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Effect of high temperatures and different water regimes on selected winter wheat varieties above-ground biomass production
Hlaváčová, M. ; Klem, Karel ; Hlavinka, Petr ; Trnka, Miroslav
The aim of this study was to assess the effect of high temperatures and soil water scarcity during anthesis on the above-ground biomass allocation of the two winter wheat varieties (Bohemia and Pannonia). The six growth chambers were used to simulate heat stress conditions within following gradient of temperature maxima: 26°C (control chamber), 29, 32, 35, 38 and 41°C. The relative humidity (RH) course and photosynthetically active radiation (PAR) intensity were controlled via protocols. Additionally, drought stressed (Dry) and well-watered (Wet) treatments were established within each growth chamber. The plants were removed from the growth chambers after 14 days and they were left until a full maturity, exposed to ambient weather conditions. The spike productivities of the main spikes and harvest indices (HI) of the main spikes were evaluated for particular treatments within both winter wheat varieties after harvest.
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Use of ESI index for drought monitoring and crop yield forecasting
Jurečka, František ; Anderson, M. ; Hlavinka, Petr ; Hain, C. ; Wayne, D. ; Gao, F. ; Johnson, D. M. ; Otkin, J. ; Žalud, Zdeněk ; Trnka, Miroslav
Remote sensing is already for many years used for various analysis providing limited factors for agriculture production. Drought monitoring, vegetation conditions in the fields and crop\n131 yield forecasting in context of climatic conditions of recent years seem to be crucial. Methods of remote sensing use various wavebands behaving differently under different surfaces and vegetation covers. Remote sensing use many indices for study of vegetation conditions and agriculture landscape and for forecasting yield. In this case, index ESI (Evaporative Stress Index) was used for drought monitoring and yield forecasting. Index ESI is used by ALEXI model (Atmosphere-Land Exchange Inverse model).\n
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Remote sensing as support tool for agricultural drought assessment
Hlavinka, Petr ; Semerádová, Daniela ; Balek, Jan ; Žalud, Z. ; Tadesse, T. ; Hayes, M. ; Wardlow, B. ; Trnka, Miroslav
Very important information about vegetation condition within wide areas (through continents and states) or for local areas in resolution from hundreds to tens of meters could be obtained from satellites within remote sensing. The temporal and spatial continuity is big advantage of this method. Namely so-called vegetation indices are often used for vegetation cover condition assessment. The aim of submitted study is to present possibility of using EVI2 (Enhanced Vegetation Index) for assessment of drought impact within vegetation. The results for selected years of the period 2000-2015 achieved using MODIS (Moderate Resolution Imaging Spectroradiometer) aboard Terra satellite are included. The data in weekly time step and for the whole Czech Republic are presented.
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The agricultural drought monitoring and its users and correspondents
Bartošová, Lenka ; Trnka, Miroslav ; Semerádová, Daniela ; Hlavinka, Petr ; Štěpánek, Petr ; Zahradníček, Pavel ; Žalud, Z.
Drought monitoring in the Czech Republic is a key element in climate monitoring. The aim of this article is to describe the possible participation of agronomists, foresters and fruiterers in drought monitoring within the Integrated Drought Monitoring System. This system monitor drought occurence weekly on the base of various information (data from model SoiClim or outputs from satellite Aqua and Terra). One of the main pillar of the monitor is also information about drought impact on yields in the cooperation with especially farmers. Their expert assessment brings insight into actual situation in agricultural landscape in weekly time step. All results are free to download in www.intersucho.cz.
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Drivers of soil moisture trends in the Czech Republic between 1961 and 2012
Trnka, Miroslav ; Brázdil, Rudolf ; Balek, J. ; Semerádová, Daniela ; Hlavinka, Petr ; Možný, M. ; Štěpánek, Petr ; Dobrovolný, Petr ; Zahradníček, Pavel ; Dubrovský, Martin ; Eitzinger, Josef ; Fuchs, B. ; Svoboda, M. ; Hayes, M. ; Žalud, Zdeněk
Soil moisture dynamics and their temporal trends in the Czech Republic are forced by various drivers. Our analysis of temporal trends indicates that shifts in drought severity between 1961 and 2012 and especially in the April, May, and June period, which displayed such results as a 50% increase in drought probability during 1961–1980 in comparison to 2001–2012. We found that increased global radiation and air temperature together with decreased relative humidity (all statistically significant at p < 0.05) led to increases in the reference evapotranspiration in all months of the growing season; this trend was particularly evident in April, May, and August, when more than 80% of the territory displayed an increased demand for soil water. These changes, in combination with the earlier end of snow cover and the earlier start of the growing season (up to 20 days in some regions), led to increased actual evapotranspiration at the start of the growing season that tended to deplete the soil moisture earlier, leaving the soil more exposed to the impacts of rainfall variability. These results support concerns related to the potentially increased severity of drought events in Central Europe. The reported trend patterns are of particular importance with respect to expected climate change, given the robustness and consistency of the trends shown and the fact that they can be aligned with the existing climate model projections. Introduction
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Reliability of regional crop yield predictions in the Czech Republic based on remotely sensed data
Hlavinka, Petr ; Semerádová, Daniela ; Balek, Jan ; Bohovič, Roman ; Žalud, Zdeněk ; Trnka, Miroslav
Vegetation indices sensed by satellite optical sensors are valuable tools for assessing vegetation conditions including field crops. The aim of this study was to assess the reliability of regional yield predictions based on the use of the Normalized Difference Vegetation Index and the Enhanced Vegetation Index derived from the Moderate Resolution Imaging Spectroradiometer aboard the Terra satellite. Data available from the year 2000 were analysed and tested for seasonal yield predictions within selected districts of the Czech Republic. In particular, yields of spring barley, winter wheat, and oilseed winter rape during 2000–2014 were assessed. Observed yields from 14 districts were collected and thus 210 examples (15 years within 14 districts) were included. Selected districts differ considerably in soil fertility and terrain configuration and represent a transect across various agroclimatic conditions (from warm/dry to relatively cool/wet regions). Two approaches were tested: 1) using 16-day temporal composites of remotely sensed data provided by the United States Geological Survey, and 2) using daily remotely sensed data in combination with an originally developed smoothing method. Yields were predicted based on established regression models using remotely sensed data as an independent parameter. In addition to other findings, the impact of severe drought episodes within vegetation was identified and yield reductions at a district level were predicted. As a result, those periods with the best relationship between remotely sensed data and yields were identified. The impact of drought conditions as well as normal or above-normal yields of the tested field crops were predicted using the proposed method within the study region up to 30 days prior to harvest.
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The influence of reduced precipitation supply on spring barley yields and the ability of crop growth models to simulate drought stress
Pohanková, Eva ; Orság, Matěj ; Hlavinka, Petr
This paper evaluates the first year (2014) of results from a field experiment with spring barley (cultivar Bojos) under reduced precipitation supply. The field experiment was carried out at an experimental station in the Czech Republic and consisted of small plots in two variants and three repetitions. The first variant was uncovered, and the second was partly covered to exclude rain throughout the entire vegetation season. For plots’ partial covering, a material was used to divert rainwater away from 70% of the plots. The main aim was to determine whether there are any differences in soil water content or in grain yield size between uncovered and partly covered plots and to compare the results obtained. Data measured in this field experiment were used to compare simulations of this field experiment in the DAISY crop growth model. Subsequently, the crop growth model’s ability to simulate grain yield, which was affected by drought stress, was explored. In reality, differences in phenological development and grain yield size were not evident. Reducing precipitation supply in DAISY by about 70% led to simulations of covered plots with reduced grain yield in accordance with the initial hypothesis. Agreement between observed and simulated grain yield was evaluated using selected statistical indicators: root mean square error (RMSE) as a parameter of average magnitude of error and mean bias error (MBE) as an indicator of systematic error. RMSE of grain yield was 2.6 t ha−1. MBE revealed grain yield undervalued by 2.6 t ha−1.
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LINCOLN – an algorithm for filtering daily NDVI MODIS data and deriving the start of the season
Bohovič, R. ; Hlavinka, Petr ; Semerádová, Daniela ; Bálek, L. ; Tadesse, T. ; Hayes, M. ; Wardlow, B. ; Trnka, Miroslav
Monitoring drought has become an important tool for farmers and agriculture decision makers. This has increased efforts to create a monitoring system using satellite data that could provide an independent and current source of real information on vegetation condition. The aim of this study was to develop an algorithm for processing Normalized Difference Vegetation Index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer. A software utility called LINCOLN was developed for this purpose. Its filtering output was further processed to yield a start of the season (SOS) metric. Different settings of the utility were tested and correlated to such phenological ground observations as the emergence of spring barley and the beginning of leaf sheath elongation in winter wheat. There was higher correlation observed in the case of winter wheat, probably due to its weaker dependence on crop sowing date. The matrix of coefficients of determination was applied to determine the optimal settings for the LINCOLN filter. The optimal absolute threshold NDVI value for SOS was set to 4,500.
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Application of growth models for local assessment of the impact of climate change on selected crops
Hlavinka, Petr ; Trnka, Miroslav ; Balek, Jan ; Dubrovský, Martin ; Pohanková, Eva ; Žalud, Zdeněk
This publication is focused on the description of specialized software named as crop growth models and its using emphasizing the application for climate change impact assessment at local scale. The ambition of this publication is to introduce brief history of the crop growth models development, its classification, actual trends of their progress and applications and last but not least, present procedure leading to the preparation of the input datasets, the initial setup, parameters calibration, validation through set of independent datasets and consequently the implementation of climate change scenarios for assessment of possible impact of future conditions on selected important field crops and set of representative sites in the Czech Republic.
Fulltext: content.csg -  PDF
Plný tet: Metodika_rustove_modely_2015 - PDF
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Remotely sensed NDVI as a support tool for agricultural drouhgt assessment
Hlavinka, Petr ; Semerádová, Daniela ; Trnka, Miroslav ; Lukas, V. ; Bohovic, R. ; Balek, J. ; Wardlow, B. ; Hayes, M. ; Tseagaye, T. ; Žalud, Zdeněk
Th e main aim of the submitted study was to introduce how the remotely sensed NDVI (Normalized Diff erence Vegetation Index) could be used for agricultural drought assessment within the Czech Republic. Th e relationship between NDVI values and observed yields of spring barley and winter wheat was analyzed for selected districts. Moreover the ability of NDVI (at district level in the form of seasonal greenness – SG) to explain the water balance or drought occurrence and severity was tested. For this purpose a data mining technique was used. A relative form of the Palmer Drought Severity Index (rPDSI) was used as a dependent variable to indicate drought occurrence. A Standardized Precipitation Index (SPI), percentage of average SG (PASG), Start of Season Anomaly (SOSA) and district identifi cation were used as independent variables. MODIS (Moderate Resolution Imaging Spectroradiometer) observations from the Terra satellite were used as a source of NDVI. Th e situation within 6 selected districts (Olomouc, Přerov, Znojmo, Břeclav, Žďár nad Sázavou and Havlíčkův Brod) during the period from 2000 to 2012 was analyzed. Promising results were achieved, so practical use of this approach (e.g. for spatial and temporal assessment of drought stress within the vegetation) could be expected.
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