Precipitation variability over the Bolivian Altiplano is strongly affected by local climate and temporal variation of large-scale atmospheric flow. Precipitation is the main water source for drinking water and agricultural production. For this reason, a better understanding of precipitation variability and its relation with climate phenomena can provide important information for forecasting of droughts and floods, disaster risk reduction, and improvement of water management. We present results of an analysis of the austral summer precipitation variability at six locations in the Bolivian Altiplano and connections to climate variability. For this purpose, the variability of the summer precipitation was related to El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), Antarctic Meridional Mode (AMM), and Atlantic Multidecadal Oscillation (AMO). A statistically significant correlation between climate indices and precipitation was found in various spectral frequencies and power. The variability of the summer precipitation was associated with the climate indices using a band-pass filter, representing the signal at a particular period of time. For the ENSO, band-pass filtering was applied for Niño3.4 and Niño3 at band~2-7 years, for NAO band 5-8 years, and for AMM band~10-13 years. The variability of summer precipitation was related to all studied climate modes by negative relationships. The physical explanation for this is first the dry air transported from the Pacific Ocean to the Altiplano during El Niño events. Second, NAO and ENSO are dynamically linked through teleconnections. Third, the intertropical convergence zone (ITCZ) shifts are northwards during the warm phases of AMM. These physical mechanisms lead to a reduced austral summer precipitation associated with positive phases of the ENSO, NAO, and AMM. The results can be used to better forecast precipitation in the Bolivian Altiplano and provide support for the development of policies to improve climate resilience and risk management of water supply.

Abstract. Drought is a major natural hazard in the Bolivian Altiplano that causes large agricultural losses. However, the drought effect on agriculture varies largely on a local scale due to diverse factors such as climatological and hydrological conditions, sensitivity of crop yield to water stress, and crop phenological stage among others. To improve the knowledge of drought impact on agriculture, this study aims to classify drought severity using vegetation and land surface temperature data, analyse the relationship between drought and climate anomalies, and examine the spatio-temporal variability of drought using vegetation and climate data. Empirical data for drought assessment purposes in this area are scarce and spatially unevenly distributed. Due to these limitations we used vegetation, land surface temperature (LST), precipitation derived from satellite imagery, and gridded air temperature data products. Initially, we tested the performance of satellite precipitation and gridded air temperature data on a local level. Then, the normalized difference vegetation index (NDVI) and LST were used to classify drought events associated with past El Niño–Southern Oscillation (ENSO) phases. It was found that the most severe drought events generally occur during a positive ENSO phase (El Niño years). In addition, we found that a decrease in vegetation is mainly driven by low precipitation and high temperature, and we identified areas where agricultural losses will be most pronounced under such conditions. The results show that droughts can be monitored using satellite imagery data when ground data are scarce or of poor data quality. The results can be especially beneficial for emergency response operations and for enabling a proactive approach to disaster risk management against droughts.

Abstract. Implementation of agriculturally related early warning systems is fundamental for the management of droughts.Additionally, risk-based approaches are superior in tackling future drought hazards. Due to data-scarcity in many regions, high resolution satellite imagery data are becoming widely used. Focusing on ENSO warm and cold phases, we employ a risk-based 15 approach for drought assessment in the Bolivian Altiplano using satellite imagery data and application of an early warning system. We use a newly established high resolution satellite dataset and test its accuracy as well as performance to similar (but with less resolution) datasets available for the Bolivian Altiplano. It is shown that during the El Niño years (warm ENSO phase), the result is great difference in risk and crop yield. Furthermore, the Normalized Difference Vegetation Index (NDVI) can be used to target specific hot spots on a very local scale. As a consequence, ENSO early warning forecasts as well as 20 possible magnitudes of crop deficits could be established by the government, including an identification of possible hotspots during the growing season. Our approach therefore should not only help in determining the magnitude of assistance needed for farmers on the local scale but also enable a pro-active approach to disaster risk management against droughts that can include economic-related instruments such as insurance as well as risk reduction instruments such as irrigation.