Pallav Kumar SHRESTHA

PhD Researcher

Department Computational Hydrosystems (CHS)
Helmholtz Centre for Environmental Research - UFZ
Permoserstraße 15, 04318 Leipzig, Germany
Phone: +49 341 235 1784

Pallav Kumar Shrestha

PhD Research Theme

My PhD aims to contribute towards locally relevant flood forecasting in managed river basins, at global scale. The first chapter of my PhD is an application paper (published in Nature Communications) where we developed and tested a high-resolution (1 km) flood early warning system, FEWS, with mHM, on a real flood event (The 2021 summer flood in Germany), retrospectively. This proof of concept produced impact forecast as well as early notice time till 100 years return period water level at each model grid.

Integrating such local level FEWS in regional/continental domains in global scale poses challenges. Gridded hydrological models, such as mHM, incur simulation errors at local level using the existing (classic or state-of-the-art) stream network upscaling methods. While hyperresolution modeling theoretically addresses this issue, its high computational cost bars its use in large-scale modeling, prompting the search for alternatives. In the second chapter of my PhD (submission preparation), we augment global hydrological models with the missing "eagle vision". We achieve this by developing a new stream network upscaling technique called subgrid catchment conservation. SCC offers three distinct advantages: 1) generates locally relevant streamflow i.e., ensures consistency of streamflow performance across catchment sizes (1 km2 to 4,680,000 km2), 2) improves consistency of streamflow across model resolution, and 3) resolves multiple gauges within a grid.

Reservoirs stand as the bastions of humanity's defence against floods. Preparing FEWS for managed basins in large-scale modeling was another challenge we tackled in the final chapter of my PhD. We developed a new reservoir module for mHM (published in WRR), an improvement over the state-of-the-art representation in large-scale modeling. The research delves into three key aspects: 1) employing machine learning methods to reverse estimate non-consumptive demands (e.g., hydropower), 2) sensitivity of simulations to reservoir bathymetry, and 3) possible thresholds to identify and exclude non-disruptive reservoirs from the model simulation.

Scientific Career

10/2017 - till date

PhD researcher
Department of Computational Hydrosystems (CHS) at UFZ, Leipzig, Germany

05/2014 - 10/2017

Water Resources Specialist and Programmer
Water Engineering and Management Program, Asian Institute of Technology (AIT), Thailand

09/2013 - 05/2014
11/2011 - 11/2013

 2011 - 2013

Research Associate
Nepal Development and Research Institute, Kathmandu, Nepal

Kathamandu Engineering College, Tribhuvan University, Nepal

M.Sc. Water Resources Engineering
Institute of Engineering, Tribhuvan University, Nepal

Publications and Software

  • Shrestha PK, Samaniego L, Rakovec O, Kumar R, Mi C, Rinke K, and Thober S (2024). Towards improved simulations of disruptive reservoirs in global hydrological modelling. Water Resources Research.
  • Najafi H, Shrestha PK, Rakovec O, Apfel H, Vorogushyn S, Thober S, Kumar R, Merz B, and Samaniego L (2024). Advancing a High-Resolution Impact-based Early Warning System for Riverine Flooding. Nature Communications.
  • Ogbu KN, Rakovec O, Shrestha PK, Samaniego L, Tischbein B, and Meresa H (2022). Testing the mHM-MPR Reliability for Parameter Transferability across Locations in North–Central Nigeria. Hydrology.
  • Bhatta B, Shrestha S, Shrestha PK and Talchabhadel R (2020). Modelling the impact of past and future climate scenarios on streamflow in a highly mountainous watershed: A case study in the West Seti River Basin, Nepal. Science of the Total Environment.
  • Mtilatila L, Bronstert A, Shrestha PK, Kadewere P and Vormoor K (2020). Susceptibility of Water Resources and Hydropower Production to Climate Change in the Tropics: The Case of Lake Malawi and Shire River Basins, SE Africa. Hydrology.
  • Shrestha M, Shrestha S and Shrestha PK (2019). Evaluation of landuse change and its impact on water yield in Songkhram River Basin, Thailand. International Journal of River Basin Management.
  • Shrestha PK, Shrestha S and Ninsawat S (2018). How significant is sub‐daily variability of rainfall for hydrological modeling of floods? – A satellite based approach to sub‐daily downscaling of gauged rainfall. Meteorological Applications.
  • Shrestha S, Hoang N, Shrestha, PK and Bhatta B (2018). Climate change impact on groundwater recharge and suggested adaptation strategies for selected Asian cities. APN Science Bulletin, 8(1). https://doi:10.30852/sb.2018.499
  • Shrestha S, Bhatta B, Shrestha M and Shrestha PK (2018). Integrated assessment of the climate and landuse change impact on hydrology and water quality in the Songkhram River Basin, Thailand. Science of the Total Environment.
  • Shrestha S, Shrestha M and Shrestha PK (2017). Evaluation of SWAT models performance to simulate river discharge in Himalayan and tropical basins of Asia. Hydrology Research.

Conference Presentations

  • Shrestha PK, Thober S, Rakovec O, Najafi H, Lorenz C, Samaniego L. Impartially resolving reservoirs of all sizes for seamless hydrological forecasting using multiscale Lake Module (mLM). American Geophysical Union General Assembly (AGU). 7 -- 14 Dec 2020, Online. AGU abstract book -
  • Shrestha PK, Samaniego L, Rakovec O, Kumar R, Júnior FV, Martins E, and Thober S. Comprehensible modeling of reservoir regulation effect on streamflow with a scalable lake-hydrology model. American Geophysical Union General Assembly (AGU). 9 -– 13 Dec 2019, San Francisco. AGU abstract book -
  • Shrestha PK, Samaniego L, Thober S, Lorenz C, Behnia S, Portele TC, Laux P, Kumar R and Rakovec O. Towards Scale Independent Lake/Dam-hydrology Mod-elling in Seasonal Forecasting of Semi-arid Regions. International Union of Geodesy and Geophysics (IUGG) General Assembly. 8 - 18 Jul 2019, Montreal. IUGG abstract book -
  • Shrestha PK, Shrestha S and Ninsawat S. Satellite based sub-daily downscaling of gauged rainfall for flood analysis via fully distributed hydrological model. THA2017 International Conference on Water Management and Climate Change towards Asias Water-Energy-Food Nexus. 25 - 27 Jan 2017, Bangkok.
  • Shrestha PK, Shrestha S and Ninsawat S. Diurnal disaggregation of precipitation measurements with TRMM how good of an alternative is it to subdaily observations for distributed hydrological modeling? 1st Symposium on Tonle Sap Water Environment. 26 – 27 August, 2016. Phnom Penh, Cambodia.
  • Shrestha PK, Shakya NM, Pandey VP, Birkinshaw SJ and Shrestha S. Model Based Land Subsidence in Kathmandu Valley, Nepal. International Conference on Resilience of Groundwater Systems to Climate Change and Human Development 8-11 February, 2016. Bangkok.
  • Shrestha PK and Shrestha S. Multivariate Evaluation of a physically based Distributed Hydrological Model in Snow-fed River Basins of in Hindu Kush Himalaya Region. 2nd International Young Researchers Workshop on River Basin Environment and Management. 5 – 6 January, 2015, Hanoi.
  • Shrestha D, Gyawali D, Basnyat DB and Shrestha PK. Bias Correction of Climate Change Projections on Koshi Basin. International conference on Climate Change, Water Resources and Disasters in Mountainous Regions: Building Resilience to Changing Climate. 27 – 29 Nov, 2013, Nepal.
  • Shrestha PK, Shakya NM, Pandey VP, and Birkinshaw SJ. Distributed groundwater modeling for analysis of landslide hazard. 4th National Symposium on Challenges and opportunities for Sustainable Management of Groundwater Resources of Kathmandu Valley, Nepal, 22 st Mar, 2013, Nepal.