Determination of Maximum Storage and Drainage Coefficient from Consecutive Days Maximum Rainfall at Different Locations in India

2020 ◽  
Vol 7 (01) ◽  
Author(s):  
ASHUTOSH UPADHYAYA ◽  
ARTI Saran KUMARI ◽  
AKRAM AHMED
Keyword(s):  
Water Management ◽  
Return Period ◽  
Daily Rainfall ◽  
Rice Fields ◽  
Rainfall Data ◽  
Adverse Impact ◽  
Research Project ◽  
Maximum Rainfall ◽  
Safe Disposal

Knowledge about the maximum possible storage of rainwater in the field and its safe disposal is very important to save crops from the adverse impact of excess rainfall. Keeping this in view, daily rainfall data of 30 to 35 years as per availability was analyzed at four centres of All India Coordinated Research Project on Water Management i.e. (i) Samastipur (ii) Ludhiana, (iii) Hisar, and (iv) Almora. In the design of agricultural structures, generally, 10 years return period is considered, so the point, where tangent drawn on the curves of 10 years return period crosses the Y-axis, gives maximum possible storage (recommended bund height) in rice fields. Maximum possible storage (bund height) corresponding to 10 years return period was found as 25 cm, 15 cm, 13 cm, and 27.5 cm and corresponding drainage coefficient as 26.3 mm/day, 6.8 mm/day, 8.4 mm/day and 24.8 mm/day for Samastipur, Ludhiana, Hisar and Almora, respectively.

Determination of Drainage Coefficient and Bund Height of Rice Fields at Gaya and Bhagalpur Districts in Bihar

2018 ◽  
Vol 5 (01) ◽  
Author(s):  
ASHUTOSH UPADHYAYA ◽  
S. K. Singh
Keyword(s):  
Return Period ◽  
Agricultural Production ◽  
Water Storage ◽  
Daily Rainfall ◽  
Crop Damage ◽  
Distribution Model ◽  
Return Periods ◽  
Maximum Rainfall ◽  
Two Parameter

Rainfall plays an important role in agricultural production, particularly in rainfed areas. Less occurrence of rainfall causes drought like situation and crops suffer due to deficit of water, whereas heavy rainfall occurring for longer duration lead to flood like situation resulting in more runoff, soil erosion and crop damage. Rice can sustain water for little longer period compared to other crops, but this crop also needs drainage. 30 years daily rainfall data was collected at Gaya and Bhagalpur districts and analyzed. Two parameter Gamma distribution model was found fitting well in 1 to 7 consecutive days maximum rainfall corresponding to return periods varying from 2 to 20 years. In order to determine drainage coefficient at Gaya and Bhagalpur districts, depthduration- return period curves were developed. Tangents were drawn on the curves from 100 mm, 150 mm and 200 mm points and slope of these tangents gave the drainage coefficients corresponding to these rain water storage levels. Since 10 years return period is generally considered in design of agricultural structures, so the poin ton Y axis, where tangent drawn on the curves of 10 years return period crosses, gives the bund height. For both Gaya and Bhagalpur bund heights were found as 24 cm and corresponding drainage coefficients as 12.5 and 25 mm/day.

scholarly journals PERKIRAAN PELUANG HUJAN UNTUK MENENTUKAN WAKTU TANAM KAPAS DI NUSA TENGGARA BARAT

2020 ◽  
Vol 9 (2) ◽  
pp. 39
Author(s):  
PRIMA D. RIAJAYA ◽  
F. T. KADARWATI ◽  
MOCH. MACHFUD
Keyword(s):  
Gossypium Hirsutum ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Cotton Yield ◽  
Rainfall Analysis ◽  
First Order ◽  
Successful Prediction ◽  
Probability Methods ◽  
Climatic Elements

<p>Curah hujan merupakan salah salu unsur iklim yang sangal berpengaruh terhadap produksi kapas Variasi hujan di lahan tadah hujan sangat linggi. Waklu tanam yang telah dilentukan sebelumnya hanya berdasarkan data curah hujan selama 1 0 Uihun Untuk mcmpcrbaiki waktu tanam tersebut, perlu dilakukan analisis hujan berdasarkan data curah hujan selama lebih dari 20 tahun untuk mendapatkan angka peluang yang lebih stabil. Analisis dilakukan berdasarkan data curah hujan lebih dari 20 tahun yang lerkumpul dari 16 slasiun hujan yang tersebar di Kabupaten Lombok Timur. lombok Tengah. Lombok Barat, Sumbawa, Bima, dan Dompu. Data dianalisis menggunakan metode peluang Markov Ordc Pertama dan perhilungan peluang sclang kering beturut-turut Waktu tanam kapas di sebagian besar I-ombok dan Sumbawa berkisar minggu pertama sampai minggu kedua Desember, minggu ketiga sampai keempal Desember di Kawo, Lombok Tengah dan Rasanae, Bima, dan minggu pertama Januari di Moyohilir, Sumbawa dan Bayan, Lombok Barat. Daerah yang beresiko linggi untuk pengembangan kapas adalah di wilayah sekilar Pringgabaya (Lombok Timur), Ulhan (Sumbawa), Donggo dan Wawo di Bima Daerah lainnya dengan kandungan air tersedia yang rendah dengan kandungan pasir lebih dari 50% seperti di 1-ape (Sumbawa) penanaman kapas hendaknya dilakukan lebih awal. Tipe iklim didominasi iklim kering dengan musim hujan yang sangat pendek sehingga tidak memungkinkan adanya pergiliran tanaman palawija-kapas Kapas hendaknya ditanam bersamaan dengan palawija mcngingal pendeknya periode hujan.</p><p>Kata kunci : Gossypium hirsutum, waktu tanam. periode kering, masa tanam</p><p> </p><p><strong>ABSTRACT </strong></p><p><strong>Prediction of rainfall probability for determination of cotton sowing times in West Nusa Tenggara</strong></p><p>Climatic elements paticularly rainfall strongly influences successful prediction of rainfed cotton yield. Rainfall vaiability varies amongst Ihe season The previous planting times were determined based on 10 years daily rainfall data. I-ongterm rainfall data arc required for rainfall analysis to get reliable probabilities. The rainfall analysis was done using Markov Chain First Order Probability and dryspell probability methods Ihe rainfall data were collected from 16 rainfall stations in West Nusa Tcnggara (Eas( Lombok, Central I-ombok, West Lombok, Sumbawa, Bima, and Dompu). Ihe planting times varied from the irst week to the second week of December for most areas of I-ombok and Sumbawa The planting limes in Kawo, Central Lombok and Rasanae, Bima were mid December: and early January in Moyohilir, Sumbawa and Bayan, West l.ombok The areas which high risk to drought are around Pringgabaya (Hast lombok), Uthan (Sumbawa), Donggo and Wawo (Bima). On sandy- areas such as I-ape (Sumbawa) cotton should be planted earlier Type of climate in most areas is dry with limited rainy season, thai relay-planting of these areas is not practiced.</p><p>Key words: Gossypium hirsutum, planting time, dryspcll, seasonal patern</p>

scholarly journals Increasing Effectiveness of The Urban Artificial Reservoir Trough Cross Section Improvement

2021 ◽  
Vol 945 (1) ◽  
pp. 012046
Author(s):  
Rizka Arbaningrum ◽  
Marelianda Al Dianty ◽  
Frederik Josef Putuhena ◽  
Rifki Priyambodo ◽  
Budianto Ontowirjo
Keyword(s):  
Land Use ◽  
Surface Area ◽  
Cross Section ◽  
Return Period ◽  
Rainfall Data ◽  
Flood Mitigation ◽  
Maximum Rainfall ◽  
Artificial Reservoir ◽  
Flood Discharge ◽  
Main Factor

Abstract Situ Ciledug is an artificial reservoir located at Tangerang Selatan, Indonesia. In 1950 known as one of the largest lakes with total area of 32.806 hectares. As time goes by, due to the construction of housing and land use around the area, the catcahment area was reduced about 19.3 hectares in 2013 and by the end of 2020 the surface area was become 16.2 hectares. Urbanization is the main factor that makes the area of Situ Ciledug’s narrower. The second impact was flooding, as a result, the flood inundates the cities around the reservoir. This study aims to increase the storage capacities by normalizing the reservoir using SWMM 5.1 software. Hydrological analysis was carried out in the first stage to find the maximum rainfall using a 100-year return period. Then result intensity of rainfall used to analyze the hyetograph as input for rainfall data in SWMM 5.1. The modeling uses a maximum of rainfall about 107 mm with a reservoir depth of 1.3 meters. The large inflow that enters the reservoir is 87.504 m3/second aand the volume is 30.145 m3/second. Therefore, it is necessary to normalize the reservoir by increasing the depth of the reservoir by 0.7 meters. Normalization is carried out to accommodate flood discharge as a solution to flood mitigation due to the overflow.

scholarly journals ESTIMATE OF THE INTENSITY-DURATION-FREQUENCY PARAMETERS OF INTENSE RAINFALL FOR THE STATE OF ALAGOAS, BRAZIL

2020 ◽  
Vol 28 ◽  
pp. 314-325
Author(s):  
João Batista Lopes da Silva ◽  
Nicole Lopes Bento ◽  
Gabriel Soares Lopes Gomes ◽  
Alcinei Ribeiro Campos ◽  
Danilo Paulúcio da Silva
Keyword(s):  
Return Period ◽  
Probabilistic Models ◽  
Daily Rainfall ◽  
The State ◽  
Data Series ◽  
Intense Rainfall ◽  
Maximum Rainfall ◽  
Rain Gauges ◽  
Intensity Duration Frequency ◽  
Using Data

The study of the rainfall characteristics is of fundamental importance since the frequency of floods has increased in several parts of Brazil due to anthropic impacts of climatic changes. Thus, this study aimed to determine the parameters of the intense rainfall equation (K, a, b, c) for 52 municipalities in the State of Alagoas using data from 164 rain gauges ta available from the National Water Agency (ANA). The data series were subjected to consistency analysis and further desegregation of maximum daily rainfall to durations of the 5; 10; 15; 20; 25; 30; 60; 360; 480; 600; 720 and 1,440 minutes and return period of 5; 10; 25; 50 and 100 years according to different probabilistic models. The adjustment of the parameters was carried out by means of non-linear regression, with R² greater than 0.949 for all the stations, considering for this purpose one station per municipality, totaling 51 municipalities of study. It was obtained that the maximum rainfall intensity predicted increases with the increase in the return period and decreases with the increase of the duration of the rain. The greater intensities were detected in the mesoregion of Eastern Alagoano and the lowest intensities in the mesoregion of Sertão Alagoano.

scholarly journals Two Rainfall-Characteristic Indices Proposed as Suitable for Agricultural Planning in Puerto Rico

1969 ◽  
Vol 57 (1) ◽  
pp. 24-41
Author(s):  
Modesto Capiel ◽  
Mariano Antoni
Keyword(s):  
Puerto Rico ◽  
Daily Rainfall ◽  
Deficiency Index ◽  
Annual Rainfall ◽  
Distribution Characteristics ◽  
Rainfall Distribution ◽  
Maximum Rainfall ◽  
Agricultural Planning ◽  
Agricultural Regions

A statistical evaluation was made of the daily rainfall at Caguas and Fajardo, covering 70- and 60-year periods. The purposes of this evaluation were: 1, To investigate the character, if any, of the rainfall distribution and of its deficiency (drought) characteristics; and 2, in the event that any character was found in rainfall in the sense of distribution and deficiency, to develop a Rainfall Deficiency Index which would be useful to agricultural and other programs and inventories. The study first consisted of determining the least rainfall in 60, 120, and 180 consecutive days, and the maximum rainfall in 30 and 90-day periods of each year. This analysis suggested the occurrence of most deficient and least deficient rainfall in 120 (or 180) day cycles during the drier part of the year within 10- to 11-year periods; the Caguas data beginning in 1899 and in 1909 at Fajardo. The suggested cycles appear to be more defined at Caguas than Fajardo. It appears that years ending in 6 or 7 almost invariably seemed to be among the driest in their respective decades; 1899 to 1968. Years ending in 1 or 2 seemed identified with least deficient and better distributed rainfall. This preliminary analysis was based mainly on the least rainfall in 120 days parameter. It was found that the ratio of the mean least rainfall in 120 days of the dry years (ending in 6 or 7) to the "wet" years (ending in 1 or 2) is 0.364 for Caguas and 0.603 for Fajardo. Also, the coefficient of variation of the data for dry and "wet" years was lower than when calculated for all years. Contrast between dry and wet years is apparent even for the least rainfall in 180 days (6 months of the year). In this respect the ratios of dry to "wet" years are 0.494 and 0.595 for Caguas and Fajardo, respectively. There is no apparent contrast, however, when the annual, or even maximum, rainfall in 90 days at the two locations is compared for "wet" and dry years. A Rainfall Deficiency Index (DEF) is proposed. Such deficiency is normally distributed for Caguas and Fajardo. This index integrates the deficiency and distribution characteristics of the annual rainfall. It can be used, therefore, as a guide for evaluating the rainfall characteristics in the agricultural regions of Puerto Rico and for the determination of priorities for supplemental irrigation. A Rainfall Distribution Coefficient (DIS) was developed as a direct means of describing the distribution characteristics of annual rainfall, and it accounts indirectly for the rainfall deficiency within a given area or areas of similar annual rainfall. DEF accounted for 74.0 and 64.4 percent of the variations in DIS at both Caguas and Fajardo.

scholarly journals Impact of Extreme Rainfall on Flood Hydrographs

2021 ◽  
Vol 884 (1) ◽  
pp. 012018
Author(s):  
I G Tunas ◽  
H Azikin ◽  
G M Oka
Keyword(s):  
Return Period ◽  
Extreme Events ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Rainfall Data ◽  
Return Periods ◽  
Daily Rainfall Data ◽  
Design Rainfall ◽  
Flood Hydrograph ◽  
Maximum Daily Rainfall

Abstract Extreme rainfall is the main factor triggering flooding in various regions of the world including Indonesia. The increase in intensity and duration of current extreme rainfall is predicted as a result of global climate change. This paper aims to analyze the impact of extreme rainfall to the peak discharge of flood hydrographs at a watershed outlet in Palu, Sulawesi, Indonesia. Maximum daily rainfall data for the period 1990-1999 recorded at the Palu Meteorological Station, Central Sulawesi were selected using the Annual Maximum Series Method, and grouped into two types. Type I is the maximum daily rainfall data with extreme events and Type II is the maximum daily rainfall data without extreme events. Frequency analysis was applied to the two data groups using the best distribution method of: Normal, Normal Log, Pearson III Log, and Gumbel to obtain the design rainfall of each data group. In the next stage, the design rainfall transformation into a flood hydrograph is performed using the Nakayasu Synthetic Unit Hydrograph based on a number of return periods in one of the rivers flowing into Palu Bay, namely the Poboya River. The analysis results show that the design rainfall graphs with both extreme rainfall and without extreme rainfall are identical at the low return period and divergent at the high return period with a difference of up to 21.6% at the 1000-year return period. Correspondingly, extreme rainfall has a greater impact at the peak of the flood hydrograph with increasing return periods ranging from -1.28% to 26.81% over the entire return period.

Analisis Karakteristik Curah Hujan pada Kawasan Hunian dan Komersial Pantai Indah Kapuk (PIK) 2 Cluster “C”

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Nur Afifah Sari ◽  
Etih Hartati ◽  
M. Candra Nugraha
Keyword(s):  
Return Period ◽  
Rainfall Intensity ◽  
Hydrological Cycle ◽  
Regional Scale ◽  
Daily Rainfall ◽  
Global Scale ◽  
Rainfall Data ◽  
Rainfall Characteristics ◽  
Climate Conditions ◽  
Drainage Channels

<p class="IJOPCMKeywards">Based on the hydrological cycle, one of the main water sources is rainwater. weather or climate conditions that occur will greatly affect the nature and condition of a rain or rainy season. On a global scale, the existence of water naturally is constant, only occurs in variations both in time and space on a regional scale. Analysis of the rainfall characteristics of Pantai Indah Kapuk (PIK) residential and commercial areas 2  Cluster "C" in Tangerang Regency, Banten Province, is for to find out the intensity of rainfall used for drainage planning. The daily rainfall data used includes 5 rain catching stations with a duration of 25 years (1994 - 2018). The Van Breen method is used to process rainfall data within a certain period into rainfall intensity with various times for drainage planning used. In the planning of drainage channels the rainfall return period used is PUH 2 for tertiary lines with selected rainfall data of 192 mm / day and PUH 5 for secondary lines with selected rainfall data of 219 mm / day. The IDF curve shows that rainfall intensity is affected by the time and return period of rainfall, where the shorter the rainfall time and the greater the return period of rainfall, the higher the intensity of rainfall produced.</p>

scholarly journals Analysis of variability and projection of extreme rainfall in West Java

2021 ◽  
Vol 893 (1) ◽  
pp. 012012
Author(s):  
R C H Hutauruk ◽  
T Amin ◽  
A M Irawan
Keyword(s):  
Climate Change ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Rainfall Data ◽  
West Java ◽  
Maximum Rainfall ◽  
Rainfall Index ◽  
Extreme Rain ◽  
Rcp 8.5 ◽  
Rainy Days

Abstract This research discusses the effect of climate change on extreme rainfall in West Java using the RCP 4.5 and RCP 8.5 scenarios by comparing daily rainfall data with model ACCESS-1, CSIROMK3.6 model, MIROC-5 from NASA Earth Exchange Global Daily Downscaled Projection (NEX-GDDP) and the ensemble of three models each season with Extreme Dependency Score (EDS) method. This study projects an extreme rainfall index of 30 years (2011-2040). The three extreme rainfall indices issued by the Expert Detection Team and the Climate Change Index (ETCCDI) consisted of Rx1day, R50mm, and R95p used in this study. The results showed that the projection period (2011-2040) used RCP 8.5 which had a trend of increasing extreme rain index that was greater than RCP 4.5. For RCP 8.5 the maximum rainfall will increase in Indramayu, Majalengka, Purwakarta, Sukabumi and Ciamis areas. Increased rainy days occurred in Bogor, Bekasi, Karawang, Purwakarta, Bandung, Sumedang, Majalengka, Cirebon, Indramayu. Extreme rainfall will increase in Bekasi, Karawang and Bogor regions.

scholarly journals CHANGE OF MAXIMUM RAIN PATTERN BASED ON RAINFALL DATA OF BANJARBARU CLIMATOLOGY STATION CAUSED BY CLIMATE CHANGE

CERUCUK ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 17
Author(s):  
Ahdianoor Fahraini ◽  
Achmad Rusdiansyah
Keyword(s):  
Climate Change ◽  
Error Function ◽  
Daily Rainfall ◽  
Gumbel Distribution ◽  
Rainfall Data ◽  
Statistical Parameters ◽  
Maximum Rainfall ◽  
High Rainfall ◽  
The Government ◽  
The Impact

According to the World Meteorological Organization that 2014 was the hottest year in which the hot weather alternated with high rainfall and floods which destroyed the people's economy. Banjarbaru, as one of the central cities of the government of South Kalimantan Province, has a topographic condition that is at an altitude of 0-500 m above sea level, causing rainfall, which is enough frequent. Banjarbaru itself is one of the cities affected by climate change in 2014. Disasters that occurred in the form of flooding at several points of residents and also crippled traffic at that time. Thus, it is important to know the pattern of maximum rainfall changes that occur. By knowing the pattern of maximum rainfall changes, the impact of the high rainfall that can occur will be minimized and can even be anticipated as early as possible.            Data processing is performed with maximum daily rainfall data of 30 years and divided into a database before and after climate change that is 25 years old data and 5 years of new data. Each database calculates the planned rainfall for the return period of 2-1000 years with the distribution obtained from the analyzed database. Next, analyze the deviation of the two data. The purpose of analyzing the deviation of old data and new data is to determine changes in the planned rainfall from both data. Deviation analysis uses the Peak-Weight Root Mean Square Error function.            The conclusion of the analysis is that based on the Statistical Parameters test, the Chi-Square test, and the Smirnov-Kolmogorov test on the old database using the Gumbel distribution and the new data using the Pearson Log Type III distribution for the calculation of the planned rain. Based on the analysis of the rain plan to get new data 5 years has the results of the rain plan is greater than the old data of 25 years and the analysis of the deviation to get the results of the new data 5 years has a greater value of deviation each time when revisiting the old data of 25 years. So it can be suggested that rainfall data with the same characteristics, can use 5 years of new data for the analysis of water building planning.

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