• Title/Summary/Keyword: Uncertainty of the estimates

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Spatial Assessment of Climate Suitability for Summer Cultivation of Potato in North Korea (기후적합도 모형을 활용한 북한지역 내 감자의 여름재배 적지 탐색)

  • Kang, Minju;Hyun, Shinwoo;Kim, Kwang Soo
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.24 no.1
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    • pp.35-47
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    • 2022
  • Expansion of potato production areas can improve the food security in North Korea because the given crop has less requirements for agricultural materials and facilities. The Global Agro-Ecological Zones (GAEZ) model, which was developed to evaluate climate suitability under different cultivation conditions, was used to identify potential areas for the potato production. The spatial estimates of crop suitability under low and high input management conditions were downloaded from the GAEZ data portal. The values of suitability were obtained at the potato occurrence sites retrieved from the Global Biodiversity Information Facility (GBIF) database. The suitable areas for the potato production were identified using a threshold value derived from the suitability estimates at the occurrence sites. It was found that 90% of the occurrence sites had the suitability index value >3,333, which was set to be the threshold value. The suitable areas in North Korea were summarized by province and county. Rice cultivation areas were excluded from the analysis. The reported relative acreage of potato production was better represented by the suitable areas under the low input management options than the high input conditions. The suitable areas also had a similar distribution to the reported acreage of potato production by county. These results indicated that the GAEZ model would be useful to identify the candidate production areas, which would facilitate the increases in potato production especially under future climate conditions. Furthermore, monthly maps of crop suitability can be used to design cropping systems that would improve crop production under the limited use of agricultural materials and facilities.

Evaluation of Modified Soil-Plant-Atmosphere Model (mSPA) to Simulate Net Ecosystem Carbon Exchange Over a Deciduous Forest at Gwangneung in 2006 (2006년 광릉 활엽수림에서 순 생태계 탄소 교환량의 모의에 대한 modified Soil-Plant-Atmosphere (mSPA) 모델의 평가)

  • Lee, Young-Hee;Lim, Hee-Jeong
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.11 no.3
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    • pp.87-99
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    • 2009
  • We evaluated modified Soil-Plant-Atmosphere model's performance to simulate the seasonal variation of net ecosystem exchange (NEE) of carbon and examined the critical controlling mechanism on carbon exchange using the model over a deciduous forest at Gwangnung in 2006. The modified Soil-Plant-Atmosphere (mSPA) model was calibrated to capture the mean NEE during the daytime (1000-1400 LST) and used to simulate gross primary productivity (GPP). Ecosystem respiration ($R_e$) has been estimated using an empirical formula developed at this site. The simulation results indicated that the daytime mean stomatal conductance was highly correlated with daily insolation in the summer. Low stomatal conductance in high insolation occurred on the days with low temperature rather than with high vapor pressure deficit. It suggests that the forest rarely experienced water stress in the summer of 2006. The model captured the observed bimodal seasonal variation with a mid-season depression of carbon uptake. The model estimates of annual GPP, $R_e$ and NEE were $964\;gC\;m^{-2}\;yr^{-1}$, $733\;gC\;m^{-2}\;yr^{-1}$, and $-231\;gCm\;^{-2}\;yr^{-1}$, respectively. Compared to the observed annual NEE, the modeled estimates showed more carbon uptake by about $140\;gC\;m^{-2}\;yr^{-1}$. The uncertainty of the estimate of annual NEE in a complex terrain is discussed.

Application of Accrual Basis for Calculation of Prolongation Cost in Construction Projects (공기연장 추가간접비 산정기준의 발생주의방식 적용 연구)

  • Jeong, Kichang;Lee, Jaeseob
    • Korean Journal of Construction Engineering and Management
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    • v.19 no.5
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    • pp.111-120
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    • 2018
  • Recently, Domestic public construction projects are experiencing a great deal of disputes because of the growing uncertainty about the criteria for calculating the prolongation cost. In addition, researchers have been studying various systems and proper cost estimates in an effort to reduce the uncertainty of these systems and the occurrence of disputes. However, there is no standard yet for social consensus. Meanwhile, The study on the classification system according to the recognition standard of accounting has been systematically studied. As a result, the concepts of accrual and cash basis are defined separately. The purpose of this study is to verify the possibility of applying the concept of 'accrual basis' to the Standard for calculation of prolongation cost. Therefore, As a result of analyzing the occurrence pattern of Job-site overhead cost, it is confirmed that actual costs can not be calculated by the cash-basis method. In particular, the implications of the necessity of the accrual-basis method should be more strictly indicated in the case of items such as indirect labor costs and welfare benefits. In addition, the contractor 's claim report and the appraisal report were examined. As a result, it was confirmed that the calculation situations of prolongation costs are biased to the cash-basis method. In this way, it is suggested that necessary to supplement the calculation standard of the actual costs from the point of view of accrual basis.

Estimation of Poisoning Cases by Use of Chemicals and Chemical Products in South Korea (물질과 제품 사용에 의한 국내 중독(poisoning) 건수 추정)

  • Park, Soyoung;Lee, Yesung;Mun, Eunchan;Nam, Minwoo;Kim, Jiwon;Park, Jihoon;Choi, Won-Jun;Choi, Sangjun;Ha, Kownchul;Jun, Hyoungbae;Park, Dong-Uk
    • Journal of Environmental Health Sciences
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    • v.46 no.5
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    • pp.565-575
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    • 2020
  • Objective: South Korea still lacks systematic national poisoning data collection or a poison control center (PC). The objectives of this study are to provide estimates of poisoning incidents in South Korea and to stress the necessity of a national poisoning surveillance framework managed by a national PC. Method: The number of poisoning incidents was estimated based on the 2018 annual report of the American Association of Poison Control Centers' National Poison Data System (NPDS). Our estimation of poisoning data was classified according to age group, reason for poison exposure, and case management site. Results: Total poisoning cases estimated numbered 326,636, which is tantamount to 631 cases per 100 thousand. Poisoning cases among those younger than five years old accounted for 71.7% in the United States. Fatal poisoning cases were estimated to be 210.63 (95% CI: 199.70-222.15). Non-intentional poisoning cases (250,378 cases, 95% CI: 249,992-250,764, 76.7%) were estimated to be far higher than intentional cases (62,399 cases, 95% CI: 62,207-62,593, 19.1%). Conclusion: Our results can be used to suggest the necessity of producing national poisoning data and establishing a PC despite the uncertainty of estimation.

A Development of Generalized Coupled Markov Chain Model for Stochastic Prediction on Two-Dimensional Space (수정 연쇄 말콥체인을 이용한 2차원 공간의 추계론적 예측기법의 개발)

  • Park Eun-Gyu
    • Journal of Soil and Groundwater Environment
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    • v.10 no.5
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    • pp.52-60
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    • 2005
  • The conceptual model of under-sampled study area will include a great amount of uncertainty. In this study, we investigate the applicability of Markov chain model in a spatial domain as a tool for minimizing the uncertainty arose from the lack of data. A new formulation is developed to generalize the previous two-dimensional coupled Markov chain model, which has more versatility to fit any computational sequence. Furthermore, the computational algorithm is improved to utilize more conditioning information and reduce the artifacts, such as the artificial parcel inclination, caused by sequential computation. A generalized 20 coupled Markov chain (GCMC) is tested through applying a hypothetical soil map to evaluate the appropriateness as a substituting model for conventional geostatistical models. Comparing to sequential indicator model (SIS), the simulation results from GCMC shows lower entropy at the boundaries of indicators which is closer to real soil maps. For under-sampled indicators, however, GCMC under-estimates the presence of the indicators, which is a common aspect of all other geostatistical models. To improve this under-estimation, further study on data fusion (or assimilation) inclusion in the GCMC is required.

Comparative assessment and uncertainty analysis of ensemble-based hydrologic data assimilation using airGRdatassim (airGRdatassim을 이용한 앙상블 기반 수문자료동화 기법의 비교 및 불확실성 평가)

  • Lee, Garim;Lee, Songhee;Kim, Bomi;Woo, Dong Kook;Noh, Seong Jin
    • Journal of Korea Water Resources Association
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    • v.55 no.10
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    • pp.761-774
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    • 2022
  • Accurate hydrologic prediction is essential to analyze the effects of drought, flood, and climate change on flow rates, water quality, and ecosystems. Disentangling the uncertainty of the hydrological model is one of the important issues in hydrology and water resources research. Hydrologic data assimilation (DA), a technique that updates the status or parameters of a hydrological model to produce the most likely estimates of the initial conditions of the model, is one of the ways to minimize uncertainty in hydrological simulations and improve predictive accuracy. In this study, the two ensemble-based sequential DA techniques, ensemble Kalman filter, and particle filter are comparatively analyzed for the daily discharge simulation at the Yongdam catchment using airGRdatassim. The results showed that the values of Kling-Gupta efficiency (KGE) were improved from 0.799 in the open loop simulation to 0.826 in the ensemble Kalman filter and to 0.933 in the particle filter. In addition, we analyzed the effects of hyper-parameters related to the data assimilation methods such as precipitation and potential evaporation forcing error parameters and selection of perturbed and updated states. For the case of forcing error conditions, the particle filter was superior to the ensemble in terms of the KGE index. The size of the optimal forcing noise was relatively smaller in the particle filter compared to the ensemble Kalman filter. In addition, with more state variables included in the updating step, performance of data assimilation improved, implicating that adequate selection of updating states can be considered as a hyper-parameter. The simulation experiments in this study implied that DA hyper-parameters needed to be carefully optimized to exploit the potential of DA methods.

Derivation of Flood Frequency Curve with Uncertainty of Rainfall and Rainfall-Runoff Model (강우 및 강우-유출 모형의 불확실성을 고려한 홍수빈도곡선 유도)

  • Kwon, Hyun-Han;Kim, Jang-Gyeong;Park, Sae-Hoon
    • Journal of Korea Water Resources Association
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    • v.46 no.1
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    • pp.59-71
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    • 2013
  • The lack of sufficient flood data being kept across Korea has made it difficult to assess reliable estimates of the design flood while relatively sufficient rainfall data are available. In this regard, a rainfall simulation based derivation technique of flood frequency curve has been proposed in some of studies. The main issues in deriving the flood frequency curve is to develop the rainfall simulation model that is able to effectively reproduce extreme rainfall. Also the rainfall-runoff modeling that can convey uncertainties associated with model parameters needs to be developed. This study proposes a systematic approach to fully consider rainfallrunoff related uncertainties by coupling a piecewise Kernel-Pareto based multisite daily rainfall generation model and Bayesian HEC-1 model. The proposed model was applied to generate runoff ensemble at Daechung Dam watershed, and the flood frequency curve was successfully derived. It was confirmed that the proposed model is very promising in estimating design floods given a rigorous comparison with existing approaches.

Regional Low Flow Frequency Analysis Using Bayesian Multiple Regression (Bayesian 다중회귀분석을 이용한 저수량(Low flow) 지역 빈도분석)

  • Kim, Sang-Ug;Lee, Kil-Seong
    • Journal of Korea Water Resources Association
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    • v.41 no.3
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    • pp.325-340
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    • 2008
  • This study employs Bayesian multiple regression analysis using the ordinary least squares method for regional low flow frequency analysis. The parameter estimates using the Bayesian multiple regression analysis were compared to conventional analysis using the t-distribution. In these comparisons, the mean values from the t-distribution and the Bayesian analysis at each return period are not significantly different. However, the difference between upper and lower limits is remarkably reduced using the Bayesian multiple regression. Therefore, from the point of view of uncertainty analysis, Bayesian multiple regression analysis is more attractive than the conventional method based on a t-distribution because the low flow sample size at the site of interest is typically insufficient to perform low flow frequency analysis. Also, we performed low flow prediction, including confidence interval, at two ungauged catchments in the Nakdong River basin using the developed Bayesian multiple regression model. The Bayesian prediction proves effective to infer the low flow characteristic at the ungauged catchment.

Impact Assessment of Spatial Resolution of Radar Rainfall and a Distributed Hydrologic Model on Parameter Estimation (레이더 강우 및 분포형 수문모형의 공간해상도가 매개변수 추정에 미치는 영향 평가)

  • Noh, Seong Jin;Choi, Shin Woo;Choi, Yun Seok;Kim, Kyung Tak
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.5
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    • pp.1443-1454
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    • 2014
  • In this study, we assess impact of spatial resolution of radar rainfall and a distributed hydrologic model on parameter estimation and rainfall-runoff response. Radar data measured by S-band polarimetric radar located at Mt. Bisl in the year of 2012 are used for the comparative study. As different rainfall estimates such as R-KDP, R-Z, and R-ZDR show good agreement with ground rainfall, R-KDP are applied for rainfall-runoff modeling due to relatively high accuracy in terms of catchment averaged and gauging point rainfall. GRM (grid based rainfall-runoff model) is implemented for flood simulations at the Geumho River catchment with spatial resolutions of 200m, 500m, and 1000m. Automatic calibration is performed by PEST (model independent parameter estimation tool) to find suitable parameters for each spatial resolution. For 200m resolution, multipliers of overlandflow and soil hydraulic conductivity are estimated within stable ranges, while high variations are found from results for 500m and 1000m resolution. No tendency is found in the estimated initial soil moisture. When parameters estimated for different spatial resolution are applied for other resolutions, 200m resolution model shows higher sensitivity compared to 1000m resolution model.

Financial Disclosure and the Cost of Equity Capital: The Empirical Test of the Largest Listed Companies of Kazakhstan

  • Baimukhamedova, Aizhan;Baimukhamedova, Gulzada;Luchaninova, Albina
    • The Journal of Asian Finance, Economics and Business
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    • v.4 no.3
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    • pp.5-17
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    • 2017
  • This study extends research into whether disclosure of corporate and financial information is associated with firms' costs of equity capital. This study sets out to examine empirically the determinants of corporate disclosure in the annual reports of 37 largest and most liquid firms listed on Kazakhstan Stock Exchange (KASE) in Kazakhstan. It also reports the results of the association between company-specific characteristics and disclosure of the sample companies. Based on the analysis of existing empirical research, the disclosure index has been constructed and regression analysis of the influence of the disclosure index on the cost of equity capital has been conducted. The obtained results show that the received findings correlate with foreign empirical studies, and the disclosure index in this sample has a negative impact on the cost of equity capital. Using cost of equity capital estimates derived from capital asset pricing model, we find that firms with higher levels of financial transparency are associated with significantly lower costs of equity capital. Economic theory assumes that by increasing the level of corporate reporting, firms not only increase their stock market liquidity, but also decrease the investors' estimation risk, arising from uncertainty about future returns and payout distributions. The results show that firms on the Kazakhstan market can reduce their cost of equity capital by increasing the level of their voluntary corporate disclosures.