Prediction of Impact of Rainfall on Paddy Harvest and Agricultural Loans in Sri Lanka
Added on 2023-01-18
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Running head: Geography
Geography
Name of the Student
Name of the university
Author’s note
Geography
Name of the Student
Name of the university
Author’s note
1Geography
Glossary of terms
IPCC: It is a body of United Nations that assess and evaluate the science linked with climatic
change. Its responds on the natural, political and economic impacts of the climatic change
Evapotranspiration (ETo): It is the sum of the evaporation and plant transpiration from the
Earth’s land and the ocean surface to the atmosphere.
Penman-Monteith formula: The FAO Penman-Monteith method is the ETo method for
determining reference evapotranspiration.
CROPWAT: It is a decision support tool that has been prepared by the Land and Water
Development Division of the FAO. It helps in the calculation of requirement of the crop water,
irrigation based on the climate, soil and the crop data.
New comprehensive rural credit scheme (NCRCS)- The scheme approves loans for the
farmers for cultivating, paddy, rice and other crops
ICT- Information and communication technology. It stresses on the telecommunication and
computers, helping the users to access, transmit and alter information.
Glossary of terms
IPCC: It is a body of United Nations that assess and evaluate the science linked with climatic
change. Its responds on the natural, political and economic impacts of the climatic change
Evapotranspiration (ETo): It is the sum of the evaporation and plant transpiration from the
Earth’s land and the ocean surface to the atmosphere.
Penman-Monteith formula: The FAO Penman-Monteith method is the ETo method for
determining reference evapotranspiration.
CROPWAT: It is a decision support tool that has been prepared by the Land and Water
Development Division of the FAO. It helps in the calculation of requirement of the crop water,
irrigation based on the climate, soil and the crop data.
New comprehensive rural credit scheme (NCRCS)- The scheme approves loans for the
farmers for cultivating, paddy, rice and other crops
ICT- Information and communication technology. It stresses on the telecommunication and
computers, helping the users to access, transmit and alter information.
2Geography
Prediction of the impact of rainfall on the paddy harvest and its ultimate effect on the
agricultural loans in banks in Sri Lanka
Based on the environmental parameters like rainfall, soil type, and the topography, Sri
Lanka has been classified into three agro-ecological zones; the wet zone, the intermediate zone
and the dry zone. When the average harvest indices related to the production of biomass was
determined, rice is the main crops grown in Sri Lanka. The maximum attainable rice yield in Sri
Lanka has been found to be 12,620 kg/ha (Samarasinghe 2003).
Climatic change that is partly caused by the increased atmospheric concentration of the
greenhouse gases, has been established as the most delirious threats in relation to agriculture.
With respect to the environmental change, the rainfall patterns have changed greatly, that has
finally affected agriculture. Paddy is the most important crop that consists of 34 % of the total
cultivation in Sri Lanka and it is the basic food of Sri Lanka. Paddy cultivation is the most
important source of employment and income of the rural population (De Silva et al. 2018). The
Two types of paddy cultivated in Sri Lanka are, Maha and Yala. Maha is the seven month
period from the month of September to March and Yala is grown from April to March. Yala has
to depend on rainfall from the second half of the first inner monsoon and mostly from the
southwest monsoon and Maha has to depend on the rainfall from Northwest monsoon and second
inner monsoon. The paddy cultivation of Sri Lanka has been largely affected by variation in the
rainfall patterns and lack of proper irrigation procedures (De Silva et al. 2007). Looking at the
trends of the annual rainfall in the Batticola region of Sri Lanka, known for paddy cultivation, a
relationship between the Maha season and rainfall can be perceived. As per the reports it has
been found, that as per the three years standard deviation monthly average, there were 14 dry
Prediction of the impact of rainfall on the paddy harvest and its ultimate effect on the
agricultural loans in banks in Sri Lanka
Based on the environmental parameters like rainfall, soil type, and the topography, Sri
Lanka has been classified into three agro-ecological zones; the wet zone, the intermediate zone
and the dry zone. When the average harvest indices related to the production of biomass was
determined, rice is the main crops grown in Sri Lanka. The maximum attainable rice yield in Sri
Lanka has been found to be 12,620 kg/ha (Samarasinghe 2003).
Climatic change that is partly caused by the increased atmospheric concentration of the
greenhouse gases, has been established as the most delirious threats in relation to agriculture.
With respect to the environmental change, the rainfall patterns have changed greatly, that has
finally affected agriculture. Paddy is the most important crop that consists of 34 % of the total
cultivation in Sri Lanka and it is the basic food of Sri Lanka. Paddy cultivation is the most
important source of employment and income of the rural population (De Silva et al. 2018). The
Two types of paddy cultivated in Sri Lanka are, Maha and Yala. Maha is the seven month
period from the month of September to March and Yala is grown from April to March. Yala has
to depend on rainfall from the second half of the first inner monsoon and mostly from the
southwest monsoon and Maha has to depend on the rainfall from Northwest monsoon and second
inner monsoon. The paddy cultivation of Sri Lanka has been largely affected by variation in the
rainfall patterns and lack of proper irrigation procedures (De Silva et al. 2007). Looking at the
trends of the annual rainfall in the Batticola region of Sri Lanka, known for paddy cultivation, a
relationship between the Maha season and rainfall can be perceived. As per the reports it has
been found, that as per the three years standard deviation monthly average, there were 14 dry
3Geography
seasons and 14 wet seasons. The paddy production has been found to be high in the Maha season
due to high rainfall and less in the Yala season for low rainfall. Cultivation of paddy is highly
affected by variations in temperature, rainfall, soil moisture and increases the frequency of
extreme events (De Silva et al. 2007). Delayed monsoon or an increased frequency of droughts
can have a delirious impact on the area of the paddy sown and harvested until the yields are
obtained (De Silva et al. 2007). The demand for water resources is projected to have been
increased due to the expansion of the area under agriculture, increasing the population,
urbanization and industrialization. According to the climatic studies by De Silva and Kawasaki
(2018) the amount of rainfall in Sri Lanka had deteriorated with time. For example, the annual
average rainfall during 1931- 1961 was estimated to have been 2005 mm, which has decreased to
1861mm during the 1961- 1990.
Prediction of climatic change
In order to support irrigation facilities and support for the bank loan, it is necessary to
predict the rainfall distribution. Hence, a spatial distributed climate change dataset for the key
variables, influencing the requirements of irrigation water (evaporation and rainfall). The
Intergovernmental Panel of the Climatic change (IPCC) had set up new tools for analysing the
climate change (De Silva et al. 2007). The population of Sri Lanka in 1990 was 16.4 million and
the projected population has been 30 million by 2050. The climate change projections has been
predicted by HadCM3. The Estimating reference evapotranspiration (ETo) had been for the
estimation of the reference evapotranspiration. Enough set of climatic variables are present for
deriving the ETo using the Penman-Monteith formula (De Silva et al. 2007). The requirements
for the paddy irrigation can be measured by using a balance model called CROPWAT, that
requires the monthly input climatic data of a particular weather season. The key data involves,
seasons and 14 wet seasons. The paddy production has been found to be high in the Maha season
due to high rainfall and less in the Yala season for low rainfall. Cultivation of paddy is highly
affected by variations in temperature, rainfall, soil moisture and increases the frequency of
extreme events (De Silva et al. 2007). Delayed monsoon or an increased frequency of droughts
can have a delirious impact on the area of the paddy sown and harvested until the yields are
obtained (De Silva et al. 2007). The demand for water resources is projected to have been
increased due to the expansion of the area under agriculture, increasing the population,
urbanization and industrialization. According to the climatic studies by De Silva and Kawasaki
(2018) the amount of rainfall in Sri Lanka had deteriorated with time. For example, the annual
average rainfall during 1931- 1961 was estimated to have been 2005 mm, which has decreased to
1861mm during the 1961- 1990.
Prediction of climatic change
In order to support irrigation facilities and support for the bank loan, it is necessary to
predict the rainfall distribution. Hence, a spatial distributed climate change dataset for the key
variables, influencing the requirements of irrigation water (evaporation and rainfall). The
Intergovernmental Panel of the Climatic change (IPCC) had set up new tools for analysing the
climate change (De Silva et al. 2007). The population of Sri Lanka in 1990 was 16.4 million and
the projected population has been 30 million by 2050. The climate change projections has been
predicted by HadCM3. The Estimating reference evapotranspiration (ETo) had been for the
estimation of the reference evapotranspiration. Enough set of climatic variables are present for
deriving the ETo using the Penman-Monteith formula (De Silva et al. 2007). The requirements
for the paddy irrigation can be measured by using a balance model called CROPWAT, that
requires the monthly input climatic data of a particular weather season. The key data involves,
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