Variable rate technology (VRT) in nutrient management has been developed in order to apply crop inputs according to the required amount of fertilizers. Meteorological conditions rarely differ within one field; however, differences in soil conditions responding to precipitation or evaporation results within field variations. These variations in soil properties such as moisture content, evapotranspiration ability, etc. requires site-specific treatments for the produced crops. There is an ongoing debate among experts on how to define management zones as well as how to define the required amount of fertilizers for phosphorus and nitrogen replenishment for winter wheat (Triticum aestivum L.) production. For management zone delineation, vegetation based or soil based data collection is applied, where various sensor technology or remote sensing is in help for the farmers. and The objective of the study reported in this paper was to investigate the effect of soil moisture data derived from Sentinel-2 satellite images moisture index and variable rate phosphorus and nitrogen fertilizer by means of variable rate application (VRA) in winter wheat in Mezőföld, Hungary. Satellite based moisture index variance at the time of sowing has been derived, calculated and later used for data comparison. Data for selected points showed strong correlation (R2 = 0.8056; n = 6) between moisture index and yield, however generally for the whole field correlation does not appear. Vegetation monitoring has been carried out by means of NDVI data calculation. On the field level, as indicated earlier neither moisture index values at sowing nor vegetation index data was sufficient to determine yield. Winter wheat production based on VRA treatment resulted significant increase in harvested crop: 5.07 t/h in 2013 compared to 8.9 t/ha in 2018. Uniformly managed (control) areas provided similar yield as VRA treated areas (8.82 and 8.9 t/ha, respectively); however, the input fertilizer was reduced by 108 kg/ha N and increased by 37 kg/ha P.
The paper describes a mathematical and physical modelling of flow of complex slurries in pipelines, i.e. a flow of slurries composed of solids covering a very broad range of particle sizes that overlaps more than one flow patterns – non-Newtonian, pseudohomogeneous, heterogeneous and fully-stratified. A typical examples are residual products (“tailings”) from mining industry with normal average particle sizes of 20 to 100 μm or more. Experimental results of flows of complex slurries composing of non-Newtonian carrier fluid and three fractions of glass particles in 50 mm pipe are presented. Depending on the particle size, particles show different flow patterns and therefore considerable differences in pressure drops. Fine particles tend behave as a homogeneous matter, while coarser particles exhibit heterogeneous behaviour and even coarser particles form a sliding bed. A mathematical 3-component predictive model for turbulent flow of complex slurries is presented based on well-established semi-empirical formulae developed originally for flows with Newtonian carrier. The predicted values of pressure drops show very reasonable agreement with experimental results and indicate suitability of the model for engineering practice.
The two-dimensional particle image velocimetry (PIV) data are inevitably contaminated by noise due to various imperfections in instrumentation or algorithm, based on which the well-established vortex identification methods often yield noise or incomplete vortex structure with a jagged boundary. To make up this deficiency, a novel method was proposed in this paper and the efficiency of the new method was demonstrated by its applications in extracting the twodimensional spanwise vortex structures from 2D PIV data in open-channel flows. The new method takes up a single vortex structure by combining model matching and vorticity filtering, and successfully locates the vortex core and draws a streamlined vortex boundary. The new method shows promise as being more effective than commonly used schemes in open-channel flow applications.
We analyse water balance, hydrological response, runoff and snow cover characteristics in the Jalovecký Creek catchment (area 22 km2, mean elevation 1500 m a.s.l.), Slovakia, in hydrological years 1989–2018 to search for changes in hydrological cycle of a mountain catchment representing hydrology of the highest part of the Western Carpathians. Daily air temperature data from two meteorological stations located in the studied mountain range (the Tatra Mountains) at higher elevations show that the study period is 0.1°C to 2.4°C warmer than the climatic standard period 1951–1980. Precipitation and snow depth data from the same stations do not allow to conclude if the study period is wetter/drier or has a decreasing snow cover. Clear trends or abrupt changes in the analysed multivariate hydrometric data time series are not obvious and the oscillations found in catchment runoff are not coherent to those found in catchment precipitation and air temperature. Several time series (flashiness index, number of flow reversals, annual and seasonal discharge maxima, runoff coefficients) indicate that hydrological cycle is more dynamic in the last years of the study period and more precipitation runs off since 2014. The snow cover characteristics and climatic conditions during the snow accumulation and melting period do not indicate pronounced changes (except the number of days with snowfall at the Kasprowy Wierch station since 2011). However, some data series (e.g. flow characteristics in March and June, annual versus summer runoff coefficients since 2014) suggest the changes in the cold period of the year.
δ18O in precipitation at station Liptovský Mikuláš (about 8.5 km south from the outlet of the Jalovecký Creek catchment) remains constantly higher since 2014 that might be related to greater evaporation in the region of origin of the air masses bringing precipitation to the studied part of central Europe. Increased δ18O values are reflected also in the Jalovecký Creek catchment runoff. Seasonality of δ18O in the Jalovecký Creek became less pronounced since 2014. The most significant trends found in annual hydrological data series from the catchment in the study period 1989–2018 have the correlation coefficients 0.4 to 0.7. These trends are found in the number of flow reversals (change from increasing to decreasing discharge and vice versa), June low flow, number of simple runoff events in summer months (June to September) and the flashiness index. The attribution analysis suggests that drivers responsible for the changes in these data series include the number of periods with precipitation six and more days long, total precipitation amount in February to June, number of days with precipitation in June to September and total precipitation in May on days with daily totals 10 mm and more, respectively. The coefficients of determination show that linear regressions between the drivers and supposedly changed data series explain only about 31% to 36% of the variability. Most of the change points detected in the time series by the Wild Binary Segmentation method occur in the second and third decades of the study period. Both hydrometric and isotopic data indicate that hydrological cycle in the catchment after 2014 became different than before.
Vapor condensation, whether due to dew or fog, may add a stable and important source of water to deserts. This was also extensively assessed in the Negev, regarded as a dew desert. Dew deserts necessitate a large reservoir of vapor, and are therefore confined to near oceans or seas. Yet, examples of such deserts are scarce. Here we try to assess whether the Tabernas Desert in SE Spain can be regarded as a dew desert, and may therefore facilitate the growth of certain organisms that otherwise would not survive the dry season. We analyze some of the abiotic conditions of four relatively dry months (June, July, August, September) in the Tabernas and Negev deserts (with the Negev taken as an example of a dew desert) during 2003–2012. The analysis showed substantially lower values of relative humidity (by 10–13%) in the Tabernas in comparison to the Negev, with RH ≥95% being on average only 0.9–1.1 days a month in the Tabernas in comparison to 9.7–13.9 days in the Negev. Our findings imply that the Tabernas Desert cannot be regarded as a dew desert, suggesting that rain will be the main factor responsible for the food web chain in the Tabernas.
The objectives of the study were to: (1) assess the strength of associations of direct CO2 and N2O emissions with the seasonal variations in the relevant soil properties under both tillage systems; 2) evaluate how CT and RT affect magnitudes of seasonal CO2 and N2O fluxes from soil. Field studies were carried out on plots for conventional tillage (up to 0.22–0.25 m) and reduced tillage (up to 0.10–0.12 m) during the growing season and post-harvest period of red clover. The results showed that daily CO2 emissions significantly correlated only with soil temperature during the growing season under conventional and reduced tillage. Soil temperature demonstrated its highest influence on daily N2O emissions only at the beginning of the growing season in both tillage systems. There were no significant inter-system differences in daily CO2 and N2O emissions from soil during the entire period of observations. Over the duration of post-harvest period, water-filled pore space was a better predictor of daily CO2 emissions from soils under CT and RT. The conventional and reduced tillage did not cause significant differences in cumulative N2O and CO2 fluxes from soil.
In an open channel with a mobile bed, intense transport of bed load is associated with high-concentrated sediment-laden flow over a plane surface of the eroded bed due to high bed shear. Typically, the flow exhibits a layered internal structure in which virtually all sediment grains are transported through a collisional layer above the bed. Our investigation focuses on steady uniform turbulent open-channel flow with a developed collisional transport layer and combines modelling and experiment to relate integral quantities, as the discharge of solids, discharge of mixture, and flow depth with the longitudinal slope of the bed and the internal structure of the flow above the bed. A transport model is presented which considers flow with the internal structure described by linear vertical distributions of granular velocity and concentration across the collisional layer. The model employs constitutive relations based on the classical kinetic theory of granular flows selected by our previous experimental testing as appropriate for the flow and transport conditions under consideration. For given slope and depth of the flow, the model predicts the total discharge and the discharge of sediment. The model also predicts the layered structure of the flow, giving the thickness of the dense layer, collisional layer, and water layer. Model predictions are compared with results of intense bed-load experiment carried out for lightweight sediment in our laboratory tilting flume.
Sand-water slurry was investigated on an experimental pipe loop of inner diameter D = 100 mm with the horizontal, inclined, and vertical smooth pipe sections. A narrow particle size distribution silica sand of mean diameter 0.87 mm was used. The experimental investigation focused on the effects of pipe inclination, overall slurry concentration, and mean velocity on concentration distribution and deposition limit velocity. The measured concentration profiles showed different degrees of stratification for the positive and negative pipe inclinations. The degree of stratification depended on the pipe inclination and on overall slurry concentration and velocity. The ascending flow was less stratified than the corresponding descending flow, the difference increasing from horizontal flow up to an inclination angle of about +30°. The deposition limit velocity was sensitive to the pipe inclination, reaching higher values in the ascending than in the horizontal pipe. The maximum deposition limit value was reached for an inclination angle of about +25°, and the limit remained practically constant in value, about 1.25 times higher than that in the horizontal pipe. Conversely, in the descending pipe, the deposition limit decreased significantly with the negative slopes and tended to be zero for an inclination angle of about −30°, where no stationary bed was observed.
The event runoff coefficient (Rc) and the recession coefficient (tc) are of theoretical importance for understanding catchment response and of practical importance in hydrological design. We analyse 57 event periods in the period 2013 to 2015 in the 66 ha Austrian Hydrological Open Air Laboratory (HOAL), where the seven subcatchments are stratified by runoff generation types into wetlands, tile drainage and natural drainage. Three machine learning algorithms (Random forest (RF), Gradient Boost Decision Tree (GBDT) and Support vector machine (SVM)) are used to estimate Rc and tc from 22 event based explanatory variables representing precipitation, soil moisture, groundwater level and season. The model performance of the SVM algorithm in estimating Rc and tc is generally higher than that of the other two methods, measured by the coefficient of determination R2, and the performance for Rc is higher than that for tc. The relative importance of the explanatory variables for the predictions, assessed by a heatmap, suggests that Rc of the tile drainage systems is more strongly controlled by the weather conditions than by the catchment state, while the opposite is true for natural drainage systems. Overall, model performance strongly depends on the runoff generation type.