The potential for sand dams to increase the adaptive capacity of East African drylands to climate change

Drylands are home to more than two billion people and are characterised by frequent, severe droughts. Such extreme events are expected to be exacerbated in the near future by climate change. A potentially simple and cost-effective mitigation measure against drought periods is sand dams. This little-known technology aims to promote subsoil rainwater storage to support dryland agro-ecosystems. To date, there is little long-term empirical analysis that tests the effectiveness of this approach during droughts. This study addresses this shortcoming by utilising multi-year satellite imagery to monitor the effect of droughts at sand dam locations. A time series of satellite images was analysed to compare vegetation at sand dam sites and control sites over selected periods of drought, using the normalised difference vegetation index. The results show that vegetation biomass was consistently and significantly higher at sand dam sites during periods of extended droughts. It is also shown that vegetation at sand dam sites recovers more quickly from drought. The observed findings corroborate modelling-based research which identified related impacts on ground water, land cover, and socio-economic indicators. Using past periods of drought as an analogue to future climate change conditions, this study indicates that sand dams have potential to increase adaptive capacity and resilience to climate change in drylands. It therefore can be concluded that sand dams enhance the resilience of marginal environments and increase the adaptive capacity of drylands. Sand dams can therefore be a promising adaptation response to the impacts of future climate change on drylands

Southeastern U.S. Vegetation Response to ENSO Events (1989–1999)

El Niño/Southern Oscillation (ENSO) is considered one of the most powerful forces driving anomalous global weather patterns. Large-scale seasonal precipitation and temperature changes influenced by ENSO have been examined in many areas of the world. The southeastern United States is one of the regions affected by ENSO events. In this study, remote sensing detection of vegetation response to ENSO phases is demonstrated with one-kilometer biweekly Normalized Difference Vegetation Index (NDVI) data (1989–1999) derived from the Advanced Very High Resolution Radiometer (AVHRR). The impacts of three ENSO phases, cold, warm and neutral, on vegetation were analyzed with a focus on two vegetation cover types, two seasons and two geographic regions within the southeastern U.S. Significant ENSO effects on vegetation were found in cropland and forest vegetation cover types based on image and statistical analysis of the NDVI data. The results indicate that vegetation condition was optimal during the ENSO neutral phase for both agricultural and natural vegetatio