Assessing climate change effects on European crop yields using the Crop Growth Monitoring System and a weather generator

2012 ◽  
Vol 164 ◽  
pp. 96-111 ◽  
Author(s):  
I. Supit ◽  
C.A. van Diepen ◽  
A.J.W. de Wit ◽  
J. Wolf ◽  
P. Kabat ◽  
...  
2014 ◽  
Vol 35 (11) ◽  
pp. 3320-3334 ◽  
Author(s):  
D. T. Mihailović ◽  
B. Lalić ◽  
N. Drešković ◽  
G. Mimić ◽  
V. Djurdjević ◽  
...  

2021 ◽  
Author(s):  
Sabina Thaler ◽  
Josef Eitzinger ◽  
Gerhard Kubu

<p>Weather-related risks can affect crop growth and yield potentials directly (e.g. heat, frost, drought) and indirectly (e.g. through biotic factors such as pests). Due to climate change, severe shifts of cropping risks may occur, where farmers need to adapt effectively and in time to increase the resilience of existing cropping systems. For example, since the early 21st century, Europe has experienced a series of exceptionally dry and warmer than usual weather conditions (2003, 2012, 2013, 2015, 2018) which led to severe droughts with devastating impacts in agriculture on crop yields and pasture productivity.</p><p>Austria has experienced above-average warming in the period since 1880. While the global average surface temperature has increased by almost 1°C, the warming in Austria during this period was nearly 2°C. Higher temperatures, changing precipitation patterns and more severe and frequent extreme weather events will significantly affect weather-sensitive sectors, especially agriculture. Therefore, the development of sound adaptation and mitigation strategies towards a "climate-intelligent agriculture" is crucial to improve the resilience of agricultural systems to climate change and increased climate variability. Within the project AGROFORECAST a set of weather-related risk indicators and tailored recommendations for optimizing crop management options are developed and tested for various forecast or prediction lead times (short term management: 10 days - 6 months; long term strategic planning: climate scenarios) to better inform farmers of upcoming weather and climate challenges.</p><p>Here we present trends of various types of long-term weather-related impacts on Austrian crop production under past (1980-2020) and future periods (2035-2065). For that purpose, agro-climatic risk indicators and crop production indicators are determined in selected case study regions with the help of models. We use for the past period Austrian gridded weather data set (INCA) as well as different regionalized climate scenarios of the Austrian Climate Change Projections ÖKS15. The calculation of the agro-climatic indicators is carried out by the existing AGRICLIM model and the GIS-based ARIS software, which was developed for estimating the impact of adverse weather conditions on crops. The crop growth model AQUACROP is used for analysing soil-crop water balance parameters, crop yields and future crop water demand.</p><p>Depending on the climatic region, a more or less clear shift in the various agro-climatic indices can be expected towards 2050, e.g. the number of "heat-stress-days" for winter wheat increases significantly in eastern Austria. Furthermore, a decreasing trend in maize yield is simulated, whereas a mean increase in yield of spring barley and winter wheat can be expected under selected scenarios. Other agro-climatic risk indicators analysed include pest algorithms, risks from frost occurrence, overwintering conditions, climatic crop growing conditions, field workability and others, which can add additional impacts on crop yield variability, not considered by crop models.</p>


Sensors ◽  
2017 ◽  
Vol 17 (3) ◽  
pp. 502 ◽  
Author(s):  
Jun Ni ◽  
Lili Yao ◽  
Jingchao Zhang ◽  
Weixing Cao ◽  
Yan Zhu ◽  
...  

Author(s):  
Josephat Okuku Oloo ◽  
Paul Omondi

Purpose In Africa, poverty and food insecurity is pervasive due to intertwined factors including, declining crop yields, land degradation and inadequate policy and institutional support. With ever-increasing populations, climate change effects will be intensified, and a major crisis is inevitable unless measures to sustain land resources are urgently taken. This paper aims to argue that vibrant rural institutions are necessary to ensure food security and environmental protection, consequently contributing to climate change resilience. Design/methodology/approach The paper demonstrates the role of institutions by evaluating two types of institutions and their impacts the “status quo” and “hybrid” institutions using case studies from the African Highlands Initiative in Uganda and International Forestry Resources and Institutions in Kenya. It further discusses a model that highlights factors affecting smallholder investment in natural resources management and how these can be used to strengthen local institutions in building their resilience against climate change effects. Findings Weak grassroots institutions characterized by low capacity, failure to exploit collective capital and poor knowledge sharing and access to information, are common barriers to sustainable land management and improved food security. Research limitations/implications Case studies from Uganda and IFRI in Kenya barriers in data collection instruments and language. Practical implications In Africa, poverty and food insecurity is pervasive due to intertwined factors including, declining crop yields, land degradation and inadequate policy and institutional support. With ever increasing populations, climate change effects will be intensified, and a major crisis is inevitable unless measures to sustain land resources are urgently taken. Social implications In Africa, poverty and food insecurity is pervasive due to intertwined factors including, declining crop yields, land degradation and inadequate policy and institutional support. With ever-increasing populations, climate change effects will be intensified, and a major crisis is inevitable unless measures to sustain land resources are urgently taken. Originality/value The paper further discusses a model that highlights factors affecting smallholder investment in natural resources management and how these can be used to strengthen local institutions in building their resilience against climate change effects.


Author(s):  
O. A. Kryvobok ◽  
O. O. Kryvoshein ◽  
T. I. Adamenko

The Crop Growth Monitoring System (CGMS) is one of the most advanced systems of monitoring the conditions of crops growth and development and forecasting their yields in agrometeorological practice. The CGMS allows to assess the conditions of growth, development and accumulation of productive biomass of a number of agricultural crops - winter wheat, barley, maize, rice, sunflower, potatoes, soybean etc. For each of the crops the system must be adapted to specific territories taking into account  meteorological, phenological, biological information and soil characteristics. The paper discusses the peculiarities of technological adaptation of the CGMS system (Crop Growth Monitoring System) including creation of a meteorological database for the period of 2000-2017 using standard meteorological observations of the Ukrainian Hydrometeorological Center (UkrHMC) network; creation of a soil characteristics database by finding a correspondences of taxonomy of the soil map of Ukraine (scale:1:2500000) to classification of soils of the WRB; creation of a database of phenological characteristics such as TSUMEM (sum of temperatures within the period from sowing to coming-up), TSUM1 (sum of temperatures within the period from coming-up to blossoming) and TSUM2 (sum of temperatures within the period from blossoming to maturity) calculated according to the data obtained from agrometeorological posts and stations of the UkrHMC network for the period of 2000 - 2015 with regard to five main crops (winter wheat, maize, spring barley, soybean and sunflower); creation of a statistical crop capacity database at the regional and district levels. In addition, the paper considers spatial schematization of calculations and aggregation of agricultural crops productivity indicators obtained as a result of the WOFOST biophysical model application. It also outlines the scheme of crop capacity forecasting based on administrative units and the estimation of forecast accuracy for winter wheat crop capacity in administrative districts of Kiev region. The link to the website containing results of operation of the CGMS-Ukraine system is as follows: http:/entln.uhmi.org.ua/case/CGMS.


2014 ◽  
Vol 61 ◽  
pp. 326-338 ◽  
Author(s):  
D. Schlabing ◽  
M.A. Frassl ◽  
M.M. Eder ◽  
K. Rinke ◽  
A. Bárdossy

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