• 제목/요약/키워드: The Parameters of Soil Moisture Prediction

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수치 지형인자를 활용한 토양수분분포 예측 (Prediction of Soil Distribution Using Digital Terrain Indices)

  • 이학수;김경현;한지영;김상현
    • 한국수자원학회논문집
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    • 제34권4호
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    • pp.391-401
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    • 2001
  • 토양수분의 공간적 분포를 예측하기 위하여 지표면 곡률관련인자, 지형흐름인자, 태양에너지 복사인자들을 계산하였다. GPS와 토양수분측정기를 활용한 산지유역에서의 토양수분측정은 토양수분의 공간적 분포자료의 구축을 가능하게 했다. 측정된 토양수분자료와 토양수분 추정인자 사이의 상관관계를 분석하였다. 다중회귀분석을 통한 토양수분 추정인자와 토양수분의 공간적 분포상황에 대한 검토는 수치고도모형(DEM)의 분석을 통한 토양수분 추정능력의 가능성과 한계성을 보여주었다.

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토양수분 예측을 위한 수치지형 인자와 격자 크기에 대한 연구 (The Resolution of the Digital Terrain Index for the Prediction of Soil Moisture)

  • 한지영;김상현;김남원
    • 한국수자원학회논문집
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    • 제36권2호
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    • pp.251-261
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    • 2003
  • 여러 가지 토양수분의 예측인자에 대한 해상도 문제를 고찰하였다. 다양한 인자에 대한 민감도는 통계적인 분석을 기반으로 논의되었다. 수치지형모형에서 세 가지 흐름 결정 알고리즘의 해상도에 대한 통계적인 분석이 수행되었다. 단방향 흐름알고리즘으로 계산한 상부사면 기여면적은 다른 두 알고리즘(다방향 알고리즘, DEMON)보다 더욱 민감한 것으로 나타났다. 습윤지수의 경우는 해상도나 계산과정의 변화에 상대적으로 민감도가 미소한 것으로 나타났다.

다양한 지표모형을 활용한 토양수분 예측 성능 평가 연구 (A Study on Soil Moisture Estimates Performance Using Various Land Surface Models)

  • 장예근;신승훈;이태화;장원석;신용철;장근창;천정화;김종건
    • 한국농공학회논문집
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    • 제64권1호
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    • pp.79-89
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    • 2022
  • Soil moisture is significantly related to crop growth and plays an important role in irrigation management. To predict soil moisture, various process-based model has been developed and used in the world. Various models (Land surface model) may have different performance depending on the model parameters and structures that causes the different model output for the same modeling condition. In this study, the three land surface models (Noah Land Surface Model, Soil Water Atmosphere Plant, Community Land Model) were used to compare the model performance (soil moisture prediction) and develop the multi-model simulation. At first, the genetic algorithm was used to estimate the optimal soil parameters for each model, and the parameters were used to predict soil moisture in the study area. Then, we used the multi-model approach based on Bayesian model averaging (BMA). The results derived from this approach showed a better match to the measurements than the results from the original single land surface model. In addition, identifying the strengths and weaknesses of the single model and utilizing multi-model methods can help to increase the accuracy of soil moisture prediction.

노지 작물의 적정 관개계획을 위한 토양수분의 공간변이성 분석 (Spatial Variability of Soil Moisture and Irrigation Scheduling for Upland Farming)

  • 최용훈;김민영;김영진;전종길;서명철
    • 한국농공학회논문집
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    • 제58권5호
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    • pp.81-90
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    • 2016
  • Due to droughts and water shortages causing severe damage to crops and other vegetations, much attention has been given to efficient irrigation for upland farming. However, little information has been known to measure soil moisture levels in a field scale and apply their spatial variability for proper irrigation scheduling. This study aimed to characterize the spatial variability and temporal stability of soil water contents at depths of 10 cm, 20 cm and 30 cm on flat (loamy soil) and hill-slope fields (silt-loamy soil). Field monitoring of soil moisture contents was used for variogram analysis using GS+ software. Kriging produced from the structural parameters of variogram was applied for the means of spatial prediction. The overall results showed that the surface soil moisture presented a strong spatial dependence at the sampling time and space in the field scale. The coefficient variation (CV) of soil moisture was within 7.0~31.3 % in a flat field and 8.3~39.4 % in a hill-slope field, which was noticeable in the dry season rather than the rainy season. The drought assessment analysis showed that only one day (Dec. 21st) was determined as dry (20.4 % and 24.5 % for flat and hill-slope fields, respectively). In contrary to a hill-slope field where the full irrigation was necessary, the centralized irrigation scheme was appeared to be more effective for a flat field based on the spatial variability of soil moisture contents. The findings of this study clearly showed that the geostatistical analysis of soil moisture contents greatly contributes to proper irrigation scheduling for water-efficient irrigation with maximal crop productivity and environmental benefits.

Development of Crop Growth Model under Different Soil Moisture Status

  • Goto, Keita;Yabuta, Shin;Sakagami, Jun-Ichi
    • 한국작물학회:학술대회논문집
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    • 한국작물학회 2019년도 추계학술대회
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    • pp.19-19
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    • 2019
  • It is necessary to maintain stable crop productions under the unsuitable environments, because the drought and flood may be frequently caused by the global warming. Therefore, it is agent to improve the crop growth model corresponded to soil moisture status. Chili pepper (Capsicum annuum) is one of the useful crop in Asia, and then it is affected by change of precipitation in consequence drought and flood occur however crop model to evaluate water stresses on chili pepper is not enough yet. In this study, development of crop model under different soil moisture status was attempted. The experiment was conducted on the slope fields in the greenhouse. The water level was kept at 20cm above the bottom of the container. Habanero (C. chinense) was used as material for crop model. Sap bleeding rate, SPAD value, chlorophyll content, stomatal conductance, leaf water potential, plant height, leaf area and shoot dry weight were measured at 10 days after treatment (DAT) and 13 DAT. Moreover, temperature and RH in the greenhouse, soil volume water contents (VWC) and soil water potential were measured. As a result, VWC showed 4.0% at the driest plot and 31.4% at the wettest plot at 13 DAT. The growth model was calculated using WVC and the growth analysis parameters. It was considered available, because its coefficient of determination showed 0.84 and there are significant relationship based on plants physiology among the parameters and the changes over time. Furthermore, we analyzed the important factors for higher accuracy prediction using multiple regression analysis.

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On-line Real Time Soil Sensor

  • Shibusawa, S.
    • Agricultural and Biosystems Engineering
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    • 제4권1호
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    • pp.28-33
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    • 2003
  • Achievements in the real-time soil spectro-photometer are: an improved soil penetrator to ensure a uniform soil surface under high speed conditions, real-time collecting of underground soil reflectance, getting underground soil color images, use of a RTK-GPS, and all units are arranged for compactness. With the soil spectrophotometer, field experiments were conducted in a 0.5 ha paddy field. With the original reflectance, averaging and multiple scatter correction, Kubelka-Munk (KM) transformation as soil absorption, its 1st and 2nd derivatives were calculated. When the spectra was highly correlated with the soil parameters, stepwise regression analysis was conducted. Results include the best prediction models for moisture, soil organic matter (SOM), nitrate nitrogen (NO$_3$-N), pH and electric conductivity (EC), and soil maps obtained by block kriging analysis.

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On-Line Real Time Soil Sensor

  • Shibusawa S.
    • Agricultural and Biosystems Engineering
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    • 제4권2호
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    • pp.45-49
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    • 2003
  • Achievements in the real-time soil spectro-photometer are: an improved soil penetrator to ensure a uniform soil surface under high speed conditions, real-time collecting of underground soil reflectance, getting underground soil color images, use of a RTK-GPS, and all units are arranged for compactness. With the soil spectrophotometer, field experiments were conducted in a 0.5 ha paddy field. With the original reflectance, averaging and multiple scatter correction, Kubelka-Munk (KM) transformation as soil absorption, its 1st and 2nd derivatives were calculated. When the spectra was highly correlated with the soil parameters, stepwise regression analysis was conducted. Results include the best prediction models for moisture, soil organic matter (SOM), nitrate nitrogen ($NO_3-N$), pH and electric conductivity (EC), and soil maps obtained by block kriging analysis.

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수리 모형을 이용한 Korea Land Data Assimilation System (KLDAS) 자료의 수문자료에 대한 영향력 분석 (Interactions between Soil Moisture and Weather Prediction in Rainfall-Runoff Application : Korea Land Data Assimilation System(KLDAS))

  • 정용;최민하
    • 한국방재학회:학술대회논문집
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    • 한국방재학회 2011년도 정기 학술발표대회
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    • pp.172-172
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    • 2011
  • The interaction between land surface and atmosphere is essentially affected by hydrometeorological variables including soil moisture. Accurate estimation of soil moisture at spatial and temporal scales is crucial to better understand its roles to the weather systems. The KLDAS(Korea Land Data Assimilation System) is a regional, specifically Korea peninsula land surface information systems. As other prior land data assimilation systems, this can provide initial soil field information which can be used in atmospheric simulations. For this study, as an enabling high-resolution tool, weather research and forecasting(WRF-ARW) model is applied to produce precipitation data using GFS(Global Forecast System) with GFS embedded and KLDAS soil moisture information as initialization data. WRF-ARW generates precipitation data for a specific region using different parameters in physics options. The produced precipitation data will be employed for simulations of Hydrological Models such as HEC(Hydrologic Engineering Center) - HMS(Hydrologic Modeling System) as predefined input data for selected regional water responses. The purpose of this study is to show the impact of a hydrometeorological variable such as soil moisture in KLDAS on hydrological consequences in Korea peninsula. The study region, Chongmi River Basin, is located in the center of Korea Peninsular. This has 60.8Km river length and 17.01% slope. This region mostly consists of farming field however the chosen study area placed in mountainous area. The length of river basin perimeter is 185Km and the average width of river is 9.53 meter with 676 meter highest elevation in this region. We have four different observation locations : Sulsung, Taepyung, Samjook, and Sangkeug observatoriesn, This watershed is selected as a tentative research location and continuously studied for getting hydrological effects from land surface information. Simulations for a real regional storm case(June 17~ June 25, 2006) are executed. WRF-ARW for this case study used WSM6 as a micro physics, Kain-Fritcsch Scheme for cumulus scheme, and YSU scheme for planetary boundary layer. The results of WRF simulations generate excellent precipitation data in terms of peak precipitation and date, and the pattern of daily precipitation for four locations. For Sankeug observatory, WRF overestimated precipitation approximately 100 mm/day on July 17, 2006. Taepyung and Samjook display that WRF produced either with KLDAS or with GFS embedded initial soil moisture data higher precipitation amounts compared to observation. Results and discussions in detail on accuracy of prediction using formerly mentioned manners are going to be presented in 2011 Annual Conference of the Korean Society of Hazard Mitigation.

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COSMO-SkyMed SAR 영상을 이용한 밀 생육 모니터링 (Monitoring Wheat Growth by COSMO-SkyMed SAR Images)

  • 김이현;홍석영;이경도;장소영;이훈열;오이석
    • 대한원격탐사학회지
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    • 제29권1호
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    • pp.35-43
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    • 2013
  • 본 연구에서는 COSMO-SkyMed 영상을 이용하여 얻어진 후방산란계수의 밀 생육시기에 따른 변화를 분석하고 생육인자와의 관계를 통하여 밀 생육추정 가능성을 모색하고자 하였다. 2012년도 농촌진흥청 국립식량과학원 시험포장에서 생육시기별로 COSMO-SkyMed 영상자료를 수집하여 후방산란계수를 산출하였고 해당시기에 생체중, 식생수분함량, 건물중, 토양수분등을 조사 및 분석하였다. 생육시기에 따라 HH-편파 후방산란계수가 증가하다가 DOY 129(5월 8일) 때 최대값을 보인 후 감소하였는데 생체중, 식생 수분함량, 건물중 등도 동일한 변화 경향을 보였다. 후방산란계수와 밀 생육인자들과의 관계를 분석한 결과 생체중(r=0.88), 식생수분함량(r=0.87)과 각각 상관계수가 높게 나타났고, 건물중(r=0.80)과도 상관성을 보였지만 토양수분(r=0.18)과는 상관성이 나타나지 않았다. 후방산란계수를 이용하여 밀 생육을 추정을 위한 회귀식을 작성하였는데 생체중($R^2$=0.80), 식생수분함량($R^2$=0.80)에서 각각 결정계수가 높게 나타났다. 본 연구를 통해 COSMO-SkyMed 영상 이용 밀 생육을 추정할 수 있었고 향후 아리랑 5호 위성(KOMPSAT-5)에 활용 가능함을 확인하였다.

대청댐 예비 방류를 위한 홍수 예보 (Flood Forecasting for Pre-Release of Taech'ong Reservoir)

  • 이재형;심명필;전일권
    • 물과 미래
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    • 제26권2호
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    • pp.99-105
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    • 1993
  • 호우발생전의 기상상태, 유역의 저류상태 그리고 과거의 패턴을 반영한 실용성 있는 홍수 예보모형을 제안하였다. 호우 예보는 구름 물리학을 토대로한 지점 호우 예보 모형을, 유출예측은 저류함수모형을 채택하였다. 홍수 예보 모형의 입력 변수는 예보 발령 시점의 지상 기온, 지상 기압, 지상 이슬점 온도 그리고 유출점의 초기 유량이다. 홍수 예보 모형의 매개 상수는 과거의 홍수 사상이 갖는 최적 상수들의 산술평균값으로 하였다. 유출률은 홍수 초기 유량을 지표로 하여 예측될 수 있게 하였다.

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