국내 논필지 모니터링 자료를 이용한 APEX-paddy 모델 적용성 평가

APEX 모형은 다양한 영농 활동의 토양과 물환경에 대한 영향을 필지 및 유역 규모로 평가하기 위해 개발된 모형이다. 최근 APEX의 주요기작을 바탕으로 논에서의 수도작 운영에 따른 물수지, 양분 유출에 대한 모의가 가능하도록 한 APEX-Paddy가 고안된 바 있다. 본연구에서는 익산 지역의 논 시험포 모니터링 자료를 이용하여 APEX-Paddy 모형의 적용성을 평가하고자 하였다. 2013년과 2014년의 논유출량과 부하량 자료를 수집하고 자동보정 툴 APEX-CUTE 4.1과 추가적 수동보정을 통해 모형의 모의성능을 검토하고 한계점을고찰하였다. 연구결과, 논의 물수지와 질소 배출부하량은 대체로 합리적인 수준의 모의성능을 보이는 한편 유사량과 인 배출부하량 모의에있어 논의 담수상태 유사배출 기작에 대한 고려가 미흡하여 모의성능에 한계가 있는 것으로 분석되었으며 원인에 대해 고찰하였다. 더불어자동보정 툴의 적용에 있어 매개변수 민감도를 바탕으로 한 수동보정 결과보다 정확도가 다소 떨어지는 경향을 보여 그 활용에 유의가필요한 것으로 판단되었다. The APEX model has been developed for assessing agricultural management efforts and their effects on soil and water at the field scale as well asmore complex multi-subarea landscapes, whole farms, and watersheds. Recently, a key component of APEX application, named APEX-Paddy, hasbeen modified for simulating water quality by considering paddy rice management practices. In this study, the performance of the APEX-Paddy modelwas evaluated using field data at Iksan experimental paddy sites in Korea. The discharge and pollutant load data during 2013 and 2014 were usedto both manually and automatically calibrate the model. The APEX auto-calibration tool (APEX-CUTE 4.1) was used for model calibration andsensitivity analysis. Results indicate that APEX-Paddy reasonably performs in predicting runoff discharge rate and nitrogen yield. However, sedimentand phosphorus yield is not correctly predicted due to the limitation of model schemes. With APEX-Paddy, the performance in reproducing thedischarge and nitrogen yield is found to be a satisfactory level after manual calibration. The manually calibrated model performed better than theautomatically calibrated model in nearly all comparisons. For runoff, manual calibration reduced PBIAS while R2 and NSE values of the automaticallycalibrated model were the same as the manual calibration. For T-N, NSE and PBIAS were reduced when using manual calibration, whereas R2 valuewas the same as manual calibration. The limitation of the APEX-Paddy model for predicting sediment, as well as the phosphorous yield, was discussedin this study.N

Comparison of CMIP6 and CMIP5 model performance in simulating historical precipitation and temperature in Bangladesh: a preliminary study

The relative performance of global climate models (GCMs) of phases 5 and 6 of the coupled model intercomparison project (CMIP5 and CMIP6, respectively) was assessed in this study based on their ability to simulate annual and seasonal mean rainfall and temperature over Bangladesh for the period 1977–2005. Multiple statistical metrics were used to measure the performance of the GCMs at 30 meteorological observation stations. Two robust multi-criteria decision analysis methods were used to integrate the results obtained using different metrics for an unbiased ranking of the GCMs. The results revealed MIROC5 as the most skillful among CMIP5 GCMs and ACCESS-CM2 among CMIP6 GCMs. Overall, CMIP6 MME showed a significant improvement in simulating rainfall and temperature over Bangladesh compared to CMIP5 MME. The highest improvements were found in simulating cold season (winter and post-monsoon) rainfall and temperature in higher elevated areas. The improvement was relatively more for rainfall than for temperature. The models could capture the interannual variability of annual and seasonal rainfall and temperature reliably, except for the winter rainfall. However, systematic wet and cold/warm biases still exist in CMIP6 models for Bangladesh. CMIP6 GCMs showed higher spatial correlations with observed data, but the higher difference in standard deviations and centered root mean square errors compared to CMIP5 GCMs indicates better performance in simulating geographical distribution but lower performance in simulating spatial variability of most of the climate variables except for minimum temperature at different timescales. In terms of Taylor skill score, the CMIP6 MME showed higher performance in simulating rainfall but lower performance in simulating temperature than CMIP5 MME for most of the timeframes. The findings of this study suggest that the added value of rainfall and temperature simulations in CMIP6 models is not consistent among the climate models used in this research. However, it sets a precedent for future research on climate change risk assessment for the scientific community

Future Changes in Precipitation and Drought Characteristics over Bangladesh under CMIP5 Climatological Projections

The impacts of climate change on precipitation and drought characteristics over Bangladesh were examined by using the daily precipitation outputs from 29 bias-corrected general circulation models (GCMs) under the representative concentration pathway (RCP) 4.5 and 8.5 scenarios. A precipitation-based drought estimator, namely, the Effective Drought Index (EDI), was applied to quantify the characteristics of drought events in terms of the severity and duration. The changes in drought characteristics were assessed for the beginning (2010–2039), middle (2040–2069), and end of this century (2070–2099) relative to the 1976–2005 baseline. The GCMs were limited in regard to forecasting the occurrence of future extreme droughts. Overall, the findings showed that the annual precipitation will increase in the 21st century over Bangladesh; the increasing rate was comparatively higher under the RCP8.5 scenario. The highest increase in rainfall is expected to happen over the drought-prone northern region. The general trends of drought frequency, duration, and intensity are likely to decrease in the 21st century over Bangladesh under both RCP scenarios, except for the maximum drought intensity during the beginning of the century, which is projected to increase over the country. The extreme and medium-term drought events did not show any significant changes in the future under both scenarios except for the medium-term droughts, which decreased by 55% compared to the base period during the 2070s under RCP8.5. However, extreme drought days will likely increase in most of the cropping seasons for the different future periods under both scenarios. The spatial distribution of changes in drought characteristics indicates that the drought-vulnerable areas are expected to shift from the northwestern region to the central and the southern region in the future under both scenarios due to the effects of climate change

An Alternative for Estimating the Design Flood Interval of Agricultural Reservoirs under Climate Change Using a Non-Parametric Resampling Technique

Agricultural reservoirs play such a central role in supplying water to rural areas that it is essential to properly estimate the design flood for agricultural reservoirs under climate change. The objective of this study was to estimate the inflow design flood interval using a non-parametric resampling technique for agricultural reservoirs under climate change. This study suggested an alternative method to point estimation using insufficient past data by providing the interval of the inflow design flood under the representative concentration pathway. To estimate the interval of the inflow design flood, we employed the bootstrap technique, which estimated the confidence interval corresponding to the 95% confidence level. This study covered a spatial range of 30 agricultural reservoirs in South Korea and a temporal range of past and three future representative periods: the base period (2015s: 1986–2015) and future periods (2040s: 2011–2040, 2070s: 2041–2070, 2100s: 2071–2100). We analyzed the results of a 200-year return period and 24-hour duration as a representative case. For the 97.5th bias-corrected and accelerated percentile value, the overall inflow design floods were larger than the base period value (2015s) with the safety factor applied. The northern and midwestern regions of South Korea showed relatively greater changes than the southeastern region. Some agricultural reservoirs showed a decrease in the design flood during the 2040s but generally increased after the 2070s. Through the non-parametric resampling technique, the interval estimation was provided considering the uncertainty of the inflow design flood. By presenting the results for three periods, we can provide policymakers with information to select according to the target period. The findings may provide an essential step in replacing a safety factor used for determining the design flood of agricultural reservoirs with the confidence interval calculated in accordance with statistical characteristics

How Ångström–Prescott Coefficients Alter the Estimation of Agricultural Water Demand in South Korea

The Food and Agriculture Organization (FAO) Penman⁻Monteith equation, recognized as the standard method for the estimation of reference crop evapotranspiration ( ET 0 ), requires many meteorological inputs. The Ångström⁻Prescott (A-P) formula containing parameters (i.e., a and b) is recommended to determine global solar radiation, one of the essential meteorological inputs, but may result in a considerable difference in ET 0 estimation. This study explored the effects of A-P coefficients not only on the estimation of ET 0 , but also on the irrigation water requirement (IWR) and design water requirement (DWR) for paddy rice cultivation, which is the largest consumer of agricultural water in South Korea. We compared and analyzed the estimates of ET 0 , IWR, and DWR using the recommended (a = 0.25 and b = 0.5) and locally calibrated A-P coefficients in 16 locations of South Korea. The estimation of ET 0 using the recommended A-P coefficients produced significant overestimation. The overestimation ranged from 3.8% to 14.0% across the 16 locations as compared to the estimates using the locally calibrated A-P coefficients, and the average overestimation was 10.0%. The overestimation of ET 0 corresponded to a variation of 1.7% to 7.2% in the overestimation of the mean annual IWR, and the average overestimation of the IWR was 5.1%. On average, the overestimation was slightly reduced to 4.8% in DWR estimation, since the effect of A-P coefficients on the IWR estimation decreased as the IWR increased. This study demonstrates how the use of A-P coefficients can alter the estimation of ET 0 , IWR, and DWR in South Korea, which underscores the importance of their proper consideration in agricultural water management

Cambio de uso de la tierra en Florida central y análisis de sensibilidad basado en la conversión agrícola a urbana extrema

This paper explored recent land use and land cover change in western central Florida, examining both socioeconomic and biophysical influences on land transformation and the impacts of that change. Between 1995 and 2006, a growth in population resulted in the conversion of agricultural areas, grasslands, and upland forests to urban areas. Additionally, the amount of extractive land uses (e.g., mining) increased by 21.8%, water reservoirs by 19.9%, and recreation areas by 13.3%. Regional climate modeling experiments suggest that the overall effects of land use change (LUC) on mesocale climates in summer days resulted in modified temperatures that were modulated by the new LU characteristics, local and synoptic atmospheric circulations, and the distance of rural and urban land uses from the shoreline. The difference between the extreme and actual LU simulations for temperature, wind speed, wind direction, and precipitation presented higher variability in the inland urbanized and rural zones. Results can be used to better understand the basic influences of LUC and urbanization on key climate parameters, and urban heat island effects in peninsular Florida under typical weather conditions

Cambio de uso de la tierra en Florida central y análisis de sensibilidad basado en la conversión agrícola a urbana extrema

This paper explored recent land use and land cover change in western central Florida, examining both socioeconomic and biophysical influences on land transformation and the impacts of that change. Between 1995 and 2006, a growth in population resulted in the conversion of agricultural areas, grasslands, and upland forests to urban areas. Additionally, the amount of extractive land uses (e.g., mining) increased by 21.8%, water reservoirs by 19.9%, and recreation areas by 13.3%. Regional climate modeling experiments suggest that the overall effects of land use change (LUC) on mesocale climates in summer days resulted in modified temperatures that were modulated by the new LU characteristics, local and synoptic atmospheric circulations, and the distance of rural and urban land uses from the shoreline. The difference between the extreme and actual LU simulations for temperature, wind speed, wind direction, and precipitation presented higher variability in the inland urbanized and rural zones. Results can be used to better understand the basic influences of LUC and urbanization on key climate parameters, and urban heat island effects in peninsular Florida under typical weather conditions

Correction: Kamruzzaman, M., et al. Evaluating the Impact of Climate Change on Paddy Water Balance Using APEX-Paddy Model. Water 2020, 12, 852

The authors wish to make the following corrections to this paper [...

Assessment of CMIP6 global climate models in reconstructing rainfall climatology of Bangladesh

This study evaluated the rainfall historical simulations of 15 Global Climate Models (GCMs) of the Coupled Model Intercomparison Project phase 6 (CMIP6) in replicating annual and seasonal rainfall climatology, their temporal variability and trends in Bangladesh for the period 1979–2014, considering ERA5 (ECMWF Reanalysis 5th Generation) reanalysis as the reference dataset. Shannon's Entropy decision-analysis was employed for GCMs' rating based on eight statistical indicators and a comprehensive rating metric for the final grading of the GCMs. The majority of the CMIP6 GCMs accurately reproduced the spatial feature of ERA5 rainfall. However, the GCMs underestimated annual rainfall by an average of 190.5 mm, with the highest underestimation in monsoon (131.76 mm) and least in winter (3.52 mm) seasons. Most GCMs also underestimated rainfall variability for all seasons except winter. Besides, the GCMs showed an increasing trend in pre-monsoon and a decreasing trend in post-monsoon rainfall like ERA5, but an opposite (negative) to ERA5 trend (positive) in monsoon season rainfall. The ensemble mean of the GCMs showed higher skill in reconstructing rainfall climatology, temporal variability and trends than the individual GCMs. The study identified MPI-ESM1-2-LR, MPI-ESM1-2-HR, and GFDL-ESM4 as the most effective GCMs in reproducing precipitation over Bangladesh. The selected models' simulation can be used for climate change impact assessment in Bangladesh after bias minimization