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Author |
Doro, L.; Jones, C.; Williams, J.R.; Norfleet, M.L.; Izaurralde, R.C.; Wang, X.; Jeong, J. |
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Title |
The Variable Saturation Hydraulic Conductivity Method for Improving Soil Water Content Simulation in EPIC and APEX Models |
Type |
Journal Article |
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Year  |
2017 |
Publication |
Vadose Zone Journal |
Abbreviated Journal |
Vadose Zone Journal |
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Volume |
16 |
Issue |
13 |
Pages |
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Keywords |
Conservation Effects Assessment; Runoff Simulation; Unsaturated Soils; United-States; Porous-Media; Moisture; Flow; Productivity; Transport; Denitrification |
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Abstract |
Soil water percolation is a key process in the life cycle of water in fields, watersheds, and river basins. The Environmental Policy Integrated Climate (EPIC) and the Agricultural Policy/Environmental eXtender (APEX) are continuous models developed for evaluating the environmental effects of agricultural management. Traditionally, these models have simulated soil water percolation processes using a tipping-bucket approach, with the rate of flow limited by the saturated hydraulic conductivity. This simple approach often leads to inaccuracy in simulating elevated soil water conditions where soil water content (SWC) levels may remain above field capacity under prolonged wet weather periods or limited drainage. To overcome this deficiency, a new sub-model, the variable saturation hydraulic conductivity (VSHC) method, was developed for simulating soil water percolation processes using a nonlinear equation to estimate the effective hydraulic conductivity as a function of the SWC and soil properties. The VSHC method was evaluated at three sites in the United States and two sites in Europe. In addition, a numerical solution of the Richards equation was used as a benchmark for SWC comparison. Results show that the VSHC method substantially improves the accuracy of the SWC simulation in long-term simulations, particularly during wet periods. At the watershed scale, results on the Riesel Y2 watershed indicate that the VSHC method enhances model performance in the high-flow regime of channel peak flows because of the improved estimation of SWC, which implies that the improved SWC simulation at the field scale is beneficial to hydrologic modeling at the watershed scale. |
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2018-09-07 |
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English |
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ISSN |
1539-1663 |
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CropM, ft_macsur |
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no |
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Call Number |
MA @ admin @ |
Serial |
5208 |
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Author |
Rusu, T.; Moraru, P.I. |
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Title |
Impact of climate change on crop land and technological recommendations for the main crops in Transylvanian Plain, Romania |
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Journal Article |
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Year |
2015 |
Publication |
Romanian Agricultural Research |
Abbreviated Journal |
Romanian Agricultural Research |
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Volume |
32 |
Issue |
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Pages |
103-111 |
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Keywords |
climate change monitoring; temperature regimes; soil moisture; adaptation technologies; transylvanian plain; agriculture; france; precipitation; circulation; adaptation; models |
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Abstract |
The Transylvanian Plain (TP) is an important agricultural production area of Romania that is included among the areas with the lowest potential of adapting to climate changes in Europe. Thermal and hydric regime monitoring is necessary to identify and implement measures of adaptation to the impacts of climate change. Soil moisture and temperature regimes were evaluated using a set of 20 data logging stations positioned throughout the plain. Each station stores electronic data regarding ground temperature at 3 depths (10, 30, 50 cm), humidity at a depth of 10 cm, air temperature (at 1 m) and precipitation. For agricultural crops, the periods of drought and extreme temperatures require specific measures of adaptation to climate changes. During the growing season of crops in the spring (April – October) in the south-eastern, southern, and eastern escarpments, precipitation decreased by 43.8 mm, the air temperature increased by 0.37 degrees C, and the ground temperature increased by 1.91 degrees C at a depth of 10 cm, 2.22 degrees C at a depth of 20 cm and 2.43 degrees C at a depth of 30 cm compared with values recorded for the northern, north-western or western escarpments. Water requirements were ensured within an optimal time frame for 58.8-62.1% of the spring row crop growth period, with irrigation being necessary to guarantee the optimum production potential. The biologically active temperature recorded in the TP demonstrates the need to renew the division of the crop areas reported in the literature. |
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1222-4227 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4650 |
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Kersebaum, K.C.; Boote, K.J.; Jorgenson, J.S.; Nendel, C.; Bindi, M.; Frühauf, C.; Gaiser, T.; Hoogenboom, G.; Kollas, C.; Olesen, J.E.; Rötter, R.P.; Ruget, F.; Thorburn, P.J.; Trnka, M.; Wegehenkel, M. |
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Title |
Analysis and classification of data sets for calibration and validation of agro-ecosystem models |
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Journal Article |
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Year |
2015 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
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Volume |
72 |
Issue |
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Pages |
402-417 |
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Keywords |
field experiments; data quality; crop modelling; data requirement; minimum data; software; different climatic zones; soil-moisture sensors; spatial variability; nitrogen dynamics; crop models; systems simulation; wheat yields; elevated co2; growth; field |
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Experimental field data are used at different levels of complexity to calibrate, validate and improve agroecosystem models to enhance their reliability for regional impact assessment. A methodological framework and software are presented to evaluate and classify data sets into four classes regarding their suitability for different modelling purposes. Weighting of inputs and variables for testing was set from the aspect of crop modelling. The software allows users to adjust weights according to their specific requirements. Background information is given for the variables with respect to their relevance for modelling and possible uncertainties. Examples are given for data sets of the different classes. The framework helps to assemble high quality data bases, to select data from data bases according to modellers requirements and gives guidelines to experimentalists for experimental design and decide on the most effective measurements to improve the usefulness of their data for modelling, statistical analysis and data assimilation. (C) 2015 Elsevier Ltd. All rights reserved. |
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English |
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1364-8152 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
4563 |
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Author |
Siebert, S.; Ewert, F.; Rezaei, E.E.; Kage, H.; Grass, R. |
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Title |
Impact of heat stress on crop yield-on the importance of considering canopy temperature |
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Journal Article |
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Year |
2014 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
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9 |
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4 |
Pages |
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Keywords |
heat stress; crop yield; temperature; soil moisture; modelling; wheat; rye; harvest index; wheat yields; climate-change; winter-wheat; grain number; extreme heat; maize; variability; irrigation; drought |
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Abstract |
Increasing crop productivity while simultaneously reducing the environmental footprint of crop production is considered a major challenge for the coming decades. Even short episodes of heat stress can reduce crop yield considerably causing low resource use efficiency. Studies on the impact of heat stress on crop yields over larger regions generally rely on temperatures measured by standard weather stations at 2 m height. Canopy temperatures measured in this study in field plots of rye were up to 7 degrees C higher than air temperature measured at typical weather station height with the differences in temperatures controlled by soil moisture contents. Relationships between heat stress and grain number derived from controlled environment studies were only confirmed under field conditions when canopy temperature was used to calculate stress thermal time. By using hourly mean temperatures measured by 78 weather stations located across Germany for the period 1994-2009 it is estimated, that mean yield declines in wheat due to heat stress during flowering were 0.7% when temperatures are measured at 2 m height, but yield declines increase to 22% for temperatures measured at the ground. These results suggest that canopy temperature should be simulated or estimated to reduce uncertainty in assessing heat stress impacts on crop yield. |
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2016-10-31 |
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English |
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ISSN |
1748-9326 |
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Notes |
CropM, ftnotmacsur |
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no |
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Call Number |
MA @ admin @ |
Serial |
4814 |
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Author |
Mansouri, M.; Dumont, B.; Leemans, V.; Destain, M.-F. |
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Title |
Bayesian methods for predicting LAI and soil water content |
Type |
Journal Article |
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Year |
2014 |
Publication |
Precision Agriculture |
Abbreviated Journal |
Precision Agric. |
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Volume |
15 |
Issue |
2 |
Pages |
184-201 |
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Keywords |
crop model; bayes; data assimilation; extended kalman filtering; particle filtering; variational filtering; leaf-area index; parameter-estimation; crop models; moisture; instruments; management; sensors; state |
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Abstract |
LAI of winter wheat (Triticum aestivum L.) and soil water content of the topsoil (200 mm) and of the subsoil (500 mm) were considered as state variables of a dynamic soil-crop system. This system was assumed to progress according to a Bayesian probabilistic state space model, in which real values of LAI and soil water content were daily introduced in order to correct the model trajectory and reach better future evolution. The chosen crop model was mini STICS which can reduce the computing and execution times while ensuring the robustness of data processing and estimation. To predict simultaneously state variables and model parameters in this non-linear environment, three techniques were used: extended Kalman filtering (EKF), particle filtering (PF), and variational filtering (VF). The significantly improved performance of the VF method when compared to EKF and PF is demonstrated. The variational filter has a low computational complexity and the convergence speed of states and parameters estimation can be adjusted independently. Detailed case studies demonstrated that the root mean square error of the three estimated states (LAI and soil water content of two soil layers) was smaller and that the convergence of all considered parameters was ensured when using VF. Assimilating measurements in a crop model allows accurate prediction of LAI and soil water content at a local scale. As these biophysical properties are key parameters in the crop-plant system characterization, the system has the potential to be used in precision farming to aid farmers and decision makers in developing strategies for site-specific management of inputs, such as fertilizers and water irrigation. |
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English |
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Abbreviated Series Title |
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Series Volume |
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Edition |
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ISSN |
1385-2256 |
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CropM, ftnotmacsur |
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Call Number |
MA @ admin @ |
Serial |
4629 |
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