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Considering that the relationships between agrometeorological drought indices and the impact of agricultural drought in Slovenia are not yet well understood, the aim of this study was to make an indicative evaluation of the success of selected drought indices, addressing topsoil layer and vegetation condition, in detecting drought in agriculture. In this study, the performance of two established drought indices—the SPEI (standardised precipitation evapotranspiration index) and the VHI (vegetation health index)—was evaluated with respect to yield values calculated with the LINGRA-N model, specifically, the ratio between actual and potential transpiration, also known as drought factor (TRANRF), actual root zone water content (SMACT), leaf area index (LAI), reserve dry weight (WRE), and root dry weight (WRT). The two grassland species selected for analysis were Dactylis glomerata L. (dg) and Lolium perenne L. (lp). For the period 2002–2020 or 2015–2020, three farm sites in Slovenia were considered for evaluation, with two farms at a higher altitude site and one farm at a lower altitude site in the Alpine region. Evaluation of the yield data with the drought indices showed that the r2 values of the linear regression for the selected years with the highest drought impacts (2003, 2013, and 2017) were highest between the two SPEI indices (SPEI-2, SPEI-3) and the model variables TRANRF, SMACT, and WRT, with r2 higher than 0.5 and statistically significant for the lower situated farm in 2013. For 2003 and 2017, the r2 values were less significant as well as for the model variable WRE for all three years selected for analysis (2003, 2013, and 2017).

Grassland Model Based Evaluation of Drought Indices: A Case Study from the Slovenian Alpine Region