Assimilation Model of Erosion and Soil Moisture Based on Remote Sensing for the Hydraulic and Hydrologic Integration of the Taleghan Watershed

Abstract

This research focuses on investigating the challenges related to watershed management theory and data accessibility in watersheds, specifically concerning the evaluation of hydrological, water, and soil problems. The first part of the research involves the use of the ARC SWAT and Google Earth Engine software to model the Taleghan watershed, analyzing subbasins separately and in communication with each other. Key parameters such as sedimentation, erosion, soil moisture, and hydrological response were investigated after modeling, calibration, validation, and uncertainty analysis and were evaluated on the basis of the region's formation and watershed parameter types. This approach can help identify potential issues and enable more effective management of the watershed.

A comprehensive study was conducted to investigate specific processes of the hydrological cycle in a particular basin, including a detailed assessment of the balance and formations of the basin, as well as an investigation of the influence of soil moisture and curve number and sediment and erosion. The calibration was performed via the SUFI2 algorithm with an objective function, which is commonly used for hydrological modeling. The precise delineation of the basin and subbasin helped to create a high-precision communication model that accurately represents the system being studied. One key area of focus in this research was erosion potential and the hydrological process of soil moisture, which has been extensively investigated and high-resolution spatial and temporal mapped. Potential scenarios have also been proposed for addressing erosion and soil moisture in the area.

Finally, integration was achieved by calibrating sensitive parameters and combining runoff, erosion and sedimentation; soil moisture; the uncertainty parameter range; the optimization scenario; other relevant factors; and swat-cup affected parameters. This integrated model can be used in other areas with similar climatic conditions to predict productivity and integration. Overall, this study provides a practical and valuable model that could be useful for future research and land management efforts.