The analytical indicators to explain the distribution of oases in arid zones using the Oases Integrated Analysis Model
Understanding the distribution of natural and artificial oases is essential for effective management of desert oases and water resources in arid regions. In order to explore characterization of Oases, we developed an ensemble method for the identification of factors influencing the distribution of o...
Guardado en:
| Autores principales: | , , , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Elsevier
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/19950f060dfa4a86ac374e3779930fa8 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: | Understanding the distribution of natural and artificial oases is essential for effective management of desert oases and water resources in arid regions. In order to explore characterization of Oases, we developed an ensemble method for the identification of factors influencing the distribution of oases in the upper reaches of the Tarim River Basin (TRB), China. To determine the affected elements of artificial and natural oases in arid lands through multi-function choices from 1990 to 2020, the Oases Integrated Analysis Model (OIAM) was used. The following input data was included in the OIAM: meteorological conditions, salinity, depth of groundwater, time sequence of Landsat images, and environmental chemicals such as calcium, bicarbonate, potassium, sodium, sulfate, and fluoride ions. Several functional methods were used to assess the efficiency of the OIAM. The results indicated that the OIAM consistently outperformed stable Wi (spatial contribution rate to Oases’ indicators). Moreover, the results from OIAM indicated that salinity and meteorological indicators influenced the spatial distribution of artificial and natural oases. For environmental chemical, Na and Mg ions were strongly associated with the distribution of artificial and natural oases, respectively. This indicates that the OIAM model effectively identifies factors influencing the distribution of artificial and natural oases in arid regions, and thus can be applied to other similar regions. |
|---|