Evaluating water availability and flow characteristics for Dikrong river in Arunachal Pradesh using Acoustic Doppler Current Profiler

• Published in: Sustainable water resources management 2024-04, Vol.10 (2), p.103, Article 103
• Main Authors: Goswami, Ghritartha, Darang, Joon, Prasad, Ram Kailash, Mandal, Sameer
• Format: Article
• Language: English
• Subjects: Acoustics; Analysis; Aquatic ecosystems; Barren lands; Bathymetry; Climate change; Creeks & streams; Data analysis; Development Economics; Doppler sonar; Earth and Environmental Science; Earth Sciences; Ecosystem management; Flow characteristics; Flow distribution; Flow pattern; Flow velocity; History; Hydrogeology; Hydrology; Hydrology/Water Resources; Investigations; Land cover; Land use; Local communities; Machine learning; Original Article; Peak floods; Planning; Profiling; Regional development; Regional planning; River banks; River basins; River discharge; River ecology; River flow; Riverbanks; Rivers; Runoff; Sediments; Soil erosion; Stream flow; Support vector machines; Sustainable Development; Trends; Varied flow; Velocity; Velocity distribution; Water availability; Water discharge; Water Policy/Water Governance/Water Management; Water resources
• ISSN: 2363-5037; 2363-5045
• DOI: 10.1007/s40899-024-01082-7

The Dikrong river, which flows through Arunachal Pradesh and Assam, holds vital importance for local communities. However, a comprehensive study on this river has been lacking for this river system. To bridge this gap, an extensive investigation for sustainable regional development and effective water resource planning in the Dikrong river basin was carried out based on Acoustic Doppler Current Profiler (ADCP), historical data analysis and Land Use/Land Cover (LULC) change analysis. The study highlights the effectiveness of ADCP's in accurately assessing various river parameters, including bathymetry mapping, current profiling, discharge measurements, and three-dimensional velocity profiling. The results indicate diverse flow patterns at different locations during low river discharge, highlighting the importance of understanding these patterns for efficient river ecosystem management. By utilizing ADCP data, the flow patterns and discharge characteristics are investigated across various transects that reveal a distinct discharge surge, particularly in the mid-section. However, varied flow velocities between river banks and the mid-section highlight the river's intricate behaviour. The historical flow patterns were examined to get insights into flow characteristics. Although historical data indicated a downward discharge trend for monthly peak flood, this is possibly due to climate change and land use alterations. Further, employing machine learning techniques (Support Vector Machine, Google Earth Engine), the study assesses LULC changes, revealing declining forest cover and increasing settlements and agriculture/barren land. Finally, it presents a comprehensive analysis of flow dynamics, water availability, erosion-prone zones, and high-risk areas along the river.