EVALUATION OF THE CLASSICAL AND MODIFIED GINU FUNCTIONS IN RELATION TO THE ARALKUM DESERT CONDITIONS
Abstract
This article adapts the topographic Ginou function, a dust storm source, to the dynamically changing landscape of the dry Aral Sea bed (Aralkum Desert). The static nature of the original Ginou function does not account for natural and artificial vegetation regeneration processes, leading to errors in dust emission estimates. The modified Ginou function integrates satellite data based on the NDVI vegetation index, allowing the model to dynamically change the surface erodibility coefficient depending on the seasonal state of the vegetation cover. The model was tested using dust storm data for all seasons of the year. It was shown that the modified function more accurately reflects seasonal surface conditions, while the classical model overestimates emission volumes, especially during growing seasons. It was found that using the modified Ginou function reduces the estimated environmental load by an average of 9%. An analysis of economic damages using the spring storm of May 27, 2018, originating in the Aralkum Desert as an example showed that using a modified function reduced the estimated loss by USD 2.49 million (9.53%) per square kilometer by taking into account vegetation cover, which prevents dust removal. It was found that the greatest damage (over USD 10 million according to the standard model) occurred in the rural sector, which is critical for the Aral Sea region in the spring. Using the modified approach prevents excessive insurance provisions and provides more accurate data for assessing the "cost of inaction" when planning phytomelioration measures for the Aral Sea bed. The proposed approach demonstrates significant effectiveness for regional monitoring of salt and dust transport and can be recommended for refining global climate models in areas of active desertification