Toggle Main Menu Toggle Search

Open Access padlockePrints

Model-based estimation of land subsidence in Kathmandu Valley, Nepal

Lookup NU author(s): Dr Stephen Birkinshaw



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


© 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This study is the first to assess land subsidence in the Kathmandu Valley, Nepal. Land subsidence simulations were based on a fully calibrated groundwater (GW) flow model developed using a coupled surface–subsurface modelling system. Subsidence is predicted to occur as a result of deep aquifer compaction due to excessive GW abstraction. The north and north-east areas at the periphery of the GW basin are hotspots for this subsidence. The estimated subsidence is most sensitive to changes in land cover within the recharge areas. The model shows the Melamchi water supply project assists in the control of subsidence to some extent. In the absence of land subsidence measurements, this paper highlights the location and the potential levels of the subsidence hazard which will be useful for hazard prevention management. Additionally, this work provides a basis to design field investigations, monitoring networks for land subsidence and upgrading the present GW monitoring network. Although the study has presented a preliminary analysis, a more comprehensive model inclusive of clay subsidence is required to address the subsidence vulnerability of the central densely populated core of the valley, which reflects the need for a comprehensive database of the hydrogeology in the valley.

Publication metadata

Author(s): Shrestha PK, Shakya NM, Pandey VP, Birkinshaw SJ, Shrestha S

Publication type: Article

Publication status: Published

Journal: Geomatics, Natural Hazards and Risk

Year: 2017

Volume: 8

Issue: 2

Pages: 974-996

Online publication date: 23/02/2017

Acceptance date: 30/01/2017

Date deposited: 03/05/2017

ISSN (print): 1947-5705

ISSN (electronic): 1947-5713

Publisher: Taylor and Francis


DOI: 10.1080/19475705.2017.1289985


Altmetrics provided by Altmetric