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BackgroundClimate change, particularly rising temperatures, negatively affects rice grain quality, increasing chalky grain percentage (CG) and hampering rice grade and price. Heat-tolerant cultivars have been bred and released since the 2000s, but the effectiveness of heat tolerance in reducing the occurrence of CG has yet to be quantified.ObjectivesThis study aimed to measure the effectiveness of breeding for better heat tolerance in reducing the negative impact of high temperatures on rice quality.MethodsThrough a systematic literature search, we developed a dataset including 1297 field observations covering 48 cultivars from five different heat tolerant ranks (HTRs) at 44 sites across Japan. A linear mixed-effect model (LME) and a random forest model (RF) were fitted to the data to analyze the effect of HTR and climatic factors such as the cumulative mean air temperature above 26 °C (TaHD), mean solar radiation, and mean relative humidity for 20 days after heading on CG.ResultsThe LME model explained 63 % of the variation with a 14% RMSE. The RF partial dependence plot revealed that the logit-transformed CG response to climate factors was linear, supporting the assumption of LME. The statistical analysis showed that CG increased as a function of TaHD (P < 0.001), with significant differences among HTRs (P < 0.001). The strongest effect of TaHD was obtained for the lowest HTR and was found to decrease with increasing HTR. CG also increased with higher relative humidity (P < 0.001) and solar radiation (P < 0.01). Based on our modeling, we estimated that as TaHD increased from 20 to 80 °Cd (equivalent to a mean temperature increase from 27 °C to 30 °C), CG increased by 66 points for cultivars with the lowest HTR, 45 points for cultivars with an intermediate HTR, and 19 points for cultivars with the highest HTR. Raising HTR by just one step (from intermediate to moderately tolerant) is projected to increase the proportion of first-grade rice at a grain-filling temperature of 27 °C, but tolerance levels need to be improved further in case of stronger warming.ConclusionsThe effect of high temperatures on CG was highly dependent on the cultivar’s HTR. Improvements in HTR effectively reduce the negative impacts of high temperatures on rice grain quality.SignificanceHeat-tolerant cultivars are projected to suppress the prevalence of CG more than threefold compared with heat-sensitive cultivars when grain-filling temperature increases from 27 to 30 °C.

The impacts of climate change and increased water use for irrigation make it difficult to manage sustainable water use and food production. Sufficient research has not been conducted on how humans adapt to water risks due to climate change. One of the difficulties in considering adaptation measures is that adaptation actions in one sector conflict with the interests of other stakeholders in the basin and trade-off relationships emerge among various sectors. Here, we examined how an effective adaptation in one sector (agriculture) influences the other (water resources) by calculating the “benefits of agricultural production” and “drought risk” under current and future climate scenarios. We built a framework consisting of two process-based models of hydrology and crop science and evaluated shifting of the transplantation date as a promising measure to avoid the degradation of rice quality in Japan. Shifting the transplantation date had opposing effects on the total yield and quality of rice, with an earlier date increasing the total yield and a later date increasing the quality. Furthermore, an earlier transplantation date reduced the drought risk. Thus, in terms of the preferred adaptation options, total yield and drought were synergistic, whereas rice quality and drought were trade-offs. Our results imply that the current transplantation date has resulted from the farmers’ motivation to maximize total yield, but this motivation may change to other factors, possibly rice quality, due to climate change. Overall, this study contributes to the understanding of how interconnected systems evolve when climate or socio-economic conditions change.

Known as the heat-mitigation effect, irrigated rice-paddy fields distribute a large fraction of their received energy to the latent heat during the growing season. The present hypothesis is that increased atmospheric CO2 concentration decreases the stomatal conductance of rice plants and increases the air temperature by means of an increased sensible heat flux. To test this hypothesis, a coupled regional atmospheric and crop energy-balance model is developed and applied to a 300 × 300 km2 region in Japan. Downscaling meteorological variables from grid-mean values of mixed land use (3 × 3 km2) generates realistic typical diurnal cycles of air temperature in rice paddies and adjacent residential areas. The model simulation shows that, on a typical sunny day in summer, doubling the CO2 concentration increases the daily maximum grid-mean air temperature, particularly where rice paddies are present, by up to 0.7 °C. This CO2 effect on the grid-mean air temperature is approximately half the effect of the reduction in rice-paddy area that is postulated to occur on a time scale similar to that of the atmospheric CO2 change. However, within the internal atmospheric boundary layer of the rice paddies, the CO2 effect on the air temperature (+ 0.44 °C) still exceeds the effects of the land-use change (+ 0.11 °C). These results show a potentially important interplay of plant physiological responses regarding atmospheric CO2 in the heat-mitigation effect of rice-paddy fields under a changing climate.

The mirid bugs Stenotus rubrovittatus and Trigonotylus caelestialium, which cause pecky rice, have become a threat to rice cultivation in Asia. Damage caused by these pests has rapidly become frequent since around 2000 in Japan. Their expansion pattern is not simple, and predicting their future spread remains challenging. Some insects with wide ranges have locally adapted variations in life‐history traits. We performed laboratory rearing experiments to assess the geographical scale of intraspecific variations in life‐history traits of S. rubrovittatus and T. caelestialium. The experiments were aimed at increasing the accuracy of occurrence estimates and the number of generations per year. These results were compared with previous research, and differences in development rates were observed between populations of different latitudes, but not of the same latitude. Finally, plotting the timing of adult emergence and the potential number of generations per year on maps with a 5‐km grid revealed that they differed greatly locally at the same latitude. These maps can be used for developing more efficient methods of managing mirid bugs in integrated pest management., Our laboratory rearing experiments revealed no difference in the relationship between temperature and the rate of development in each developmental stage of the two mirid bug species from the same latitude in northern Japan. On the other hand, comparison of data on the development rates in Tohoku region and those of previous studies in other areas revealed that the relationship between temperature and the rate of development showed geographical variations between populations of both species at different latitudes. We mapped the timing of adult emergence of the first generation and the potential number of generations per year using the daily mean temperature and our data on the two species’ development in an effective accumulated temperatures model.

The effects of climate change on the reduction of internal bond strength (IB) of particleboard subjected to various climatic conditions in Japan were predicted. The temperature increased throughout Japan with increasing greenhouse gas (GHG) emissions, so the climate deterioration index (climate index for predicting the IB reduction of particleboard; a high index indicates a large IB reduction) also increased to decrease IB. The number of low-temperature areas decreased because of climate change. The rupture of bonding points in particleboard caused by outdoor exposure led to a IB reduction, and biodeterioration accelerated this reduction. In high-temperature areas, particleboard was found to be prone to biodeterioration, and the IB significantly reduced. An area wherein there was a significant decrease in the IB spread along the Pacific Ocean side of western Japan and the Sea of Japan in central Japan in relation to increasing GHG emissions. Particleboards are difficult to use outdoors because of climate change.

There is concern about positive feedbacks between climate change and methane (CH4) emission from rice paddies. However, appropriate water management may mitigate the problem. We tested this hypothesis at six field sites in central Thailand, where the irrigated area is rapidly increasing. We used DNDC-Rice, a process-based biogeochemistry model adjusted based on rice growth data at each site to simulate CH4 emission from a rice-rice double cropping system from 2001 to 2060. Future climate change scenarios consisting of four representative concentration pathways (RCPs) and seven global climate models were generated by statistical downscaling. We then simulated CH4 emission in three water management practices: continuous flooding (CF), single aeration (SA), and multiple aeration (MA). The adjusted model reproduced the observed rice yield and CH4 emission well at each site. The simulated CH4 emissions in CF from 2051 to 2060 were 5.3 to 7.8%, 9.6 to 16.0%, 7.3 to 18.0%, and 13.6 to 19.0% higher than those from 2001 to 2010 in RCPs 2.6, 4.5, 6.0, and 8.5, respectively, at the six sites. Regionally, SA and MA mitigated CH4 emission by 21.9 to 22.9% and 53.5 to 55.2%, respectively, relative to CF among the four RCPs. These mitigation potentials by SA and MA were comparable to those from 2001 to 2010. Our results indicate that climate change in the next several decades will not attenuate the quantitative effect of water management practices on mitigating CH4 emission from irrigated rice paddies in central Thailand.

As surface warming threatens rice production in temperate climates, the importance of cool regions is increasing. Cultivar choice is an important adaptation option for coping with cli- mate change but is generally evaluated with a single metric for a few hypothetical cultivars. Here, we evaluate adaptation to climate change based on multiple metrics and cultivars in presently cool climates in Japan. We applied the outputs of a global climate model (MIROC5) with a Repre- sentative Concentration Pathways 4.5 scenario, dynamically downscaled to a 10 km mesh for the present (1981�2000) and future (2081�2099) climate conditions. The data were input into a rice- growth model, and the performances of 10 major cultivars were compared in each mesh. With the present-day leading cultivars, the model predicted reduced low-temperature stress, a regional average yield increase of 17%, and several occurrences of high-temperature stress. The most suit- able cultivars in each grid cell changed dramatically because of climate change when a single metric was used as a criterion, and the yield advantage increased to 26%. When yield, cold, and heat stress were taken into account, however, the currently leading cultivars maintained superi- ority in 64% of the grid cells, with an average regional yield gain of 22%, suggesting a require- ment for developing new cultivars by pyramiding useful traits. A trait such as low sensitivity to temperature for phenology helps in ensuring stable growth under variable temperatures. Increas- ing photoperiod sensitivity can be an option under future climates in relatively warmer regions.

Analyses of the technological and climatic factors that influence regional yield can provide insights into how production systems can be improved in the future. We analyzed the effects of changes in climate and nitrogen input on the time course of rice yields of nine rice-producing provinces in China for the period between 1961 and 2003. We developed a regional-scale model that considered both climate and nitrogen flow in the rice paddy. Observed yields (Y obs) tripled during the period, of which 65 % of the increase was accounted for by the estimated yield (Y est) based on changes in nitrogen input and climate. The remaining 35 % was attributed to other technological factors (α = Y obs/Y est), which include improvements in cultivars and pest management, for example. Contribution of α became pronounced after 1980 and accounted for 69 and 90 % of the yield increases in the 1980s and 1990s, respectively. Nitrogen input had much greater impacts on Y est (90 %) than did climate, but Y est/nitrogen input dropped substantially. Significant positive effects were observed for CO2 fertilization effects, which differed significantly among provinces; their relative contribution to the increase in Y est ranged from 1.0 to 7.4 %. The effect of temperature change on Y est was negative and significant in three provinces, but not for the overall average. To meet future rice demand and to improve nitrogen use efficiency, full use of possible positive interactions among cultivars, nitrogen management, and climate is required.

Reliable regional-scale representation of crop growth and yields has been increasingly important in earth system modeling for the simulation of atmosphere-vegetation-soil interactions in managed ecosystems. While the parameter values in many crop models are location specific or cultivar specific, the validity of such values for regional simulation is in question. We present the scale dependency of likely parameter values that are related to the responses of growth rate and yield to temperature, using the paddy rice model applied to Japan as an example. For all regions, values of the two parameters that determine the degree of yield response to low temperature (the base temperature for calculating cooling degree days and the curvature factor of spikelet sterility caused by low temperature) appeared to change relative to the grid interval. Two additional parameters (the air temperature at which the developmental rate is half of the maximum rate at the optimum temperature and the value of developmental index at which point the crop becomes sensitive to the photoperiod) showed scale dependency in a limited region, whereas the remaining three parameters that determine the phenological characteristics of a rice cultivar and the technological level show no clear scale dependency. These results indicate the importance of using appropriate parameter values for the spatial scale at which a crop model operates. We recommend avoiding the use of location-specific or cultivar-specific parameter values for regional crop simulation, unless a rationale is presented suggesting these values are insensitive to spatial scale.

Aim Recent changes in crop yields have implications for future global food security, which are likely to be affected by climate change. We developed a spatially explicit global dataset of historical yields for maize, soybean, rice and wheat to explore the historical changes in mean, year-to-year variation and annual rate of change in yields for the period 1982–2006. Location This study was conducted at the global scale. Methods We modelled historical and spatial patterns of yields at a grid size of 1.125° by combining global agricultural datasets related to the crop calendar and harvested area in 2000, country yield statistics and satellite-derived net primary production. Modelled yields were compared with other global datasets of yields in 2000 (M3-Crops and MapSPAM) and subnational yield statistics for 23 major crop-producing countries. Historical changes in modelled yields were then examined. Results Modelled yields explained 45–81% of the spatial variation of yields in 2000 from M3-Crops and MapSPAM, with root-mean-square errors of 0.5–1.8 t ha−1. Most correlation coefficients between modelled yield time series and subnational yield statistics for the period 1982–2006 in major crop-producing regions were greater than 0.8. Our analysis corroborated the incidence of reported yield stagnations and collapses and showed that low and mid latitudes in the Southern Hemisphere (0–40°S) experienced significantly increased year-to-year variation in maize, rice and wheat yields in 1994–2006 compared with that in 1982–93. Main conclusions Our analyses revealed increased instability of yields across a broad region of the Southern Hemisphere, where many developing countries are located. Such changes are likely to be related to recent yield stagnation and collapses. Although our understanding of the impacts of recent climate change, particularly the incidence of climate extremes, on crop yields remains limited, our dataset offers opportunities to close parts of this knowledge gap.

We developed a dataset of local-scale daily climate change scenarios for Japan (called ELPIS-JP) using the stochastic weather generators (WGs) LARS-WG and, in part, WXGEN. The ELPIS-JP dataset is based on the observed (or estimated) daily weather data for seven climatic variables (daily mean, maximum and minimum temperatures; precipitation; solar radiation; relative humidity; and wind speed) at 938 sites in Japan and climate projections from the multi-model ensemble of global climate models (GCMs) used in the coupled model intercomparison project (CMIP3) and multi-model ensemble of regional climate models form the Japanese downscaling project (called S-5-3). The capability of the WGs to reproduce the statistical features of the observed data for the period 1981–2000 is assessed using several statistical tests and quantile–quantile plots. Overall performance of the WGs was good. The ELPIS-JP dataset consists of two types of daily data: (i) the transient scenarios throughout the twenty-first century using projections from 10 CMIP3 GCMs under three emission scenarios (A1B, A2 and B1) and (ii) the time-slice scenarios for the period 2081–2100 using projections from three S-5-3 regional climate models. The ELPIS-JP dataset is designed to be used in conjunction with process-based impact models (e.g. crop models) for assessment, not only the impacts of mean climate change but also the impacts of changes in climate variability, wet/dry spells and extreme events, as well as the uncertainty of future impacts associated with climate models and emission scenarios. The ELPIS-JP offers an excellent platform for probabilistic assessment of climate change impacts and potential adaptation at a local scale in Japan.

We have studied future changes in the atmospheric and hydrological environments in Northeast Thailand from the viewpoint of risk assessment of future cultural environments in crop fields. To obtain robust and reliable estimation for future climate, ten general circulation models under three warming scenarios, B1, A1B, and A2, were used in this study. The obtained change trends show that daily maximum air temperature and precipitation will increase by 2.6°C and 4.0%, respectively, whereas soil moisture will decrease by c.a. 1% point in volumetric water content at the end of this century under the A1B scenario. Seasonal contrasts in precipitation will intensify: precipitation increases in the rainy season and precipitation decreases in the dry season. Soil moisture will slightly decrease almost throughout the year. Despite a homogeneous increase in the air temperature over Northeast Thailand, a future decrease in soil water content will show a geographically inhomogeneous distribution: Soil will experience a relative larger decrease in wetness at a shallow depth on the Khorat plateau than in the surrounding mountainous area, reflecting vegetation cover and soil texture. The predicted increase in air temperature is relatively consistent between general circulation models. In contrast, relatively large intermodel differences in precipitation, especially in long-term trends, produce unwanted bias errors in the estimation of other hydrological elements, such as soil moisture and evaporation, and cause uncertainties in projection of the agro-climatological environment. Offline hydrological simulation with a wide precipitation range is one strategy to compensate for such uncertainties and to obtain reliable risk assessment of future cultural conditions in rainfed paddy fields in Northeast Thailand.

Projected global warming is expected to increase the occurrence of heat-induced spikelet sterility (HISS) of rice (Oryza sativa L.). Previous chamber experiments have shown that HISS can occur where temperature at flowering time exceeds the threshold temperature of around 35°C. The occurrence of HISS is, however, difficult to predict because the thermal conditions of rice canopy can be different from the air temperature under field condition. To cope with this, we developed a simple micrometeorology model focusing canopy and panicle temperatures; IM2PACT (Integrated Micrometeorology Model for Panicle And Canopy Temperature) as a tool to be incorporated into general meteorology databases. The IM2PACT was validated by leaf transpiration retarding (RT) experiment. During their flowering stage, leaf temperature elevated by RT treatment, which caused warming and drying of the air inside the canopy, resulting in the elevation of the panicle temperature (Tp). The IM2PACT well simulated the RT experiment, and was proved to simulate not only the Tp magnitude but also the effects on Tp of leaf transpiration characteristics via changes in micrometeorology inside the canopy. The IM2PACT was applied to the meteorology dataset based on ANEMOS in order to analyse the Tp at Kanto and Tokai regions of extremely hot summer in 2007. There was a great gap in spatial distributions between the Tp and the daily maximum air temperature which is commonly used as a measure of HISS, because the difference of meteorology, especially relative humidity, among areas altered the panicle-air temperature difference. This strongly suggests that we must refer to the Tp instead of the air temperature in daily maximum, as a measure variable for HISS. The IM2PACT is a powerful tool to elucidate the Tp in the climate change impact study to bridge between the responses of crop susceptible to heat and the meteorological data.

The spatiotemporal characteristics of high summertime temperatures, which can cause high-temperature injuries to rice, during the recent period of climatic variability (1978-2010) in Japan were analyzed and quantified by using daily gridded meteorological data with high spatial resolution and GIS data. Several indices based on heat-dose (defined as the cumulative temperature exceeding a certain threshold) were introduced to assess the impact of heat stress on rice production and quality. Specifically, we examined the utility of these indices for evaluating quality declines in rice. Time series of heat-dose indices based on maximum and minimum summertime temperatures showed that heat stress intensity increased remarkably from 1994. Moreover, high values of a heat-dose index based on a daily mean temperature exceeding 26°C during the 20 days after the heading date of rice showed a clear association with a decline in observed rice quality, whereas no clear relationship was apparent between decreased rice quality due to heat stress and average temperature. We also examined the effect of heat stress on spikelet fertility and ripening in the rice cultivar Koshihikari in four representative regions of Japan by using two indices, a heat-dose index based on a daily maximum temperature exceeding 35°C during 7 days around the heading date, and one based on a daily mean temperature exceeding 26°C during the 20 days after heading. The first index showed large interannual variability in the four regions because of its high dependence on the timing of heading.

Downward shortwave flux at the surface over China was derived from sunshine duration data using parameters of Jordan sunshine recorders. The sunshine duration data were obtained as routine meteorological data and ad- justed as necessary for the eects of topography, station surroundings, altitude, and atmospheric turbidity. Calculated flux was verified by in situ observations. Daily flux was calculated at more than 190 stations in China, Climatic maps (statistical period: 1971-2000) of surface solar radiation were produced and have been made public. The sunshine duration-based shortwave flux was used to check satellite observation-based datasets. Two ver- sions of satellite-based surface radiation budget datasets (SRB 2.0 and SRB 3.0) from NASA's Langley Research Center were investigated. Compared with the SRB 2.0 dataset, the SRB 3.0 dataset showed improved shortwave flux, especially over western China and the Tibetan Plateau.

This article outlined the statistical downscaling methods (SDMs) and how they derive climatic inputs for the impact models (referred to as the climate change scenario) from the outputs of dynamic global/regional climate models. To help select an appropriate method from various SDMs, the authors categorizes the SDMs into four functional categories, i.e. (1) temporal disaggregation, (2) spatial disaggregation, (3) estimation of elements not directly supplied by climate models, and (4) bias correction, and referred to some anecdotal studies of each category. In addition, a practical example of the generation of climate change scenario at a site was demonstrated to provide a concrete image for researchers trying to use SDMs. This introductory guide will help select an appropriate SDM to fill the gap between accessible climate model outputs and the requirements of impact studies.

We have developed a method for estimating hourly global solar radiation (GSR) from hourly sunshine duration data. This procedure requires only hourly sunshine duration as the input data and utilizes hourly precipitation and daily snow cover as auxiliary data to classify time intervals into six cases according to weather conditions. To obtain hourly GSR using a simple algebraic form, a quadratic function of the solar elevation angle and the sunshine duration ratio is used. Daily GSR is given by a sum of hourly GSRs. We evaluated the performance of the newly developed method using data obtained at 67 meteorological stations and found that the estimated GSR is highly consistent with that observed. Hourly and daily root-mean-square misfits are approximately 0.2 MJ/m2/h (~55 W/m2) and 1.4 to 1.5 MJ/m2/day (~16 to 17 W/m2), respectively. Our classification of weather conditions is effective for reducing estimation errors, especially under cloudy skies. Since the sunshine duration is observed at more meteorological stations than GSR, the proposed new method is a powerful tool for obtaining solar radiation with hourly resolution and a dense geographical distribution. One of the proposed methods, GSRgrn, can be applicable to hourly GSR estimations at different observation sites by setting local parameters (the precipitable water, surface albedo, and atmospheric turbidity) suitable to the sites. The hourly GSR can be applied for various micrometeorological studies, such as the heat budget of crop fields.

To estimate the regional and seasonal characteristics of the secular change in surface air temperature (SAT) over the agricultural land of Japan, we firstly analyzed the urban climate effect involving 17 general meteorological observatories selected by the Japan Meteorological Agency, and secondly, newly defined 19 stations mainly located in rural areas of Japan as representative of Japanese agro-land (Rural-19). As following analyses for regional and seasonal changes of the SAT trends, SAT was found to increase remarkably in February throughout Japan and in July over East Japan, although slightly decreasing in August and December over North Japan. The averaged trend in terms of temperature increase in the Rural-19 for each month during the period 1980-2004 was estimated to be within the range 0.3-1.4°C of the daily minimum and 0.5-2.4°C of the daily maximum SATs, respectively. The trend of the maximum SAT shows remarkable regional and seasonal variations compared with that of the minimum SAT.

We estimated monthly atmospheric turbidity from hourly observation data of global solar radiation under cloudless skies at 67 stations all over Japan. Using an empirical formula for calculating global solar radiation, we determined atmospheric turbidity as the best-fit parameter. The estimated turbidity is consistent with the observation by the Japan Meteorological Agency. Sub-nationwide increases in atmospheric turbidity, caused by forest fires or Asian dust events, are detected in time series. Some temporal changes in atmospheric turbidity are also found in a small area. Such local phenomena are hardly detectable by sparse distribution of the stations for direct solar radiation observation. The accuracy of the global solar radiation estimation can be improved by considering the seasonal variation of the turbidity. Since Angstrom’s turbidity coefficient is directly linked with the volumetric aerosol content, the present method is useful for monitoring the spatial distribution of aerosols. In addition, the present method using the densely distributed observation network of global solar radiation has an advantage in compensating for the sparseness of the current atmospheric turbidity observation in Japan.

資料番号: PA0910028000

This paper introduces the Agriculture, Forestry and Fisheries Research Council of Japan (AFFRC) model, an integrated model that predicts future rice production in the Mekong River basin by taking into account the effect of global warming on both the water cycle and the rice economy. The model focuses especially on the water balance of paddy fields for different farmland water use systems. We defined six categories of irrigated paddies and three categories of rain-fed paddies on the basis of their systems of water usage. We included a process-based model to predict future rice production, accounting for daily changes in available water resources such as precipitation. Many models of crop production treat rice in the same way as other crops; the particular characteristics of rice farming are considered in more detail in our model. Our results show that it is possible to estimate future rice production in the Mekong River basin by taking into account changes in available water, and to model the resultant effects on the grain market.

Rain-fed lowlands are major agricultural ecosystems used for rice production in Northeast Thailand. Developing a tool to assess the effects of variable water conditions on the regional scale yield is also important to predict the effects of climate change on food supply. To estimate regional yields, we need a simple but accurate measure of the crop calendar (i.e., the distribution of planting dates), which has a strong influence on grain yield. In this article, we modeled the dependence of the crop calendar on rainfall patterns based on a survey of the region’s farmers as a part of an effort to provide a stronger basis for regional yield estimates. Our survey, conducted in 11 provinces for 2 years, confirmed the existence of large windows for sowing and transplanting versus narrow windows for heading and harvesting for rain-fed lowland rice culture in all the provinces. Variable water, soil, and toposequential conditions in the paddy fields were responsible for the large sowing and transplanting windows, whereas the use of photoperiod-sensitive varieties explained the narrow windows for heading and harvesting. The crop calendar was well expressed as a function of cumulative precipitation from June onward. When the crop calendar model was combined with a simple phenology-based model that uses growing degree-days adjusted by a day-length factor, we could estimate the rice crop calendar under rain-fed lowland conditions with acceptable accuracy. The model described in this article will be combined with a crop growth model to improve regional yield estimates for rain-fed lowland rice.

Rice productivity in rainfed paddy fields varies with seasonal changes of water availability in which the conditions of flooding are affected by the water balance. Hydrometeorological measurements were performed in a rainfed paddy field in Northeast Thailand from July 2004 to December 2006 to analyze the water balance. As a result of our measurements, climatologically conditions were classified as semi-humid with an annual precipitation of 1,100 mm/year and annual potential evaporation of 1,660 mm/year in both the year. The surface layer of the paddy soil was clayey and the hydraulic conductivity was very low, so groundwater levels remained below the soil surface even under flooded conditions during the rainy season. Seasonal changes in the amount of soil water were very small, comprising only less than 16% of the total precipitation during the rainy season. Consequently, an effective precipitation of less than 180 mm was enough to establish standing water in the rainfed paddy field.

The relationship between agricultural water demand and supply has been of interest to government decision makers and scientists because of its importance in water resources management. We developed a water cycle model for eastern Eurasia that can estimate water requirements for crop growth and evaluate the demand–supply relationships of agricultural water use on a continental scale. To produce an appropriate water cycle, the model was constructed based on small drainage basins. To validate the model performance with respect to simulated runoff, which is here considered as the available water resource, we compared our outputs with those of other models and with observed river discharges. The results show that this model is comparable to other models and that it is applicable for the evaluation of water cycles at continental scale. We defined two types of crop water deficits (CWDs) as indicators of agricultural water demand. These were formulated by considering the physical processes of crop water use; we did not include water consumption that is dependent on cultivation management practices, such as water losses in irrigation systems. We assessed the reliability of our indicators by comparison with indicators from other studies and with published statistics related to agricultural water use. These comparisons suggest that our indicators are consistent with independent data and can provide a reasonable representation of water requirements for crop growth.

Methane (CH4) is a greenhouse gas, and paddy fields are one of its main anthropogenic emission sources. To mitigate this emission based on effective management measures, CH4 emission from paddy fields must be quantified at a national scale. In Japan, country-specific emission factors have been applied since 2003 to estimate national CH4 emission from paddy fields. However, this method cannot account for the effects of weather conditions and temporal variability of nitrogen fertilizer and organic matter application rates; thus, the estimated emission is highly uncertain. To improve the accuracy of national-scale estimates, we calculated country-specific emission factors using the DeNitrification-DeComposition-Rice (DNDC-Rice) model. First, we calculated CH4 emission from 1981 to 2010 using 986 datasets that included soil properties, meteorological data, and field management data. Using the simulated site-specific emission, we calculated annual mean emission for each of Japan's seven administrative regions, two water management regimes (continuous flooding and conventional mid-season drainage), and three soil drainage rates (slow, moderate, and fast). The mean emission was positively correlated with organic carbon input to the field, and we developed linear regressions for the relationships among the regions, water management regimes, and drainage rates. The regression results were within the range of published observation values for site-specific relationships between CH4 emission and organic carbon input rates. This suggests that the regressions provide a simplified method for estimating CH4 emission from Japanese paddy fields, though some modifications can further improve the estimation accuracy.

We studied the relationship between climatic conditions, such as temperature, precipitation, and solar radiation, and net primary production (NPP) estimated using the Miami model for Japan, China, and other regions in Asia. In the Miami model, NPP is constrained by either air temperature or precipitation. Our analysis showed that, in Japan, NPP is predominantly constrained by temperature, whereas precipitation is the major constraint factor in some portions of China, such as the region in the south of the Huang He River and in northwestern China. We also clarified that in the period when the average temperature was 5 degrees Celsius or more and precipitation was 50% or more of potential evapotranspiration, NPP is mostly proportional to solar radiation. In the present study, we defined the amount of solar radiation under these conditions as production effective solar radiation (PESR). This factor indicated available solar radiation for NPP. We further calculated the conversion coefficient with which PESR is converted into the NPP of natural vegetation. The conversion coefficient was 0.35 to 0.37 gMJ-1 and in general agreement with the values derived from radiation use efficiency (RUE) presented by Monteith (1977). A comparison of annual solar radiation (ASR) and PESR showed that PESR was up to 20% smaller in Japan, and up to 40% smaller than ASR in China. It showed that up to 40% of ASR does not contribute to NPP in some parts of Japan due to the constraint of air temperature, and that up to 20% of ASR is not utilized for NPP in the south of Huang He River due to the constraint of precipitation. The fraction of ASR that is not used by NPP was higher in India and Pakistan, where 20 to 60% of ASR does not play a role in the production of biomass due to the constraint of precipitation. These results showed the possibility of estimating the NPP using PESR under climatic constraints in various types of vegetation.

Distribution of air temperature around Guyuan Prefecture, south part of Ningxia in China, which has only a few meteorological observation sites, was estimated in 2km×2km mesh size by using the following methods; 1) regression estimation by altitude of each mesh, 2) regression estimation by surface temperature estimated from GMS infrared data, 3) multiple regression estimation by topographical factors of each mesh, which were calculated using altitude mesh data around the study area, 4) multiple regression estimation by NDVI and altitude of each mesh.Hourly air temperature was estimated by methods 1) and 2). Correlation coefficients by method 1) were low in winter morning, but were sufficiently high in other time. During the daytime, estimation by method 2) was accurate enough. But in most cases, accuracy of surface temperature method was lower than the method by using altitude, which was caused by low resolution of GMS data.Monthly mean temperature and monthly mean maximum and minimum temperatures were estimated by methods 1), 3) and 4). Correlation coefficients by method 1) were low in winter, especially in monthly mean minimum temperature. For method 3), stepwise regression analysis was used to decide the most effective topographical factors for the monthly mean minimum temperature. As a result, some topographical factors except altitudes were selected in winter and estimation using selected topographical factors was more accurate than using altitude only. This result indicates that the effect of topographical factors for air temperature was larger than that of altitude in winter morning. For method 4), stepwise regression analysis was carried out and NDVI was selected for several months. Estimation using NDVI and altitude was more accurate than using only altitude. These results indicate that the condition of ground vegetation affect the air temperature distribution in summer.