Open AccessDEVELOPMENT OF A SEMI-DISTRIBUTED HYDROLOGICAL MODEL FOR GLACIATED PUNATSHANGCHU BASIN IN BHUTAN
Author(s) -
Vasker Sharma,
Jessica Jorden,
Pedro Manso,
Giovanni De Cesare
Publication year - 2021
Publication title -
journal of applied engineering, technology and management
Language(s) - English
Resource type - Journals
eISSN - 2789-0848
pISSN - 2707-4978
DOI - 10.54417/jaetm.v1i1.19
Subject(s) - hydropower , flood myth , structural basin , environmental science , water resource management , hydrology (agriculture) , drainage basin , sustainability , resource (disambiguation) , glacier , water resources , environmental resource management , geology , physical geography , geography , computer science , geomorphology , engineering , ecology , cartography , computer network , geotechnical engineering , archaeology , electrical engineering , biology
Hydropower plays a pivotal role in the socio-economic development of Bhutan where water resource is abundantly available and therefore several hydropower plants are being planned and a few under construction. However, with the presence of several potentially dangerous glacier lakes within the higher elevations, the country is always at the risk of Glacial Lake Outburst Flood (GLOF) and climate change which poses higher uncertainty regarding the sustainability of hydropower reservoirs in the long run. To understand the hydrological response of the basin, where new hydropower plants are going to be installed soon, a complex semi-distributed hydrological model has been prepared for the Punatshangchu basin using RS MINERVE. After calibration and validation of the model, it is observed that the model reflects low relative volume bias (-0.196 - 0.050) and high Nash efficiency (0.540 - 0.990) which is an important aspect to be considered for any hydropower dam and its operational schemes. Such a model is a viable tool well adapted to an operational flood forecasting system and management. With the built-in scheme for hydropower, reservoir, planner, and turbines within RS Minerve, it could be used to understand the array of scenarios for planning and operations.