Balsher S. Sidhu

Bio

I am a Senior Climate Researcher at Riskthinking.AI, where I lead and co-lead multiple projects related to financial risk from climate change across sectors such as agriculture, energy, real estate, insurance and finance, and government (municipal, state, and national levels). I also specialize in projects on climate solutions, including land-based carbon storage and other mitigation strategies.

Previously, I was a Postdoctoral Research Fellow at the Institute for Resources, Environment and Sustainability at The University of British Columbia Vancouver, where I also earned my PhD funded by the Government of Canada’s Vanier Canada Graduate Scholarship. My research focused on understanding the complex bi-directional relationships between land use systems and climatic change using advanced statistical and machine learning techniques.

I was a contributing author to the Water chapter in the Sixth IPCC Assessment Report (Working Group II) and consulted for the World Bank on the Atlas of Sustainable Development Goals 2020. I have published in high-impact academic journals on climate change and sustainable development. I have also been interviewed by print, television, and radio media for my expertise on these topics, and presented my work at multiple international conferences and invited lectures.

2-page Resume (updated Oct 2024)
Comprehensive CV (updated Oct 2024)
Google Scholar profile

Education

2021     Ph.D., Resources, Environment and Sustainability
             University of British Columbia, Vancouver, Canada
             Dissertation: Indian agriculture in a changing climate: A statistical analysis

2016     M.A.Sc., Civil Engineering
             University of Toronto, Toronto, Canada
             Dissertation: Pre-oxidation strategies for improvement of biofiltration performance

2013     B.Tech., Civil Engineering
             Indian Institute of Technology Delhi, New Delhi, India
             Dissertation: Performance evaluation of AERMOD and CALINE4 for air quality modelling

Contact

Email: balsher.sidhu@gmail.com
LinkedIn: Balsher Singh Sidhu

Research

Climate Risk Analysis and Financial Modeling

At Riskthinking.AI, I lead and co-lead projects focused on assessing financial risks associated with climate change. My work involves developing models that integrate climate data with financial metrics to help organizations understand and mitigate their climate-related financial exposure. This includes analyzing climate scenarios, assessing potential impacts on asset values, and providing actionable insights for resilient decision-making in the face of climate risks.

Reconciling Natural Climate Solutions with Clean Fuel Requirements for Achieving Net-Zero Emissions in Canada

To achieve Canada’s net-zero emissions target by 2050, natural climate solutions (NCS) like carbon storage in land ecosystems are vital. However, the transition to clean energy, especially in hard-to-decarbonize sectors, may compete with NCS for land and feedstock, leading to inflated emission reduction estimates. My postdoctoral research aimed to reconcile emission reductions from NCS with Canada’s clean fuel requirements through spatial analysis of data, including Canada’s Census of Agriculture and carbon accumulation maps.

Crop Yield Prediction Models: Decision Support Tools for Designing Climate-Resilient Agricultural Systems

In my doctoral research, I developed statistical models to predict crop yields in India up to 2100 under various emission scenarios. Someday, when I have spare time (you know, that mythical creature everyone talks about), I plan to extend that work into web-based decision support tools that facilitate both immediate crop yield forecasting based on current and forecasted weather, as well as long-term yield predictions considering climate change scenarios.

Selected Publications

Likely impacts of the 2022 heatwave on India's wheat production

Balsher Singh Sidhu

Environmental Research Letters, 18(2) 2023, 105001

Abstract (click to expand): The 2022 Indian heatwave impacted key geographies of wheat production in northwestern and central India. It coincided with this crop's harvest season in the region, and is expected to have considerably reduced national wheat production. Here we provide spatially disaggregated estimates of the likely impact on wheat yield using statistical relationships derived from historical climate and wheat yield data. Compared to a normal year (median of 1992–2021 climate), national wheat production in 2022 is expected to have fallen by 4.5%; some regions may have experienced wheat yield losses of up to 15%. Our analysis can also be analyzed as a proof of concept for using current and forecasted weather data to estimate real-time impact of short-term weather variability on end-of-season crop yields, even while the crop season is ongoing.

How can machine learning help in understanding the impact of climate change on crop yields?

Balsher Singh Sidhu, Zia Mehrabi, Navin Ramankutty and Milind Kandlikar

Environmental Research Letters, 18(2), 2023, 024008

Abstract (click to expand): Ordinary least squares linear regression (LR) has long been a popular choice among researchers interested in using historical data for estimating crop yield response to climate change. Today, the rapidly growing field of machine learning (ML) offers a wide range of advanced statistical tools that are increasingly being used for more accurate estimates of this relationship. This study compares LR to a popular ML technique called boosted regression trees (BRTs). We find that BRTs provide a significantly better prediction accuracy compared to various LR specifications, including those fitting quadratic and piece-wise linear functions. BRTs are also able to identify break points where the relationship between climate and yield undergoes significant shifts (for example, increasing yields with precipitation followed by a plateauing of the relationship beyond a certain point). Tests we performed with synthetically simulated climate and crop yield data showed that BRTs can automatically account for not only spatial variation in climate–yield relationships, but also interactions between different variables that affect crop yields. We then used both statistical techniques to estimate the influence of historical climate change on rice, wheat, and pearl millet in India. BRTs predicted a considerably smaller negative impact compared to LR. This may be an artifact of BRTs conflating time and climate variables, signaling a potential weakness of models with excessively flexible functional forms for inferring climate impacts on agriculture. Our findings thus suggest caution while interpreting the results from single-model analyses, especially in regions with highly varied climate and agricultural practices.

On the relative importance of climatic and non-climatic factors in crop yield models

Balsher Singh Sidhu, Zia Mehrabi, Milind Kandlikar and Navin Ramankutty

Climatic Change, 173(8), 2022, 1-21

Abstract (click to expand): Statistical crop models, using observational data, are widely used to analyze and predict the impact of climate change on crop yields. But choices in model building can drastically influence the outcomes. Using India as a case study, we built multiple crop models (rice, wheat, and pearl millet) with different climate variables: from the simplest ones containing just space and time dummy variables, to those with seasonal mean temperature and total precipitation, to highly complex ones that accounted for within-season climate variability. We observe minimal improvement in overall model performance with increasing model complexity using standard accuracy metrics like the root mean square error and adjusted R2, suggesting the simplest models, also the most parsimonious, are often the best. However, we find that simpler models, such as those including only seasonal climate variables, fail to fully capture impacts of climate change and extreme events as they can confound the influence of climate on crop yields with space and time. Automated model and variable selection based on parsimony principles can produce predictions that are not fit for purpose. Statistical models for estimating the impacts of climate change on crop yields should therefore be based on a conjunctive use of domain theory (for example plant physiology) with accuracy and performance metrics.

Chapter 4: Water. IPCC 6th Assessment Report (Working Group II).

Martina Caretta, Aditi Mukherji, ... Balsher Singh Sidhu, et al.

Climate Change 2022: Impacts, Adaptation and Vulnerability : Sixth Assessment Report of the IPCC (Working Group II Contribution), 2022, 551-712

Abstract (click to expand): Chapter 4 of the IPCC 6th Assessment Report (Working Group II) assesses current climate change impacts on the global water cycle, projected water-related risks for human and natural systems, and adaptation options and effectiveness.

A scoping review of research funding for small-scale farmers in water scarce regions

Vincent Ricciardi, Abdrahmane Wane, Balsher Singh Sidhu, et al.

Nature Sustainability, 3, 2020, 836-844

Abstract (click to expand): Water scarcity is a global issue that disproportionately affects small-scale farmers in low- and middle-income countries (LMICs). Through geospatial analysis, we estimated that less than 37% of small-scale farms probably have irrigation in water scarce regions across LMICs, compared with 42% of non-small-scale farms. Through a literature synthesis assisted by machine learning, we then systematically mapped the existing research for on-farm interventions that improve the incomes or yields of small-scale farmers in water scarce regions. We mapped over 888 on-farm interventions used to combat water scarcity from 560 publications and showed a research bias towards yields rather than livelihoods. We found gaps in evidence for many commonly proposed solutions, including livestock management, digital technology and solutions to protect natural resources at the farm-level, such as buffer strips. Our findings can be used to set a funding agenda for research on the geographies that are most at risk of water scarcity and the interventions that most lack evidence.

Power tariffs for groundwater irrigation in India: A comparative analysis of the environmental, equity, and economic tradeoffs

Balsher Singh Sidhu, Milind Kandlikar and Navin Ramankutty

World Development, 128(1), 2020, 104836

Abstract (click to expand): Groundwater irrigation using electric pumps plays a key role in India’s agricultural water supply. Power utilities across different states use two common tariff modes to charge groundwater consumers: flat tariffs, where payments are fixed according to a pump’s power rating, and metered tariffs based on units of power actually consumed. In this review, we use empirical evidence from past studies across multiple jurisdictions in India to compare the two tariff structures in terms of three key features: administrative burden on utilities; equity of groundwater access between high-income and low-income farmers; and influence on farmers’ pumping behavior. Our analysis shows that flat tariffs have low administrative costs and more equitable distributional outcomes, but provide no incentive to farmers for water conservation. Conversely, metered tariffs have the potential to encourage judicious consumption, but are expensive to manage and disadvantageous to low-income farmers who often buy water from wealthier groundwater well owners. Flawed tariff policies, in conjunction with large subsidies for agricultural power, have caused rapid groundwater depletion in many regions as well as massive financial losses to power utilities and governments – both state and central. Since there is considerable heterogeneity in agricultural practices and groundwater availability across India, we propose location-specific strategies for rationalizing agricultural power tariffs in different regions. While the groundwater-abundant eastern regions can benefit from a hybrid flat-cum-metered tariff that encourages farmer-to-farmer water sales, western states facing unsustainable groundwater exploitation should develop tariff policies that ration power, prioritize its supply during the most critical seasons, and reward farmers who reduce their groundwater consumption. Not only will such tariff policies help conserve groundwater, but also augment government financial resources for social welfare programs such as education, health, energy access etc. Thus, improved power policies can provide substantial assistance in India’s progress towards multiple UN Sustainable Development Goals.

Talks and Presentations

Invited talks

• Using statistical models for predicting future crop yields. Washington State University, USA. 01 Mar 2023.

• What can statistical models tell us about future crop yields? Achieving the Sustainable Development Goals in Theory and Practice. University of Delaware, USA. 07 Oct 2022.

• Making Indian agriculture resilient to climate change. Early Career Researchers Talk Series. International Water Management Institute, India. 19 Sep 2022.

• Impact of climate variability on crop yields in India. Science and Technology for the New Age: Acquisition, Analyses and Adaptation. University of Alberta, Canada. 04 Mar 2021.

• Sensitivity of crop yields to climate variability. Food Seminar Series. University of Sussex, UK. 03 Mar 2021.

Conference presentations

• Sidhu BS, Kodamana R, Hall S, Soman R, Langotsky K, Wiebe A, Dembo R (2024). Development of a forest-buffer based Fire Weather Index metric for global wildfire risk assessment. Accepted for presentation at AGU Fall Meeting 2024.

• Sidhu BS, Soman R, Hall S, Kodamana R, Langotsky K, Wiebe A, Dembo R (2024). Stochastic modelling of future cyclone risk: insights from high-resolution simulations of recent category-5 events in Mexico and Grenada. Accepted for presentation at AGU Fall Meeting 2024.

• Kodamana R, Hall S, Langotsky K, Soman R, Sidhu BS, Wiebe A, Dembo R (2024). Assessing climate risk to investment portfolios using Monte Carlo simulations for global risk aggregation from assets. Accepted for presentation at AGU Fall Meeting 2024.

• Wiebe A, Sidhu BS, Kodamana R, Dembo R, Wu, S, Hall S, Kurkute S (2023). Accounting for contemporary extreme weather phenomena during downscaling and bias correction of climate data: a comparative analysis of the CMIP6 Global Climate Models. AGU Fall Meeting 2023. Virtual.

• Sidhu BS (2023). Including the impact of prevailing weather patterns in end-of-season crop yield forecasts: a case study of Indian wheat and the 2022 heatwave. 5th Canadian Wheat Symposium. University of British Columbia, Vancouver, Canada.

• Sidhu BS, Kandlikar M, Ramankutty N (2021). Indian agriculture in a changing climate: Using CMIP6 projections for predicting yields of multiple crops to 2100. AGU Fall Meeting 2021. Virtual.

• Sidhu BS, Mehrabi Z, Kandlikar M, Ramankutty N (2020). Machine learning methods for estimating the impact of climate change on Indian crop yields. AGU Fall Meeting 2020. Virtual.

• Sidhu BS, Kandlikar M, Ramankutty N (2019). Sub-seasonal monsoon variability as a driver of crop yields in India. Water Future Conference. Indian Institute of Science, Bangalore, India.

• Sidhu BS, Kandlikar M, Ramankutty N (2019). Power tariffs for groundwater irrigation in India: A comparative analysis of the environmental, equity, and economic tradeoffs. Water Future Conference. Indian Institute of Science, Bangalore, India.

• Sidhu BS, Mehrabi Z, Kandlikar M, Ramankutty N (2019). Assessing the resilience of Indian agriculture to monsoon variability. Global Land Project. University of Bern, Bern, Switzerland.

• Sidhu BS, Kandlikar M, Ramankutty N (2018). Restructuring agricultural power tariffs in India to meet multiple Sustainable Developments Goals. Sustainability and Development Conference 2018. University of Michigan, Ann Arbor, United States.

• Sidhu BS, Kandlikar M, Ramankutty N (2018). Optimized agricultural power tariffs as a means of achieving Sustainable Developments Goals in India. International Conference on Engaging Canada and India: Challenges of Sustainable Development Goals. New Delhi, India.

• Sidhu BS, Taylor-Edmonds L, McKie MJ, Andrews RC (2016). Combining biofiltration with pre-oxidation for improved removal of organic matter. Water Quality Technology Conference and Exposition. Indianapolis, United States.

• Sidhu BS, Taylor-Edmonds L, Andrews RC (2016). Pre-oxidation strategies for biofiltration performance improvement. Canadian National Conference on Drinking Water. Ottawa, Canada.

• Sidhu BS, Nemani V, Ondul B, Sharma D, Wong K (2016). In-pipe hydroelectricity generation from wastewater flow. Cities of Tomorrow Showcase. Toronto, Canada.

• Sidhu BS, Sharma, D, Tuteja, T, Gupta, S, Kumar, A (2013). Human health risk assessment of heavy metals from Bhalaswa landfill. International Humboldt Kolleg on Management of Water, Energy and Bio-resources in Changing Climate Regime. New Delhi, India.

• Sidhu BS, Pandit A, Kumar A (2012). Titanium dioxide nanoparticles removal from water. 6th World Aqua Congress. New Delhi, India.

Teaching

Course Instructor

2022, 2023     Analytical Methods in Sustainability Science (ENVR 440), University of British Columbia
96% “favorable” score (students who “Agreed” / “Strongly Agreed”) for facilitating overall learning
Letter of commendation from Dean (Sciences) for some of the highest student evaluations
2018, 2019       Climate Change & Energy Futures (IRES VSP), UBC Vancouver Summer Program

Teaching Assistant

2019                  Introduction to Sustainability (ASIC 220), University of British Columbia
2017                  Analytical Methods in Sustainability Science (ENVR 440), University of British Columbia
2017                  Sustainable Energy: Policy and Governance (CONS 425), University of British Columbia
2014 - 2015      Water and Wastewater Treatment Processes, University of Toronto
2014 - 2015      Environmental Impact and Risk Assessment (CIV 440), University of Toronto
2013                  Urban Engineering Ecology (CIV 220), University of Toronto
2013                  Introduction to Environmental Engineering (CEL 212), IIT Delhi
2012                  Indian economic problems and policies (HUL 216), IIT Delhi

Other Teaching Activities and Skills Development

2018 - 2019      Course Development: Developed data-driven, interdisciplinary case study modules for
                           teaching sustainability analysis across multiple courses, University of British Columbia
2018 -                Guest Lectures on sustainability and climate change for UBC’s First-Year Seminars,
                           Extended Learning program, Climate Teaching Connector, and Science 101 course.
2017                  Course Instructor Certificate, Instructional Skills Workshop, University of British Columbia
2017                  Associate, Centre for the Integration of Research, Teaching and Learning (NSF)

Scholarships and Awards

Scholarships

2018 - 2021      Vanier Canada Graduate Scholarship, NSERC Canada
2016 - 2020      Four Year Doctoral Fellowship, University of British Columbia
2016                  Olav Slaymaker Scholarship for Environment, University of British Columbia
2013 - 2015      Graduate Student Fellowship, University of Toronto
2013 - 2016      Graduate Research Assistant Scholarship, University of Toronto
2011 - 2012      Scholarship for Academic Excellence, IIT Delhi
2006 - 2013      National Talent Search Examination Scholarship, Government of India

Awards

2018                  Graduate Student Travel Award, University of British Columbia
2016                  RES Student Travel Award, University of British Columbia
2016 - 2021      International Tuition Award, University of British Columbia
2016                  Faculty of Science Graduate Award, University of British Columbia
2016                  Winner, Cities of Tomorrow competition, Ontario Urban Mayors’ Caucus
2011                  Summer Undergraduate Research Award, IIT Delhi
2007                  Third Rank, National Frank Anthony Memorial Debate

Public Outreach

Are we running out of clean water?
I collaborated with TED-Ed to produce a short lesson, accessible to a wider global audience, on the world’s water consumption patterns and the role citizens can play in ensuring sustainable consumption of this precious resource.

The Colours of Food Security
An exhibit by the Land Use and Global Environment lab at UBC Vancouver to showcase a series of bold and striking maps that present a vivid picture of global agriculture and key issues surrounding our food systems by viewing them from multiple angles.

The Nature of Food
A collaborative blog project of the Land Use and Global Environment lab on everything related to agriculture, food security, environment, and academia in general.

Articles in newspapers and magazines

• Half the world is facing water scarcity, floods and dirty water - large investments are needed for effective solutions. The Conversation. 28 Feb 2022.
• Farm reform needed for sustainability, but government’s three acts won’t deliver it. The India Cable. 12 Mar 2021.
• Groundwater depletion in Punjab: Time for a major policy overhaul. Thrive, CGIAR Research Program on Water, Land and Ecosystems. 5 Jun 2020.
• Don’t demonise farmers. The Tribune. 18 Nov 2019.

Past Shenanigans

Before starting my research journey on land use and climate change in 2016, I was trained as an engineer. My undergraduate and master’s degrees in Civil Engineering gave me the opportunity to dabble with multiple research topics, including earthquake-resistant buildings, risk assessment of heavy metals in groundwater, removal of titanium dioxide nanoparticles from water, air pollution modelling using AERMOD and CALINE 4, and advanced drinking water treatment processes.

But I always wanted to work in the field of agriculture and sustainability. This desire probably stems from the fact that I grew up in Punjab (India), a state in north-western India. This region was home to the Green Revolution in the 1960s, and is often called the breadbasket of India. But rapid increase in food production came at a huge cost to our water resources.

Punjab derives its name from the Persian words panj (five) and āb (water), meaning the “land of five rivers”. But today my state has gained notoriety for its rapidly depleting groundwater levels. The most recent government report notes that groundwater extraction in Punjab has already reached 165% (of naturally available recharge), and the state has maximum percentage of wells showing groundwater depletion among all states in India. My article on the causes and potential solutions for this problem can be found here.

Here is a photo of a groundwater extraction well, 1.5 million of which dot Punjab’s landscape today. Many eventually run dry, including the one on my grandfather’s farm. Having seen the undesirable outcomes of unsustainable farming practices at close quarters, I want to contribute towards making our agricultural and land use systems more sustainable and climate-resilient. It seems to be my Ikigai.

The code for this website was re-purposed from Gautam Rao’s public Github repository.