Hydrological modelling of largest braided river of India using MIKE Hydro River software with rainfall runoff, hydrodynamic and snowmelt modules

Abstract

The Brahmaputra River is one of the world's largest river systems, India's largest braided river, and its springtime runoff and downstream streamflow are mostly due to snowmelt processes. This study analysed and used TRMM/GFS rainfall, PET, and snowmelt data as inputs to a RR model, which is based on the MIKE Hydro River NAM software package. The mathematical model was calibrated against the available observed discharge data for the sub-catchments. The model performed reasonably well and simulated discharge in good agreement with observed discharge in terms of timing, rate, volume, and shape of the hydrograph. During the calibration procedure, the optimum values of the nine RR-NAM parameters are obtained. The performance of each model has been checked against measured discharge using a coefficient of determination (R2). It is observed that the value of R2 varies from 0.6 to 0.86. This is deemed acceptable for the purposes of this study. In addition to R2, the overall Water Balance error is also checked. The WBL error is less than 6%. Despite the inherent uncertainties in hydrological modelling, it is determined that the calibrated RR-NAM model can be utilized for the Brahmaputra basin's Flood Forecasting and Early Warning System design, as well as water resource management and planning.

Quantitative analysis of hydropower potential in the upper Beas basin using geographical information system and MIKE 11 Nedbor Afrstromnings Model (NAM)

“…Similarly, Yadav et al (2019) utilized the MIKE‐NAM 11 to estimate R‐R in the Sher River basin and determined that the CK 1 , CK 2 and CQOF parameters were particularly sensitive. The similar sensitive parameters were also found by Pareta (2023) to model the snowmelt process in the Brahmaputra river basin. In this study, the utilization of sensitivity analysis played a crucial role in enhancing the calibration process by pinpointing the parameters that required prioritization.…”

“…The most significant and sensitive parameters were discovered to be Lmax, CK 1 , CK 2 and CQOF, respectively, with the p value less than 0.05. However, the remaining parameters were discovered to be non‐sensitive because of low disparities (Pareta, 2023). The study's findings, which were supported by various researchers such as Wakigar (2017), Yadav et al (2019) and Pareta (2023), highlighted the significance of sensitivity analysis in improving the calibration of the MIKE NAM.…”

“…However, the remaining parameters were discovered to be non‐sensitive because of low disparities (Pareta, 2023). The study's findings, which were supported by various researchers such as Wakigar (2017), Yadav et al (2019) and Pareta (2023), highlighted the significance of sensitivity analysis in improving the calibration of the MIKE NAM. Wakigar (2017) demonstrated that in the Upper Guder Catchment, the Umax, Lmax, CQOF and CK 1 , CK 2 parameters of the MIKE 11 NAM were crucial for streamflow forecasting.…”

“…Previous studies have established the effectiveness of MIKE 11 NAM in simulating water availability for basins influenced by both rain-fed and snow-fed conditions (Nguyen et al, 2023;Pareta, 2023;Parvaze et al, 2023;Pham Van & Le, 2023). Efficient utilization of water resources is crucial for sustainable development, and as a pivotal component of water resource management, the identification of high-potential hydropower locations in rivers becomes imperative.…”

Morphological Model for Erosion Prediction of India’s Largest Braided River Using MIKE 21C Model

“…A braided river is characterised by a network of multiple, interweaving channels that divide and rejoin, creating a distinctive braided appearance (Schuurman and Kleinhans, 2011;Gao et al, 2022;Pareta, 2023). Typically found in mountainous regions, these rivers transport relatively coarse and diverse sediments down steep gradients.…”