Abstract ID: 3.8584 | Reviewing | Poster | TBA | TBA

Assessment of the hydropower potential is an instrumental that enables various associated stakeholders to acquire financial investments for future electricity production. Estimation of the discharge plays a pivotal role in assessing hydropower potential. To assess the hydropower potential existing tools/models such as SWAT, QSWAT, HPAT are used. However, these models are limited to computational efficiency of discharge values. There is a widely acknowledged model called Glacio-hydrological Degree-day Model (GDM) which is known for its better computational efficiency. But no one has directly applied this model for assessing the hydropower potential. Therefore, the aim of this study was to leverage GDM to assess the hydropower potential. To accomplish the aim of this study it was carried out through three phases, I, II, and III. During Phase I, literature review and data preparation were carried out. Then after phase II the model was calibrated and validated. Finally, phase III was carried out through two steps, identification of potential hydropower sites and estimating its potential and predicting the future discharge under two scenarios SSP245 and SSP585. Budhi Gandaki River Basin (BGRB) was selected as a case study area to accomplish the objective of this study. The obtained NSE and VD values for the modelling period were 0.843 and -9.35% respectively while validation period, the values of NSE and VD were 0.86 and -7.45%. This indicates satisfactory model performance. This study identified 35 total hydro potential sites with total capacity of 6308MW at 40% flow exceedance. Furthermore, the results generated from the future prediction of discharge values and contribution of different components following two climatic scenarios, SSP245 and SSP585 for the period of 2020–2100 shows an average increase of simulated discharge by 8.88% and 42.6% respectively. This study can be demonstrated as empirical evidence for the application of the GDM for hydropower potential assessment. From high level perspective, this study contributes to manage water resources effectively and meeting the growing clean energy demand in an era of climate change.