Doctor Shiva Khanal


Graduated PhD 2023

Thesis Title

Objective quantification of Nepal’s forest carbon stocks in support of the REDD+ Programme: a methodological study combining remote sensing, forest inventory data and statistical modelling

Research Project

Deforestation and forest degradation cause carbon emissions while sustainable management of forests can increase carbon sequestration. The Reducing Emissions from Deforestation and Forest Degradation (REDD+) scheme was proposed as a cost-effective approach for developing countries to reduce carbon emissions through a financial incentive mechanism. A reference level (expressed as tonnes of CO2 equivalent per year for a reference period) provides a benchmark to evaluate future emission pathways for countries. Transparent, rigorous, and scientifically sound methods are required to establish forest reference levels and measurement, and a reporting and verification (MRV) system for monitoring changes in carbon stocks. Accurate monitoring of forest carbon stocks is a fundamental requirement for REDD+ but has been a critical challenge for many REDD+ countries.

Using Nepal as a case study, I aim to improve the estimates of national forest carbon stocks by modelling spatiotemporal variation in forest carbon and its drivers. I will be using field datasets collected as part of the national forest resource assessment of Nepal. The general approach for the study involves integration of field observation with spatial datasets such as satellite images, terrain and gridded climate data using models.

Species composition, human intervention/disturbance, topography and climate are recognized as the major drivers of the magnitude, spatial distribution, and uncertainty in estimates of forest carbon stocks.  I aim to understand how these sources of uncertainty can be minimized to improve the quantification of national scale forest carbon stocks.  Integrated understanding of forest carbon dynamics requires consideration of key carbon pools.  As compared to forest above ground biomass (AGB), the soil organic carbon (SOC) pool is often ignored in reporting.  I aim to provide the most accurate estimate of national forest SOC stocks and examine the environmental controls through spatially-explicit prediction of SOC using field sample of SOC stocks and environmental co-variables.  The research outputs will help better understand the variability in forest carbon in general and, importantly, be directly relevant to supporting improvements in forest carbon monitoring approaches for REDD+ countries.

Bushfire Research

Our research also includes the role of fire and its effects on global change. Please see here (opens in a new window) for further details on our bushfire research.


Khanal S, Nolan RH, Medlyn BE, Boer MM, (2023) 'Mapping soil organic carbon stocks in Nepal's forests', Scientific reports, vol.13, no.1, p 8090

Clarke H, Nolan RH, De Dios VR, Bradstock R, Griebel A, Khanal S, Boer MM, (2022) 'Forest fire threatens global carbon sinks and population centres under rising atmospheric water demand', Nature Communications, vol.13, no.1, Article no.7161


Professor Matthias Boer, Professor Belinda Medlyn, Dr Rachael Nolan


Graduated Research Masters (Honours) 2015

Thesis Title

Quantifying post-fire recovery of forest canopy structure and its environmental drivers using satellite image time-series.

Research Project

Improving our understanding of the carbon cycle and its spatiotemporal variability is a major priority for environmental research and policy making. Accurate estimates of how much CO2 ecosystems can absorb are crucial for reliable projections of atmospheric CO2, future climate conditions, ecosystem services and economic viability of international carbon accounting schemes. Disturbances such as drought and fire directly influence the productive capacity of ecosystems. Changes in the frequency, intensity and duration of warm/dry weather conditions may affect fire regimes of forest ecosystems with potentially large impacts for the global carbon cycle. Post-fire recovery of ecosystem productivity depends on the intensity of disturbance, site conditions as well as environmental factors. This makes understanding of magnitude and pattern of productivity recovery very important for quantifying carbon sequestration and potential effect on climate change. In this study I aim to calibrate satellite based estimates of carbon uptake with continuous observations at several flux towers to characterise and understand the spatiotemporal dynamics of the post-fire recovery process in SE Australian forests burnt by major bushfires. I will be estimating forest canopy and carbon dynamics using MODIS images. The findings from this study will help quantify the regional forest carbon canopy and carbon dynamics.

Research Project Supervisors

Dr Matthias Boer and Dr Remko Duursma

View the Thesis

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