scholarly journals Comparison of Different Analyzing Techniques in Identifying Rainfall Trends for Colombo, Sri Lanka

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Anushka Perera ◽  
Thilini Ranasinghe ◽  
Miyuru Gunathilake ◽  
Upaka Rathnayake
Keyword(s):  
Sri Lanka ◽  
Trend Analysis ◽  
Water Distribution ◽  
Graphical Method ◽  
Sustainable Use ◽  
Distribution Networks ◽  
Rainfall Trends ◽  
Slope Estimator ◽  
Trend Identification ◽  
Annual Scale

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.

scholarly journals Rainfall Trend Analysis in Uma Oya Basin, Sri Lanka, and Future Water Scarcity Problems in Perspective of Climate Variability

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Bhabishya Khaniya ◽  
Isuru Jayanayaka ◽  
Pradeep Jayasanka ◽  
Upaka Rathnayake
Keyword(s):  
Sri Lanka ◽  
Climate Variability ◽  
Trend Analysis ◽  
Water Scarcity ◽  
Global Climate ◽  
Development Project ◽  
Intermediate Period ◽  
Rainfall Trends ◽  
Dry Zone ◽  
Slope Estimator

The effect of climate variability on the rainfall pattern is canvassed on the Uma Oya river basin, Sri Lanka, consisting of 5 rainfall gauging stations. The Uma Oya basin (720 km2) is given utmost precedence due to environmental concerns seen in the ongoing Uma Oya multipurpose development project (529 million USD worth) which is expected to divert water to the southeast dry zone of the country while adding 231 GWh/year electricity to the national grid. The rainfall data for a period of 26 years (1992–2017) were analysed using Mann–Kendall’s test and Sen’s slope estimator test to identify the rainfall trends. Both of these trend analysis test results depict only one negative trend for Hilpankandura Estate for the month of June; however, the seasonal trend analysis and annual trend analysis do not support this observation. Nevertheless, Mann–Kendall’s test showed potential positive trends for the 3 rainfall gauging stations Kirklees Estate, Ledgerwatte Estate, and Welimada Group only in the 1st intermediate period (March-April), and this is well supported by the monthly trend analysis. Other than these trends, the results do not show any significant negative trends in the Uma Oya catchment. Therefore, the results vividly explain that there is no threat of water scarcity to the catchment area being resistant to changing global climate for the past 26 years.

scholarly journals Comparison of Statistical, Graphical, and Wavelet Transform Analyses for Rainfall Trends and Patterns in Badulu Oya Catchment, Sri Lanka

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Ashika M. Ruwangika ◽  
Anushka Perera ◽  
Upaka Rathnayake
Keyword(s):  
Climate Change ◽  
Sri Lanka ◽  
Trend Analysis ◽  
Wavelet Transforms ◽  
Kendall Test ◽  
Discrete Wavelet ◽  
Rainfall Trend ◽  
Analysis Methods ◽  
Rainfall Trends ◽  
Mann Kendall Test

Climate change has adversely influenced many activities. It has increased the intensified precipitation events in some places and decreased the precipitation in some other places. In addition, some research studies revealed that the climate change has moved seasons in the temporal scale. Therefore, the changes can be seen in both spatial and temporal scales. Thus, analyzing climate change in the localized environments is highly essential. Rainfall trend analysis in a localized catchment can improve many aspects of water resource management not only to the catchment itself but also to some of the related other catchments. This research is carried to identify the rainfall trends in Badulu Oya catchment, Sri Lanka. The catchment is important as it is in the intermediate climate zone and rich in agricultural productions. Four rain gauges (namely, Badulla, Kandekatiya, Lower Spring Valley, and Ledgerwatte Estate) were used to analyze the rainfalls in the resolutions of monthly, seasonally, and annually. 30-year monthly cumulative rainfall data for the above four gauging stations are analyzed using various standard tests. Nonparametric tests including Mann–Kendall test and sequential Mann–Kendall test and innovative trend analysis methods are used to identify the potential rainfall trends in Badulu Oya catchment. In addition, continuous wavelet transforms and discrete wavelet transforms tests are carried out to check the patterns on rainfall to the catchment. The trend analysis methods are compared against each other to identify the better technique. The results reveal that the nonparametric Mann–Kendall test is powerful to produce the statistically significant rainfall trends in qualitative and quantitative manner. Mann–Kendall analysis shows a positive trend to Ledgerwatte Estate in monthly (3.7 mm in February and 7.4 mm in October), seasonal (6.9 mm in the 2ndintermonsoon), and annual (3 mm annually) scales. However, the analysis records one decreasing rainfall trend to Kandekatiya (8.1 mm in December) only in monthly scale. Nevertheless, it was found that the graphical method can be easily used in qualitative analysis, while discrete wavelet transformations are efficient in identifying the rainfall patterns effectively.

scholarly journals An Enhanced Innovative Triangular Trend Analysis of Rainfall Based on a Spectral Approach

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 727
Author(s):  
Bilel Zerouali ◽  
Nadhir Al-Ansari ◽  
Mohamed Chettih ◽  
Mesbah Mohamed ◽  
Zaki Abda ◽  
...  
Keyword(s):  
Trend Analysis ◽  
Rainfall Variability ◽  
Extreme Rainfall ◽  
Discrete Wavelet ◽  
Rainfall Time Series ◽  
Extreme Rainfall Event ◽  
Good Efficiency ◽  
High Rainfall ◽  
Trend Identification ◽  
Annual Scale

The world is currently witnessing high rainfall variability at the spatiotemporal level. In this paper, data from three representative rain gauges in northern Algeria, from 1920 to 2011, at an annual scale, were used to assess a relatively new hybrid method, which combines the innovative triangular trend analysis (ITTA) with the orthogonal discrete wavelet transform (DWT) for partial trend identification. The analysis revealed that the period from 1950 to 1975 transported the wettest periods, followed by a long-term dry period beginning in 1973. The analysis also revealed a rainfall increase during the latter decade. The combined method (ITTA–DWT) showed a good efficiency for extreme rainfall event detection. In addition, the analysis indicated the inter- to multiannual phenomena that explained the short to medium processes that dominated the high rainfall variability, masking the partial trend components existing in the rainfall time series and making the identification of such trends a challenging task. The results indicate that the approaches—combining ITTA and selected input combination models resulting from the DWT—are auspicious compared to those found using the original rainfall observations. This analysis revealed that the ITTA–DWT method outperformed the ITTA method for partial trend identification, which proved DWT’s efficiency as a coupling method.

scholarly journals Development of an Interface in MATLAB for Trend Analysis of Hydro-Meteorological Data

2019 ◽  
Author(s):  
J. P. Patil ◽  
A. Sarangi ◽  
D. K. Singh
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
Statistical Methods ◽  
Meteorological Data ◽  
Rainfed Agriculture ◽  
Analysis Process ◽  
Mk Test ◽  
Rainfall Trends ◽  
Change Trend ◽  
Slope Estimator

This study presents an interface, ‘Climate Change Trend Analysis (CCTA)’, developed in MATLAB® environment to analyze the trends using non-parametric statistical methods, Mann-Kendall (MK) test and modified Mann-Kendall (MMK) test with Sen’s slope estimator. The interface was used to determine trend in annual and seasonal (kharif) rainfall depths in Pune district acquired from 13 observatories. The developed interface automates the trend analysis process, which can further use for detecting variability and trends in the meteorological as well as other hydrological and agricultural parameters. The observed rainfall trends during monsoon would play a significant role for rainfed agriculture in Pune district.

scholarly journals RAINFALL TRENDS ANALYSIS IN TÂRGU MUREȘ CITY, ROMÂNIA

2021 ◽  
Vol 31 (1) ◽  
pp. 45-56
Author(s):  
Ion BUGLEA ◽  
Keyword(s):  
Standard Deviation ◽  
Trend Analysis ◽  
Coefficient Of Variation ◽  
Kendall Test ◽  
Precipitation Data ◽  
Monthly Average ◽  
Maximum Value ◽  
Rainfall Trends ◽  
Trends Analysis ◽  
Slope Estimator

The aim of this study is the detection of trends of precipitation from (1986-2020) over Târgu Mureș city. Precipitation data for 35 years were processed with MS Excel spreadsheets to find monthly, seasonal and annual variability of rainfall. The Mann-Kendall test was used for trend analysis of precipitation and the Sen’s slope estimator was used for the magnitude of variation. The calculations of the two methods were performed using the MAKESENS program. The standard deviation and the coefficient of variation were used to highlight the dispersion. Results show that all three scales (annual, seasonal and monthly show a tendency to increase rainfall. The highest monthly average of precipitation is 227.70 mm (August, 2005), and the lowest monthly average of precipitation is 0.80 mm (November, 2011). The maximum value of annual precipitation is 852.60 mm and was registered in 2005, and the minimum value was 408.70 mm registered in 2000.

An Advanced Software to Manage a Smart Water Network with Innovative Metrics and Tools Based on Social Network Theory

10.29007/gvnz ◽  
2018 ◽  
Author(s):  
Armando Di Nardo ◽  
Michele Di Natale ◽  
Anna Di Mauro ◽  
Eva Martínez Díaz ◽  
Jose Antonio Blázquez Garcia ◽  
...  
Keyword(s):  
Social Network ◽  
Network Theory ◽  
Water Distribution ◽  
Distribution Networks ◽  
Social Network Theory ◽  
Geographical Information ◽  
Water Network ◽  
Time Data ◽  
Water Losses ◽  
Operational Conditions

The recent development and applications of social network theory in many fields of engineering (electricity, gas, transport, water, etc.) allows both the understanding of networks and to improve their management. Social network theory coupled to the availability of real time data and big data analysis techniques can change drastically the traditional approaches to manage civil networks. Recently, some authors are working to apply this novel approach, based on social network theory, on the water distribution networks using: a) graph partitioning algorithms to define optimal district meter areas both for water losses identification and for water network protection, b) innovative topological, energy and hydraulic indices to analyze performance; and c) GIS (Geographical Information System) to provide a more effective display of results and to improve network behavior in specific operational conditions. In this paper, a novel release 3.5 of SWANP software, that implements all these features, was tested on a real large water network in Alcalá de Henares, Spain.

Analisis Hidrolis dan Jejak Karbon Jaringan Distribusi Air Bersih di Pulau Kecil Padat Penduduk (Pulau Lengkang Kecil, Kota Batam)

2020 ◽  
Vol 21 (2) ◽  
pp. 227-235
Author(s):  
Muhammad Rizki Apritama ◽  
I Wayan Koko Suryawan ◽  
Yosef Adicita
Keyword(s):  
Water Supply ◽  
Distribution System ◽  
Water Distribution ◽  
Treatment Plant ◽  
Primary Source ◽  
Distribution Networks ◽  
Clean Water ◽  
Island Community ◽  
Dug Wells ◽  
Centralized Wastewater Treatment

ABSTRACTThe clean water supply system network on Lengkang Kecil Island was developed in 2019. A small portion of the community's freshwater comes from harvesting rainwater and dug wells, which are only obtained during the rainy season. The primary source of clean water used by the community comes from underwater pipelines with a daily discharge of 0.86 l/sec. The water supply of the Lengkang Kecil Island community is 74.3 m3/day, with 146 House Connections (HCs) and to serve public facilities such as elementary schools, primary health centers, and mosques. Hydraulic evaluation of clean water distribution using EPANET 2.0 software on flow velocity shows the lowest rate of 0.29 m/s and the highest of 1.21 m/s. The lowest pressure value in the distribution system is 6.94-6.96 m and headloss units in the range 0.08-0.25 m/km. These three criteria are still within the distribution network design criteria (feasible). A carbon footprint can be calculated from each activity from the analysis of the evaluation of clean water distribution networks. The most massive emissions came from pumping activities with 131 kg CO2-eq, followed by emissions from wastewater 62.5 kgCO2-eq. Further research is needed to determine the quality of wastewater and the design for a centralized wastewater treatment plant (IPALT) to improve Lengkang Kecil Island residents' living standards.Keywords: Lengkang Kecil Island, water, EPANET, carbon footprintABSTRAKJaringan sistem penyediaan air bersih pada Pulau Lengkang Kecil dimulai pada tahun 2019. Sebagian kecil air bersih yang digunakan masyarakat berasal dari pemanenan air hujan dan sumur gali yang hanya didapat pada musim hujan. Sumber air bersih utama yang digunakan masyarakat berasal dari pengaliran perpipaan bawah laut dengan debit harian 0,86 l/detik. Kebutuhan air masyarakat Pulau Lengkang Kecil adalah 74,3 m3/hari dengan 146 Sambungan Rumah (SR) serta untuk melayani fasilitas umum seperti sekolah dasar (SD), puskesmas, dan masjid. Evaluasi hidrolis distribusi air bersih dengan menggunakan software EPANET 2.0 terhadap kriteria kecepatan aliran menunjukkan nilai terendah 0,29 m/s dan tertinggi 1,21 m/s. Nilai sisa tekan dalam sistem distribusi adalah 6,94–6,96 m dan unit headloss pada kisaran 0,08–0,25 m/km. Ketiga kriteria ini masih berada dalam kriteria desain jaringan distribusi (layak). Dari analisis evaluasi jaringan distribusi air bersih, dapat dihitung jejak karbon yang dihasilkan dari setiap kegiatannya. Emisi terbesar berasal dari kegiatan pemompaan dengan nilai 131 kgCO2-eq, diikuti dengan emisi yang berasal dari air limbah dengan nilai 62,5 kgCO2-eq. Penelitian lanjutan diperlukan untuk mengetahui kualitas dari air limbah dan desain untuk instalasi pengolahan air limbah terpusat (IPALT) untuk meningkatkan taraf hidup penduduk Pulau Lengkang Kecil.Kata kunci: Pulau Lengkang Kecil, air, EPANET, jejak karbon

A study on appropriate investment of pipeline rehabilitation for water distribution network

2005 ◽  
Vol 5 (2) ◽  
pp. 31-38
Author(s):  
A. Asakura ◽  
A. Koizumi ◽  
O. Odanagi ◽  
H. Watanabe ◽  
T. Inakazu
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Water Supply ◽  
Water Distribution ◽  
Ad Hoc ◽  
Distribution Network ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Optimal Basis ◽  
Model Case

In Japan most of the water distribution networks were constructed during the 1960s to 1970s. Since these pipelines were used for a long period, pipeline rehabilitation is necessary to maintain water supply. Although investment for pipeline rehabilitation has to be planned in terms of cost-effectiveness, no standard method has been established because pipelines were replaced on emergency and ad hoc basis in the past. In this paper, a method to determine the maintenance of the water supply on an optimal basis with a fixed budget for a water distribution network is proposed. Firstly, a method to quantify the benefits of pipeline rehabilitation is examined. Secondly, two models using Integer Programming and Monte Carlo simulation to maximize the benefits of pipeline rehabilitation with limited budget were considered, and they are applied to a model case and a case study. Based on these studies, it is concluded that the Monte Carlo simulation model to calculate the appropriate investment for the pipeline rehabilitation planning is both convenient and practical.

A Review on Data Mining Techniques Towards Water Sustainability Issues

2020 ◽  
Vol 13 (5) ◽  
pp. 818-826
Author(s):  
Ranjan Kumar Panda ◽  
A. Sai Sabitha ◽  
Vikas Deep
Keyword(s):  
Data Mining ◽  
Natural Resources ◽  
Environmental Sustainability ◽  
Water Distribution ◽  
Research Work ◽  
Distribution Networks ◽  
Environmental Data ◽  
World Population ◽  
Water Sustainability ◽  
Rapid Urbanization

Sustainability is defined as the practice of protecting natural resources for future use without harming the nature. Sustainable development includes the environmental, social, political, and economic issues faced by human being for existence. Water is the most vital resource for living being on this earth. The natural resources are being exploited with the increase in world population and shortfall of these resources may threaten humanity in the future. Water sustainability is a part of environmental sustainability. The water crisis is increasing gradually in many places of the world due to agricultural and industrial usage and rapid urbanization. Data mining tools and techniques provide a powerful methodology to understand water sustainability issues using rich environmental data and also helps in building models for possible optimization and reengineering. In this research work, a review on usage of supervised or unsupervised learning algorithms in water sustainability issues like water quality assessment, waste water collection system and water consumption is presented. Advanced technologies have also helped to resolve major water sustainability issues. Some major data mining optimization algorithms have been compared which are used in piped water distribution networks.

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