Nevin Manimala Statistics

Methods and technologies for spatial analysis of regional ecosystems based on the watershed approach

Integr Environ Assess Manag. 2022 Jun 22. doi: 10.1002/ieam.4652. Online ahead of print.


The watershed management approach is an efficient tool for organizing and implementing natural resource management at the regional and interregional levels. Statistical processing of watershed information contributes to a comprehensive assessment of the environment of the river watersheds at different hierarchical levels. The purpose of this work is to use spatial analysis and data simulation for assessing the state of ecosystems in hydrologically-defined geographic areas like watersheds. The minimal watersheds of the “pilot” territory of four watersheds in Eastern Siberia with an average area of about 1 ha are used as elementary territorial units. For each watershed, spatial analysis tools form a set of attributes of unique natural characteristics, which are obtained using ground and satellite data. Such a set of attributes can be used to assess the state of the territory employing various methods of mathematical modeling and statistical and cluster analysis. Watershed modeling of the territory was carried out based on MERIT Hydro digital elevation model. Based on Terra MODIS satellite information, data on temperature, vegetation indices, and vegetation cover were obtained for each watershed. The NASA GPM reanalysis data were used to generate the data on accumulated precipitation for all elementary watersheds. Analysis of the seasonal dynamics of the surface temperature in the study area was made, and statistical distributions of temperature variations during the year were obtained for each watershed. Effective temperature sum was calculated. Statistical values and average annual characteristics of trends in several vegetation indices were obtained for each watershed. The necessary methods and technologies for generating, storing, and processing data on each watershed have been developed. This article is protected by copyright. All rights reserved. © 2022 SETAC.

PMID:35730526 | DOI:10.1002/ieam.4652

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