Improving Complementary Methods to Predict Evapotranspiration for Data Deficit Conditions and Global Applications Under Climate Change

A reliable estimate of evapotranspiration (ET) in river basins is important for the purpose of water resources planning and management. ET represents a significant portion of rainfall in the water budget; therefore, the uncertainty in estimating ET can lead to the inaccurate prediction of water resources. While remote sensing techniques are available to estimate ET, such methods are expensive and necessary data may not be readily available. Classical methods of estimating ET require detailed land use/cover information that are not readily available in rural river basins. Complementary methods provide simple and reliable approaches to estimate ET using meteorological data only. However, these methods have not been investigated in detail to assess the overall applicability and the needs for revisions if any. In this work, an improved approach to use the complementary methods using readily available meteorological data is presented. The methodology is validated using 34 global FLUXNET sites with heterogeneous land use/cover, climatic, and physical conditions. The method was compared with classical methods using Ghana as a study area where original pioneering studies of ET have been performed. The work was extended to develop global maps of ET and water surplus (precipitation - ET) for the 20th century followed by climate change-induced 21st century estimates for 2040-2069 and 2070-2099 periods. The emission scenario used was the moderate A1B with the global climate models CGCM3.1 and HADGEM1. The results were assessed at different scales from global to regional such as for potential outcomes of climate change on ET and water surplus

Bibliometric analysis of worldwide scientific literature in mobile - health: 2006–2016

Abstract Background The advancement of mobile technology had positively influenced healthcare services. An emerging subfield of mobile technology is mobile health (m-Health) in which mobile applications are used for health purposes. The aim of this study was to analyze and assess literature published in the field of m-Health. Methods SciVerse Scopus was used to retrieve literature in m-Health. The study period was set from 2006 to 2016. ArcGIS 10.1 was used to present geographical distribution of publications while VOSviewer was used for data visualization. Growth of publications, citation analysis, and research productivity were presented using standard bibliometric indicators. Results During the study period, a total of 5465 documents were published, giving an average of 496.8 documents per year. The h-index of retrieved documents was 81. Core keywords used in literature pertaining to m-Health included diabetes mellitus, adherence, and obesity among others. Relative growth rate and doubling time of retrieved literature were stable from 2009 to 2015 indicating exponential growth of literature in this field. A total of 4638 (84.9%) documents were multi-authored with a mean collaboration index of 4.1 authors per article. The United States of America ranked first in productivity with 1926 (35.2%) published documents. India ranked sixth with 183 (3.3%) documents while China ranked seventh with 155(2.8%) documents. VA Medical Center was the most prolific organization/institution while Journal of Medical Internet Research was the preferred journal for publications in the field of m-Health. Top cited articles in the field of m-Health included the use of mobile technology in improving adherence in HIV patients, weight loss, and improving glycemic control in diabetic patients. Conclusion The size of literature in m-Health showed a noticeable increase in the past decade. Given the large volume of citations received in this field, it is expected that applications of m-Health will be seen into various health aspects and health services. Research in m-Health needs to be encouraged, particularly in the fight against AIDS, poor medication adherence, glycemic control in Africa and other low income world regions where technology can improve health services and decrease disease burden