Synoptic weather typing and typhoon with an application to Chiayi, Taiwan: potential for future climate change impact analysis

In this study, an automated synoptic weather typing was employed to identity the weather types most likely associated with daily typhoon/typhoon-related heavy rainfall events for Chiayi, Taiwan. The synoptic weather typing was developed using principal components analysis, an average linkage clustering procedure, and discriminant function analysis. The classification results showed that the synoptic weather typing was successful at identifying typhoon-related weather types. Five synoptic weather types (Weather Types 1–5) were identified over the past 11-year period as the primary typhoon-related weather types. These five typhoon-related weather types can capture 34 out of 36 total typhoon-related heavy rainfall days (>50 mm/d) and all nine cases with typhoon-related daily rainfall >200 mm during the period March 1998–December 2008. This result suggests that synoptic weather typing can be useful to identify historical typhoon/typhoon-related heavy rainfall events. Moreover, the method has potential to assess climate change impacts on the frequency/intensity of future typhoon/typhoon-related heavy rainfall events using future downscaled GCM climate data.     

Assessment and validation of CLIGEN-simulated rainfall data for Northern Taiwan

By using CLIGEN and long-term meteorological data, consecutive daily rainfall data can be simulated. At present, the applicability of CLIGEN to regions other than the United States remains to be tested. In this study, CLIGEN was first applied in a subtropical monsoon climate region. Rainfall data from 1961 to 1990 at three weather stations in northern Taiwan were collected, and rainfall parameters and patterns were validated. The results showed no significant difference in the mean and distribution patterns between observed and simulated values for rainfall parameters including precipitation for each month, wet days for each month, precipitation on wet days for each month and standard deviation of daily precipitation for each month. Regarding rainfall pattern, after re-calibration of storm pattern coefficients, the accuracy of the simulated storm duration was greatly enhanced. However, the simulated daily maximum 5- and 30-min peak intensities were overestimated, and there is room for improvement.     

山西省玉米生育前期降水概率与特征分析

利用山西省春玉米区95个气象站1971～2005年4～6月逐日降水资料,分析了影响玉米出苗和苗期生长的降水条件的变化。结果表明,春季第一场透雨多数年份出现在适播期内,且有提前的趋势,有利于玉米播种出苗,但各站无透雨年出现几率较大,应引起足够的重视;苗期降水变化较大且严重不足,对玉米苗期生长利少弊多。     

Teleconnection of rainfall time series in the central Nile Basin with sea surface temperature

We investigated teleconnections of rainfall time series in the central Nile Basin (Sudan and South Sudan) with localities in the global sea surface temperature (SST) field, using monthly rainfall data from 11 gauging stations from 1960 to 1999. Annual rainfall ranged from 100 mm in the north to more than 700 mm in the south, and all stations had a strong contrast between rainy and dry seasons with rainless dry periods of several months. Rainfall time series at the stations were categorized as strongly seasonal, with precipitation concentration index exceeding 16 and seasonality index exceeding 0.9. The rainfall stations were classified into four zones on the basis of annual rainfall, seasonality, and cross-correlations among the stations. We calculated cross-correlations of interannual rainfall time series in summer (July and August) with the global SST field. For short lag times (0 or 1 month), summer rainfall in Zones I and II (northern arid regions) had significant correlations with SST over the eastern Mediterranean Sea and southern Indian Ocean, summer rainfall in Zone III (semiarid region) had significant negative correlations with SST over the Indian Ocean, and summer rainfall in Zone IV (southern wet region) had significant correlations with SST over tropical areas and the southwestern Pacific Ocean. For long lag times (3–6 months), Nile Basin summer rainfall time series had significant correlations with SST in various regions of the Atlantic and Indian Oceans but not the Pacific Ocean. Rainfall in Zones I and II had positive correlations (significance level?<?0.01) with SST south of Greenland and around the Azores Islands and negative correlations with SST south of Madagascar; rainfall in Zone III had negative correlations with SST in parts of the Indian Ocean; and rainfall in Zone IV had significant positive correlations with SST southwest of South Africa and negative correlations with SST in the southwestern Indian Ocean. In sum, rainfall in three of the zones (I, II, and IV) had significant positive and negative correlations with SST in parts of the Indian and Atlantic Oceans. For each of these zones, one positive correlation and one negative correlation were selected and correlations with the time series of the difference between the two SST records were calculated. Correlations of Nile Basin rainfall with the SST differences were stronger than the original positive and negative correlations. The resulting time series of SST difference were applied to an artificial neural network to predict summer rainfall, yielding satisfactory correlation coefficients between the observed and predicted summer rainfall (r?>?0.70).     

2020年江苏春茶减产原因分析

2020年江苏早春气温平稳上升,几乎未发生晚霜冻,茶叶产量较往年却减产10%~20%。文章利用主产区气象站历史观测资料和2020年茶叶生产相关资料,分析其减产原因,认为2020年早春气温异常偏高,开采期比常年提前10 d以上,3月17—27日最高气温基本维持在20℃以上,采摘洪峰来得早,受疫情影响引起的茶场人力不足,严重影响茶叶采摘进度,造成茶园产量降低。此外,2019年秋季持续干旱和2020年采摘期多降水过程,对茶叶生产也造成了负面影响。     

Export rate of dissolved organic matter from paddy fields during cultivation-activity events

The aim of this study is to quantify the dissolved organic carbon (DOC) of drainage water from paddy fields in agricultural areas of Tottori prefecture, Japan. In four experimental paddy fields, DOC concentration varied much from 1.1 to 10.1 mg C l⁻¹, and was the highest during heavy runoff that occurred in April when there was a non-agricultural period. However, variation in DOC concentration did not always correspond to rainfall, but depended more on cultivation-activity events such as tilling, planting, draining in summer, and final draining in autumn. The water discharge rate from each experimental field was estimated by using a hydrologic model (the Tank Model and a genetic algorithm). Daily DOC export rate per unit area of three experimental paddy fields was calculated to be 0.0074, 0.0052, and 0.0081 kg a⁻¹ day⁻¹, respectively. The daily DOC export rate showed large seasonal variation with the highest value in May and June. It can be concluded that DOC export from paddy fields can be a substantial source of DOC in receiving waters, and the export rate depends much on cultivation method practice. It might be suggested that DOC export from paddy fields can be controlled by a better water management practice of farmers.     

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.     

Assessing the impact of climate change on annual typhoon rainfall—a stochastic simulation approach

Rainfall amount drawn by typhoon events accounts for a significant portion of annual rainfall in Taiwan. Changes in typhoon rainfall due to climate change may have severe consequences for water resources management. A stochastic simulation approach is proposed for evaluation of changes in typhoon rainfall under certain climate change scenarios. The number of typhoon events and total rainfall of individual typhoon events are, respectively, considered as random variables of the Poisson and Gamma distributions. Climate change scenarios were set by varying various degrees of changes in average number of typhoon events annually and the mean of event-total rainfall. Using stochastic simulation, basin-wide annual typhoon rainfalls were simulated for the Shihmen Reservoir watershed in northern Taiwan. It is found that 10% increases in average annual number of typhoon events and mean event-total rainfall will result in 18% increase in the annual typhoon rainfall of 5-year return period, whereas the annual typhoon rainfall of 10-year return period will increase by 15% under the same climate change scenario. Such increases may cause significant increase in reservoir sediment and pose challenges to reservoir management.     

海南岛典型农业土壤产流与面源污染特征分析

采用径流场结合人工模拟降雨方式,研究各种降雨条件下海南岛不同土地类型产流产沙的规律与面源污染特征。结果表明：土壤（泥沙）产流系数与平均流失速率表现为暴雨＞大雨＞中雨,且暴雨时的泥沙平均流失速率为中雨时的416％、大雨时的261％,在中雨、大雨和暴雨强度下,平均径流系数分别为24.49％、33.97％和53.40％;雨强对土壤营养物质流失速率的影响达到显著水平,COD、有机质和氮素以径流流失为主,磷素以泥沙流失为主;土壤径流和泥沙中的COD、有机质、氮素和磷素流失速率随雨强的增大而增大,坡度也可明显影响面源污染物的流失;海南岛农业土壤平均流失量为3.79 t/（hm2·a）,中雨强度条件时为1.92 t/（hm2·a）,大雨强度条件时为2.57 t/（hm2·a）,暴雨强度条件时为6.87 t/（hm2·a）。海南岛农业土壤的水土流失强度较高,海南农业土壤的水土流失与农田污染物输出状况不容乐观。     

热带气旋影响下海南岛卫星降水估计产品的检验分析

利用2007～2011年海南热带气旋过程的地面站雨量资料，对国家卫星气象中心和中国气象局上海台风所基于FY2D和GMS-5红外亮温资料研发的卫星降水估计产品进行定量评估。结果表明：无论是6 h还是24 h降水，FY2D降水估计产品对海南热带气旋降水的反演精度要比GMS-5降水估计产品高；FY2D和GMS-5卫星估计降水具有估测大暴雨以上强降水的优势，对热带气旋强降水预报业务具有参考性；对6h强降水估计能力的空间分布而言，FY2D降水估计产品估测能力为岛西高，岛东低。GMS-5降水估计产品的估测能力为岛北高，岛南低；登陆海南岛北部地区的热带气旋降水估计技巧比登陆海南岛南部地区的热带气旋高；两种卫星降水估计产品对中小尺度强降水极值估计偏弱。     

Forecasting the emergence of the adult orange wheat blossom midge,Sitodiplosis mosellana (Géhin) (Diptera: Cecidomyiidae) in Belgium

Agronomists often underestimate the damage inflicted by the orange wheat blossom midge, Sitodiplosis mosellana (Géhin), a wheat (Triticum aestivum L.) pest. The main risk arises when the emergence of the adult midges coincides with wheat ear emergence. The emergence of adult midges was monitored in Belgium over four years and analysed against climate data, establishing the significance of specific rainfall events as triggers for the final phase of development prior to emergence. This discovery, combined with experience from previous models, was incorporated into a new forecasting model, described in this paper. The new model consists of three separate phases. The first phase comprised a temperature accumulation of 250 degree-days (DD) above 3 °C, starting from 1 January. Once this initial condition is satisfied, the second phase starts, and it lasts until the occurrence of a double signal consisting of a rise in the mean daily temperature up to 13 °C, followed by rainfall. This rainfall event triggers an accumulation phase of 160 DD above 7 °C. Once this last condition is met, the adults emerge.     

Comparison of a pasture-based system of milk production on a high rainfall, heavy-clay soil with that on a lower rainfall, free-draining soil

The objective of this study was to compare the biological and economic efficiency of a seasonal pasture‐based spring calving system of milk production on a high‐rainfall, heavy‐clay soil [Kilmaley (KMY)] to that on a lower‐rainfall free‐draining soil [Moorepark (MPN)] in Ireland. The physical performance data were obtained from a 3‐year study (1998–2000) carried out at both sites. Analysis of the system of milk production at the two sites was undertaken using the Moorepark Dairy System Model. Herbage dry‐matter production was greater at the MPN site with a greater proportion being produced between 1 September and 1 May. On average, over the 3 years, the system of milk production at the MPN site had a higher stocking rate (2·34 vs. 1·89 cows ha^?1), higher milk production per cow (6421 vs. 5781 kg per cow), longer grazing season (250 vs. 149 d) and a higher proportion of the diet of the herd from grazed grass (0·70 vs. 0·40) than at KMY. Economic analysis showed that, in a 468 100 kg European Union milk quota scenario, the profitability at the MPN site was €28 417 greater than at the KMY site. At similar milk production per cow it was €19 138 greater. Monte Carlo simulation showed that the MPN site was stochastically dominant over the KMY site. Sensitivity analyses showed that farm profit was most sensitive to changes in milk price. The results also indicated that milk production in the future may not be sustainable economically on high‐rainfall, heavy‐clay soils in Ireland.     

Determinants of groundnut rosette virus disease occurrence in Uganda

Groundnut rosette virus disease (GRVD) is the major constraint to groundnut (Arachis hypogaea) production in Uganda. It is principally transmitted by the groundnut aphid (Aphis craccivora Koch). The disease is known to cause total crop failure in cases where susceptible varieties are used. During any particular season, GRVD displays variations in incidence and severity in different agro-ecologies within the country, but the reasons for the varying disease patterns remain unclear. This study was aimed at establishing the factors influencing the occurrence of GRVD in Uganda. Trials were established for three seasons in four groundnut growing locations situated in different agro-ecologies in Uganda. Four groundnut genotypes were used as treatments in a randomized complete block design with four replications. Disease progress and aphid populations were assessed at 4, 8 and 12 weeks after planting. Data on environmental factors; particularly rainfall, temperature and wind speed were obtained from standard meteorological stations located at/near the study sites. Soil samples and yield data were also obtained in each season. The study revealed that disease incidence; severity and groundnut yields were significantly affected by season, location and genotype. The same applied to their three way interactions. Levels of disease infection were found to be majorly influenced by rainfall and wind speed. Disease incidence and severity were generally higher in conditions with less rainfall and low wind speeds. The Pearson's two tailed correlation between total rainfall and disease incidence for all trial sites was negative and highly significant (r = −0.280, P ≤ 0.01). The same was true for wind speed and disease incidence (r = −0.476, P ≤ 0.01). However, there was no conclusive trend between temperature and disease incidence with the Pearson's two tailed correlation showing significantly positive and negative trends depending on location.     

Estimation of the spatial rainfall distribution using inverse distance weighting (IDW) in the middle of Taiwan

In this article, we used the inverse distance weighting (IDW) method to estimate the rainfall distribution in the middle of Taiwan. We evaluated the relationship between interpolation accuracy and two critical parameters of IDW: power (?? value), and a radius of influence (search radius). A total of 46 rainfall stations and rainfall data between 1981 and 2010 were used in this study, of which the 12 rainfall stations belonging to the Taichung Irrigation Association (TIA) were used for cross-validation. To obtain optimal interpolation data of rainfall, the value of the radius of influence, and the control parameter-?? were determined by root mean squared error. The results show that the optimal parameters for IDW in interpolating rainfall data have a radius of influence up to 10?C30?km in most cases. However, the optimal ?? values varied between zero and five. Rainfall data of interpolation using IDW can obtain more accurate results during the dry season than in the flood season. High correlation coefficient values of over 0.95 confirmed IDW as a suitable method of spatial interpolation to predict the probable rainfall data in the middle of Taiwan.     

早稻空秕率与抽穗开花期气象条件分析

为探讨早稻抽穗开花期气象因子对空秕率的影响,趋利避害,确保高产稳产,利用娄底农业气象观测站1981～2010年的早稻空秕率、发育期资料,以及娄底国家地面气象站的气象要素,分析早稻抽穗开花期光、温、水等气象条件与空壳率、秕粒率、空壳率＋秕粒率的相关性,选取相关性好的气象因子,阐述气象条件对空秕率的影响。结果表明：降水量、降水日数、日平均相对湿度、日最高气温是引起空秕率变化的主要气象因子。降水量、降水日数、日平均相对湿度与空秕率成正相关,日最高气温与空秕率成负相关。     

Terraced paddy field rainfall-runoff mechanism and simulation using a revised tank model

Terraced paddy fields play important roles in water and soil conservation because their water storage effect reduces and delays flood peaks. This study applies the terraced paddy field rainfall-runoff mechanism to the tank model. Though the traditional four-section tank model can easily simulate rainfall-runoff in a terraced paddy field, it has many parameters that are difficult to calibrate. To address the shortcomings of the traditional four-section tank model, this study develops a revised tank model to simulate rainfall-runoff. This study selects a terraced paddy field located in Hsuing-Pu village in Hsiuing-Chu County as the experimental field. The field under investigation was equipped with automatic monitoring stations, water-stage, and rain gauges. These stations collected data on rainfall and water flow to simulate the rainfall-runoff model in that region. To simulate the runoff behavior of the experimental terraced paddy field, two rainfall events were selected from the gathered data and five normal evaluation indexes based on static and hydrological theory were applied to calculate the results of simulation simultaneously. The revised tank model performed better than expected, and precisely predicted the variations and trends in flow charge. Comparison with representation indexes proved that the revised tank model is an appropriate and valuable tool for rainfall-runoff simulation.     

A decision support system for agricultural drought management using risk assessment

Since predicted changes in climate will modify temperature and rainfall patterns, there are concerns about the potential impacts of these changes on agricultural drought and agricultural water resources management. An agricultural drought is influenced by several factors such as rainfall, soil characteristics, crops, and reservoir water supply and may be defined as the imbalance of water circulation in paddy and water environments. In particular, soil moisture and water supply for reservoir demand are the most direct and important indicators of agricultural drought events. In the past, conventional drought management approaches based on climatic and meteorological observations have been the primary tools used for measuring drought severity. Because of the spatial and temporal variability and multiple impacts of drought, it is necessary to improve tools to determine the onset, severity, spatial extent, and end of the drought conditions. Improved and available data for mapping and monitoring of this phenomenon are also needed. Effective and efficient drought management can be achieved through drought monitoring based on the ability to assess current conditions and provide improved tools to adapt and mitigate the impacts of future changes. In this article, a methodology is developed to support the risk-based decision-making process involved in agricultural drought management using the following four strategies: drought assessment and monitoring, drought forecast and outlook, drought countermeasures, and drought records management.     

Water quality monitoring and multivariate statistical analysis for rural streams in South Korea

South Korea is located in the Asian monsoon region, and paddy rice farming is one of the important agricultural activities, which may contribute to the non-point source pollution of inland water bodies along with rainfall runoff. The status of water quality in rural streams located throughout South Korea was examined in this study by water quality monitoring and statistical analysis. Totally six surveys were conducted in 2003 and 2005 to monitor 300 streams located in rural subwatersheds; these streams are affected by agricultural activities and water supply for agricultural practices. The monitoring was performed at the terminal point of each subwatershed. In each study year, the streams were monitored in the three hydrological periods (April, July, and October) to observe differences in the impacts of agricultural activity and rainfall pattern. During the surveys, 15 water quality parameters were measured and interpreted using multivariate statistical methods including factor analysis and cluster analysis. Results show that the water quality of the rural streams monitored in this study appeared to meet the Korean water quality criteria for agricultural use, which are 8.0 and 100 mg/L for biochemical oxygen demand and suspended solids, respectively. In terms of organic contamination and suspended solids, the best stream water quality was observed in October compared to other periods. This can be attributed to the fact that October follows the rice-harvesting period and has low rainfall; thus the streams are probably less affected by agricultural activities and surface runoff. The three hydrological periods did not show much variation in the nitrogen and phosphorus parameters related to stream water nutrient conditions. Factor analysis indicates that the first five factors for April explained about 67% of the total sample variance. In July, the first four factors explained about 60% of the total variance, while the first four factors for October explained about 65%. Cluster analysis reveals that the streams could be divided into four groups in April and October and five groups in July. The box-and-whisker plots of the physicochemical variables indicate that Group A had the best water quality among the groups. This study demonstrates that the rural stream water quality of South Korea in the Asian monsoon region can be greatly affected by agricultural activities such as paddy rice farming and rainfall patterns.     

A STUDY OF THE INTAKE OF DRINKING WATER BY DAIRY COWS AT GRASS

The average daily intake of drinking water of two groups of 10 spring-calved Ayrshire cows, one gronp on a paddock and the other on a Wye College system of grazing, was measured on 4 days/week for 20 weeks. Trends in water intake were similar on both systems, the average daily intake being 23.0 ±8.5 kg (5.1 ± 1.9 gal)/cow. The average DM content of the herbage was 17.8% and the mean air temperature 134°C (56 1°F). The weight of water drunk was positively related to the daily milk yield and the DM percentage of the herbage, and negatively related to daily rainfall and relative humidity. All of these relationships were significant. Possible changes in the provision of water for dairy cows at grass are discussed.     

Investigating the interactive mechanisms between surface water and groundwater over the Jhuoshuei river basin in central Taiwan

In Taiwan, groundwater commonly becomes important water resources in dry periods, and/or areas lack of water storage facility due to its low cost, steady water supply and good water quality. However, improper groundwater development brings about serious decreases in groundwater levels and land subsidence which causes disasters, such as seawater intrusion or soil salination, accompanied with environmental and economic losses. It is critical to develop strategies for water resources conservation in mountainous areas. The complex heterogeneity of mountainous physiographic environment makes it challenging in the forecasts of groundwater level variations, particularly in mountainous areas. Artificial neural networks (ANNs) have been recognized as an effective modeling tool for complex nonlinear systems in the last two decades. This study aims to investigate the interactive mechanisms of groundwater at the mountainous areas of the Jhuoshuei river basin in central Taiwan through analyzing and modeling the groundwater level variations. Several issues are discussed in this study, which includes the correlation between groundwater level variation and rainfall as well as streamflow, the identification of groundwater recharge patterns and effective rainfall thresholds for estimating groundwater level variations. The results indicate: (1) the daily variation of groundwater level is closely correlated with river flow and one-day antecedent rainfall based on correlation analyses; (2) effective rainfall thresholds can be identified successfully; (3) groundwater level variations can be classified into four types for monitoring wells; and (4) the daily variations of groundwater level can be well estimated by constructed ANNs. The identified interactive mechanisms between surface water and groundwater can facilitate the mountainous water resource conservation strategy for better water management, especially irrigation water supply and for alleviating land subsidence in downstream areas in the future.