Assessing the impact of climate change on the land hydrology in Taiwan

The gradually increased temperature resulting from the enhanced greenhouse effects has been found to be an important factor of changes to the global climate which in turn might significantly affect the Earth's hydrological cycles. The possible outcomes of warming climate are changes of precipitation, surface runoff, evapotranspiration, and frequency of extreme weather events, such as floods and droughts. However, such changes at the global scale may not reflect the variations on a regional scale, and more so at the local scale. In this study, a physically based water balance model was applied to study the impact of climate change on the land hydrology, focusing on trends of surface runoff, evapotranspiration, and infiltration in Taiwan. Model forcing of composite temperatures and precipitations were generated by a weather generation model in association with nine climate change scenarios, including outputs of equilibrium experiments and special reports on emissions scenarios, from the IPCC. Although discrepancies among different climate change scenarios are significant, the trend of more extreme precipitations and surface runoffs were observed in most scenarios' runs. The increase of evapotranspiration in both wet and dry seasons is persistent among different scenarios throughout the island due to the projected consistently higher temperature. Although the trends of infiltration for wet and dry seasons are opposite in curtain scenarios, a decreased yearly infiltration was found in most cases as the result of increased precipitation intensity and more evapotranspiration. Timely adaption measures for water resources managements and natural hazard mitigations are required to face these changes of land hydrology components under changing climate.     

Estimation of regional renewable water resources under the impact of climate change

The purpose of this paper is to develop an estimation model for regional renewable water resources under climate change conditions. Working with Japan??s high-resolution GCM-type JMA/MRI TL959L60 future rainfall modeling data in SRES-A1B condition, first we revise the modeling data through the Quadrant Transformation Method (QTM), and then use the Thornthwaite method for potential evapotranspiration to establish regional evapotranspiration data and estimate future renewable water resources. This study focuses on Taiwan??s four water resource regions to estimate renewable water resources for each region between 2080 and 2099. The results indicate that average annual renewable water resource volume for Taiwan as a whole will drop by 12.3% from 67.5 to 59.2?km³, as compared with the average from 1949 through 2000.     

Evaluation of future climate change impact on snow hydrology for a mountainous watershed of South Korea using SLURP model and NOAA AVHRR images

This study is to evaluate the future potential climate impact on snow hydrology using SLURP model for a 6661.0 km² mountainous watershed of South Korea. For the model test, the NOAA AVHRR images were analyzed to prepare snow-related data of the model. Snow cover areas were extracted using channels 1, 3, and 4, and the snow depth was spatially interpolated using snowfall data of 11 ground meteorological stations. With the snowmelt parameters (snow cover area, snow water equivalent, and snow depth), the model was calibrated for 2 sets (2002–2003, 2004–2005), and verified for 2 sets (1997–1998 and 2001–2002) using the calibrated parameters. The average Nash–Sutcliffe efficiencies during the full year period (December to November) and snowmelt period (December to April) were 0.60 and 0.66, respectively. The future climate data of CCCma CGCM2 SRES A2 and B2 scenarios were adjusted and downscaled using change factor method. By the future impact of climate change, the annual dam inflows were projected to change maximum ?29.3 and ?30.4 % for 2090s A2 scenario and 2030s for B2 scenario, respectively. The future dam inflow increased in winter season (December to February) up to 222.0 %, while other periods decreased up to 54.8 %. The future snowmelt increased in December and January by the future temperature increase of 3.9 °C in minimum. The future snowmelt for the 2 months affected the dam inflows during the winter season.     

Assessing the impact of climate change on basin-average annual typhoon rainfalls with consideration of multisite correlation

The effects of climate change on synoptic scale storms like typhoons can have profound impacts on practices of water resources management. A stochastic multisite simulation approach is proposed for assessing the impact of climate changes on basin-average annual typhoon rainfalls (BATRs) under certain synthesized climate change scenarios. Number of typhoon events and event-total rainfalls are considered as random variables characterized by the Poisson and gamma distributions, respectively. The correlation structure of event-total rainfalls at different rainfall stations is found to be significant (higher than 0.80) and plays a crucial role in the proposed stochastic simulation approach. Basin-average annual typhoon rainfalls were simulated for the Shihmen Reservoir watershed in northern Taiwan by considering changes in the mean values of annual number of typhoon events and event-total rainfalls, while assuming the correlation structure of multisite typhoon rainfalls to remain unchanged. The simulation results indicate that changes in expected values of BATR can be easily projected with simpler models; however, changes in extreme properties of BATR are more complicated. Comparing to changes in expected values of BATRs, lesser changes in more extreme events can be observed. This is due to the reduction in coefficient of skewness of gamma distribution BATR under different climate change scenarios. With consideration of the multisite correlation structure, changes in BATRs become more significant. Thus, in assessing the impacts of climate change on many hydrological and environmental variables which exhibit significant spatial correlation pattern, the multisite correlation structure needs to be taken into consideration.     

Foliar micromorphology of Felicia muricata Thunb., A South African medicinal plant

The foliar micromorphology of Felicia muricata (Thunb.) Nees (Asteraceae) was observed with the JEOL (JSM-6390LV) Scanning Electron Microscope (SEM). Both the abaxial and adaxial surfaces were characterized by anisocytic stomata which were more prevalent on the abaxial surface than the adaxial surface. The leaves have only one type of multicellular non-glandular trichomes that are long and cylindrical, tapering to a sharp point and running parallel to the leaf surface in the direction of the apices. Crystal deposits were also observed on the surfaces of the leaves near the stomata. Energy dispersive X-ray spectroscopy-SEM shows that Na, Al, Si, and K were the major constituents of the crystal analyzed. Since no glandular trichomes were present on the leaves of this herb, the bioactive components present in this plant may be produced in some other tissues in the leaf other than the trichomes.     

Antifungal activity of leaf extracts from South African trees against plant pathogens

The antifungal activity of acetone, methanol, hexane and dichloromethane leaf extracts of six plant species (Bucida buceras, Breonadia salicina, Harpephyllum caffrum, Olinia ventosa, Vangueria infausta and Xylotheca kraussiana) were evaluated for antifungal activity against seven plant pathogenic fungal species (Aspergillus niger, Aspergillus parasiticus, Colletotricum gloeosporioides, Penicillium janthinellum, Penicillium expansum, Trichoderma harzianum and Fusarium oxysporum). These plant species were selected from 600 evaluated inter alia, against two animal fungal pathogens. All plant extracts were active against the selected plant pathogenic fungi. Of the six plant species, B. buceras had the best antifungal activity against four of the fungi, with minimum inhibitory concentration (MIC) values as low as 0.02 mg/ml and 0.08 mg/ml against P. expansum, P. janthinellum, T. harzianum and F. oxysporum. Some of the plant extracts had moderate to low activity against other fungi, indicating that the activity is not based on a general metabolic toxicity. P. janthinellum, T. harzianum and F. oxysporum were the most sensitive fungal species, with a mean MIC of 0.28 mg/ml, while the remaining four fungi were more resistant to the extracts tested, with mean MICs above 1 mg/ml. The number of active compounds in the plant extracts was determined using bioautography with the listed plant pathogens. No active compounds were observed in some plant extracts with good antifungal activity as a mixture against the fungal plant pathogens, indicating possible synergism between the separated metabolites, B. salicina and O. ventosa were the most promising plant species, with at least three antifungal compounds. Leaf extracts of different plant species using different methods (acetone, hexane, DCM and methanol) had antifungal compounds with the same R_f values. The same compounds may be responsible for activity in extracts of different plant species. Based on the antifungal activity, crude plant extracts may be a cost effective way of protecting crops against fungal pathogens. Because plant extracts contain several antifungal compounds, the development of resistant pathogens may be delayed.     

Hydrologic impact of climate change with adaptation of vegetation community in a forest-dominant watershed

This study evaluated the impact on watershed hydrology by predicting future forest community change under a climate change scenario. The Soil and Water Assessment Tool (SWAT) was selected and applied to Chungju dam watershed (6,642 km²) of South Korea. The SWAT was calibrated and validated for 6 years (1998–2003) using the daily streamflow data from three locations. For the future evaluation of forest community and hydrology, the MIROC3.2 HiRes monthly climate data were adopted. The future data were corrected using 30 years (1977–2006, baseline period) of measured weather data, and they were daily downscaled by the Long Ashton Research Station-Weather Generator statistical method. To predict the future forest vegetation cover, the baseline forest community was modeled by a multinomial LOGIT model using variables of baseline precipitation, temperature, elevation, degree of base saturation, and soil organic matter, and the future forest community was predicted using the future precipitation and temperature scenario. The future temperature increase of 4.8 °C by 2080s (2070–2099) led to prediction of 30.8 % decrease of mixed forest and 75.8 % increase of coniferous forest compared to the baseline forest community. For the baseline evapotranspiration (ET) of 491.5 mm/year, the 2080s ET under the forest community change was 591.1 mm/year, whereas it was 551.8 mm/year with the remaining forest community stationary. The different ET results considering the future forest community clearly affected the groundwater recharge and streamflow in sequence.     

Assessment of agricultural drought vulnerability to climate change at a municipal level in South Korea

This study aimed to analyze the future vulnerability to agricultural drought of the Korean administrative units of cities (Si) and counties (Gun) following the climate change phenomenon. To assess the vulnerability in a quantitative manner and also to deal with different physical and socioeconomic data on the occurrence of agricultural drought, principal component analysis (PCA), a multivariate statistical analysis method, was adopted, and a vulnerability index, regional vulnerability index to agricultural drought (RVI_AD), was suggested. RVI_AD having a range from 0.0 to 1.0 was calculated by rescaling the weighted summation of principal component scores. The analysis was performed with all 21 standardized variables in each administrative unit of Si and Gun: 3 sensitivity variables, 8 exposure variables, and 10 adaptation variables. It resulted in four principal components explaining about 85.7% of the total variance, and the third principal component, comprised of only climate variables, was used for applying future climate data from the RCP 8.5 scenario. The districts of Chungchongnam-Do (M1), Jeollabuk-Do (L1), and Jeollanam-Do (L2) were evaluated as having the highest vulnerability to agricultural drought based on the climate change scenario, not only in the present but also in future. Despite the limitation inherent in the PCA, the approach in this study could reflect different factors other than climate factors on minimizing subjective interruption, and such is expected to contribute to improving the decision-making for diagnosing the drought adaptation capacity in a region and developing measures to mitigate the drought damage.     

黄板对茶园末代绿盲蝽种群动态及空间分布型的影响

该文研究了黄板对茶园绿盲蝽种群动态及空间分布型的影响。在绿盲蝽高发期,黄板处理对绿盲蝽的发生量有着很好的控制作用,与对照处理差异显著;应用几种聚集度指标的计算公式和1wao、Taylor的回归方程式,分析和测定结果表明在绿盲蝽高发期,黄板处理改变了绿盲蝽的空间分布型,为均匀分布,对照处理为聚集分布。     

Interval number fuzzy linear programming for climate change impact assessments of reservoir active storage

The major uncertainty in the climate change impact study inherits from applying the predictions of General Circulation Models (GCMs). Different results might be obtained by using various GCMs’ predictions, which causes difficulties on the decision making of water resources management. This study proposed an integrated hydrological simulations and optimization framework, consisting of a fuzzy linear programming model with interval numbers, a streamflow simulation model, and agricultural water demand projections, to evaluate the impacts of climate change on reservoir active storage. The reservoir inflows are simulated by the WatBal model, while agricultural water demands are predicted based on the projected change of potential evapotranspiration. Inflows and water demands are used to formulate an interval number fuzzy linear programming model. Fuzzy relationships are used to describe tolerable deficits of water resources, and the interval number is employed to indicate ranges of possible inflows and water demands. This systematic framework is applied to study the Tsengwen reservoir watershed to provide an optimal interval of active storage. The results further indicate the higher tolerable deficit, the smaller difference between superior and inferior active storage.     

气候变化对甘肃胡麻生产的影响

利用1981—2000年甘肃全省71站点胡麻产量和生长期(4～10月)气象资料,用EOF、小波分析和积分 回归等统计分析方法分析胡麻产量的时空特征,以及不同气象因子对胡麻产量的影响。结果表明,胡麻产量分布 由北向南依次递减;在降水量变化一定的条件下,胡麻产量随温度的升高而降低;在温度变化一定的条件下,胡麻 产量随降水的增加而增加,适时早播可避免胡麻籽粒期高温对产量的影响。为适应气候变化,应积极试验扩大复 种面积,提高商品量。     

Prediction of paddy field change based on climate change scenarios using the CLUE model

This study simulated land-cover change using the Conversion of Land Use and its Effects (CLUE) model and predicted future changes in paddy field area under climate change scenarios A1B, A2, B1, and B2 of the Special Report on Emissions Scenarios (SRES). The CLUE model is a dynamic spatial land-use simulation model considering competition among land-use types in relation to socioeconomic and biophysical driving factors. Yongin, Icheon, and Anseong, South Korea, were selected as study areas, and scenarios were developed for regional-level simulation of land-use change. Binary logistic regressions were also conducted to evaluate the relationships between land uses and its driving factors. Finally, the simulation results suggested future changes of paddy field area under the scenario conditions. In all the scenarios, demand for cropland, including paddy and upland, decreased continuously throughout the simulation period of 2000–2100. The decrease in cropland area was particularly steep in scenario A2 in 2050. The receiver operating characteristic (ROC) values indicated that the spatial patterns of land-cover types based on the regressions were reasonably explained by the driving factors. According to the scenarios developed and location characteristics, in scenario A1B, paddy field areas were mainly transformed into built-up areas, while in the other scenarios paddy field areas were mainly transformed into forest. The approach used in this study is expected to enable exploration of future land-use changes under other development constraints and detailed scenarios.     

Estimating the potential effects of climate change on rice production in Thailand

Paddy and Water Environment - This study estimates the potential effects of climate change on rice production in Thailand based on historical data from 1989 to 2009. An econometric panel data model...     

The impact of climate change on global food supply and demand, food prices, and land use

Climate change induced crop yield change affects food production of countries to varying degrees, depending on the location of the farming activities. Differentiated yield changes of crops may lead to reallocation of agricultural land among uses. Key food exporters may reshuffle due to diverse climate change impact on crop farming among countries. We use a multi-region, multi-sector computable general equilibrium (CGE) model, which considers crop suitability of land in the optimal reallocation decision of land between uses, to simulate the impact on global food production, prices, and land use of crop yield change due to climate change as projected under the IPCC SRES scenario A2. Our findings show that developing countries are more adversely affected by climate change than developed countries. Developed countries are mostly located in higher latitudes, and climate change benefits the crop yield of these areas. In contrast, developing countries of the lower latitudes suffer from the reduction in crop yield being induced by climate change. Considering the fast growing population in the developing world, developed countries are expected to serve as the world’s key food exporters by 2020 should the climate change occurs as scenario A2 indicates.     

Long-term patterns in European brown hare population dynamics in Denmark: effects of agriculture, predation and climate

Background

In Denmark and many other European countries, harvest records suggest a marked decline in European brown hare numbers, a decline often attributed to the agricultural practice. In the present study, we analyse the association between agricultural land-use, predator abundance and winter severity on the number of European brown hares harvested in Denmark in the years 1955 through 2000.

Results

Winter cereals had a significant negative association with European brown hare numbers. In contrast to this, root crop area was positively related to their numbers. Remaining crop categories were not significantly associated with the European brown hare numbers, though grass out of rotation tended to be positively related. The areas of root crop production and of grass out of rotation have been reduced by approximately 80% and 50%, respectively, while the area of winter cereals has increased markedly (>70%). However, European brown hare numbers were primarily negatively associated with the number of red fox. Finally, we also found a positive association between mild winters and European brown hare numbers.

Conclusion

The decline of Danish European brown hare populations can mainly be attributed to predation by red fox, but the development in agricultural land-use during the last 45 years have also affected the European brown hare numbers negatively. Additionally, though mild winters were beneficial to European brown hares, the increasing frequency of mild winters during the study period was insufficient to reverse the negative population trend.     

SWAT modeling of best management practices for Chungju dam watershed in South Korea under future climate change scenarios

Suitable and practicable best management practices (BMPs) need to be developed due to steadily increasing agricultural land development, intensified fertilization practices, and increased soil erosion and pollutant loads from cultivated areas. The soil and water assessment tool model was used to evaluate the present and future proper BMP scenarios for Chungju dam watershed (6,642 km²) of South Korea, which includes rice paddy and upland crop areas. The present (1981–2010) and future (2040s and 2080s) BMPs of streambank stabilization, building recharge structures, conservation tillage, and terrace and contour farming were examined individually in terms of reducing nonpoint source pollution loads by applying MIROC3.2 HiRes A1B and B1 scenarios. Streambank stabilization achieved the highest reductions in sediment and T-N, and slope terracing was a highly effective BMP for sediment and T-P removal in both present and future climate conditions.     

The effect of climate change on global potato production

The effect of climate change on global potato production was assessed. Potential yields were calculated with a simulation model and a grid with monthly climate data for current (1961–1990) and projected (2010–2039 and 2040–2069) conditions. The results were mapped and summarized for countries. Between 1961–1990 and 2040–2069 the global (terrestrial excluding Antarctica) average temperature is predicted to increase between 2.1 and 3.2 C, depending on the climate scenario. The temperature increase is smaller when changes are weighted by the potato area and particularly when adaptation of planting time and cultivars is considered (a predicted temperature increase between 1 and 1.4 C). For this period, global potential potato yield decreases by 18% to 32% (without adaptation) and by 9% to 18% (with adaptation). At high latitudes, global warming will likely lead to changes in the time of planting, the use of later-maturing cultivars, and a shift of the location of potato production. In many of these regions, changes in potato yield are likely to be relatively small, and sometimes positive. Shifting planting time or location is less feasible at lower latitudes, and in these regions global warming could have a strong negative effect on potato production. It is shown that heat-tolerant potato cultivars could be used to mitigate effects of global warming in (sub)tropical regions.     

Impact of climate change on paddy field irrigation in southern Taiwan

Climate change can have a serious impact on water resources. The main agricultural product in southern Taiwan is rice, the planting of which consumes far more water than other crops. This makes agriculture in Taiwan especially vulnerable to climate change. In this study, we used the generalized watershed loading functions (GWLF) hydrological model to simulate the discharge of the Kaoping River under climate change scenarios A2 and B2 as released by the Intergovernmental Panel on Climate Change. We discussed the potential impact of climate change on water resources based on the results of GWLF simulations carried out using rainfall and temperature data from five general circulation models (GCMs). The simulation results indicate that river discharge in the wet season increases significantly, and decreases in the dry season. The discharge variations from using the various GCMs as inputs fall within the range of ?26 to +15 % for the dry season and ?10 to +82 % for the wet season. The variation in available water will seriously impact the first period rice farming (the period between the beginning of January and the end of May) in southern Taiwan. Consequently, effective reduction in conveyance loss in the irrigation canal systems and proper fallowing of paddy fields will be the main challenges to Taiwan’s agricultural sector for alleviating the impact of climate change. For further decision making, we show the effects of adapting to climate change by various degrees of the following two methods: fallowing paddy fields to various degrees and reducing conveyance loss in irrigation canal systems.     

Methodologies for simulating impacts of climate change on crop production

Ecophysiological models are widely used to forecast potential impacts of climate change on future agricultural productivity and to examine options for adaptation by local stakeholders and policy makers. However, protocols followed in such assessments vary to such an extent that they constrain cross-study syntheses and increase the potential for bias in projected impacts. We reviewed 221 peer-reviewed papers that used crop simulation models to examine diverse aspects of how climate change might affect agricultural systems. Six subject areas were examined: target crops and regions; the crop model(s) used and their characteristics; sources and application of data on [CO₂] and climate; impact parameters evaluated; assessment of variability or risk; and adaptation strategies. Wheat, maize, soybean and rice were considered in approximately 170 papers. The USA (55 papers) and Europe (64 papers) were the dominant regions studied. The most frequent approach used to simulate response to CO₂ involved adjusting daily radiation use efficiency (RUE) and transpiration, precluding consideration of the interacting effects of CO₂, stomatal conductance and canopy temperature, which are expected to exacerbate effects of global warming. The assumed baseline [CO₂] typically corresponded to conditions 10-30 years earlier than the date the paper was accepted, exaggerating the relative impacts of increased [CO₂]. Due in part to the diverse scenarios for increases in greenhouse gas emissions, assumed future [CO₂] also varied greatly, further complicating comparisons among studies. Papers considering adaptation predominantly examined changes in planting dates and cultivars; only 20 papers tested different tillage practices or crop rotations. Risk was quantified in over half the papers, mainly in relation to variability in yield or effects of water deficits, but the limited consideration of other factors affecting risk beside climate change per se suggests that impacts of climate change were overestimated relative to background variability. A coordinated crop, climate and soil data resource would allow researchers to focus on underlying science. More extensive model intercomparison, facilitated by modular software, should strengthen the biological realism of predictions and clarify the limits of our ability to forecast agricultural impacts of climate change on crop production and associated food security as well as to evaluate potential for adaptation.