Probabilistic evaluation of climate change impacts on paddy rice productivity in Japan

Projecting the impacts of climate change includes various uncertainties from physical, biophysical, and socioeconomic processes. Providing a more comprehensive impact projection that better represents the uncertainties is a priority research issue. We used an ensemble-based projection approach that accounts for the uncertainties in climate projections associated with general circulation models (GCMs) and biophysical and empirical parameter values in a crop model. We applied the approach to address the paddy rice yield change in Japan in the 2050s (2046–2065) and 2090s (2081–2100) relative to the 1990s (1981–2000). Seventeen climate projections, nine (eight) climate projections performed by seven (six) GCMs conditional on the Special Report on Emission Scenarios (SRES) A1B (A2), were included in this projection. In addition, 50 sets of biophysical and empirical parameter values of a large-scale process-based crop model for irrigated paddy rice were included to represent the uncertainties of crop parameter values. The planting windows, cultivation practices, and crop cultivars in the future were assumed to be the same as the level in the baseline period (1990s). The resulting probability density functions conditioned on SRES A1B and A2 indicate projected median yield changes of +?17.2% and +?26.9% in Hokkaido, the northern part of Japan, in the 2050s and 2090s with 90% probability intervals of (??5.2%, +?40.3%) and (+?6.3%, +?51.2%), relative to the 1990s mean yield, respectively. The corresponding values in Aichi, on the Pacific side of Western Japan, are 2.2% and ??0.8%, with 90% probability intervals of (??15.0%, +?14.9%) and (??33.4%, +?17.9%), respectively. We also provided geographical maps of the probability that the future 20-year mean yield will decrease and that the future standard deviation of yield for 20 years will increase. Finally, we investigated the relative contributions of the climate projection and crop parameter values to the uncertainty in projecting yield change in the 2090s. The choice of GCM yielded a relatively larger spread of projected yield changes than that of the other factors. The choice of crop parameter values could be more important than that of GCM in a specific prefecture.     

The water impacts of climate change mitigation measures

A variety of proposed activities to mitigate greenhouse gas emissions will impact on scarce water resources, which are coming under increasing pressure in many countries due to population growth and shifting weather patterns. However, the integrated analysis of water and carbon impacts has been given limited attention in greenhouse mitigation planning. In this Australian case study, we analyse a suite of 74 mitigation measures ranked as highest priority by one influential analysis, and we find that they have highly variable consequences for water quantity. We find: (1) The largest impacts result from land-based sequestration, which has the potential to intercept large quantities of water and reduce catchment yields, estimated to exceed 100 Mm³/MtCO₂-e of carbon mitigated (100,000 l per tonne CO₂-e). (2) Moderate impacts result from some renewable power options, including solar thermal power with a water cost estimated at nearly 4 Mm³/MtCO₂-e. However, the water impacts of solar thermal power facilities could be reduced by designing them to use existing power-related water supplies or to use air or salt-water cooling. (3) Wind power, biogas, solar photovoltaics, energy efficiency and operational improvements to existing power sources can reduce water demand through offsetting the water used to cool thermal power generation, with minor savings estimated at 2 Mm³/MtCO₂-e and amounting to nearly 100 Mm³ of water saved in Australia per annum in 2020. This integrated analysis significantly changes the attractiveness of some mitigation options, compared to the case where water impacts are not considered.     

High resolution modeling of the regional impacts of climate change on irrigation water demand

In the Arkansas River Basin in southeastern Colorado, surface irrigation provides most of the water required for agriculture. Consequently, the region’s future could be significantly affected if climate change impacts the amount of water available for irrigation. A methodology to model the expected impacts of climate change on irrigation water demand in the region is described. The Integrated Decision Support Consumptive Use model, which accounts for spatial and temporal variability in evapotranspiration and precipitation, is used in conjunction with two climate scenarios from the Vegetation-Ecosystem Modeling and Analysis Project. The two scenarios were extracted and scaled down from two general circulation models (GCMs), the HAD from the Hadley Centre for Climate Prediction and Research and the CCC from the Canadian Climate Centre. The results show significant changes in the water demands of crops due to climate change. The HAD and CCC climate change scenarios both predict an increase in water demand. However, the projections of the two GCMs concerning the water available for irrigation differ significantly, reflecting the large degree of uncertainty concerning what the future impacts of climate change might be in the study region. As new or updated predictions become available, the methodology described here can be used to estimate the impacts of climate change.     

Assessing regional impacts and adaptation strategies for climate change: the Washington Climate Change Impacts Assessment

Climate change in the twenty-first century will strongly affect the processes that define natural and human systems. The Washington Climate Change Impacts Assessment (WACCIA) was intended to identify the nature and effects of climate change on natural and human resources in Washington State over the next century. The assessment focused on eight sectors that were identified as being potentially most climate sensitive: agriculture, energy, salmon, urban stormwater infrastructure, forests, human health, coasts, and water resources. Most of these sectors are sensitive in one way or another to water availability. While water is generally abundant in the state under current climate conditions, its availability is highly variable in space and time, and these variations are expected to change as the climate warms. Here we summarize the results of the WACCIA and identify uncertainties and common mechanisms that relate many of the impacts. We also address cross-sectoral sensitivities, vulnerabilities, and adaptation strategies.     

Impact of climate change on irrigation water demand of dry season Boro rice in northwest Bangladesh

Climate change will affect irrigation water demand of rice via changes in rice physiology and phenology, soil water balances, evapotranspiration and effective precipitation. As agriculture is the main sector of water use in Bangladesh, estimation of the agricultural water demand in the changing environment is essential for long-term water resources development and planning. In the present paper, a study has been carried out to estimate the change of irrigation water demand in dry-season Boro rice field in northwest Bangladesh in the context of global climate change. The study shows that there will be no appreciable changes in total irrigation water requirement due to climate change. However, there will be an increase in daily use of water for irrigation. As groundwater is the main source of irrigation in northwest Bangladesh, higher daily pumping rate in dry season may aggravate the situation of groundwater scarcity in the region.     

Assessing the impacts of climate change on rice yields in the main rice areas of China

This paper assesses the impact of climate change on irrigated rice yield using B2 climate change scenario from the Regional Climate Model (RCM) and CERES-rice model during 2071--2090. Eight typical rice stations ranging in latitude, longitude, and elevation that are located in the main rice ecological zones of China are selected for impact assessment. First, Crop Estimation through Resource and Environment Synthesis (CERES)-rice model is validated using farm experiment data in selected stations. The simulated results represent satisfactorily the trend of flowering duration and yields. The deviation of simulation within ± 10% of observed flowering duration and ± 15% of observed yield. Second, the errors of the outputs of RCM due to the difference of topography between station point and grid point is corrected. The corrected output of the RCM used for simulating rice flowering duration and yield is more reliable than the not corrected. Without CO₂ direct effect on crop, the results from the assessment explore that B2 climate change scenario would have a negative impact on rice yield at most rice stations and have little impacts at Fuzhou and Kunming. To find the change of inter-annual rice yield, a preliminary assessment is made based on comparative cumulative probability at low and high yield and the coefficient variable of yield between the B2 scenario and baseline. Without the CO₂ direct effect on rice yield, the result indicates that frequency for low yield would increase and it reverses for high yield, and the variance for rice yield would increase. It is concluded that high frequency at low yield and high variances of rice yield could pose a threat to rice yield at most selected stations in the main rice areas of China. With the CO₂ direct effect on rice yield, rice yield increase in all selected stations.     

An assessment of climate change impacts and adaptation for the Torres Strait Islands, Australia

Adaptive practices are taking place in a range of sectors and regions in Australia in response to existing climate impacts, and in anticipation of future unavoidable impacts. For a rich economy such as Australia’s, the majority of human systems have considerable adaptive capacity. However, the impacts on human systems at the intra-nation level are not homogenous due to their differing levels of exposure, sensitivity and capacity to adapt to climate change. Despite past resilience to changing climates, many Indigenous communities located in remote areas are currently identified as highly vulnerable to climate impacts due to their high level of exposure and sensitivity, but low capacity to adapt. In particular, communities located on low-lying islands have particular vulnerability to sea level rise and increasingly intense storm surges caused by more extreme weather. Several Torres Strait Island community leaders have been increasingly concerned about these issues, and the ongoing risks to these communities’ health and well-being posed by direct and indirect climate impacts. A government agency is beginning to develop short-term and long-term adaptation plans for the region. This work, however, is being developed without adequate scientific assessment of likely ‘climate changed futures.’ This is because the role that anthropogenic climate change has played, or will play, on extreme weather events for this region is not currently clear. This paper draws together regional climate data to enable a more accurate assessment of the islands’ exposure to climate impacts. Understanding the level of exposure and uncertainty around specific impacts is vital to gauge the nature of these islands’ vulnerability, in so doing, to inform decisions about how best to develop anticipatory adaptation strategies over various time horizons, and to address islanders’ concerns about the likely resilience and viability of their communities in the longer term.     

National-level factors affecting planned,public adaptation to health impacts of climate change

Our understanding of whether adaptive capacity on a national level is being translated into adaptation policies, programs, and projects is limited. Focusing on health adaptation in Annex I Parties to the UNFCCC, we examine whether statistically significant relationships exist between regulatory, institutional, financial, and normative aspects of national-level adaptive capacity and systematically measured adaptation. Specifically, we (i) quantify adaptation actions in Annex I nations, (ii) identify potential factors that might impact progress on adaptation and select measures for these factors, and (iii) calculate statistical relationships between factors and adaptation actions across countries. Statistically significant relationships are found between progress on adaptation and engagement in international environmental governance, national environmental governance, perception of corruption in the public sector, population size, and national wealth, as well as between responsiveness to health vulnerabilities, population size and national wealth. This analysis contributes two key early empirical findings to the growing literature concerning factors facilitating or constraining adaptation. While country size and wealth are necessary for driving higher levels of adaptation, they may be insufficient in the absence of policy commitments to environmental governance. Furthermore, governance and/or incentive frameworks for environmental governance at the national level may be an important indicator of the strength of national commitments to addressing health impacts of climate change.     

气候变化对水资源影响预估常用指标

正全球气候变暖已成共识。自20世纪50年代至今,全球几乎所有地区都在持续变暖。IPCC第五次评估报告(AR5)显示,全球温度将进一步升高[1]。以1986—2005年为基准,预计全球地表温度在2016—2035年将升高0.3～0.7℃,2081—2100年升高0.3～4.8℃[2]。全球变暖导致一系列环境问题:海洋温度及地球表面温度上升,     

Enhancing the relevance of Shared Socioeconomic Pathways for climate change impacts,adaptation and vulnerability research

This paper discusses the role and relevance of the shared socioeconomic pathways (SSPs) and the new scenarios that combine SSPs with representative concentration pathways (RCPs) for climate change impacts, adaptation, and vulnerability (IAV) research. It first provides an overview of uses of social–environmental scenarios in IAV studies and identifies the main shortcomings of earlier such scenarios. Second, the paper elaborates on two aspects of the SSPs and new scenarios that would improve their usefulness for IAV studies compared to earlier scenario sets: (i) enhancing their applicability while retaining coherence across spatial scales, and (ii) adding indicators of importance for projecting vulnerability. The paper therefore presents an agenda for future research, recommending that SSPs incorporate not only the standard variables of population and gross domestic product, but also indicators such as income distribution, spatial population, human health and governance.     

Assessment of climate change impacts on climate variables using probabilistic ensemble modeling and trend analysis

Water resources in snow-dependent regions have undergone significant changes due to climate change. Snow measurements in these regions have revealed alarming declines in snowfall over the past few years. The Zayandeh-Rud River in central Iran chiefly depends on winter falls as snow for supplying water from wet regions in high Zagrous Mountains to the downstream, (semi-)arid, low-lying lands. In this study, the historical records (baseline: 1971–2000) of climate variables (temperature and precipitation) in the wet region were chosen to construct a probabilistic ensemble model using 15 GCMs in order to forecast future trends and changes while the Long Ashton Research Station Weather Generator (LARS-WG) was utilized to project climate variables under two A2 and B1 scenarios to a future period (2015–2044). Since future snow water equivalent (SWE) forecasts by GCMs were not available for the study area, an artificial neural network (ANN) was implemented to build a relationship between climate variables and snow water equivalent for the baseline period to estimate future snowfall amounts. As a last step, homogeneity and trend tests were performed to evaluate the robustness of the data series and changes were examined to detect past and future variations. Results indicate different characteristics of the climate variables at upstream stations. A shift is observed in the type of precipitation from snow to rain as well as in its quantities across the subregions. The key role in these shifts and the subsequent side effects such as water losses is played by temperature.

     

The implications of climate policy for the impacts of climate change on global water resources

This paper assesses the implications of climate policy for exposure to water resources stresses. It compares a Reference scenario which leads to an increase in global mean temperature of 4 °C by the end of the 21st century with a Mitigation scenario which stabilises greenhouse gas concentrations at around 450 ppm CO₂e and leads to a 2 °C increase in 2100. Associated changes in river runoff are simulated using a global hydrological model, for four spatial patterns of change in temperature and rainfall. There is a considerable difference in hydrological change between these four patterns, but the percentages of change avoided at the global scale are relatively robust. By the 2050s, the Mitigation scenario typically avoids between 16 and 30% of the change in runoff under the Reference scenario, and by 2100 it avoids between 43 and 65%. Two different measures of exposure to water resources stress are calculated, based on resources per capita and the ratio of withdrawals to resources. Using the first measure, the Mitigation scenario avoids 8-17% of the impact in 2050 and 20-31% in 2100; with the second measure, the avoided impacts are 5-21% and 15-47% respectively. However, at the same time, the Mitigation scenario also reduces the positive impacts of climate change on water scarcity in other areas. The absolute numbers and locations of people affected by climate change and climate policy vary considerably between the four climate model patterns.     

Least-cost adaptation options for global climate change impacts on the Brazilian electric power system

Global climate change induced by the emission of greenhouse gases may pose challenges to energy security. The vulnerability of energy sources, in particular of renewable sources, to climate change raises the need to identify adaptation measures. This paper applies an integrated resource planning approach to calculate least-cost adaptation measures to a set of projected climate impacts on the Brazilian power sector. The methodology used has the advantage of finding optimal solutions that take into consideration the whole energy chain and the interactions between energy supply and demand. Results point in the direction of an increased installed capacity based, mostly, on natural gas, but also sugarcane bagasse, wind power and coal/nuclear plants, to compensate for a lower reliability of hydroelectric production, amongst other impacts. The indirect effect of these results is the displacement of natural gas from other consuming sectors, such as industry, in favor of its use for power generation. Results obtained are, however, based on the techno-economic premises used in the simulation, which may vary in the long term.     

Regional assessment of climate change impacts on coastal and fluvial ecosystems and the scope for adaptation

Ecosystem changes in floodplains could be a major issue during the twenty-first century as designated habitat areas are affected by climate change and floodplain management options. As part of the RegIS project, a Regional Impact Simulator has been developed to investigate these potential changes. This paper presents the methodologies and results of biodiversity metamodels used within the Regional Impact Simulator for two regions of the UK: East Anglia and North West England. Potential impacts and adaptations to future climate and socio-economic scenarios are analysed for three habitat types in floodplains (saltmarsh, coastal grazing marsh and fluvial grazing marsh) and selected species. An important finding is that management choices, which can be linked to socio-economic futures have a greater potential impact on habitat viability than climate change. The choices society makes will therefore be key to protection and conservation of biodiversity. The analyses also show that coastal grazing marsh is the most vulnerable habitat to sea-level rise, although there is a scope for substituting losses with fluvial grazing marsh. These results indicate that these methods provide a useful approach for assessing potential biodiversity changes at the regional scale, including the effect of different policies.     

Classifying knowledge on climate change impacts, adaptation, and vulnerability in Europe for informing adaptation research and decision-making: A conceptual meta-analysis

Knowledge on climate change impacts, adaptation, and vulnerability is fragmented, because it is found in disparate case studies which use inconsistent terminology and focus on distinct aspects relevant to adaptation. While large-scale syntheses such as the Assessment Reports of the Intergovernmental Panel on Climate Change provide a high level overview and are useful for international decision-making, there is a need for systematic and flexible access to this research-based knowledge in order to aid future adaptation research and decision-making. Against this background, we present a ‘conceptual’ meta-analysis, a novel approach to meta-analyse studies on climate change impacts, adaptation, and vulnerability in Europe. The meta-analysis results in a classification scheme for relating the diverse studies. This scheme consists of (i) a classification of studies according to the type of adaptation-relevant results they produce and (ii) a hierarchical classification of the regional and thematic context of studies. The implementation of this scheme, for example in the form of a database, overcomes some of the identified gaps of current adaptation knowledge representation. We furthermore present a quantitative analysis of the classified studies that exemplifies how the developed classification scheme can be applied to get a systematic and quantitative overview of the knowledge they contain. Thus, the conceptual meta-analysis and the classification scheme represent a first step towards a systematisation of knowledge on climate change impacts, adaptation, and vulnerability and may be seen as a useful complement to qualitative literature reviews.