No abstract

Crop loss due to drought is a complex issue, because it changes according to the drought intensity and duration, and the developmental stage of the plants when drought occurs. In order to assess the drought-induced decline in crop harvest, drought variability and the yield sensitivity of winter wheat, maize, sugar beet, and sunflower to drought during their growing seasons is investigated in the Republic of Moldova. This is then used as an example of the response of non-irrigated crops to increasing drought tendency in south-eastern Europe. The quantification of drought was done by using the standardized precipitation evapotranspiration index (SPEI) at 1-to 12-month lags during the period from 1951 to 2012. The relationship between drought at various time scales and the standardized yield residuals series (SYRS) for individual crops over the country and the Balti chernozem steppe of Moldova (represented by Balti experimental site) for the 1962-2012 farming years were investigated. In order to detect the trends and the shifts in the SPEI time series over 62 years, the non-parametric, Mann-Kendall and Pettitt tests were used for each month of the year to cover the main life cycle of the crops. The trend analysis of agricultural drought emphasizes an increasing trend from June to October, and becomes significant in the southern region at the 95% level during July to September. The SPEI highlights the main periods of dry/wet persistence and the regional characteristics of drought which are present in the Southern region, and make this region more prone to severe drought persistence, mostly during the last decade. Drought during the plant reproductive stages may significantly reduce grain yield potential, the relation between the SYRS and the SPEI explaining up to 62% of the low-yield variability.

The timing of maturity of grapes depends on the weather conditions during the growing season. This study relies on the dependence of harvest dates on the air temperature and dry/wet conditions. Recorded observations show that increases in air temperature and dryness are associated with earlier grape harvests. Documentary data of grape harvests from the Bohemian wine-growing region (mainly northwest of Prague) were combined with mean Standardized Precipitation Evapotranspiration Index (SPEI) series starting in 1841 and ordinary least square regression with subsequent scaling to reconstruct the mean SPEI values for this area for April to August from 1499 to 2012. The reconstructed SPEI series explains 75% of the drought variability since 1841. All dry years that were detected by the reconstructed April−August SPEI values correlate well with years of excellent and good red wine of vintage quality for 1499−1840. A comparison of the reconstructed series with other SPEI reconstructions from the Czech Lands (the recent Czech Republic) based on documentary and instrumental data shows good agreement. The results demonstrate that grape harvest series may be used as a proxy for drought reconstruction in the central European region.

This study presents a detailed analysis on the role of snow cover during the cold season (October-March) on soil moisture deficit and drought development during the growing season (April-September) in the lowland and highland sites in the Czech Republic. Besides daily, weekly and seasonal series of basic snow-cover characteristics [the first day and the last day of snow cover, the number of days with snow cover (DSC), snow depth and snow water equivalent (SWE)] and soil water content measurements, six drought indices have been used in this study to quantify drought. Accumulations of years with significantly below average DSC/SWE were recorded in the early 1960s, mid-1980s, late 1990s and most of the 2000s. The trend towards an earlier end date of snow cover is found in both lowland and highland sites. However, the most significant shift in the dates of early end of snow cover has been identified to occur mostly in the hilly areas while in the lowland areas, these changes are not that evident. Liquid precipitation more than solid precipitation (snowfall) during the cold season lead to weakening correlation between SWE/DSC and the subsequent early summer (April-May-June, AMJ) soil moisture. Snow-cover characteristics can significantly influence soil water saturation during the first part of the growing season, while seasonal amount of SWE can explain up to 45% of soil moisture variability during AMJ season. More than 52% of dry AMJ followed after cold seasons with poor snow, and 42% of wet AMJ season followed after cold seasons with abundant snow. The strength of correlation between drought indices and soil moisture anomalies is higher in later summer. The negative anomalous snow characteristics in conjunction with winter and AMJ drought amplify lingering impact on the depletion of soil moisture in the later summer.KEY WORDS anomalous snow seasons; snow-cover depth; snow water equivalent; snow phenology; soil moisture; drought indices (SPI, SPEI, PDSI, scPDSI, Z-index, scZ-index)

The European Cooperation in Science and Technology (COST) Action ES1404 “HarmoSnow”, entitled, “A European network for a harmonized monitoring of snow for the benefit of climate change scenarios, hydrology and numerical weather prediction” (2014-2018) aims to coordinate efforts in Europe to harmonize approaches to validation, and methodologies of snow measurement practices, instrumentation, algorithms and data assimilation (DA) techniques. One of the key objectives of the action was “Advance the application of snow DA in numerical weather prediction (NWP) and hydrological models and show its benefit for weather and hydrological forecasting as well as other applications.” This paper reviews approaches used for assimilation of snow measurements such as remotely sensed and in situ observations into hydrological, land surface, meteorological and climate models based on a COST HarmoSnow survey exploring the common practices on the use of snow observation data in different modeling environments. The aim is to assess the current situation and understand the diversity of usage of snow observations in DA, forcing, monitoring, validation, or verification within NWP, hydrology, snow and climate models. Based on the responses from the community to the questionnaire and on literature review the status and requirements for the future evolution of conventional snow observations from national networks and satellite products, for data assimilation and model validation are derived and suggestions are formulated towards standardized and improved usage of snow observation data in snow DA. Results of the conducted survey showed that there is a fit between the snow macro-physical variables required for snow DA and those provided by the measurement networks, instruments, and techniques. Data availability and resources to integrate the data in the model environment are identified as the current barriers and limitations for the use of new or upcoming snow data sources. Broadening resources to integrate enhanced snow data would promote the future plans to make use of them in all model environments.