the world academy of sciences for the advancement of science in developing countries


15 October 2013

Scientist models the spread of deserts

Chinese scientist Zheng Xiaojing, from the Lanzhou University, Lanzhou, China (concurrently the president of the Xi’dian University, China), has devised a mathematical model to predict the formation and evolution of dune fields, as well as their displacement. Her model, which applies to all the deserts on Earth, could be used to devise strategies to achieve better protection of villages against sand storms and the onrush of deserts.

Zheng Xiaojing discussed her results at the 24th General Meeting of TWAS, the world academy of sciences for the advancement of science in developing countries, held in Buenos Aires from 30 September to 4 October.

Desertification is an ever-increasing phenomenon. Earth, involving one third of land surface (48 million square kilometres) with a spread speed close to 6,000 square kilometres per year. Australia, Saudi Arabia and China rank among the top three countries for desert areas. People protect villages and goods using vertical barriers and grass patches, but in most cases the problem is addressed with little or no strategic planning.

"Desert spreading rates have greatly increased during these years," pointed out Zheng Xiaojing "rising from 3-4 metres per year in 1998-2003, to 8-10 metres per year from 2003 to 2008. China is particularly affected by this phenomenon, and this observation prompted my laboratory to address the problem of dunes’ formation using a mathematical approach, since aerial photos and land measurements are not sufficient to make decent predictions."

Dunes are classified according to their shape: barchan dunes resemble the half moon and are more common on desert edges; transverse dunes run in stripes, and preferentially pave deserts’ hinterlands. Dunes’ formation and evolution is influenced by many factors, in particular by grains shape and thickness, as well as by winds’ direction and force. Season is also important, because it changes winds’ direction and speed. This, in turn, acts as dune modifier. All these factors, and others as well, must be kept in consideration when simulating dune shaping and evolution. 

To allow a more precise prediction of dunes’ formation and speed of desertification, Zheng Xiaojing devised with a mathematical algorithm called "Triple-jump model". This model successfully reveals the influence of wind speed, wind erosion and surface condition, which all influence the pattern of dune formation.

"To analyze a square area hundreds kilometres wide, we have split it into small squares of one by one metre," explained Zheng Xiaojing. "Then, on these small patches have applied a mathematical formula that keeps track of erosion degree (particles lift by the wind), covering factors (particles covering neighbours) and the so-called 'splash', the bouncing effect of particles among each other."

Running simulations that cover from as little as few years to a hundred years, the Chinese scientist proved that dunes grow in height according also to the thickness of the initial layer. For example, a two-metre dune under the influence of spring winds, which are stronger than in other seasons, can travel 28 metres in as little as six months. "By applying this kind of calculations to wider areas we may predict deserts’ evolution, and suggest how to best protect from sandy winds."

The same calculations applied to desert-oasis transition zones allowed the scientist to determine the cost-effectiveness of one kind of straw, grid-like barrier normally used by local populations. "According to our models," pointed out the scientist "some transition areas could be protected with equal success with barriers with reduced areas, placed with adequate orientation. This would help to achieve the same protection, with less costs."

Cristina Serra

This website does not use profiling cookies, but only first and third party technical cookies, including cookies from social media plugins.
To learn more about our cookie policy or to change your cookie settings, click here.
By using this website and clicking “accept”, you consent to the use of cookies in accordance with our cookie policy.