Jaap De Gruijter
Jaap De Gruijter has been selected by the Pedometrics Committee on Prizes and Awards to receive the Webster Medal at the 19th World Congress on Soil Science in Brisbane, Australia, 2010. Jaap has made a substantive contribution to the development of pedometrics over a period of more than 40 years. Jaap’s contribution has been one of consistent innovation and extremely high quality. His approach to pedometrics has been one of finding elegant solutions to substantive problems in soil science rather than simply the application of statistical methods to soil problems. As examples of this we highlight Jaap’s contribution to the development of an efficient formal method of estimating soil map quality, and his contribution to sampling theory and practice. Jaap was instrumental in setting up the Pedometrics Working Group, and throughout his career he has been a leader in pedometrics and has contributed to the development of the discipline, and particularly the mentoring of younger colleagues. He was the leader of the team on Soil Inventory Methods at Alterra, Wageningen, the Netherlands.
Ben Marchant is currently researching the use of geostatistical techniques to map and monitor variables in the environment on the Rothamsted Research, Harpenden, UK. His primary interests are in the design of efficient sample schemes for these maps and in the development of robust geostatistical techniques which are not overly affected by outlying or erroneous measurements. He previously worked at Silsoe Research Institute applying signal processing techniques to problems in Biosystems Engineering. In 2010, Ben Marchant has been appointed the secretary of the newly created Working Group (WG) on Soil Monitoring under IUSS.
Jasper A. Vrugt
Jasper A. Vrugt is an assistant professor at the University of California, Irvine, and holds a joint appointment in the Department of Civil and Environmental Engineering and the Department of Earth System Science. He graduated from the Universiteit van Amsterdam (UvA, the Netherlands). His current research group uses optimality principles, Bayesian statistics, Monte Carlo simulation and evolutionary strategies to better analyze the mismatch between models and data and help improve theory, understanding and predictability of environmental systems. He regularly develops new methods and uses parallel computing to solve the most complex and computationally demanding (inverse) problems. He draws inspiration from emerging model-data synthesis problems in surface hydrology, soil physics, hydrogeophysics, and hydrometeorology.