Water Consumption by Livestock Systems from 2002–2020 and Predictions for 2030–2050 under Climate Changes in the Czech Republic

The livestock system in Europe relies on a complex holistic equilibrium that is the outcome of an interplay of demand, market, crop production, livestock production, land use, water availability, and other factors. When modeling future scenarios of water consumption by livestock systems, the most suitable tools result from the interconnectivity of growth models, economic models, and climate models. We integrated the Environmental Policy Integrated Climate growth model (EPIC), animal-level model (RUMINANT), economic model (Global Biosphere Management Model, GLOBIOM), EURO-CORDEX climate models, and regression models. This study developed novel livestock production scenarios for individual regions of the Czech Republic with estimations of the categories of livestock that have been bred during the last 20 years and will be bred in the future and what their water consumption will be, both throughout the year and in particular seasons. First, the numbers of farm animals, namely, cattle, pigs, sheep, horses, goats, and poultry in 2002–2020 were evaluated, and their numbers were predicted for the following years until 2050. Second, livestock water consumption per region was determined based on the number of livestock individuals. Third, changes in the amount of water consumed by livestock per year in individual regions in 2050 compared to 2005 were estimated

Long-term changes in drought indices in eastern and central Europe

This study analyses long-term changes in drought indices (Standardised Precipitation Index—SPI, Standardised Precipitation–Evapotranspiration Index—SPEI) at 1 and 3 months scales at 182 stations in 11 central and eastern European countries during 1949–2018. For comparative purposes, the necessary atmospheric evaporative demand (AED) to obtain SPEI was calculated using two methods, Hargreaves-Samani (SPEIH) and Penman-Monteith (SPEIP). The results show some relevant changes and tendencies in the drought indices. Statistically significant increase in SPI and SPEI during the cold season (November–March), reflecting precipitation increase, was found in the northern part of the study region, in Estonia, Latvia, Lithuania, northern Belarus and northern Poland. In the rest of study domain, a weak and mostly insignificant decrease prevailed in winter. Summer season (June–August) is characterized by changes in the opposite sign. An increase was observed in the north, while a clear decrease in SPEI, reflecting a drying trend, was typical for the southern regions: the Czech Republic, Slovakia, Hungary, Romania, Moldova and southern Poland. A general drying tendency revealed also in April, which was statistically significant over a wide area in the Czech Republic and Poland. Increasing trends in SPI and SPEI for September and October were detected in Romania, Moldova and Hungary. The use of SPEI instead of SPI generally enhances drying trends

Use of Euro-CORDEX Models for Drought Prediction with Respect to Black Frosts and Rain Deficit during the Cold Season

This paper focuses on the analysis of changes in the distribution of frequency, duration and magnitude of drought for various time scales for two future time periods, 2041 - 2070 and 2071 - 2100 and compared to the reference period 1981 - 2010 under the two Representative Concentration scenarios RCP4.5 and RCP8.5. Dry events are calculated and analysed according to the classification of the standardized precipitation evapotranspiration index (SPEI) and the standardized precipitation index (SPI). Estimates of future drought projections based on the SPI tend to underestimate risk, while risk of the SPEI drought magnitude increases by the end of the century, even if precipitation increases moderately

Drought stress impact on vegetable crop yields in the Elbe River lowland between 1961 and 2014

The study is focused on drought stress that is detrimental to yield formation of field-grown vegetables in the lowland regions of the Czech Republic. Extensive vegetable yield losses are attributed to drought, often in combination with heat or other stresses. The objective of this research was to investigate, under field conditions, the effect of drought stress quantified by the Standardized Precipitation Evapotranspiration Index (SPEI) on yield variability of key vegetable crops growing in the Elbe River lowland, representing central European agriculture conditions. Additionally, we also tried to determine the period of crop with the highest sensitivity to drought (PCSD) of vegetable crops over the Elbe River lowland. Historical climate datasets for a regular gridded network with a high horizontal resolution of 10 km (CZGRIDS) and 305 climatological stations from the Czech Hydrometeorological Institute were applied. The SPEI at 1-, 3-, and 6-month lags was calculated for the period 1961-2014 based on precipitation and input dataset for the reference evapotranspiration (ETr) by the Penman-Monteith (PM) method. Moreover, the difference between daily precipitation and crop evapotranspiration (ETc) has been used to calculate the mean crop water balance (D) per main growth stages, as an indicator of plant stress. This improvement increased the applicability of the SPEI in agriculture drought impact on rainfed and/or irrigated field crops grown under various agronomic management systems. To understand how the SPEI, over the period 1989-2014, controlled the yield variation, we calculated the percentage of yield losses and gains for each crop. When the value of SPEI at 3-month lag–as a measure of the balance between the water availability and the atmospheric water demand–for PCSD was between -1.49 and 0.99, the yield moderately increased for Fruiting vegetables (e.g. tomatoes, cucumber). Conversely, when the SPEI-3 in the key development stage dropped below -3.0, the yield losses were about -30% and a negative influence is apparent from threshold of the SPEI≤-1.5. The effect of the SPEI on yield formation of vegetable cultivars grown under filed conditions was achieved up to 62% in the study region.El estudio se centra en los perjuicios causados por las sequías sobre los cultivos en las regiones bajas de la República Checa. Grandes pérdidas en los cultivos se han atribuido a las sequías, a menudo en combinación con el calor y otros tipos de estress. El objetivo de este trabajo fue investigar el efecto de las sequías cuantificado mediante el Índice de Precipitación Evapotranspiración estandarizada (SPEI) sobre la variabilidad de la producción de cultivos clave en las tierras bajas del río Elba. Se utilizaron bases climáticas históricas para una cuadrícula de alta resolución horizontal de 10 km y 305 estaciones climatológicas del Instituto Hidrometeorológico Checo. Se calculó el SPEI para intervalos de 1, 3 y 6 meses en el periodo 1961-2014, basado en la precipitación y en la evapotranspiración de referencia (ET) utilizando el método de Penman-Monteith. Además, la diferencia entre la precipitación diaria y la evapotranspiración del cultivo se  ha utilizado para calcular el balance medio del cultivo (D) para los principales estadios del crecimiento, como un indicador de estress de las plantas. Esta mejora metodológica aumentó la aplicabilidad del SPEI en el impacto agrícola de la sequía sobre cultivos de secano  y/o regadío bajo diferentes sistemas de gestión agronómica. Para comprender cómo controla el SPEI la variación de la producción, calculamos el porcentaje de pérdidas y ganancias para cada cultivo. Cuando el valor del SPEI en un plazo de tres meses  (como medida del balance entre la disponibilidad de aguay la demanda atmosférica de agua) estaba entre 1,49 y 0,99, la producción aumentaba moderadamente en el caso de las plantas de fruto (por ej., tomates, pepinos). Por el contrario, cuendo el SPEI-3 descendió por debajo de -3,0 en un estadio clave de desarrollo, las pérdidas de producción fueron de alrededor del 30%, y una influencia negativa fue apreciable a partir de un umbral de SPEI<1,5

Snow Data Assimilation and Evaluation Methods for Hydrological, Land Surface, Meteorological and Climate Models – A COST Action HarmoSnow Assessment Questionnaire

This chapter is based on outcomes of the working group 3 Questionnaire of the COST Action ES1404 (www.harmosnow.eu) and provides a discussion of snow data assimilation in research and operational applications, which will be presented in detail in a manuscript (Helmert et al., 2018)