• Title/Summary/Keyword: Terrestrial Water Storage

Search Result 14, Processing Time 0.024 seconds

Impact of assimilating the terrestrial water storage on the water and carbon cycles in CLM5-BGC

  • Chi, Heawon;Seo, Hocheol;Kim, Yeonjoo
    • Proceedings of the Korea Water Resources Association Conference
    • /
    • 2021.06a
    • /
    • pp.204-204
    • /
    • 2021
  • Terrestrial water storage (TWS) includes all components of water (e.g., surface water, groundwater, snow and ice) over the land. So accurately predicting and estimating TWS is important in water resource management. Although many land surface models are used to predict the TWS, model output has errors and biases in comparison to the observation data due to the model deficiencies in the model structure, atmospheric forcing datasets, and parameters. In this study, Gravity Recovery And Climate Experiment (GRACE) satelite TWS data is assimilated in the Community Land Model version 5 with a biogeochemistry module (CLM5.0-BGC) over East Asia from 2003 to 2010 by employing the Ensemble Adjustment Kalman Filter (EAKF). Results showed that TWS over East Asia continued to decrease during the study period, and the ability to simulate the surface water storage, which is the component of the CLM derived TWS, was greatly improved. We further investigated the impact of assimilated TWS on the vegetated and carbon related variables, including the leaf area index and primary products of ecosystem. We also evaluated the simulated total ecosystem carbon and calculated its correlation with TWS. This study shows that how the better simulated TWS plays a role in capturing not only water but also carbon fluxes and states.

  • PDF

Estimation of Average Terrestrial Water Storage Changes in the Korean Peninsula Using GRACE Satellite Gravity Data (GRACE 위성 중력자료를 활용한 한반도의 평균 수자원변화량 산정)

  • Lee, Sang-Il;Kim, Joon-Soo;Lee, Sang-Ki
    • Journal of Korea Water Resources Association
    • /
    • v.45 no.8
    • /
    • pp.805-814
    • /
    • 2012
  • Most hydrologic data are obtained by ground observations. New observation methods are needed for some regions to overcome difficulties in accessibility and durability of long-term observation. In 2002, NASA launched twin satellites named GRACE which were designed to measure the gravitational field of the earth. Using the GRACE monthly gravity level-2 data, we calculated terrestrial water storage change (TWSC) of the Korean peninsula in various spatial smoothing radii (0 km, 300 km, 500 km). For the validation of GRACE-based TWSC, we compared it with land-based TWSC which was obtained using the ground observation data: precipitation and evaporation from WAMIS, and runoff from GLDAS. According to the mean square-error test, GRACE-based TWSC best fits the land-based one at 500 km smoothing radius. The variation of the terrestrial water storage in the Korean peninsula turned out to be 0.986 cm/month, which means that appropriate measures should be prepared for sustainable water resources management.

TWSC Estimation using GRACE Satellite Gravity Data (GRACE 인공위성 중력 자료를 이용한 수자원변화량(TWSC) 산정)

  • Kim, Joon-Soo;Lee, Sang-Il
    • Proceedings of the Korea Water Resources Association Conference
    • /
    • 2011.05a
    • /
    • pp.377-381
    • /
    • 2011
  • 지구는 지속적으로 변화하는 동력학적 시스템이며, 지표면 형상 및 지구 내부의 질량분포도 계속 변화하고 있다. 지구시스템의 질량재분배 과정에서 발생되는 밀도 차이는 중력장의 미세한 변이를 초래한다. 미 항공우주센터(NASA)와 독일 국립 항공우주연구센터(DLR)에서 공동으로 개발한 GRACE (Gravity Recovery And Climate Experiment) 인공위성은 지구의 중력장을 측정하는 위성으로, 2002년부터 현재까지 9년 동안 활동해왔다. 본 연구에서는 한반도(북위 $37.5^{\circ}\sim41.5^{\circ}$, 동경 $125.5^{\circ}\sim130.5^{\circ}$)의 월평균 수자원변화량(TWSC: Terrestrial Water Storage Change)을 산정하기 위해 미국 텍사스대학교 공간연구센터(CSR)에서 가우시안 필터링을 통해 구면조화함수의 계수 형태로 제공된 총 94개월(2002 년 8월~2010년 6월)의 자료(Level-2)를 이용하였다. Level-2 자료는 해양조석, 고체지구조석 및 지구자전으로 인한 극조석 등 조석의 영향과 대기와 해양의 변동성으로 인한 비조석 영향을 보정한 것이다. 이렇게 산정한 TWSC를 수자원관리정보시스템(WAMIS)과 전지구지표동계화시스템(GLDAS)을 통해 제공되는 자료와 비교 분석하였다. 본 연구를 통해 GRACE 중력장 자료가 수자원총량의 산정과 검증을 위한 대안으로 활용될 수 있음과, 수문요소의 불확실성을 낮출 수 있는 새로운 수문자료로의 활용 가능성을 확인하였다.

  • PDF

Analysis of Water Storage Variation in Yangtze River Basin and Three Gorges Dam Area using GRACE Monthly Gravity Field Model (GRACE 월별 중력장모델을 이용한 양자강유역 및 삼협댐 지역 저수량 변화 분석)

  • Huang, He;Yun, Hong-Sic;Lee, Dong-Ha;Jeong, Tae-Jun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
    • /
    • v.27 no.3
    • /
    • pp.375-384
    • /
    • 2009
  • The GRACE satellite, Launched in March 2002, is applied to research on glacial melt of polar regions, glacial isostatic adjustment(GIA), sea level change, terrestrial water storage(TWS) variation of river basin and large-scale earthquake etc. In this research, the TWS variation of Yangtze river basin from August, 2002 to January, 2009 is analyzed using Level-2 GRACE monthly gravity field model. Particularly, gravity changes of the Three Gorges Dam during the impoundment process in 2003, 2006 and 2008 is observed by estimating equivalent water thickness(EWT). The research results show the distinct annual and seasonal changes of Yangtze river basin, and its amplitude of annual variation is 2.3cm. In addition, we compare the results with water resource statistics and hydrologic observation data to confirm the possibility of research of TWS variation of river basin using GRACE observation data, and also the satellite gravity data is of great help for the research on the movement and periodic changes of river basin.

Reconstruction of Terrestrial Water Storage of GRACE/GFO Using Convolutional Neural Network and Climate Data

  • Jeon, Woohyu;Kim, Jae-Seung;Seo, Ki-Weon
    • Journal of the Korean earth science society
    • /
    • v.42 no.4
    • /
    • pp.445-458
    • /
    • 2021
  • Gravity Recovery and Climate Experiment (GRACE) gravimeter satellites observed the Earth gravity field with unprecedented accuracy since 2002. After the termination of GRACE mission, GRACE Follow-on (GFO) satellites successively observe global gravity field, but there is missing period between GRACE and GFO about one year. Many previous studies estimated terrestrial water storage (TWS) changes using hydrological models, vertical displacements from global navigation satellite system observations, altimetry, and satellite laser ranging for a continuity of GRACE and GFO data. Recently, in order to predict TWS changes, various machine learning methods are developed such as artificial neural network and multi-linear regression. Previous studies used hydrological and climate data simultaneously as input data of the learning process. Further, they excluded linear trends in input data and GRACE/GFO data because the trend components obtained from GRACE/GFO data were assumed to be the same for other periods. However, hydrological models include high uncertainties, and observational period of GRACE/GFO is not long enough to estimate reliable TWS trends. In this study, we used convolutional neural networks (CNN) method incorporating only climate data set (temperature, evaporation, and precipitation) to predict TWS variations in the missing period of GRACE/GFO. We also make CNN model learn the linear trend of GRACE/GFO data. In most river basins considered in this study, our CNN model successfully predicts seasonal and long-term variations of TWS change.

Improving an index for surface water detection

  • Hu, Yuanming;Paik, Kyungrock
    • Proceedings of the Korea Water Resources Association Conference
    • /
    • 2022.05a
    • /
    • pp.144-144
    • /
    • 2022
  • Identifying waterbody from remote sensing images, namely water detection, helps understand continuous redistribution of terrestrial water storage and accompanying hydrological processes. It also allows us to estimate available surface water resources and help effective water management. For this problem, NDWI (Normalized Difference Water Index) and MNDWI (Modified Normalized Difference Water Index) are widely used. Although remote sensing indexes can highlight remote sensing image in the water, the noise and the spatial information of the remote sensing image are difficult to be considered, so the accuracy is difficult to be compared with the visual interpretation (the most accurate method, but it requires a lot of labor, which makes it difficult to apply). In this study, we attempt to improve existing NDWI and MNDWI to better water detection. We establish waterbody database of South Korea first and then used it for assessing waterbody indices.

  • PDF

Sentinel-1 SAR image-based waterbody detection technique for estimating the water storage in agricultural reservoirs (농업저수지의 저수량 추정을 위한 Sentinel-1 SAR 영상 기반 수체탐지 기법)

  • Jeong, Jaehwan;Oh, Seungcheol;Lee, Seulchan;Kim, Jinyoung;Choi, Minha
    • Journal of Korea Water Resources Association
    • /
    • v.54 no.7
    • /
    • pp.535-544
    • /
    • 2021
  • Agricultural water occupies 48% of water demand, and management of agricultural reservoirs is essential for water resources management within agricultural basins. For more efficient use of agricultural water, monitoring the distribution of water resources in agricultural reservoirs and agricultural basins is required. Therefore, in this study, three threshold determination methods (i.e., fixed threshold, Otsu threshold, Kittler-Illingworth (KI) threshold) were compared to detect terrestrial water bodies using Sentinel-1 images for 3 years from 2018 to 2020. The purpose of this study was to evaluate methods for determining threshold values to more accurately estimate the reservoir area. In addition, by analyzing the relationship between the water surface and water storage at the Edong, Gosam, and Giheung reservoirs, water storage based on the SAR image was estimated and validated with observations. The thresholding method for detecting a waterbody was found to be the most accurate in the case of the KI threshold, and the water storage estimated by the KI threshold indicated a very high agreement (r = 0.9235, KGE' = 0.8691). Although the seasonal error characteristics were not observed, the problem of underestimation at high water levels may occur; the relationship between the water surface and the water storage could change rapidly. Therefore, it is necessary to understand the relationship between the water surface area and water storage through ground observation data for a more accurate estimation of water storage. If the use of SAR data through water resources satellites becomes possible in the future, based on the results of this study, it is judged that it will be beneficial for monitoring water storage and managing drought.

Investigating production parameters and impacts of potential emissions from soybean biodiesel stored under different conditions

  • Ayoola, Ayodeji Ayodele;Adeniyi, David Olalekan;Sanni, Samuel Eshorame;Osakwe, Kamsiyonna Ikenna;Jato, Jennifer Doom
    • Environmental Engineering Research
    • /
    • v.23 no.1
    • /
    • pp.54-61
    • /
    • 2018
  • Biodiesel production parameters and the impact analysis of the potential emissions from both soybean biodiesel and washing water stored in three different environmental conditions were investigated. The effects of the reaction temperature, methanol/oil mole ratio and catalyst concentration on biodiesel yield were considered. And the results showed optimum biodiesel yield of 99% obtained at $54^{\circ}C$, 7 methanol/oil mole ratio and 0.4 wt/wt % catalyst concentration. The potential emissions from both the biodiesel produced and washing water stored (for six weeks) in refrigerator (${\leq}10^{\circ}C$), vacuum (50 kPa) and direct exposure to atmosphere were identified and quantified. Impact analysis of the emissions involved their categorization into: terrestrial acidification, freshwater eutrophication, human toxicity, terrestrial ecotoxicity, climate change and freshwater ecotoxicity. Freshwater ecotoxicity category had the most pronounced negative impact of the potential emissions with $5.237710^{-2}kg\;1,4-DB\;eq$. emissions in Atmosphere, $4.702610^{-2}kg\;1,4-DB\;eq$. emissions in Refrigerator and $3.966110^{-2}kg\;1,4-DB\;eq$. emissions in Vacuum. Climate change had the least effect of the emissions with $6.214106^{-6}kg\;CO_2\;eq$. in Atmosphere, $3.9310^{-6}kg\;CO_2\;eq$. in Refrigerator and $1.6710^{-6}kg\;CO_2\;eq$. in Vacuum. The study showed that the order of preference of the storage environments of biodiesel is vacuum environment, refrigerated condition and exposure to atmosphere.

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
    • /
    • v.33 no.6_1
    • /
    • pp.993-1001
    • /
    • 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.