IDŐJÁRÁS Quarterly Journal of the Hungarian Meteorological Service Vol. 118, No. 1, January March, 2014, pp - PDF

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IDŐJÁRÁS Quarterly Journal of the Hungarian Meteorological Service Vol. 118, No. 1, January March, 2014, pp Facts about the use of agrometeorological information in Hungary and suggestions for making

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IDŐJÁRÁS Quarterly Journal of the Hungarian Meteorological Service Vol. 118, No. 1, January March, 2014, pp Facts about the use of agrometeorological information in Hungary and suggestions for making that more efficient Zoltán Varga Department of Agrometeorology, Faculty of Agricultural and Food Sciences, University of West Hungary, Vár 2, H-9200 Mosonmagyaróvár, Hungary (Manuscript received in final form February 15, 2013) Abstract Demands on use of information upon relationship between meteorological conditions and agricultural production were from the beginning of meteorology and from the beginning of human civilization. The sudden development of natural sciences during the 19th and 20th centuries opened up a new prospect in producing meteorological information which was of use to food processing. On the other hand, contemporary agricultural development needed supply of more detailed and more practical agrometeorological information. Increasing importance of ecological agriculture at the expense of intensive farming systems and uncertain effects of climate change did not reduce the want for agrometeorological information; in fact, they extended the needs for those in the last decades. But positive tendencies of domestic agrometeorological research and information service in the second half of the 20th century declined till the 1990s, and there is no reason to be optimistic on the grounds of current situation. This work attempts to review not only possibilities and results of agrometeorological information supply, but also interdisciplinary factors, such as factors of economical development and regulation, education, agricultural-advisory system, etc., which set back the development of this area. The base of our investigations is a SWOT analysis which is a strategic planning method of economical sciences used to evaluate strengths, weaknesses, opportunities, and threats involved in a project. This way we try to answer the following questions: - Why is agrometeorology no longer an important economical factor in Hungary? - How could we make agrometeorological research and information service become a productive economical factor again? Key-words: agrometeorological information, agrometeorological research, SWOT analysis, climate change, decision-making 79 1. Introduction The agrometeorological use of information started after the cold event called as Younger Dryas. The climate shock a drastic warming - following that event caused a significant rise in sea level, and it changed the coastlines and topography of continents. But after that neither the sea level (topography), nor the climatic conditions changed enormously, so it helped the mankind to develop from hunter-gatherer to agricultural societies in the early Holocene (Behringer, 2010). According to Bernal (1963), it is important to make a distinction between prescientific stage of cognition and stages of history of science. Those early attempts to come to know and to influence the environmental (meteorological) effects on agricultural production belonged to the previous one of course. The ancient ploughmen awaked to their dependence on their environment and especially on weather and climate. Namely, they discovered that more sunshine and higher temperature accelerated development of plants and more rainfall caused higher yields. Results of observations about relationship between meteorological conditions and development, growth, and yields of crops came down from father to son, but this kind of knowledge could not have been quantified. People tried to influence natural forces, but it happened in a superstitious and mystificated way as they were not able to discover causal relationships. Anyhow, these efforts were the first although not scientific attempts to use agrometeorological information (Varga, 2010). A new approach, which supposed that the world around us could have been discovered and which focused on understanding the causal relationships between phenomena of that world, rose in the first millennia BC and it helped scientific thinking to improve. It was a beneficial method also for meteorological and applied (agro)meteorological studies. Several findings and ideas including some erroneous ones of that era were undisputed and unsurpassable knowledge of the given area of science for the following two thousand years. The only way for gathering information was the theoretical (speculative) one, as instrumental measurements still were not possible. It obstructed to define numerically the processes and attributes of atmosphere and relationships of climate-agriculture-soil system, respectively. Consequently, use of agrometeorological information was not able to develop for further centuries. The sudden development of natural sciences during the 19th and 20th centuries opened up a new prospect in producing meteorological information which was of use to food processing. On the other hand, contemporary agricultural development needed supply of more detailed and more practical agrometeorological information. The science of agrometeorology developed parallel with agriculture, and it worked as a prerequisite of agricultural production in those decades. That period can be considered as the days of glory for using agrometeorological information. The well-organized agrometeorological 80 information supply system met the demand of intensive crop production better and better. To make the first move for this a network of phenological stations for observing the development of field crops was organized under the direction of Zoltan Varga-Haszonits by the Hungarian Meteorological Institute (now: Hungarian Meteorological Service). To help this work, a monograph (manual) was published (Varga-Haszonits, 1967), then observers working in collective farm systems were drawn into the phenological network. That study used also the database collected by the National Institute for Agricultural Quality Control (now: Central Agricultural Office). The most comprehensive Hungarian phenological database especially for the period can be built up by unification of those two databases organized by the National Institute for Agricultural Quality Control and Hungarian Meteorological Service, respectively. The phenological data for field crops collected by the observational network of Hungarian Meteorological Service were stored at and used by the Department of Agricultural Information Supply and later by the Department of Agrometeorological Forecasting. The agrometeorological information service using those data worked under the direction of Zoltan Varga-Haszonits, after that it was organized by Sándor Dunay. Agroclimatological model-based crop yield forecasts were done for decades on behalf of the agricultural ministry. Increasing importance of ecological agriculture at the expense of intensive farming systems and uncertain effects of climate change did not reduce the want for agrometeorological information; in fact, they extended the needs for those in the last decades. But positive tendencies of domestic agrometeorological research and information supply in the second half of the 20th century declined till the 1990s and there is no reason to be optimistic on the grounds of current situation. This way we try to answer the following questions: Why and what kind of - agrometeorological information is important for agricultural production? Why is agrometeorology no longer an important economical factor in Hungary? How could we make agrometeorological research and information service become a productive economical factor again? 2. The SWOT analysis of agrometeorological information service Position, possibilities, and problems of agrometeorological information service were surveyed by the help of SWOT (sometimes SLOT) analysis. This method is a strategic planning used to evaluate strengths, weaknesses (or limitations), opportunities, and threats involved in a project. The internal and external factors which are favorable or unfavorable to achieve the objective can be determined (Székely, 2000). Identification of SWOTs is important, because they can inform 81 later steps in planning to achieve the objective. The usefulness of this method is not limited to profit-seeking organizations. SWOT analysis may be used in any decision-making situation when a desired objective has been defined (URL 1 ). The objective of our examined area is to help agricultural decisions and to raise food production a higher level. So it seemed to be reasonable to estimate the internal advantageous and disadvantageous characteristics of agrometeorological research and information supply, as well as the external opportunities and threats of those by means of this generally accepted method. Table 1 summarizes the SWOTs of agrometeorological information service. Table 1. The SWOTs of agrometeorological information service Internal origin External origin Helpful (+) Harmful (-) Strengths: the agricultural production`s need for agrometeorological information domestic agrometeorological research includes all important approaches of that science information supply can be based on results of former agrometeorological research interdisciplinary nature of agrometeorology Opportunities: growing need for interdisciplinary research more attention should be payed to investigation of agricultural impacts of global warming former favorable experiences suggest that agrometeorological information supply can work in Hungary the potential to handle data and information by computers and exchange them globally is growing high-level food production and food security need adequate information supply Weaknesses/Limitations: stochastic relationships of soil-atmosphereagriculture system over-emphasizing the importance of individual factors sometimes meteorological effects are treated as background noise by farmers inexact data and information supply the biological respects are usually in the rough in climate scenarios Threats: current academic structures do not foster interactions between biological and physical scientists problems of educational and agriculturaladvisory systems financial problems legal and economical regulation of agricultural production does not always inspire use of agrometeorological information problems of observational networks tendency for senescence of agrometeorological experts 2.1. Strengths It can be stated that a permanently high level agriculture which always tries to make the best of its environmental potential can not be realized without using agrometeorological information. The must for agricultural information supply is 82 explained by multiple influences of atmosphere on agricultural production. In support of this, let us have a short review of relationship between meteorological factors and crop production. The atmosphere can be considered as a system of terms and conditions for plant production. The climate fundamentally determines: which plants can not be grown in a given area (see the failed attempts for growing orange or cotton in Hungary in the 1950s), which species and varieties can be planted there, and in which period of the year are those plants able to grow (it could be basically decided if we compared the length of actual growing season of crops to beginning and end of potentially available growing season (in weather and climate respect)). The atmosphere means also system of resources for agriculture. Plants are not able to produce organic matter without climatic resources (energy and substances) which come from or through the surrounding atmosphere. Amounts of factors which are required for both photosynthesis and respiration, such as water (precipitation), carbon dioxide, oxygene, carbohydrates, temperature, and photosyntheticallay active radiation, are significantly influenced by weather and climate. The atmospheric factors work as a system of affecting factors for plants. Crops are constantly influenced by (meteorological) factors of their environment during the whole growing season. Intensity of life processes continually changes as a result of favorable or unfavorable, development accelerating or delaying, yield increasing or yield decreasing effects. More unfavorable values of meteorological elements cause more serious anomalies of life processes. Influences of meteorological elements below the lower or above the upper threshold values can be considered as damaging effects. The frequency of those marks production risk of varieties and hybrids. That is why the atmospheric relations are risk factors for farming as well (Varga-Haszonits and Varga, 1999). There is a continuous must for decision-making in agricultural practice. The quality of decision-making determines the level of farming. Decisions can be divided into two groups on the base of term of their implication. Strategic decisions are fundamental, directional, and over-arching. They affect long term goals. Tactical (or operational) decisions affect the day-today implementation of strategic decisions and are for short term. Strategy defines the what is to be done and tactics define the how. Decision-making always needs information, but information requirements depend on kind of decision. Both tactical and strategic decisions of farming demand agrometeorological information. Tactical decisions need information about weather and short term forecast, however, strategic planning needs climatic information and long term forecast. 83 Farming success basically depends on the base of decision-making. Effectiveness of planning is influenced by thoroughness of the decision-maker. In this respect, decisions can be divided into the following groups: intuitionbased decisions, past experience-based decisions, and decision based on professionally collected and processed data and scientific information. Intuition means instinctive and unconscious knowing without deduction or reasoning. This first group also includes decisions based on information of doubtful origin. Effectiveness of these decisions is low, but it is not zero. So we can make even good intuition-based decisions, but in this case we can not know why it works. All farming decisions without agrometeorological information belong to this group. For the most part of past experience-based decisions, recent experiences are used. It is because of the fact that memory of bygone days fades from our minds. However there is no guarantee for similar meteorological conditions or effects of consecutive years. Sometimes climatic features of distant time periods are analogous. That is why this kind of decision is also a hazardous one. A further problem is that individual experiences are not able to give enough information for a complex approach of agrometeorological problems. That complex approach is assured only by decisions based on professionally collected and processed data and scientific information. Scientific information supply developed from individual experiences by making those more objective, integrated, and verifiable (Varga, 2010). In the case of those decisions we also know probability of effectiveness for different alternatives. Effectiveness of these decisions is in general high, but it is not 100 %. So we can make even inexact scientific information-based decisions, but in this case we can search the source of the problem and it helps to make better decisions in the future. For this reason, good agrometeorological decisions require exact data and information supply. The appropriate data come from professional agrometeorological observation networks or from laboratory or field experiments. The other two principal elements of agrometeorological information service are theoretical and methodical research and information service itself. These three elements have to be in close connection with each other, and all of them must depend largely on the agricultural requirements (Varga-Haszonits, 1983, 1997). Some typical characteristics of a functional agrometeorological information service are described in the following. The basic element of the system is data collection. The efforts in various countries led to the recognition of a need for combining and coordinating phenological and meteorological observations. Data of professional network of meteorological observations combined with data from additional measurements of soil properties (temperature, moisture etc.) and with data from phenological and other agricultural observations provide an integrated database for research of atmosphere-soil-plant system. Agrometeorological information service can use all available observed or measeured data of controlled origin. 84 The data must be elaborated and analyzed. The detected false data have to be corrected or excluded from the database. Data analysis is a process of cleaning and transforming data. Afterwards, the analyzed data should be transformed into agricultural research or directly into agricultural information service. The goal of this process is highlighting useful agrometeorological information, suggesting conclusions, and supporting decision-making. It is important to send not data, but helpful information for users. This is the task and strength of agrometeorological service. The objective of agrometeorological research is to study and numerically determine the influence of meteorological elements on plant development and yield of crops. The investigations in this field consist of the following research areas: agroclimatological studies, agromicrometeorological model research, elaboration of new agrometeorological forecasting methods, and verification of new results. The investigations include analysis of databases, field experiments, and laboratory experiments (Varga-Haszonits, 1983). The data measured in these experiments are much more detailed than that of observational network, because those are measured by special instruments. Therefore, on the basis of these data, the atmosphere-(soil)-crop basic relationships can be elaborated and can be used as fundamental knowledge for agroclimatological modeling. The obtained relationships between meteorological factors and life processes of crops are fundamental knowledge for agrometeorological information service. The results have to be expressed in objective, mathematically exact terms which do not depend on the person giving information. We can change mainly characteristics of plants and agricultural production technologies as input parameters - in the case of field experiments, however, also modified weather conditions can be studied in laboratory experiments (in plastic tunnels or houses, greenhouses, climate chambers, or phytotrones). Therefore, field experiments allow examining the current agricultural production and laboratory experiments are suitable for also simulating and giving information about the future conditions of plant production. The analysis of agroclimatological databases is based on long-term data series. These studies include investigations of climatic conditions of crop production and relationship between climate and agricultural production, as well as determination of regions or zones with different agroclimatologic characteristics and conditons. These surveys can use much longer but less detailed dataseries than that of agroclimatological experiments. In the case of building an agroclimatological database, it is very important to check the reliability of data sets of different origin. Methodological investigations including models for forecasting soil moisture, actual evapotranspiration, plant development, crop yield, etc. - allow detailed analysis of climate-agriculture relationship and help decision-making on the base of verified information. 85 The verification of methods means that we compare the values obtained by elaborated methods with the actual measured or observed values. The accuracy of results is measured by error of estimation that is the difference between calculated and measured value and then by s
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