When it comes to climate change, the very first thing comes to most of our mind is the rising temperature, even though climate change is having a significant impact on the water cycle. Agriculture, including crop cultivation, is the most weather- and climate-dependent economic activity. With the help of various weather-plant models and statistical correlation studies, it can be established that the average yield-increasing and yield-reducing effect of weather reaches or exceeds 20% for most economic plants. Precipitation is a climatic element which is showing extreme variability in space and time and the spatial distribution of precipitation is becoming more and more extreme year after year. Our research focused on the spatial distribution of precipitation on horizontal scale up to 1-2 km. We established a low-cost rain gauge network in Csabacsűd located on the Great Hungarian Plain where we did daily measurements (N46.49°, E20.39°, 85 m above sea level) with 18 plastic rain gauges which is widely used in the Hungarian private sphere. We examined the qualitative and quantitative correlations of the data with the help of the ESRI ArcGIS software. Spatial variance, deviation, an CV values of precipitation were calculated using Microsoft Office Excel. The results show significant areal differences in daily amount of precipitation within the small (1.5 km x 0.8 km) study area. The largest absolute difference in the small settlement reached 17 mm on 12.07.2018. The smallest value was 25 mm, the largest value was 42 mm and the distance between these stations is 1.4 km. Precipitation shows a large spatial inhomogeneity especially in daily or shorter timescales. It was clearly visible in 2019 that the standard deviation and the CV value showed a decrease compared to the 2018 research year. However, larger differences were also detected this year with a difference of 8.8 mm in the case of a distance of 1400 meters. On 22.06.2019, a difference in the amount of precipitation of 3.7 mm was detected between two gauges located 220 meters apart. This value represents a difference of 1.68 mm/100 m. These data show that on-site measurements are needed in the growing season for practical agrometeorological purposes such as irrigation scheduling.

precipitation, spatial distribution, rain gauge network

agronomy

Presentation: poster