scholarly journals Extraction of rainfall intensity data from the chart records of cumulative rainfall gauges

1991 ◽  
Vol 34 (4) ◽  
pp. 559-561
Author(s):  
S. G. Bradley ◽  
C. D. Stow ◽  
W. R. Gray
Keyword(s):  
Rainfall Intensity ◽  
Intensity Data ◽  
Cumulative Rainfall

Simulating debris flows triggered by rainfall in Shiyang gully, China

2020 ◽  
Author(s):  
Jiaoyang Li
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Rainfall Intensity ◽  
Intensity Increase ◽  
Short Term ◽  
Rain Area ◽  
Cumulative Rainfall ◽  
Event Flow ◽  
Warning Time ◽  
Main Factor

<p>A debris flow occurred in Shiyang gully, located between Hebei Province and Beijing, on 8 June 2017, resulting in 6 people dead or injured. Short-term heavy rainfall is the main factor that triggered this event, however, the meteorological agency didn’t forecast this event very well. In this study, numerical simulation using FLO-2D was performed to reproduce the debris flow event (flow depths, flow velocities, and sediment depositions)occurred in 2017. The results of the field survey showed that the influential range of debris flow is consistent with the simulation results. Simulated depth accuracy is greater than 70%. Then, we used FLO-2D is calibrated to simulate debris flows disasters under different rainfall scenarios. The results showed that, the Beijing needs to be warned when the accumulated precipitation is 40mm at the rainfall intensity of 1mm/min. As cumulative rainfall and rainfall intensity increase, the risk of Shiyang gully is increasing.  This study used FLO-2D simulated process of debris flows triggered by rainfall. The results showed the early warning time and influential range for different intensity ,accumulated precipitation, and rain area, which is beneficial to the debris flow management in the western mountainous areas of Beijing.</p>

scholarly journals Analisa Karakteristik Dan Distribusi Hujan Pada Kawasan DAS Batang Hari Kabupaten Dharmasraya

2019 ◽  
Vol 14 (2) ◽  
pp. 15
Author(s):  
Hartati -
Keyword(s):  
Catchment Area ◽  
Rainfall Intensity ◽  
Global Climate ◽  
Intensity Data ◽  
Water Control ◽  
Rainfall Distribution ◽  
Thiessen Polygon ◽  
Curve Method ◽  
Log Normal ◽  
Polygon Method

Batang Hari is the 2nd biggest DAS in Indonesia. About 76% of Batang Hari DAS is located in Jambi Province, the entire 24%is in West Sumatera Province. Batang Hari dam which was built on 1997 is one of infrastrcture at Public Work ministery under management at Balai Wilayah Sungai Sumatera V (BWSS V) his high potential of water stock. Optimum discharge of Batang Hari Dam is about 86 m3/sec. In the recently years DAS Batang Hari has been disturbed by some changes like catchment area utilized fot other purpose, change on global climate done to greenhouse effectwhich causingintensity of rain as well as flood. This climate change then will affected standard for engineering design for making a water control buiding which may injuireaccurate waterfall intensity data. Study of rainfall intensity obtained from 3 (three) nearby stations will show the characteristic dam trend of distribution with reperted period. Cousistency of data using Mass Curve method and local rain analysis to be done by Arithmatic & Thiessen Polygon method. To analysis trend of rainfall distribution. We use : Normal, Log Normal, Log Person type III and Gumbel methods. For complaince test of distribution, we use Chi-Kuadrat and Smirnov-Kolmogorov methods. Refer to result of distribution using Chi-Kuadrat and Smirnov-Kolmogorov methods for Arithmatic methods it is adviced to use Gumbel method to evaluate distribution trend; because critical deviation is smell comparing to available in table, with rainfall with repeating period 2,5,10,25,50 and 100 years are 124,08 mm, 1168,56 mm, 198,01 mm, 235,22 mm, 262,83 mm, 290,23 mm and Thiessen Polygon 106,93 mm, 138,22 mm, 158,94 mm, 185,11 mm, 204,53 mm, 223,81 mm

Correlation Analysis among Meteorological Factors and PM10 Concentrations in the Atmosphere and Rainwater Quality using Multivariate Methods

2021 ◽  
Author(s):  
Taeyong Kim ◽  
Minjune Yang
Keyword(s):  
Correlation Analysis ◽  
Rainfall Intensity ◽  
Meteorological Factors ◽  
Pearson Correlation ◽  
Principal Component ◽  
Relative Magnitude ◽  
Chemical Quality ◽  
Weather System ◽  
Rainfall Events ◽  
Cumulative Rainfall

<p>This study investigates the effect of meteorological factors on the concentration of PM<sub>10</sub> (particulate matter 10) in the atmosphere and evaluates the variation of chemical quality in rainwater using correlation analysis at Daeyeon dong, Busan, South Korea. The real-time concentration of PM<sub>10</sub> in the atmosphere was measured automatically during eleven rainfall events with a custom-built PM<sub>10</sub> sensor node. The 183 rainfall samples were analyzed for chemical quality (pH and electrical conductivity (EC)). The values of meteorological factors (humidity, wind speed, wind direction, temperature, cumulative rainfall, and rainfall intensity) were obtained from an automatic weather system (AWS) in Nam-gu, Busan. Pearson correlation analysis and principal component analysis (PCA) were performed to identify relationships among PM<sub>10</sub> concentrations, meteorological factors, and chemical quality in rainwater. Cumulative rainfall and rainfall intensity had negative correlations with the concentration of PM<sub>10</sub> (r =  −0.52, and −0.35), and other meteorological factors were shown no correlation with the concentration of PM<sub>10</sub>. When the rainfall intensity was strong (> 5 mm/h), the concentration of PM<sub>10 </sub>showed a negative correlation with the cumulative rainfall (r = −0.55) and pH (r = −0.7). However, for the weak rainfall intensity (< 5 mm/h), there was no correlation between the PM<sub>10</sub> concentration with cumulative rainfall and pH. The results of this study provide an understanding of the interaction between PM<sub>10 </sub>concentrations and hydro-meteorological factors and can be used as a decision tool to evaluate the relative magnitude of PM<sub>10</sub> reduction resulting from various rainfall types.</p>

scholarly journals Analysis of Soil Erosion Induced by Heavy Rainfall: A Case Study from the NE Abruzzo Hills Area in Central Italy

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1314 ◽  
Author(s):  
Tommaso Piacentini ◽  
Alberto Galli ◽  
Vincenzo Marsala ◽  
Enrico Miccadei
Keyword(s):  
Soil Erosion ◽  
Heavy Rainfall ◽  
Rainfall Intensity ◽  
Strong Impact ◽  
Landscape Changes ◽  
Rainfall Events ◽  
Hilly Area ◽  
Cumulative Rainfall ◽  
Heavy Soil ◽  
Heavy Rainfall Events

Soil erosion induced by heavy rainfall deeply affects landscape changes and human activities. It depends on rainfall distribution (e.g., intensity, duration, cumulative per event) and is controlled by the interactions between lithology, orography, hydrography, land use, and vegetation. The Abruzzo piedmont coastal hilly area has been affected by several heavy rainfall events in the last decades. In this work, we investigated three ~1-day heavy rainfall (>35 mm/h and 100–220 mm/day) events in 2007, 2011, and 2012 that occurred in the clayey hilly coastal NE Abruzzo area, analyzing cumulative rainfall, intensity, and duration while mapping triggered geomorphological effects (soil erosion and accumulation) and evaluating average erosion. The analysis provides contributions to a soil erosion assessment of clayey landscapes that characterizes the Adriatic hilly area, with an estimation of rainfall-triggering thresholds for heavy soil erosion and a comparison of erosion in single events with rates known in the Mediterranean area. The triggering threshold for heavy soil erosion shows an expected value of ~100–110 mm. The estimated average soil erosion is from moderate to high (0.08–3.08 cm in ~1-day heavy rainfall events) and shows a good correlation with cumulative rainfall and a poor correlation with peak rainfall intensity. This work outlines the strong impact of soil erosion on the landscape changes in the Abruzzo and Adriatic hilly areas.

Service Area Expansion of Quasi-Millimeter FWA Systems Through Site Diversity Based on Detailed Rainfall Intensity Data

2008 ◽  
Vol 56 (10) ◽  
pp. 3285-3292 ◽  
Author(s):  
Takashi Maruyama ◽  
Yushi Shirato ◽  
Mamoru Akimoto ◽  
Masashi Nakatsugawa
Keyword(s):  
Rainfall Intensity ◽  
Service Area ◽  
Intensity Data ◽  
Site Diversity ◽  
Area Expansion

scholarly journals Determining the Effective Range of Radar Horizontal Reflectivity-Rainfall Intensity Relationship

2020 ◽  
Vol 20 (2) ◽  
pp. 13-23
Author(s):  
Minseok Kang ◽  
Chulsang Yoo
Keyword(s):  
Size Distribution ◽  
Drop Size ◽  
Rainfall Intensity ◽  
Drop Size Distribution ◽  
Intensity Data ◽  
Theoretical Estimation ◽  
Paired Data ◽  
Estimated Parameters ◽  
The Difference ◽  
Derivation Procedure

This study evaluated the applicability of the reflectivity-rainfall (Z-R) relationship using horizontal reflectivity. We reviewed the derivation procedure of the Z-R relationship and transformed the equation to estimate the parameters of drop size distribution from the observational data. The parameters of drop size distribution were estimated for the paired data of horizontal reflectivity and rainfall rate observed at the Gwanaksan and Biseulsan radar stations by applying this equation. Subsequently, the representative values of these estimated parameters were used to derive the Z-R relationship. Finally, we evaluated the performance of the Z-R relationship for representing the observed horizontal reflectivity-rainfall intensity data. It was observed that the difference between the theoretical estimation and the observed data increases as the radar reflectivity decreases. Moreover, the results confirmed that the Z-R relationship based on the assumption of exponentially distributed drop size distribution may not be applicable for all reflectivity ranges.

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