Future drought risk in Africa: Integrating vulnerability, climate change, and population growth

Drought risk refers to the potential losses from hazard imposed by a drought event, and it is generally characterized as a function of vulnerability, hazard, and exposure. In this study, drought risk is assessed at a national level across Africa, and the impacts of climate change, population growth, and socioeconomic vulnerabilities on drought risk are investigated. A rigorous framework is implemented to quantify drought vulnerability considering various sectors including economy, energy and infrastructure, health, land use, society, and water resources. Multi-model and multi-scenario analyses are employed to quantify drought hazard using an ensemble of 10 regional climate models and a multi-scalar drought index. Drought risk is then assessed in each country for 2 climate emission pathways (RCP4.5 and RCP8.5), 3 population scenarios, and 3 vulnerability scenarios during three future periods between 2010 and 2100. Drought risk ratio is quantified, and the role of each component (i.e. hazard, vulnerability, and exposure) is identified, and the associated uncertainties are also characterized. Results show that drought risk is expected to increase in future across Africa with varied rates for different models and scenarios. Although northern African countries indicate aggravating drought hazard, drought risk ratio is found to be highest in central African countries as a consequent of vulnerability and population rise in that region. Results indicate that if no climate change adaptation is implemented, unprecedented drought hazard and risk will occur decades earlier. In addition, controlling population growth is found to be imperative for mitigating drought risk in Africa (even more effective than climate change mitigation), as it improves socioeconomic vulnerability and reduces potential exposure to drought

Recent advances in functionalized polymer membranes for biofouling control and mitigation in forward osmosis

Forward osmosis (FO) is an osmotically driven process widely studied for water desalination, wastewater treatment, and water reuse, as well as dilution and concentration of aqueous streams. However, its application is still hampered by the lack of ideal draw solutes, high-performance membranes, and fouling/biofouling. Biofouling is particularly challenging when FO is applied for seawater desalination and wastewater treatment. Over the last decade, many attempts have been made to exploit advances in materials science to obtain membranes with anti-biofouling properties to prevent or to reduce the detrimental effects of this phenomenon. In this review, we address the various approaches of membrane surface functionalization for biofouling control and mitigation. Recent developments in surface modification of thin-film composite and asymmetric membranes using surface coating, surface functionalization, and incorporation of tailored materials for biofouling control in FO are critically discussed. The future perspectives of anti-biofouling materials and FO membranes are reviewed to shed light on the future research directions for developing the true potential surface modification approach for the FO process

Accounting for downscaling and model uncertainty in fine-resolution seasonal climate projections over the Columbia River Basin

Climate change is expected to have severe impacts on natural systems as well as various socio-economic aspects of human life. This has urged scientific communities to improve the understanding of future climate and reduce the uncertainties associated with projections. In the present study, ten statistically downscaled CMIP5 GCMs at 1/16th deg. spatial resolution from two different downscaling procedures are utilized over the Columbia River Basin (CRB) to assess the changes in climate variables and characterize the associated uncertainties. Three climate variables, i.e. precipitation, maximum temperature, and minimum temperature, are studied for the historical period of 1970–2000 as well as future period of 2010–2099, simulated with representative concentration pathways of RCP4.5 and RCP8.5. Bayesian Model Averaging (BMA) is employed to reduce the model uncertainty and develop a probabilistic projection for each variable in each scenario. Historical comparison of long-term attributes of GCMs and observation suggests a more accurate representation for BMA than individual models. Furthermore, BMA projections are used to investigate future seasonal to annual changes of climate variables. Projections indicate significant increase in annual precipitation and temperature, with varied degree of change across different sub-basins of CRB. We then characterized uncertainty of future projections for each season over CRB. Results reveal that model uncertainty is the main source of uncertainty, among others. However, downscaling uncertainty considerably contributes to the total uncertainty of future projections, especially in summer. On the contrary, downscaling uncertainty appears to be higher than scenario uncertainty for precipitation. © 2017 Springer-Verlag Berlin Heidelber

Integrating biodiversity, remote sensing, and auxiliary information for the study of ecosystem functioning and conservation at large spatial scales

Assessing patterns and processes of plant functional, taxonomic, genetic, and structural biodiversity at large scales is essential across many disciplines, including ecosystem management, agriculture, ecosystem risk and service assessment, conservation science, and forestry. In situ data housed in databases necessary to perform such assessments over large parts of the world are growing steadily. Integrating these in situ data with remote sensing (RS) products helps not only to improve data completeness and quality but also to account for limitations and uncertainties associated with each data product. Here, we outline how auxiliary environmental and socioeconomic data might be integrated with biodiversity and RS data to expand our knowledge about ecosystem functioning and inform the conservation of biodiversity. We discuss concepts, data, and methods necessary to assess plant species and ecosystem properties across scales of space and time and provide a critical discussion of outstanding issues