This study investigated the variability of agricultural drought severity,as depicted by vegetation indices,and the bias in identifying drought events when considering a stationary vs nonstationary climate reference.Th...This study investigated the variability of agricultural drought severity,as depicted by vegetation indices,and the bias in identifying drought events when considering a stationary vs nonstationary climate reference.The work leveraged gridded climate data(NCEP CFSv2,CHIRPS 1981–2022),soil properties(OpenLandMap),satellite imagery(Sentinel2/Landsat,2000–2022),and future climate projections(NEX-GDDP,2050)together with local knowledge of selected farms,to augment drought monitoring techniques and identify potential issues for agriculture.For the study domain,significant differences were observed when comparing drought characteristics using stationary and nonstationary drought indexes,with biases being not ubiquitous in either space or time of year.When developing sustainable drought mitigation and adaptation strategies,decision-makers should carefully address this uncertainty to avoid a possible underestimation of drought magnitude.Results showed a drought increase(∼50%)by the mid and late twenty-first century.Projection of future climate highlighted an even more significant impact(∼80%)with a wide variability of risk across the domain.As drought impact was also related to soil organic carbon(SOC),our results suggest that improving SOC content could be a sustainable strategy for enhancing soil drought resilience,especially in areas commonly characterized by low concentrations of organic carbon and nutrients.The analysis highlighted that drought impacts were also modulated by investment in irrigation infrastructure and irrigation efficiency.Researchers and land managers could apply the proposed analysis design to address historical,current and future indicators of vegetation conditions within irrigated regions.By providing spatio-temporal information on the patterns of drought impacts and their bias,this study supports identifying priority regions for targeted drought risk reduction and adaptation options,including water resources and soil management sustainability criteria,to move towards more resilient agricultural systems.展开更多
基金funded by the Lessinio,Euganeo,Berico(LEB)Land-Reclamation Consortium,within the framework of the Piano Irriguo della Regione Veneto(D.G.R.n.1101,July 31,2018)。
文摘This study investigated the variability of agricultural drought severity,as depicted by vegetation indices,and the bias in identifying drought events when considering a stationary vs nonstationary climate reference.The work leveraged gridded climate data(NCEP CFSv2,CHIRPS 1981–2022),soil properties(OpenLandMap),satellite imagery(Sentinel2/Landsat,2000–2022),and future climate projections(NEX-GDDP,2050)together with local knowledge of selected farms,to augment drought monitoring techniques and identify potential issues for agriculture.For the study domain,significant differences were observed when comparing drought characteristics using stationary and nonstationary drought indexes,with biases being not ubiquitous in either space or time of year.When developing sustainable drought mitigation and adaptation strategies,decision-makers should carefully address this uncertainty to avoid a possible underestimation of drought magnitude.Results showed a drought increase(∼50%)by the mid and late twenty-first century.Projection of future climate highlighted an even more significant impact(∼80%)with a wide variability of risk across the domain.As drought impact was also related to soil organic carbon(SOC),our results suggest that improving SOC content could be a sustainable strategy for enhancing soil drought resilience,especially in areas commonly characterized by low concentrations of organic carbon and nutrients.The analysis highlighted that drought impacts were also modulated by investment in irrigation infrastructure and irrigation efficiency.Researchers and land managers could apply the proposed analysis design to address historical,current and future indicators of vegetation conditions within irrigated regions.By providing spatio-temporal information on the patterns of drought impacts and their bias,this study supports identifying priority regions for targeted drought risk reduction and adaptation options,including water resources and soil management sustainability criteria,to move towards more resilient agricultural systems.
