ANALYSIS OF DRAINAGE CHANNEL CAPACITY AT SINDANG STREET IN SINDANG HOUSE PUMP AREA

<p>Sindang street, which is located in North Rawabadak Sub-district, Koja District, is one of the areas in North Jakarta Administrative City which is an area that is prone to flooding. Even though a working pump house is available, there are still puddles in several places. One of the problems that occur is the channel that drains water into the storage pool narrowing due to sedimentation in the channel. By analyzing the channel using the Log Pearson III distribution method using data obtained from the STA Tanjung Priok Rainfall Station, the rainfall intensity that occurs in a 5 year cycle is 170.748 mm, the Mononobe equation is used to find the intensity of rain per hour that occurs. Then it can be searched for the planned rain discharge using a Rational Method so that it is known that there are 2 channels, namely (P and Q) unable to accommodate the rainfall that occurs.</p>

Log Pearson III Distribution and Gumbel Distribution Model for Rainfall Data in Pekanbaru

Rainfall is very important for human life. Both high and low rainfall can cause some problems, ranging from flood to drought. We can see that flood can be found in several big cities, and one of them is in Pekanbaru. Therefore, rainfall data analysis is needed to know the model and the pattern of rainfall distribution. In turn, the result can be used as a consideration for the development of the city or the formulation of policy in Pekanbaru’s governance. In this study, Log Pearson III distribution and Gumbel distribution model were used to analyze data of rainfall in Pekanbaru from January 2011 to April 2017. The purpose of this study was to determine the best rainfall model among Log Pearson III and Gumbel Distribution. To estimate parameters from both models, we used Maximum Likelihood and Newton Rephson method. Based on the use of the AIC and BIC test, this study results showed that Log Pearson III is better than Gumbel distribution in modeling the rainfall data of Pekanbaru.

ANALISA STATISTIK DEBIT BANJIR DAN DEBIT ANDALAN SUNGAI KOMERING SUMATERA SELATAN

River flow discharge is one of the most important hydrological parameters for the management of water resources because river flow data is required for future pusposes assuming the process characteristics are unchanged. Komering River is one of the largest rivers in the Province South Sumatra which is quite a big role in the lives of people who are in the sub Komering watershed. The magnitude of the flood discharge and dependable flow Komering River is very important to to be taken into account, by analyzing the flood discharge can be done flood management, while by analyzing the dependable flow can be done planning river water utilization. The research based on the collection of secondary data obtained from Departemen Pekerjaan Umum Sumatera Selatan and Balai Besar Wilayah Sungai Sumatera VIII, discharge data from 2000 to 2010 and maps needed to know the study area. All the data are correlated where the analysis is intended to determine the statistics of flood discharge and dependable flow Komering River. From the results of analyzes obtained that the distribution can be used to predict flooding in the river discharge is Gumbel distribution with estimate the flood discharge for 2 years return period 1007.57 m³/dt, for 5 years return period 1459.79 m³/dt, for 10 years return period 1759.20 m³/dt, for 25 years return peiod 2137.50 m³/dt, for 50 years return period 2418.15 m³/dt, and for 100 years return period 2696.73 m³/dt. Based on analysis of dependable flow, Month Basic Plan Method, thatLog Pearson III distribution can be used to analyze River Komering dependable flow. The highest dependable flow of is 226.20 m³/dt and the lowest dependable flow is 62.08 m³/dt.

Study on the frequency of heavy rainfall in Huong Khe district, Ha Tinh province

Rainfall intensity, duration and frequency of 24 consecutive hours or longer (48h, 72h, 96h) are very essential for the assessment of flood risk and the design of the reservoirs and dams in Huong Khe district, Ha Tinh province. The analysis of flood-causing rainfall and the actual floods from 1990 to 2012 has shown that floods usually occur when: a) 24-hour continuous rainfall reacheds 710.6mm or more; b) Heavy rains which lasted longer than 24 hours and reached 548.9mm/24h to 630.2mm/48h or more; c) Heavy rains lasted from 72 hours to 96 hours and reached from 534.5mm/72h to 575.6mm/96h. The following conclusions have been drawn from analysis results of development of the empirical and theoretical exceedance frequencies of Pearson III distribution of 24h-96h heavy rainfall: a) All the theoretical and empirical frequency data have very high correlation coefficient from 0.891 (24h rainfall) to about 0.948 (72h-96h rainfall); b) For 24h rainfall, the actual rainfall of the empirical P of 13% to 26% is about 40mm lower than the theoretical rainfall, while the actual rainfall of the empirical P of 8.7% is about 80mm higher than the theoretical value, and that of the empirical P of 4.35% is about 175mm higher than the theoretical value; the actual rainfall at empirical P of 8.7% is corresponding to theoretical P of 4.5%, and actual rainfall at empirical P of 4.35% is corresponding to theoretical P of ~1%; c) For 48h and 72h rainfall, the empirical and theoretical frequency data are very close to each other for the P in the range of 8.7% to 30%, only empirical P of 4.35% is much far from theoretical one and corresponding to rainfall frequency of ~1%; d) For 96h rainfall, the empirical and theoretical frequency data are very close to each other for most P range, only empirical P of 8.7% and 4.35% are somehow far from theoretical ones and corresponding to rainfall of theoretical frequencies of ~4.5% and ~1%, respectively.

PEMILIHAN DISTRIBUSI PROBABILITAS PADA ANALISA HUJAN DENGAN METODE GOODNESS OF FIT TEST

Rainfall event is a stochastic process, so to explain and analyze this processes the probability theory and frequency analysisare used. There are four types of probability distributions.They are normal, log normal, log Pearson III and Gumbel. To find the best probabilities distribution, it will used goodness of fit test. The tests consist of chi-square and smirnov-kolmogorov. Results of the chi-square test for normal distribution, log normal and log Pearson III was 0.200, while for the Gumbel distribution was 2.333. Results of Smirnov Kolmogorov test for normal distribution D = 0.1554, log-normal distribution D = 0.1103, log Pearson III distribution D = 0.1177 and Gumbel distribution D = 0.095. All of the distribution can be accepted with a confidence level of 95%, but the best distribution is log normal distribution.Kejadian hujan merupakan proses stokastik, sehingga untuk keperluan analisa dan menjelaskan proses stokastik tersebut digunakan teori probabilitas dan analisa frekuensi. Terdapat empat jenis distribusi probabilitas yaitu distribusi normal, log normal, log pearson III dan gumbel. Untuk mencari distribusi probabilitas terbaik maka akan digunakan pengujian metode goodness of fit test. Pengujian tersebut meliputi uji chi-kuadrat dan uji smirnov kolmogorov. Hasil pengujian chi kuadrat untuk distribusi normal, log normal dan log pearson III adalah 0.200, sedangkan untuk distribusi gumbel 2.333. Hasil pengujian smirnov kolmogorov untuk distribusi normal dengan nilai D = 0.1554, distribusi log normal dengan nilai D = 0.1103, distribusi log pearson III dengan nilai D = 0.1177 dan distribusi gumbel dengan nilai D = 0.095. Seluruh distribusi dapat diterima dengan tingkat kepercayaan 95%, tetapi distribusi terbaik adalah distribusi log normal.

Floods in Serbia in the 1999-2009 period: Hydrological analysis and flood protection measures

The review on greatest floods recorded in Vojvodina and central Serbia within the period from 1999 to 2009 is given in this paper. For 13 hydrological stations, that recorded the greatest floods for the present period, probability of occurrence of these floods has been accomplished. Based on analysis of time series of discharge and water level maximum, performed by applying probability theory and mathematical statistics, and calculated theoretical probability distribution function of floods, probability of occurrence of flood has been obtained. Most often the best agreement with the empirical distribution function had a Log-Pearson III, Pearson III distribution. These results can be used for dimensioning of hydro-technical objects for flood protection. The most significant causes for floods recorded in this period were melting of snow and intensive rainfall. In this paper the current situation of flood protection and future development of flood protection measures were also presented. .