The Agricultural Policy/Environmental eXtender (APEX) model is widely used for evaluating agricultural conservation efforts and their effects on soil and water. A key component of APEX application in Korea is simulating the water quality impacts of rice paddies because rice agriculture claims the largest cropland area in the country. In this study, a computational module called APEX-Paddy (National Academy of Agricultural Sciences, Wanju, Korea) is developed to simulate water quality with considering pertinent paddy management practices, such as puddling and flood irrigation management. Data collected at two experimental paddy sites in Korea were used to calibrate and validate the model. Results indicate that APEX-Paddy performs well in predicting runoff discharge rate and nitrogen yield while the original APEX highly overestimates runoff rates and nitrogen yields on large storm events. With APEX-Paddy, simulated and observed flow and mineral nitrogen yield (QN) are found to be highly correlated after calibration (Nash & Sutcliffe Efficiency (NSE) = 0.87 and Percent Bias (PBIAS) = −14.6% for flow; NSE = 0.68 and PBIAS = 2.1% for QN). Consequently, the APEX-Paddy showed a greater accuracy in flow and QN prediction than the original APEX modeling practice using the SCS-CN (Soil Conservation Service-Curve Number) method.

This research aims to assess the impact of climate change on water balance components in irrigated paddy cultivation. The APEX-Paddy model, which is the modified version of the APEX (Agricultural Policy/Environmental eXtender) model for paddy ecosystems, was used to evaluate the paddy water balance components considering future climate scenarios. The bias-corrected future projections of climate data from 29 GCMs (General Circulation Models) were applied to the APEX-Paddy model simulation. The study area (Jeonju station) forecasts generally show increasing patterns in rainfall, maximum temperature, and minimum temperature with a rate of up to 23%, 27%, and 45%, respectively. The hydrological simulations suggest over-proportional runoff–rainfall and under-proportional percolation and deep-percolation–rainfall relationships for the modeled climate scenarios. Climate change scenarios showed that the evapotranspiration amount was estimated to decrease compared to the baseline period (1976–2005). The evaporation was likely to increase by 0.12%, 2.21%, and 7.81% during the 2010s, 2040s, and 2070s, respectively under Representative Concentration Pathway (RCP)8.5, due to the increase in temperature. The change in evaporation was more pronounced in RCP8.5 than the RCP4.5 scenario. The transpiration is expected to reduce by 2.30% and 12.62% by the end of the century (the 2070s) under RCP4.5 and RCP8.5, respectively, due to increased CO₂ concentration. The irrigation water demand is generally expected to increase over time in the future under both climate scenarios. Compared to the baseline, the most significant change is expected to increase in the 2040s by 3.21% under RCP8.5, while the lowest increase was found by 0.36% in 2010s under RCP4.5. The increment of irrigation does not show a significant difference; the rate of increase in the irrigation was found to be greater RCP8.5 than RCP4.5 except in the 2070s. The findings of this study can play a significant role as the basis for evaluating the vulnerability of rice production concerning water management against climate change.

Extreme climatic events have increased in frequency and intensity over tha last decades due to global warming. Our study evaluates spatial distribution of changes in climate extreme indices on the Korean Peninsula by downscaled high-resolution data based on an empirical quantile mapping technique and 29 global climate models. Grid‐based observation data with 3.0 km resolution derived from weather stations with data covering 30 years from 1976 to 2005 using a modified PRISM approach were used as reference data for bias-correction. Future projections until 2100 based on two Representative Concentration Pathway (RCP) scenarios of CMIP5 were considered for the variables of daily precipitation, minimum temperature, and maximum temperature. We finally estimated spatial changes in climate extreme indices at 3.0 km resolution. The reproducibility assessment of simple precipitation intensity index (SDII) and annual total precipitation in wet days (PRCPTOT) showed applicability of techniques for downscaling, with the biggest difference of 2.66% and 1.91%, respectively, compared to the observation. The annual maximum 5-day precipitation (Rx5day) and annual maximum value of maximum temperature (TXx) showed highest increase rate under the far future period and RCP8.5 scenario. The derived spatial distribution of climate extreme indices based on a multi‐model ensemble can contribute to vulnerability assessment at a national scale by reducing uncertainties caused by selecting a specific climate model.

Reducing management intensity according to the topography of pastures can change the dominant plant species from sown forages to weeds. It is unclear how changes in species dominance in plant community drive spatial variation in soil bacterial community characteristics and functions in association with edaphic condition. Analysing separately the effects of both plant communities and soil chemical properties on bacterial community is crucial for understanding the biogeographic process at a small scale. In this paper, we investigated soil bacterial responses in five plant communities (two forage and three weed), where >65% of the coverage was by one or two species. The structure and composition of the bacterial communities in the different microbiome were analysed using sequencing and their characteristics were assessed using the Functional Annotation of Prokaryotic Taxa (FAPROTAX) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Firmicutes and Planctomycetes responded only to one specific plant community, and each plant community harboured unique operational taxonomic units (OTUs) at the species level. There were a large percentage of uniquely absent OTUs for specific plant communities, suggesting that a negative effect is critical in the relationship between plants and bacteria. Bacterial diversity indices were influenced more by soil chemical properties than by plant communities. Some putative functions related to C and N recycling including nitrogen fixation were correlated with pH, electrical conductivity (EC) and nutrient levels, and this also implied that some biological functions, such as ureolysis and carbon metabolism, may decline when fertilisation intensity is reduced. Taken together, these results suggest that a shift of dominant species in plant community exerts individual effects on the bacterial community composition, which is different from the effect of soil chemical properties.

The Agricultural Policy/Environmental eXtender (APEX) model is widely used for evaluating agricultural conservation efforts and their effects on soil and water. A key component of APEX application in Korea is simulating water quality impacts of rice paddies because rice agriculture claims the largest cropland area in the country. In this study, a computational module called APEX-Paddy is developed to simulate water quality with considering pertinent paddy management practices such as puddling, flood irrigation management. Data collected at two experimental paddy sites in Korea were used to calibrate and validate the model. Results indicate that APEX-Paddy performs well in predicting runoff discharge rate and nitrogen yield while the original APEX highly overestimates runoff rates and nitrogen yields on large storm events. With APEX-Paddy, simulated and observed flow and mineral nitrogen yield (QN) are found to be highly correlated after calibration (Nash & Sutcliffe Efficiency (NSE) = 0.87 and Percent Bias (PBIAS) = −14.6% for flow; NSE = 0.68 and PBIAS = 2.1% for QN). Consequently, the APEX-Paddy showed a greater accuracy in flow and QN prediction than the original APEX modeling practice using the SCS-CN method.