Climate Change and Impacts

Climate Change is a urgent global challenge, and our researchers are dedicated to understanding its intricate dynamics and assessing its impacts on ecosystems, communities, and the planet as a whole. Through innovative studies and advanced modeling techniques, our goal is to provide insights into changing climate patterns and develop strategies to mitigate its adverse effects.

Study 1:

  • The study compares an artificial neural network (ANN) and a regression-based statistical downscaling model (SDSM) in Colombo, Sri Lanka. ANN excels in downsizing precipitation, showing lower biases and RMSE than SDSM.
  • The research combines SDSM with ANN for better results. Future RCP 8.5 projections foresee temperature increases of 2.83 °C (SDSM) and 3.03 °C (TDNN), and rainfall rises of 33% (SDSM) and 63% (TDNN) by the 2080s.

Study 2:

  • This study assesses climate change's effect on rainfed rice yield in Northeast Thailand, employing the CERES-rice growth model. Future scenarios foresee substantial yield declines under the ECHAM4 A2 climate scenario, ranging from 17.81% to 27.59% versus the 1997-2006 average yield.
  • To counteract these effects, the study suggests agro-adaptation measures like nutrient management, adjusted planting dates, and the use of high-temperature-tolerant hybrid rice cultivars.

Study 3:

  • This study investigates the potential impact of global climate change on rice production in northeastern Thailand, an area already grappling with floods, droughts, and poor soil quality. Various rice varieties demonstrate diverse responses across different soil types, with most varieties showing a declining yield trend for 2050-2059 and 2090-2099.
  • The Chang rice variety emerges as a promising choice to sustain yields under forthcoming climatic conditions. Notably, the study underscores the considerable influence of factors like area, solar radiation, and temperature on rice production, with increased radiation and temperature resulting in reduced yields.

Study 4:

  • This study uses detailed GCM precipitation data to examine climate change's impact on the upper Bagmati river basin, focusing on precipitation patterns. Comparing observed and GCM data reveals the need for downscaling and bias correction, especially for precipitation frequency and intensity.
  • The findings indicate a significant increase in annual precipitation in the future, particularly during the monsoon season, while other months experience decreases. The study also emphasizes more frequent heavy precipitation events, which could affect water supply, agriculture, and flood management in the region.

 Study 5:

  • This study assesses the potential consequences of climate change on severe flooding in flood-prone Colombo, Sri Lanka, situated in the Kelani River's floodplains.

  • Future climate scenarios for the Kelani basin are examined via Global Circulation Model (GCM) data to predict extreme rainfall scenarios and their impact on Colombo's flooding.
  • Modeling techniques are employed to simulate flood inundations, offering insights into the extent and consequences of flooding. The study also highlights adaptation strategies to mitigate Colombo's flood-related challenges.

Study 6:

  • Study proposes enhancing rice production in non-waterstressed Asian regions during wet seasons using appropriate medium or long-duration rice varieties and efficient nutrient management.
  • Researchers employed the ORYZA 1N crop growth simulation model to select rice varieties and optimize nitrogen usage.
  • The model accurately predicted grain yield, biomass, and leaf area index for medium and long-duration varieties during the 2000 wet season.
  • Recommendation for farmers in favorable lowland areas without water stress is the "Ranjit" rice variety with 80 kg N per hectare in four equal applications.
  • Technology verification trials demonstrated improved rice yield compared to traditional practices.

Study 7:

  • Study focuses on calibrating CERES-Rice model using real data for IR 36 rice in Cuttack, Orissa.
  • Model accurately predicts growth events and yield with different nitrogen levels.
  • Impact of Atmospheric Brown Clouds on solar radiation stress examined using historical weather data.
  • 30% less solar radiation leads to 4% yield drop in non-fertilized conditions.
  • High nitrogen (120 kg N/ha) worsens radiation stress impact, causing up to 12% yield reduction due to decreased grain formation.
  • Emphasizes need to manage solar radiation stress and nitrogen levels for better rice production in similar settings.

Study 8:

  • Rainfall during inter-monsoon period (Feb-Apr) in Sri Lanka has consistently decreased since the early 1970s.
  • Herath and Ratnayake (2003) analyzed rainfall patterns using data from 62 rain gauges in the central region from 1963 to 1993.
  • The analysis showed a decreasing trend in rainfall for the first inter-monsoon season (Mar-Apr) across all gauges.
  • Farmers and residents in the region have reported changes in weather patterns over the past 30 years.
  • The decrease in rainfall may be linked to the Atmospheric Brown Cloud, caused by high aerosol concentrations in the atmosphere.

Study 9: 

  • IPCC aids in climate change mitigation and adaptation since the 1980s.
  • Water experts develop systems for changing weather patterns and water issues due to climate change.
  • Global warming impacts temperature, evaporation, and precipitation.
  • Changes in precipitation affect floods, droughts, and water resources.
  • Asian Brown Cloud affects rainfall, temperature, and solar radiation.
  • Understanding climate change's link to sustainable development is crucial.
  • Conference by UN University and Sri Lanka examined climate change's impact on water resources.
  • Aims to offer insights through workshops.