• Title/Summary/Keyword: precipitation events

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Satellite-based Rainfall for Water Resources Application

  • Supattra, Visessri;Piyatida, Ruangrassamee;Teerawat, Ramindra
    • Proceedings of the Korea Water Resources Association Conference
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    • 2017.05a
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    • pp.188-188
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    • 2017
  • Rainfall is an important input to hydrological models. The accuracy of hydrological studies for water resources and floods management depend primarily on the estimation of rainfall. Thailand is among the countries that have regularly affected by floods. Flood forecasting and warning are necessary to prevent or mitigate loss and damage. Merging near real time satellite-based precipitation estimation with relatively high spatial and temporal resolutions to ground gauged precipitation data could contribute to reducing uncertainty and increasing efficiency for flood forecasting application. This study tested the applicability of satellite-based rainfall for water resources management and flood forecasting. The objectives of the study are to assess uncertainty associated with satellite-based rainfall estimation, to perform bias correction for satellite-based rainfall products, and to evaluate the performance of the bias-corrected rainfall data for the prediction of flood events. This study was conducted using a case study of Thai catchments including the Chao Phraya, northeastern (Chi and Mun catchments), and the eastern catchments for the period of 2006-2015. Data used in the study included daily rainfall from ground gauges, telegauges, and near real time satellite-based rainfall products from TRMM, GSMaP and PERSIANN CCS. Uncertainty in satellite-based precipitation estimation was assessed using a set of indicators describing the capability to detect rainfall event and efficiency to capture rainfall pattern and amount. The results suggested that TRMM, GSMaP and PERSIANN CCS are potentially able to improve flood forecast especially after the process of bias correction. Recommendations for further study include extending the scope of the study from regional to national level, testing the model at finer spatial and temporal resolutions and assessing other bias correction methods.

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Evaluating the impacts of extreme agricultural droughts under climate change in Hung-up watershed, South Korea

  • Sadiqi, Sayed Shajahan;Hong, Eun-Mi;Nam, Wan-Ho
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.143-143
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    • 2021
  • Climate change indicators, mainly frequent drought which has happened since the drought of 1994, 1995, and 2012 causing the devastating effect to the agricultural sector, and could be more disruptive given the context of climate change indicators by increasing the temperature and more variable and extreme precipitation. Changes in frequency, duration, and severity of droughts will have enormous impacts on agriculture production and water management. Since both the possibility of drought manifestation and substantial yield losses, we are propositioning an integrated method for evaluating past and future agriculture drought hazards that depend on models' simulations in the Hung-up watershed. to discuss the question of how climate change might influence the impact of extreme agriculture drought by assessing the potential changes in temporal trends of agriculture drought. we will calculate the temporal trends of future drought through drought indices Standardized Precipitation Evapotranspiration Index, Standardized Precipitation Index, and Palmer drought severity index by using observed data of (1991-2020) from Wonju meteorological station and projected climate change scenarios (2021-2100) of the Representative Concentration Pathways models (RCPs). expected results confirmed the frequency of extreme agricultural drought in the future projected to increase under all studied RCPs. at present 100 years drought is anticipated to happen since the result showing under RCP2.6 will occur every 24 years, RCP4.5 every 17 years, and RCPs8.5 every 7 years, and it would be double in the largest warming scenarios. On another side, the result shows unsupportable water management, could cause devastating consequences in both food production and water supply in extreme events. Because significant increases in the drought magnitude and severity like to be initiate at different time scales for each drought indicator. Based on the expected result that the evaluating the impacts of extreme agricultural droughts and recession could be used for the development of proactive drought risk management, policies for future water balance, prioritize sustainable strengthening and mitigation strategies.

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Fog Type Classification and Occurrence Characteristics Based on Fog Generation Mechanism in the Korean Peninsula (안개 생성 메커니즘 기반 안개 유형 분류 및 한반도 지역내 발생 특성 분석)

  • Eun ji Kim;Soon-Young Park;Jung-Woo Yoo;Soon-Hwan Lee
    • Journal of Environmental Science International
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    • v.32 no.12
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    • pp.883-898
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    • 2023
  • To investigate the occurrence characteristics and types of fog on the Korean Peninsula over the past three years (2020 to 2022), data from 96 synoptic meteorological observatories and 21 ocean buoys were collected and analyzed. We included precipitation fog, which occurs after precipitation events, and cloud-base lowering fog, which is caused by the development of lower-level clouds, with a total six subtypes of fog. In the case of cloud-base lowering fog, the occurrence frequency at 2.6% was not high at 2.6%, but the duration of low visibility below 200 m was very long at 6.9 hours. The seasonal frequency of fog is low in spring and winter, high in summer over islands and coastal areas, and high in autumn over inland areas. The frequency of inland fog, which is characterized by high radiation fog and dense fog, requires attention in terms of transportation safety, with an occurrence time of 0500 LST to 1000 LST. Therefore, systematic analysis of precipitation fog and cloud-base lowering, as well as radiation and advection fog, is required in the analysis of recognizing fog as a disaster and causing transportation disorders.

Drought index forecast using ensemble learning (앙상블 기법을 이용한 가뭄지수 예측)

  • Jeong, Jihyeon;Cha, Sanghun;Kim, Myojeong;Kim, Gwangseob;Lim, Yoon-Jin;Lee, Kyeong Eun
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.5
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    • pp.1125-1132
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    • 2017
  • In a situation where the severity and frequency of drought events getting stronger and higher, many studies related to drought forecast have been conducted to improve the drought forecast accuracy. However it is difficult to predict drought events using a single model because of nonlinear and complicated characteristics of temporal behavior of drought events. In this study, in order to overcome the shortcomings of the single model approach, we first build various single models capable to explain the relationship between the meteorological drought index, Standardized Precipitation Index (SPI), and other independent variables such as world climate indices. Then, we developed a combined models using Stochastic Gradient Descent method among Ensemble Learnings.

Towards an Integrated Drought Monitoring with Multi-satellite Data Products Over Korean Peninsular (위성자료를 활용한 한반도 전역의 가뭄 통합 모니터링 방안)

  • Kim, Youngwook;Shim, Changsub
    • Korean Journal of Remote Sensing
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    • v.33 no.6_1
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    • pp.993-1001
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    • 2017
  • Drought is a worldwide natural disaster with extensively adverse impacts on natural ecosystems, agricultural products, social communities and regional economy. Various global satellite observations, including SMAP soil moisture, GRACE terrestrial water storage, Terra and Aqua vegetation productivity, evapotranspiration, and satellite precipitation measures are currently used to characterize seasonal timing and inter-annual variations of regional water supply pattern, vegetation growth, drought events, and its associated influence ecosystems and human society. We suggest the satellite monitoring system development to quantify meteorological, eco-hydrological, and socio-ecological factors related to drought events, and characterize spatial and temporal drought patterns in Korea. The combination of these complementary remote sensing observations(visible to microwave bands) provide an effective means for evaluating regional variations in the timing, frequency, and duration of drought, and availability of water supply influencing vegetation and crop growth. This integrated drought monitoring could help national capacity to deal with natural disasters.

Characteristic Change Analysis of Rainfall Events using Daily Rainfall Data (일강우자료를 이용한 강우사상의 변동 특성 분석)

  • Oh, Tae-Suk;Moon, Young-Il
    • Journal of Korea Water Resources Association
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    • v.42 no.11
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    • pp.933-951
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    • 2009
  • Climate change of global warming may affect the water circulation in Korea. Rainfall is occurred with complex of multiple climatic indices. Therefore, the rainfall is one of the most significant index due to climate change in the process of water circulation. In this research, multiple time series data of rainfall events were extracted to represent the rainfall characteristics. In addition, the occurrence of rainfall time series analyzed by annual, seasonal and monthly data. Analysis method used change analysis of mean and standard deviation and trend analysis. Also, changes in rainfall characteristics and the relative error was calculated during the last 10 years for comparison with past data. At the results, significant statistical results weren't showed by randomness of rainfall data. However, amount of rainfall generally increased last 10 years, and number of raining days had trend of decrease. In addition, seasonal and monthly changes in the rainfall characteristics can be found to appear differently.

A Study on the Effect of Ground-based GPS Data Assimilation into Very-short-range Prediction Model (초단기 예측모델에서 지상 GPS 자료동화의 영향 연구)

  • Kim, Eun-Hee;Ahn, Kwang-Deuk;Lee, Hee-Choon;Ha, Jong-Chul;Lim, Eunha
    • Atmosphere
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    • v.25 no.4
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    • pp.623-637
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    • 2015
  • The accurate analysis of water vapor in initial of numerical weather prediction (NWP) model is required as one of the necessary conditions for the improvement of heavy rainfall prediction and reduction of spin-up time on a very-short-range forecast. To study this effect, the impact of a ground-based Global Positioning System (GPS)-Precipitable Water Vapor (PWV) on very-short-range forecast are examined. Data assimilation experiments of GPS-PWV data from 19 sites over the Korean Peninsula were conducted with Advanced Storm-scale Analysis and Prediction System (ASAPS) based on the Korea Meteorological Administration's Korea Local Analysis and Prediction System (KLAPS) included "Hot Start" as very-short-range forecast system. The GPS total water vapor was used as constraint for integrated water vapor in a variational humidity analysis in KLAPS. Two simulations of heavy rainfall events show that the precipitation forecast have improved in terms of ETS score compared to the simulation without GPS-PWV data. In the first case, the ETS for 0.5 mm of rainfall accumulated during 3 hrs over the Seoul-Gyeonggi area shows an improvement of 0.059 for initial forecast time. In other cases, the ETS improved 0.082 for late forecast time. According to a qualitative analysis, the assimilation of GPS-PWV improved on the intensity of precipitation in the strong rain band, and reduced overestimated small amounts of precipitation on the out of rain band. In the case of heavy rainfall during the rainy season in Gyeonggi province, 8 mm accompanied by the typhoon in the case was shown to increase to 15 mm of precipitation in the southern metropolitan area. The GPS-PWV assimilation was extremely beneficial to improving the initial moisture analysis and heavy rainfall forecast within 3 hrs. The GPS-PWV data on variational data assimilation have provided more useful information to improve the predictability of precipitation for very short range forecasts.

Future PMPs projection according to precipitation variation under RCP 8.5 climate change scenario (RCP 8.5 기후변화 시나리오의 강수량 변화에 따른 미래 PMPs의 전망)

  • Lee, Okjeong;Park, Myungwoo;Lee, Jeonghoon;Kim, Sangdan
    • Journal of Korea Water Resources Association
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    • v.49 no.2
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    • pp.107-119
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    • 2016
  • Since future climate scenarios indicate that extreme precipitation events will intensity, probable maximum precipitations (PMPs) without being taken climate change into account are very likely to be underestimated. In this study future PMPs in accordance with the variation of future rainfall are estimated. The hydro-meteorologic method is used to calculate PMPs. The orographic transposition factor is applied in place of the conventional terrain impact factor which has been used in previous PMPs estimation reports. Future DADs are indirectly obtained by using bias-correction and moving-averaged changing factor method based on daily precipitation projection under KMA RCM (HEDGEM3-RA) RCP 8.5 climate change scenario. As a result, future PMPs were found to increase and the spatially-averaged annual PMPs increase rate in 4-hour and $25km^2$ was projected to be 3 mm by 2045. In addition, the increased rate of future PMPs is growing increasingly in the future, but it is thought that the uncertainty of estimating PMPs caused by future precipitation projections is also increased in the distant future.

Prospect of extreme precipitation in North Korea using an ensemble empirical mode decomposition method (앙상블 경험적 모드분해법을 활용한 북한지역 극한강수량 전망)

  • Jung, Jinhong;Park, Dong-Hyeok;Ahn, Jaehyun
    • Journal of Korea Water Resources Association
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    • v.52 no.10
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    • pp.671-680
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    • 2019
  • Many researches illustrated that the magnitude and frequency of hydrological event would increase in the future due to changes of hydrological cycle components according to climate change. However, few studies performed quantitative analysis and evaluation of future rainfall in North Korea, where the damage caused by extreme precipitation is expected to occur as in South Korea. Therefore, this study predicted the extreme precipitation change of North Korea in the future (2020-2060) compared to the current (1981-2017) using stationary and nonstationary frequency analysis. This study conducted nonstationary frequency analysis considering the external factors (mean precipitation of JFM (Jan.-Mar.), AMJ (Apr.-Jun.), JAS (Jul.-Sept.), OND (Oct.-Dec.)) of the HadGEM2-AO model simulated according to the Representative Concentration Pathway (RCP) climate change scenarios. In order to select external factors that have a similar tendency with extreme rainfall events in North Korea, the maximum annual rainfall data was obtained by using the ensemble empirical mode decomposition (EEMD) method. Correlation analysis was performed between the extracted residue and the external factors. Considering selected external factors, nonstationary GEV model was constructed. In RCP4.5, four of the eight stations tended to decrease in future extreme precipitation compared to the present climate while three stations increased. On the other hand, in RCP8.5, two stations decreased while five stations increased.

Inorganic Nutrient Inputs from Precipitation, Throughfall, and Stemflow in Pinus densiflora and Quercus mongolica Stands in an Urban Forest Ecosystem

  • Kim, Kee Dae
    • Journal of Environmental Science International
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    • v.28 no.10
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    • pp.813-829
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    • 2019
  • We measured the amount of precipitation, stemflow, and throughfall and concentrations of nine major inorganic nutrients ($H^+$, ${NH_4}^+$, $Ca^{2+}$, $Mg^{2+}$, $K^+$, $Na^+$, $Cl^-$, ${NO_3}^-$, and ${SO_4}^{2-}$) to investigate the nutrient inputs into soil from precipitation in Pinus densiflora and Quercus mongolica stands from September 2015 to August 2016. The precipitation inputs of $H^+$, ${NH_4}^+$, $Ca^{2+}$, $Mg^{2+}$, $K^+$, $Na^+$, $Cl^-$, ${NO_3}^-$, and ${SO_4}^{2-}$ into soil were 0.170, 15.124, 42.227, 19.218, 14.050, 15.887, 22.391, 5.431, and $129.440kg{\cdot}ha^{-1}{\cdot}yr^{-1}$, respectively. The P. densiflora stemflow inputs were 0.008, 0.784, 1.652, 1.044, 0.476, 0.651, 1.509, 0.278, and $9.098kg{\cdot}ha^{-1}{\cdot}yr^{-1}$, and those for Q. mongolica were 0.008, 0.684, 2.429, 2.417, 2.941, 1.398, 2.407, 0.436, and $13.504kg{\cdot}ha^{-1}{\cdot}yr^{-1}$, respectively. The P. densiflora throughfall inputs were 0.042, 21.518, 52.207 27.694, 20.060, 24.049, 37.229, 10.241, and $153.790kg{\cdot}ha^{-1}{\cdot}yr^{-1}$, and those for Q. mongolica were 0.032, 15.068, 42.834, 21.219, 20.294, 20.237, 24.288, 5.647, and $119.134kg{\cdot}ha^{-1}{\cdot}yr^{-1}$, respectively. Of the total throughfall flux (i.e., stemflow + throughfall flux) of the nine ions for the two species, ${SO_4}^{2-}$ had the greatest total throughfall flux and $H^+$ had the lowest. The net throughfall fluxes of the ions for the two species had various correlations with the precedent dry period, rainfall intensity, rainfall amount, and pH of precipitation. The soil pH under the Q. mongolica canopy (4.88) was higher than that under the P. densiflora canopy (4.34). The difference in the soil pH between the two stands was significant (P < 0.01), but the difference in soil pH by the distance from the stems of the two species was not (P > 0.01). This study shows the enrichments of inorganic nutrients by two representative urban forests in temperate regions and the roles of urban forests during rainfall events in a year.