Identifying rainfall trends in highly urbanized area is extremely important for various planning and implementation activities, including designing, maintaining and controlling of water distribution networks and sewer networks and mitigating flood damages. However, different available methods in trend analysis may produce comparable and contrasting results. Therefore, this paper presents an attempt in comparing some of the trend analysis methods using one of the highly urbanized areas in Sri Lanka, Colombo. Recorded rainfall data for 10 gauging stations for 30 years were tested using the MannKendall test, Sen’s slope estimator, Spearman’s rho test, and innovative graphical method. Results showcased comparable findings among three trend identification methods. Even though the graphical method is easier, it is advised to use it with a proper statistical method due to its identification difficulties when the data scatter has some outliers. Nevertheless, it was found herein that Colombo is under a downward rainfall trend in the month of July where the area receives its major rainfall events. In addition, the area has several upward rainfall trends over the minor seasons and in the annual scale. Therefore, the water management activities in the area have to be revisited for a sustainable use of water resources.
Purpose: Food and agriculture are frequently affected from on-going climate change. A significant percentage of annual harvest is lost due to extreme climatic conditions in different parts of the world. Sri Lanka is considered as a country which is vulnerable to climate change. Therefore, this research presents a detailed analysis to find out the non-linear relationships between the rainfall and paddy harvest in two major provinces of Sri Lanka.Research Method: North-central and North-western provinces as two major agricultural areas were selected for the study. Rainfall trends were identified using non-parametric Mann-Kendall and Sen's slope estimator tests. The artificial neural network (ANN) approach was used to establish non-linear relationships between rainfall and paddy yield.Findings: There was no significant (p > 0.05) linear correlation between rainfall amount and the rainfed paddy yield in tested locations. However, no clear relationship between the rainfall and rain fed yield were found in the 14 predefined functions (polynomial, logarithmic, exponential and trigonometric) derived using ANN where the calculated coefficients of determination were less than 0.3.
Research Limitations:Due to lack of other climate variables such as temperatures, a significant relationship was not observed in this study.
Originality/value:We have shown that non-linear artificial neural network approach can be used to study the impact of climate on agricultural production in Sri Lanka.
Isolation of DNA from environmental samples is a crucial step in microbial community analyses through molecular methods. The present study was conducted to evaluate a DNA extraction protocol from paddy soil with a comparison on quality, quantity and integrity of the isolated DNA and to determine the suitability of extracted DNA for downstream applications in microbial community analyses. Three protocols (i.e. PEG/NaCl, Mannitol/CTAB and Sodium Phosphate Buffer) used for the extraction of DNA from different types of soil were attempted on paddy soil. The quality and quantity of the extracted genomic DNA was quantified spectrophotometrically and integrity was checked by gel electrophoresis. The efficiency of DNA extraction by the three protocols was compared with a commercial soil DNA extraction kit (Norgen's Soil DNA Isolation Plus Kit). Further, quality of the extracted DNA for PCR amplification was assessed using universal primer pairs for bacteria and fungi. DNA extracted using PEG/NaCl method resulted in the highest DNA concentration, while the highest purity was recorded by the DNA extracted by Mannitol/CTAB method (A260/A280 = 1.61 and A260/A230 = 1.15). Expected PCR products targeting 16s rDNA and ITS regions were obtained from the DNA samples extracted by Mannitol/CTAB method. Therefore, Mannitol/CTAB method used in the present study is suitable to extract high-quality DNA from paddy soil for molecular microbial studies.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.