Modeling of transpiration reduction in van Genuchten-Mualem type soils

We derive an analytic expression for the matric flux potential (M) for van Genuchten-Mualem (VGM) type soils which can also be written in terms of a converging infinite series. Considering the first four terms of this series, the accuracy of the approximation was verified by comparing it to values of M estimated by numerical finite difference integration. Using values of the parameters for three soils from different texture classes, the proposed four-term approximation showed an almost perfect match with the numerical solution, except for effective saturations higher than 0.9. Including more terms reduced the discrepancy but also increased the complexity of the equation. The four-term equation can be used for most applications. Cases with special interest in nearly saturated soils should include more terms from the infinite series. A transpiration reduction function for use with the VGM equations is derived by combining the derived expression for M with a root water extraction model. The shape of the resulting reduction function and its dependency on the derivative of the soil hydraulic diffusivity D with respect to the soil water content theta is discussed. Positive and negative values of dD/d theta yield concave and convex or S-shaped reduction functions, respectively. On the basis of three data sets, the hydraulic properties of virtually all soils yield concave reduction curves. Such curves based solely on soil hydraulic properties do not account for the complex interactions between shoot growth, root growth, and water availabilit

General procedure to initialize the cyclic soil water balance by the Thornthwaite and Mather method

The original Thornthwaite and Mather method, proposed in 1955 to calculate a climatic monthly cyclic soil water balance, is frequently used as an iterative procedure due to its low input requirements and coherent estimates of water balance components. Using long term data sets to establish a characteristic water balance of a location, the initial soil water storage is generally assumed to be at field capacity at the end of the last month of the wet season, unless the climate is (semi-) arid when the soil water storage is lower than the soil water holding capacity. To close the water balance, several iterations might be necessary, which can be troublesome in many situations. For (semi-) arid climates with one dry season, Mendon a derived in 1958 an equation to quantify the soil water storage monthly at the end of the last month of the wet season, which avoids iteration procedures and closes the balance in one calculation. The cyclic daily water balance application is needed to obtain more accurate water balance output estimates. In this note, an equation to express the water storage for the case of the occurrence of more than one dry season per year is presented as a generalization of Mendon a's equation, also avoiding iteration procedures

Evaporation Through a Dry Soil Layer: Column Experiments

Modeling of water vapor transport through a dry soil layer (DSL), typically formed in the top soil during dry seasons in arid and semi-arid areas, is still problematic. Previous laboratory experiments in controlled environments showed that the only vapor transport process through the DSL is by Fick's law of diffusion. However, field experiments exhibited consistently higher evaporation rates than predicted by diffusion flow only. Some proposed reasons for the mismatch were: (a) daily cycles of condensation and evaporation in the DSL due to changes in solar radiation; (b) wind effects on air movement in the DSL; (c) atmospheric pressure fluctuations; (d) nonlinear influence of the DSL thickness on the evaporation process. To link the laboratory experiments with field observations, we performed soil column experiments in the laboratory with thick (>50 cm) DSL, and with different wind speeds, two radiative lamp schedules (continuous and 12 h daily cycles) and different thicknesses of DSL. Atmospheric pressure, air temperature and humidity were measured continuously. The results show that the evaporation rates observed are larger than those predicted by diffusion flow only. We found that it was possible to model the evaporation rates as a function of atmospheric pressure fluctuations. In conclusion, atmospheric pressure fluctuations can induce evaporation rates in DSL larger than estimated by diffusion flow only, possibly explaining the discrepancy between laboratory and field evaporation rates

Auditing predictive models : a case study in crop growth

Methods were developed to assess and quantify the predictive quality of simulation models, with the intent to contribute to evaluation of model studies by non-scientists. In a case study, two models of different complexity, LINTUL and SUCROS87, were used to predict yield of forage maize under Dutch meteorological conditions. The models predict yield under potential conditions, i.e. temperature- and radiation limited yield, assuming other production factors to be optimal.After a review of concerns voiced in model-based applied research, the simulation models were described in a systematic manner to simplify access to the software code. A model analysis showed that the models contain switches, describing abrupt changes occurring in the crop (e.g. change of temperature driven leaf area growth to photosynthesis driven leaf growth; onset of leaf senescence). Some switches introduced discontinuities in the relation between state variables and parameters. Such properties make non-standard approaches for parameter estimation necessary.Subsequently, the empirical basis of the simulation model was reviewed in terms of parameter values and their uncertainty, as derived from literature. The results were used to evaluate the predictive quality given the parameter uncertainty. Predictive quality given the parameter uncertainty was low; parameter estimation to adapt the model to local conditions was necessary.Different procedures to calibrate the models were discussed and presented. For the combination of models and the data available in this case study, parameters had to be selected. Selection was based on the ranking of the parameters on the basis of their contribution to output uncertainty. Non-selected parameters were fixed at their default value. Calibration using a controlled random search algorithm for a point estimation procedure was executed for both models. In the estimation procedure a compromise was sought between different types of problems: estimation bias, parameter identifiability and local minima.The parameter estimates were used to generate predictions. A comparison between predictions and measured data was used to evaluate the predictive quality of the models in terms that are relevant for the application. To do so, the concept of a link hypothesis was introduced. It defines the anticipated relation between prediction and measurement. Deviations from the anticipated relation were used to quantify predictive quality. Predictive quality was shown to depend strongly on the procedure used to generate predictions, i.e. procedures combining results based on multiple calibration sets yielded better predictions than predictions based on a single data set.To translate predictive quality in terms of usefulness of the simulation model prediction errors were compared to those of benchmark predictors (simple statistical predictors). LINTUL and SUCROS87 differed in their performance in relation to the benchmark predictors.Procedures developed in this thesis suggested that facilitating model evaluation requires actions that are not easily executed within the context of project-based, often time-limited, applied research. Investment in the methodological basis and in the empirical basis of the models prior to their application will be required.</p

Comparison of five soil organic matter decomposition models using data from a 14C and 15N labeling field experiment

Five alternatives of the previously published MOMOS model (MOMOS-2 to -6) are tested to predict the dynamics of carbon (C) and nitrogen (N) in soil during the decomposition of plant necromass. 14C and 15N labeled wheat straw was incubated over 2 years in fallow soils of the high Andean Paramo of Venezuela. The following data were collected: soil moisture, total 14C and 15N and microbial biomass (MB)-14C and -15N, daily rainfall, air temperature and total radiation. Daily soil moisture was predicted using the SAHEL model. MOMOS-2 to -4 (type 1 models) use kinetic constants and flow partitioning parameters. MOMOS-2 can be simplified to MOMOS-3 and further to MOMOS-4, with no significant changes in the prediction accuracy and robustness for total-14C and -15N as well as for MB-14C and -15N. MOMOS-5 (type 2 models) uses only kinetic constants: three MB-inputs (from labile and stable plant material and from humified compounds) and two MB-outputs (mortality and respiration constants). MOMOS-5 did not significantly change the total-14C and -15N predictions but markedly improved the predictive quality and robustness of MB-14C and -15N predictions (with a dynamic different from the predictions by other models). Thus MOMOS-5 is proposed as an accurate and ecologically consistent description of decomposition processes. MOMOS-6 extends MOMOS-5 by including a stable humus compartment for long-term simulations of soil native C and N. The improvement of the predictions is not significant for this 2-year experiment, but MOMOS-6 enables prediction of a sequestration in the stable humus compartment of 2% of the initially added 14C and 5.4% of the added 15

Антибіотикопрофілактика в хірургії

Наук. кер.: М.Г. КононенкоГнійно-запальні післяопераційні ускладнення за останні десятиріччя набувають все більшої актуальності. Це вже стає проблемою. Такі ускладнення необхідно попереджувати. Для забезпечення тканин операційного поля антибіотиком у ефективній (бактерицидній) концентрації на весь період хірургічного втручання проводять антибіотикопрофілактику (АБП). Вона є складовою частиною комплексної профілактики гнійно-запальних ускладнень. При цитуванні документа, використовуйте посилання http://essuir.sumdu.edu.ua/handle/123456789/2734

Importance of root depth distribution for modeling of the interactions between water, soil, vegetation and atmosphere

Large scale modeling as in GCM, commonly disregards much complexity to avoid high numerical demands. The simplifications affect model outcome and for a number of these, we assess the errors that may be involve