obtained with some of the highly brackish waters, over application of these waters would threaten the sustainability of crop production in the region.

The study deals with the assessment of the solid transport in the wadi Mouillah watershed (Tafna, Algeria). Sediment transport is a complex phenomenon. The quantity of sediment transported is very important, and it fills in the reservoirs. The scale is out of proportion in semiarid areas. Algeria is one of the most affected countries by this phenomenon. A simple method, based on average discharges, easy to implement, has been developed for estimating the sediment yield using dou-ble correlation method (a first one between liquid discharge – solid concentration and a second one between solid flow – concentration). It is based on hydrometric data (liquid flow, concentrations and sediment discharges) with applications analysis on seasonal and annual scales for data’s of Sidi Belkheir station at the outlet of the wadi Mouillah watershed (North-West of Algeria). The obtained results by the application of this method are very encouraging because of the quite significant correlation coefficients found (≥59% for the first correlation and ≥88% for the second correlation). The water-shed of Mouillah produces between 43 730 and 56 410 Mg·y–1 as suspended sediment load against 48.56∙103 to 53.3∙103 m3·y–1 of liquid intake.