scholarly journals Comparison of Normal Ratio Method and Distance Power Method for Estimating Missing Rainfall Data with Three Neighboring Stations

2021 ◽  
pp. 1-9
Author(s):  
Celeste A. De Asis
Keyword(s):  
Correlation Coefficient ◽  
Daily Rainfall ◽  
T Test ◽  
Monthly Rainfall ◽  
Rainfall Data ◽  
Ratio Method ◽  
Power Method ◽  
Daily Rainfall Data ◽  
Normal Ratio ◽  
Better Than

This study compared the performances of Normal Ratio Method and Distance Power Method as a tool for estimating missing rainfall data. The data utilized are the rainfall data of the three neighboring station of Catarman, Northern Samar, Philippines. These stations are Catbalogan Station (Samar Province), Legazpi (Bicol Province) and Masbate (Masbate Province). The observed daily rainfall data for the Catarman (Northern Samar), Catbalogan, Legazpi, and Masbate were obtained from the Philippine Atmospheric Geographical Astronomical Services Administration. The monthly rainfall were computed for the three (3) neighboring stations (Catbalogan, Legazpi, Masbate). The evaluation used the T-test for correlated samples and the Pearson’s Correlation Coefficient for the monthly rainfall data computed of the three neighboring Station of Catarman, Northern Samar with the three neighboring stations. Based from the results, Normal Ratio Method performs better than Distance Power Method as applied to three neighboring stations.

Revised Normal Ratio Methods for Imputation of Missing Rainfall Data

2016 ◽  
Vol 13 (1) ◽  
pp. 83
Author(s):  
Siti Nur Zahrah Amin Burhanuddin ◽  
Sayang Mohd Deni ◽  
Norazan Mohamed Ramli
Keyword(s):  
Missing Data ◽  
Daily Rainfall ◽  
Peninsular Malaysia ◽  
Rainfall Data ◽  
Ratio Method ◽  
Accurate Estimation ◽  
Trimmed Mean ◽  
Coordinate Method ◽  
Target Station ◽  
Normal Ratio

A good quality of rainfall data is highly necessary in hydrological and meteorological analyses. Lack of quality in rainfall data will influence the process of analyses and subsequently, produce misleading results. Thus, this study is aimed to propose modified missing rainfall data treatment methods that produced more accurate estimation results. In this study, the old normal ratio method and the modified normal ratio based on trimmed mean are combined with geographical coordinate method. The performances of these modified methods were tested on various levels of the missing data of 36 years complete daily rainfall records from eighteen meteorology stations in Peninsular Malaysia. The results indicated that both modified methods improved the estimation of missing rainfall values at the target station based on the least error measurements. Modified normal ratio based on trimmed mean with geographical coordinate method is found to be the most appropriate method for station Batu Kurau and Sg. Bernam while modified old normal ratio with geographical coordinate is the most accurate in estimating the missing data at station Genting Klang.

Revised Normal Ratio Methods for Imputation of Missing Rainfall Data

2016 ◽  
Vol 13 (1) ◽  
pp. 83 ◽  
Author(s):  
Siti Nur Zahrah Amin Burhanuddin ◽  
Sayang Mohd Deni ◽  
Norazan Mohamed Ramli
Keyword(s):  
Missing Data ◽  
Daily Rainfall ◽  
Peninsular Malaysia ◽  
Rainfall Data ◽  
Ratio Method ◽  
Accurate Estimation ◽  
Trimmed Mean ◽  
Coordinate Method ◽  
Target Station ◽  
Normal Ratio

A good quality of rainfall data is highly necessary in hydrological and meteorological analyses. Lack of quality in rainfall data will influence the process of analyses and subsequently, produce misleading results. Thus, this study is aimed to propose modified missing rainfall data treatment methods that produced more accurate estimation results. In this study, the old normal ratio method and the modified normal ratio based on trimmed mean are combined with geographical coordinate method. The performances of these modified methods were tested on various levels of the missing data of 36 years complete daily rainfall records from eighteen meteorology stations in Peninsular Malaysia. The results indicated that both modified methods improved the estimation of missing rainfall values at the target station based on the least error measurements. Modified normal ratio based on trimmed mean with geographical coordinate method is found to be the most appropriate method for station Batu Kurau and Sg. Bernam while modified old normal ratio with geographical coordinate is the most accurate in estimating the missing data at station Genting Klang.

scholarly journals KARASTERISTIK CURAH HUJAN DAN ALIRAN DAS LARONA KABUPATEN LUWU TIMUR SULAWESI SELATAN

2013 ◽  
Vol 14 (2) ◽  
pp. 83
Author(s):  
Djazim Syaifullah
Keyword(s):  
Rainy Season ◽  
Daily Rainfall ◽  
Monthly Rainfall ◽  
Rainfall Data ◽  
Water Reservoirs ◽  
Light Rain ◽  
Daily Rainfall Data ◽  
Moderate Condition

IntisariKarasteristik curah hujan dan aliran DAS Larona telah dilakukan dengan menggunakan data curah hujan dan aliran (inflow). Data curah hujan 7 buah stasiun data bulanan dan harian 10 sampai 29 tahun dan 8 buah stasiun penakar otomatis untuk mendapatkan data jam-jaman. Nilai inflow biasanya dihitung berdasarkan data outflow. Hasilnya menunjukkan bahwa daerah di sekitar Mahalona, bagian tenggara Matano dan bagian Barat Laut Towuti mempunyai konsentrasi curah hujan yang paling besar. DAS ini masuk musim kering pada bulan Agustus dan September, sementara bulan bulan yang lain termasuk bulan basah. Curah Hujan bulanan maksimum terjadi pada bulan April dengan nilai sekitar 360 mm, sedangkan curah hujan bulanan minimum terjadi pada bulan September sekitar 105 mm. DAS Larona didominasi oleh hujan ringan (kurang dari 5 mm dalam satu harinya) dengan durasi hujan  dominan kurang dari 1 jam (rata-rata sekitar 47 % dari total kejadian hujan). Dari nilai koefisien aliran yang berkisar 0.6 menunjukkan bahwa DAS Larona masih berada pada kondisi moderate dalam hal sebagai reservoir air  AbstractPrecipitation and flow charasteristics of the Larona watershed was conducted by use of the rainfall and inflow data. There are monthly and daily rainfall data 10 until 29 year long for 78 automatic rainfall stations. The value of inflow was calculated based on outflow.The results show that the region around Mahalona, the southeastern of Matano and part of Northwest of Towuti have the most concentration of rainfall. This Catchment came into rainy season on August until September, while other month in the rainy season. Maximum monthly rainfall occurs in april with the value of around 360 mm, while the minimum monthly rainfall happened in september around 105 mm. The Llarona catchment was dominated by light rain (less than 5 mm/day) with the duration of rainfall less than 1mm/hour. From the value of the stream coefficients shows that Larona Catchment are still at moderate condition in terms as water reservoirs

scholarly journals COMPARISON OF SCS UH AND CLARK METHODS FOR RAINFALL–RUNOFF MODEL IN DELUWANG WATERSHED

2018 ◽  
Vol 2 (01) ◽  
pp. 77
Author(s):  
Muhammad Arifin ◽  
Entin Hidayah ◽  
Wiwik Yunarni Widiarti
Keyword(s):  
Hydrological Modeling ◽  
Daily Rainfall ◽  
Water Source ◽  
Rainfall Data ◽  
Rainfall Runoff ◽  
Unit Hydrograph ◽  
Direct Runoff ◽  
Daily Rainfall Data ◽  
Rainfall Runoff Model ◽  
Better Than

Deluwang River water source is widely used for the needs of irrigation, plantation, and the fulfillment of domestic life. Given the importance of the role of water in Deluwang watershed, then he had to do the management of watershed. The proper management of watershed hydrological modeling requires accurate. Rainfall-runoff using HEC-HMS applications. This research aims tocomparison 2 methods in direct runoff. Therefore this study uses two methods, namely SCS Unit Hydrograph method and method of Clark Unit Hydrograph. On the calibration process using daily rainfall data and daily debit year 2006, whereas in the validation process using daily rainfall data and daily debit years 2007 to 2012. The results of the calibration using Clark Unit Hydrograph method better than using SCS Unit Hydrograph method with Nash's value 0,700 than 0,539. While the results of the validation of modeling using Clark Unit Hydrograph method is better than using SCSUnit Hydrograph method with a value of Nash 0,541 than 0,368. Sungai Deluwang sumber airnya banyak dimanfaatkan untuk kebutuhan irigasi, perkebunan, serta pemenuhan kehidupan rumah tangga. Mengingat pentingnya peranan air pada DAS Deluwang, maka perlu  dilakukannya pengelolaan DAS. Pengelolaan DAS yang tepat membutuhkan pemodelan  hidrologi yang akurat. Pemodelan hujan aliran menggunakan aplikasi HEC-HMS. Penelitian ini bertujuan membandingkan 2 metode yang terdapat pada direct runoff. Oleh karena itu penelitian ini menggunakan dua metode, yaitu metode SCS Unit Hydrograph dan metode Clark Unit Hydrograph. Pada proses kalibrasi menggunakan data curah hujan harian dan debit harian tahun 2006, sedangkan pada proses validasi menggunakan data curah hujan harian dan debit harian tahun 2007 sampai 2012. Hasil kalibrasi menggunakan  metode Clark Unit Hydrograph lebih bagus dibandingkan menggunakan metode SCS Unit Hydrograph dengan nilai Nash 0,700 berbanding 0,539. Sedangkan hasil validasi pemodelan menggunakan  metode Clark Unit Hydrograph lebih bagus dibandingkan menggunakan metode SCS Unit Hydrograph dengan nilai Nash 0,541 berbanding 0,368.

The effect of weather, drainage efficiency and duration of spring cultivations on barley yields in England

1972 ◽  
Vol 7 (2) ◽  
pp. 79-83 ◽  
Author(s):  
L P Smith
Keyword(s):  
Yield Loss ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Work Schedule ◽  
Average Yield ◽  
Daily Rainfall Data ◽  
Arable Farming ◽  
Work Distribution

Daily rainfall data for twenty years in arable farming areas are analysed with respect to four standards of drainage and for three lengths of schedule of spring work. Distribution and frequency in time of available work days are interpreted in terms of lateness of sowing and of barley yield. Formulae are established to calculate average yield loss in terms of drainage standard and work schedule, enabling estimates to be made of the effect of planned improvements.

scholarly journals Bayesian Time Series Modelling of the Italian Daily Rainfall Data using Mixed Distribution

2019 ◽  
Vol 8 (4) ◽  
pp. 2279-2288
Keyword(s):  
Time Series ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Seasonal Effects ◽  
Model Parameters ◽  
Daily Rainfall Data ◽  
Mixed Distribution ◽  
Time Series Modelling ◽  
Bayesian Time Series ◽  
The Ideal

A combination of continuous and discrete elements is referred to as a mixed distribution. For example, daily rainfall data consist of zero and positive values. We aim to develop a Bayesian time series model that captures the evolution of the daily rainfall data in Italy, focussing on directly linking the amount and occurrence of rainfall. Two gamma (G1 and G2) distributions with different parameterisations and lognormal distribution were investigated to identify the ideal distribution representing the amount process. Truncated Fourier series was used to incorporate the seasonal effects which captures the variability in daily rainfall amounts throughout the year. A first-order Markov chain was used to model rainfall occurrence conditional on the presence or absence of rainfall on the previous day. We also built a hierarchical prior structure to represent our subjective beliefs and capture the initial uncertainties of the unknown model parameters for both amount and occurrence processes. The daily rainfall data from Urbino rain gauge station in Italy were then used to demonstrate the applicability of our proposed methods. Residual analysis and posterior predictive checking method were utilised to assess the adequacy of model fit. In conclusion, we clearly found that our proposed method satisfactorily and accurately fits the Italian daily rainfall data. The gamma distribution was found to be the ideal probability density function to represent the amount of daily rainfall.

scholarly journals Structural break or long memory: an empirical survey on daily rainfall data sets across Malaysia

2013 ◽  
Vol 17 (4) ◽  
pp. 1311-1318 ◽  
Author(s):  
F. Yusof ◽  
I. L. Kane ◽  
Z. Yusop
Keyword(s):  
Long Memory ◽  
Structural Breaks ◽  
Structural Break ◽  
Daily Rainfall ◽  
Least Square ◽  
Rainfall Data ◽  
Data Sets ◽  
Original Series ◽  
Empirical Survey ◽  
Daily Rainfall Data

Abstract. A short memory process that encounters occasional structural breaks in mean can show a slower rate of decay in the autocorrelation function and other properties of fractional integrated I (d) processes. In this paper we employed a procedure for estimating the fractional differencing parameter in semiparametric contexts proposed by Geweke and Porter-Hudak (1983) to analyse nine daily rainfall data sets across Malaysia. The results indicate that all the data sets exhibit long memory. Furthermore, an empirical fluctuation process using the ordinary least square (OLS)-based cumulative sum (CUSUM) test for the break date was applied. Break dates were detected in all data sets. The data sets were partitioned according to their respective break date, and a further test for long memory was applied for all subseries. Results show that all subseries follows the same pattern as the original series. The estimate of the fractional parameters d1 and d2 on the subseries obtained by splitting the original series at the break date confirms that there is a long memory in the data generating process (DGP). Therefore this evidence shows a true long memory not due to structural break.

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