The design and construction of amelioration systems (irrigation, drainage) should precede diagnosis of soil water regime (SWR), to estimate its need and design parameters. It means, it is needed to calculate cyclic course of so called soil water regime characteristics. As soil water regime characteristic can be used soil moisture of the soil root zone at some depth, soil water potential at certain depth, soil water content of the root zone, as they are affected by evapotranspiration and its components. Seasonal courses of soil water regime characteristics differ, therefore it is necessary to estimate statistical parameters of SWR characteristics during relatively long period of minimum twenty seasons. This paper presents method of plant transpiration regime assessment, based on seasonal canopy transpiration series, calculated retrospectively by mathematical model HYDRUS-ET. Novelty of this approach is using of the empirical relationship between the seasonal transpiration totals and biomass production (yield). Cumulative frequency distribution curve of seasonal transpiration was chosen as a basic characteristic. This approach allows to estimate cumulative frequency curves of yields and cumulative frequency of potential yields. The difference is cumulative frequency of yields optimized by irrigation system. This allows to transform expected yields increase to investment and operational price and to compare expenditure to profit. This approach is illustrated on loess soil with maize canopy during 31 seasons. and Predtým, ako sa vyprojektuje a vybuduje hydromelioračná stavba, je nevyhnutné diagnostikovať vodný režim pôdy (VRP), to znamená určiť vlastnosti cyklických chodov charakteristík VRP. Ako charakteristiky režimu vody v pôde môžu byť využité: vlhkosť koreňovej oblasti pôdy, vlhkostný potenciál vo vybraných hĺbkach pôdy, obsah vody v koreňovej oblasti pôdy, ktoré sú ovplyvnené evapotranspiráciou a jej zložkami - transpiráciou a výparom. Sezónne chody vybraných charakteristík VRP sa v jednotlivých rokoch výrazne líšia, preto je potrebné určiť štatistické vlastnosti charakteristík VRP za dostatočne dlhé obdobie, najmenej dvadsiatich rokov. Údaje pre analýzu boli získané matematickým modelovaním pohybu vody v pôde pomocou matematického modelu HYDRUS-ET. Ako základná charakteristika bola vybraná transpirácia porastu. Vlastnosti režimu odberu vody porastom určuje čiara prekročenia úhrnov transpirácie konkrétneho porastu za jeho vegetačné obdobie. Prínosom tejto práce je metóda kvantitatívneho hodnotenia vplyvu sezónnych úhrnov transpirácie na úrodu, prostredníctvom všeobecne akceptovanej empirickej závislosti medzi produkciou biomasy a úhrnom transpirácie za vegetačné obdobie. Prostredníctvom tejto závislosti boli určené čiary prekročenia úrod, potenciálnych úrod a rozdielov medzi nimi, čo reprezentuje možnosti zvýšenia produkcie biomasy hydromelioračným opatrením. Takto sa dali transformovať možné zmeny sezónnych úhrnov transpirácie na ekonomickú rovinu a porovnať ekonomický prínos zmeny VRP s nákladmi na jej uskutočnenie. Metodický postup je ilustrovaný analýzou VRP porastu kukurice počas 31 vegetačných období.
Stony soils are composed of fractions (rock fragments and fine soil) with different hydrophysical characteristics. Although they are abundant in many catchments, their properties are still not well understood. This article presents basic characteristics (texture, stoniness, saturated hydraulic conductivity, and soil water retention) of stony soils from a mountain catchment located in the highest part of the Carpathian Mountains and summarizes results of water flow modeling through a hypothetical stony soil profile. Numerical simulations indicate the highest vertical outflow from the bottom of the profile in soils without rock fragments under ponding infiltration condition. Simulation of a more realistic case in a mountain catchment, i.e. infiltration of intensive rainfall, shows that when rainfall intensity is lower than the saturated hydraulic conductivity of the stony soil, the highest outflow is predicted in a soil with the highest stoniness and high initial water content of soil matrix. Relatively low available retention capacity in a stony soil profile and consequently higher unsaturated hydraulic conductivity leads to faster movement of the infiltration front during rainfall.
Knowledge of the distribution of plant roots in a soil profile (i.e. root density) is needed when simulating root water uptake from soil. Therefore, this study focused on evaluating barley and wheat root densities in a sand-vermiculite substrate. Barley and wheat were planted in a flat laboratory box under greenhouse conditions. The box was always divided into two parts, where a single plant row and rows cross section (respectively) was simulated. Roots were excavated at the end of the experiment and root densities were assessed using root zone image processing and by weighing. For this purpose, the entire area (width of 40 and height of 50 cm) of each scenario was divided into 80 segments (area of 5x5 cm). Root density in each segment was expressed as a root percentage of the entire root cluster. Vertical root distributions (i.e. root density with respect to depth) were also calculated as a sum of root densities in each 5 cm layer. Resulting vertical root densities, measured evaporation from the water table (used as the potential root water uptake), and the Feddes stress response function model were used for simulating substrate water regime and actual root water uptake for all scenarios using HYDRUS-1D. All scenarios were also simulated using HYDRUS-2D. One scenario (areal root density of barley sown in a single row, obtained using image analysis) is presented in this paper (because most scenarios showed root water uptakes similar to results of 1D scenarios). The application of two root detecting techniques resulted in noticeably different root density distributions. Differences were mainly attributed to the fact that fine roots of high density (located mostly at the deeper part of the box) had lower weights in comparison to the weight of few large roots (at the box top). Thus, at the deeper part, higher root density (with respect to the entire root zone) was obtained using the image analysis in comparison to that from the gravimetric analysis. Conversely, lower root density was obtained using the image analysis at the upper part in comparison to that from the gravimetric analysis. On the other hand, fine roots overlapped each other and therefore were not visible in the image, which resulted in lower root density values from image analysis. Root water uptakes simulated with HYDRUS-1D using diverse root densities obtained for each cereal declined differently from the potential root water uptake values depending on water scarcity at depths of higher root density. and Usually, an earlier downtrend associated with gradual root water uptake decreases and vice versa. Similar root water uptakes were simulated for the presented scenario using the HYDRUS1D and HYDRUS-2D models. The impact of the horizontal root density distribution on root water uptake was, in this case, less important than the impact of the vertical root distribution resulting from different techniques and sowing scenarios.
Vegetation and biocrust play crucial roles in dune stability and mobility, and their interaction can lead to bistability, temporal oscillations, and hysteresis. We studied a two-dimensional (2D) mathematical model of vegetation and biogenic crust cover dynamics on sand dunes. Under a certain parameter range, the space-independent version of the model exhibited the bi-stability of an oscillatory state and a steady state, and we studied the 2D dynamics of the model under these parameters. The patterns developed by the 2D model showed a high degree of spatial heterogeneity and complexity depending on the initial conditions and on the state type across the front. The results suggest that spatial heterogeneity and complexity can evolve from the intrinsic dynamics between vegetation and biocrust, even without natural geodiversity and spatiotemporal climate fluctuations. In the real world, these two types of intrinsic and extrinsic heterogeneity processes interact such that it is difficult to distinguish between them.