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title NISCHAL KAFLE

👨‍🎓 Ph.D. Candidate | 🌧️ Hydrologist | 🧠 Extreme Value Analyst

🐍 Pythonista
📍 University of Memphis | 🌐 From the high mountains of Nepal
📫 nkafle@memphis.edu | nkafle.29@gmail.com
🌍 Google Scholar
🔗 LinkedIn

About Me

I am a Ph.D. candidate in Civil Engineering at the University of Memphis, specializing in stochastic hydrology, meteorology, and engineering designs. My PhD research aims to enhance the understanding and modeling of extreme rainfall, particularly short-duration for urban infrastructure design, climate resilience and flood risk management.

"Science, to me, is a process of decoding the unseen, especially where water and uncertainty meet." – Nischal Kafle

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🧪 Current Work & Research Highlights

  • 📦 nsEVDx – Open-source Python package for modeling non-stationary extreme value distributions

  • 📊 Trend detection in extreme rainfall using Bayesian and frequentist approach

  • 🌦️ Integrating Remote Sensing and Transformers for drought and flood prediction

  • 🔍 Neighborhood-based Trend Detection
    A novel spatial method to detect nonstationarity in rainfall extremes (Submitted)

  • 📈 Effect of Minimum Interevent Time (MIT)
    Evaluating how MIT choices impact regional DDF curves (Submitted)

  • 🎯 Extracting Spatially Independent Regional Partial Duration Series
    Using radar and storm motion to extract independent rainfall extremes (AGU 2024, manuscript in prep)

  • ⛅ Rainfall Disaggregation with Transformers
    Disaggregating daily rainfall to sub-daily (n-minute) using deep learning (In preparation)

  • 🛰️ Impact of Spatio-temporal Resolution of Rain Gauge Network in Regional DDF Values
    Studying how spatial/temporal gauge density influences DDF estimation (AGU & ASCE-EWRI 2024)

  • 🏙️ Urban Flood Modeling
    Simulated flood events in South Memphis, a historically underserved community, using the 2018 Germantown storm in PCSWMM; created flood inundation maps & animations for city planning use

    Participated in 3 community meetings, informing over 120 residents about localized flood risks and preparedness strategies, contributing to more informed local planning discussions

  • 📉 Bias Correction & Downscaling of GCMs
    Compared statistical methods in Chilean basins under climate change scenarios

  • 🌱 Green Infrastructure Siting with ML
    Applied machine learning to locate optimal GSI sites using hydrologic connectivity metrics

Professional Experience

Gazetted Officer – Water Resources Engineer

Ministry of Irrigation, Department of Irrigation, Nepal | Aug 2015 – Aug 2021

  • Managed technical operations for 150+ irrigation and disaster mitigation projects, engaging local farmers for active participation
  • Led environmental impact assessments, hazard mapping, and community training programs
  • Collaborated with international partners (ADB, World Bank) to develop water resource policies and procurement guidelines for 7 irrigation projects - Conducted groundwater research for a federal projects in Lumbini Province

Consulting Engineer, Project Manager & GIS Expert

Bright Future International Pvt. Ltd. | Dec 2014 – Jul 2015

  • Developed transportation master plans for 5 rural municipalities in Nepal’s hilly regions
  • Facilitated ward committee meetings to incorporate local feedback into planning

CV

📄 my CV (link to your CV file or page)
🌐 Personal Website
💬 Open to research and collaboration opportunities

📚 References

  • are available inside the CV