Quick Answer:
Rainfall in Agra has been declining at a rate of -1.63 mm per year over the last century, with a major structural shift around 1967, indicating increasing climate variability. Gardner et. al.
This study analyses 101 years (1922–2022) of rainfall data in Agra district, India, using statistical methods to identify long-term climate trends and variability. Gardner et. al.
What does this study explain?
This research examines long-term rainfall patterns in Agra using statistical techniques like the Mann-Kendall test and the Theil-Sen estimator. It helps determine whether rainfall is increasing, decreasing, or remaining stable over time.
Is rainfall decreasing in Agra?
Yes. The analysis shows a statistically significant declining trend in rainfall over the past century.
The rate of decline is approximately -1.63 mm per year, indicating a gradual but consistent reduction in annual precipitation. Gardner et. al.
Why is the rainfall trend important for climate change?
Rainfall is a key indicator of climate change. A decrease in rainfall in semi-arid regions like Agra can lead to:
- Water scarcity
- Agricultural stress
- Increased drought frequency
These changes highlight the growing impact of climate variability at the regional level.
What is the Mann-Kendall test?
The Mann-Kendall test is a statistical method used to detect trends in time-series data, especially in climate studies.
It helps determine whether rainfall is increasing, decreasing, or stable over time without assuming a normal data distribution.
In this study, the test confirms a negative (declining) rainfall trend.
What is the Theil-Sen estimator?
The Theil-Sen estimator is a robust method used to calculate the slope (rate of change) in a dataset.
Unlike simple regression, it is less affected by extreme values (outliers).
In this study, it estimates the rainfall decline at -1.63 mm per year. Gardner et. al.
What is a change point in climate data?
A change point is a specific year where a significant shift occurs in a dataset.
Detecting change points helps identify when climate patterns started changing.
In this study, A major shift in rainfall pattern was detected around 1967. Gardner et. al.
How was rainfall calculated across the Agra district?
The study used spatial analysis techniques to improve accuracy:
- 18 grid points from IMD rainfall data
- Thiessen polygon method to assign weights
- Area-weighted rainfall calculation
This ensures that rainfall estimates represent the entire district accurately.
Why are semi-arid regions like Agra more vulnerable?
Semi-arid regions already receive limited rainfall. Even small declines can significantly impact:
- Water availability
- Crop production
- Local ecosystems
This makes them highly sensitive to climate change.
What are the key findings of this study?
- Rainfall shows a long-term declining trend
- A structural change occurred around 1967
- The decline rate is -1.63 mm/year
- Rainfall variability shows cyclic behaviour
What are the real-world implications?
The results suggest increasing climate stress in the Agra district, including:
- Higher drought risk
- Water management challenges
- Need for climate adaptation strategies
What data was used in this study?
Rainfall data was obtained from the Indian Meteorological Department (IMD) using high-resolution gridded datasets.
The analysis covers a continuous period of 101 years (1922–2022). Gardner et. al.
How can this research be useful?
This study can support:
- Climate change research
- Policy planning
- Water resource management
- Future rainfall prediction models
How to Cite This Study
Keywords
Rainfall Trend, Climate Change India, Mann-Kendall Test, Theil-Sen Estimator, Change Point Detection, Agra Climate, IMD Rainfall Data