基于SWAT模型的大安市降水入渗量变化的模拟研究

针对近年的研究热点,通过SWAT模型对半干旱、盐碱化严重的吉林省大安市进行降水入渗模拟。以2000、2004和2008年遥感影像解译得到的土地利用数据为基础,结合SWAT模型的模拟结果,讨论LUCC与降水入渗量的相关关系。2008年与2000年相比,难利用地的面积有所降低,旱地、草地等发生了大面积的增加,研究区内土地状况有所好转。通过SWAT模型运行得到的结果显示:2008年的平均降水入渗量为56.27 mm,比2000年的值高。利用降水入渗系数法进行计算,也得到了2008年的降水入渗量高于2000年的结果,这与SWAT模型模拟得到的结果有着相同的趋势,且平均降水入渗量的标准偏差为5.27,说明SWAT模型对于研究区有良好的适应性。同时,根据土地利用数据和SWAT模型模拟数据可以得知,LUCC对研究区的降水入渗量存在着一定的相关性。     

砂田抑制蒸发功能随覆砂年限的演变规律

【目的】研究压砂覆盖(砂田)保温及抑制蒸发功能随砂田退化程度的演变规律。【方法】基于多年Landsat卫星数据,使用辐射传输方程法反演香山地区砂田地表温度(LST),结合田间地表温度监测,对比砂田与裸地的地表温度变化,分析了砂田抑制土壤蒸发的机理,并探讨了砂田的功效与砂田使用年限的关系。【结果】砂田在LST-NDVI梯形空间中贴近于暖边,其土壤水分比耕地少,接近于干土层。因此,砂田可以隔离辐射与土壤表层,从而减小潜热通量,抑制土壤蒸发。砂田昼夜温差明显比裸地大,且对于西瓜等作物,砂田的有效地表积温也比裸地提高了10%。【结论】砂田退化过程可分为纯砾石阶段、砂土混合阶段和砂土连通阶段,从砂田的保温及抑制蒸发功能来看,砂田的有效使用年限为25～30 a。     

温度和湿度对土壤中噁唑酰草胺降解的影响

噁唑酰草胺是一种芳氧苯氧丙酸酯类除草剂,近年来在我国使用面积快速上升。本文建立了土壤中噁唑酰草胺的快速灵敏检测方法,测定了土壤温度和湿度对土壤中噁唑酰草胺降解的影响。研究结果表明建立的土壤中噁唑酰草胺的高效液相色谱检测方法,最低定量限(LOQ)为4.00×10~(-3)μg/kg,最低检测限LOD为1.20×10~(-3)μg/kg。土壤温度为5、15、25和35℃时,土壤中10 mg/kg的噁唑酰草胺半衰期分别为16.8、9.9、3.5和0.9 d;土壤湿度为40%和80%时,土壤中噁唑酰草胺的半衰期分别为3.6和4.3 d。与土壤湿度相比,土壤温度对土壤中噁唑酰草胺降解的影响更大。     

低温环境下饲粮核黄素添加水平对蛋鸭激素分泌的影响

本试验旨在研究低温环境下饲粮核黄素添加水平对蛋鸭激素分泌的影响.试验采用两因素有重复完全交叉设计,温度设2个水平[适温(18±1)℃,T1;低温(2±1)℃,T2];核黄素设3个水平,在基础饲粮中分别添加4、16、32 mg/kg 核黄素.选用12周龄健康的金定鸭(母)144只,随机分成6个处理,每个处理6个重复,每个...     

不同补水方式下砂壤土渗滤系统对硝态氮去除效果

在水资源短缺的北京地区利用再生水回补城市河湖,一方面对于水资源的可持续利用有着十分重要的作用,另一方面也可能带来地下水环境的潜在污染风险.该文采用100 cm砂壤土柱模拟(河湖岸底)土地渗滤系统,设置定水头淹水、交替淹水落干、定流速补水和侧向补水4种不同再生水回补方式,研究再生水中硝态氮(NO3-N)在土地渗滤系统中的去除效果和迁移转化规律.结果表明,当水力负荷在0.25~2.65 cm/d范围内时,渗滤系统对NO3-N的去除率随着水力负荷的增大而减小;侧向补水方式下渗滤系统对NO3-N的去除效果最优,平均去除率高达96.1%.在定水头淹水和侧向补水方式下,系统对NO3-N的去除主要发生在土柱的上部,而交替淹水落干和定流速补水条件下,土柱中下部对NO3-N也有一定的去除作用.渗滤系统对NO3-N的去除主要取决于系统内部微生物的分布情况,土层中的反硝化细菌数量越大,该土层对NO3-N的去除率就越高.当水温在15~32℃范围内变化时,定水头淹水和交替淹水落干补水方式下,系统对NO3-N的去除率与温度分别呈指数和幂函数关系.该研究表明土地渗滤系统可实现再生水的进一步净化处理,可为再生水安全回补河湖提供参考.     

A comparison of cardinal temperatures estimated by linear and nonlinear models for germination and bulb growth of forage brassicas

Forage brassicas are widely used as a supplementary feed in temperate pasture systems but there is a lack of quantitative data about their growth and development. Furthermore, numerous models are available to estimate cardinal temperatures but there is uncertainty about whether linear or nonlinear models should be used. Initially a germination experiment was used to describe the rate response of nine forage brassicas to temperature. Three models were compared to estimate cardinal temperatures and the two best models were used for thermal time (Tt) accumulation for three groups of forage brassicas. Cardinal temperatures, defined as the base (T_b), optimum (T_opt) and maximum (T_m), differed among groups of species for the bilinear and Lactin models but were similar within a group of species for these models. In most cases, cardinal temperatures estimated by the bilinear and Lactin models for the B. rapa group ranged from 3 to 4 °C for T_b, 31 °C for T_opt and 41 to 48 °C for T_m. For the B. napus and B. napus biennis groups these temperatures ranged from 0 to 3 °C for T_b, 29 to 33 °C for T_opt and 38 °C for T_m. The B. oleracea group had temperatures from 0 to 1 °C for T_b, 25 to 27 °C for T_opt and 35 °C for T_m. A second data set based on hypocotyl thickening was used to estimate the base temperature (T_b) for bulb growth of turnips and swedes. Both models estimated an average T_b of 4.2 °C for bulb turnips and an average of 3.7 °C for swedes. The Lactin model was considered the most adequate model to describe temperature responses where as, in some cases, the bilinear model had to be modified to account for changes in the rate of development. More importantly, an appropriate range of test temperatures was crucial for the estimation of reliable cardinal temperatures, independent of the model used.     

基于叶气温差的生育中期冬小麦水分亏缺诊断研究

为了获取叶片尺度基于叶气温差的冬小麦生育中期水分亏缺诊断阈值,分析了冬小麦叶气温差的典型日变化及其与土壤水分、空气温度及太阳辐射等因子的相互关系,揭示了冬小麦叶气温差对光合气体交换参数的影响,确定了冬小麦叶片水分利用效率较适宜的非气孔限制值及叶气温差范围。结果表明,冬小麦叶气温差在不同的土壤水分条件下表现出不同的日变化规律,随光量子通量增加而升高,随土壤水分、气温增加而降低;4、5和6月冬小麦叶片水分利用效率较适宜的非气孔限制值范围分别为0.7~1.3、1.1~2.0和0.9~1.5,叶气温差控制范围分别为-1.2~0.4、-1.5~-1和-1.25~-0.9℃。     

Can additional N fertiliser ameliorate the elevated CO2‐induced depression in grain and tissue N concentrations of wheat on a high soil N background?

Elevated CO₂ stimulates crop yields but leads to lower tissue and grain nitrogen concentrations [N], raising concerns about grain quality in cereals. To test whether N fertiliser application above optimum growth requirements can alleviate the decline in tissue [N], wheat was grown in a Free Air CO₂ Enrichment facility in a low‐rainfall cropping system on high soil N. Crops were grown with and without addition of 50–60 kg N/ha in 12 growing environments created by supplemental irrigation and two sowing dates over 3 years. Elevated CO₂ increased yield and biomass (on average by 25%) and decreased biomass [N] (3%–9%) and grain [N] (5%). Nitrogen uptake was greater (20%) in crops grown under elevated CO₂. Additional N supply had no effect on yield and biomass, confirming high soil N. Small increases in [N] with N addition were insufficient to offset declines in grain [N] under elevated CO₂. Instead, N application increased the [N] in straw and decreased N harvest index. The results suggest that conventional addition of N does not mitigate grain [N] depression under elevated CO₂, and lend support to hypotheses that link decreases in crop [N] with biochemical limitations rather than N supply.     

A calibration method of detecting soil water content based on the information-sharing in wireless sensor network

In agricultural production, there is contradiction between the cost and accuracy of detection during the course of acquiring soil water content (θ) online. This conflict is one of the core issues of automatic water-saving irrigation technology in agriculture. At the same time, capacitive soil moisture sensor (CSMS) has received considerable attention, for it can acquire θ with low cost and high precision, and meet the application requirements of wireless sensor network (WSN). But CSMS is vulnerable to the soil temperature (T_s) and salinity (S_s) in the measurement process. Therefore, this study took EC-5 sensor for example to establish water detection calibration models of soil temperature and salinity for single sensor, using Least Squares Support Vector Machines on MatLAB (LS-SVMlab) as the tool. On this basis, we explored the spatial variability of T_s and S_s, and then a method, which could be used to calibrate the output signals of sensors in multi-point network, was proposed based on the information-sharing (T_s or S_s) technology of WSN. Through laboratory experiment, we effectively reduced the impact of soil temperature and salinity on the single sensor. In example analysis, we investigated the detection precision and costs under different information-sharing radiuses (r). And the results indicated that the method we proposed based on the information-sharing technology of WSN could successfully calibrate the influence of soil temperature and salinity on sensors in multi-point network, and it was an efficacious approach to determine the balance between the calibration accuracy of moisture sensor and the investment of agricultural production. For example, while the calibration precision of soil temperature and salinity is respectively 1%, the costs can be reduced by 30%.     

Soil enzyme activities during the 2011 Texas record drought/heat wave and implications to biogeochemical cycling and organic matter dynamics

Extreme droughts and heat waves due to climate change may have permanent consequences on soil quality and functioning in agroecosystems. During November 2010 to August 2011, the Southern High Plains (SHP) region of Texas, U.S., a large cotton producing area, received only 39.6 mm of precipitation (vs. the historical avg. of 373 mm) and experienced the hottest summer since record keeping began in 1911. Several enzyme activities (EAs) important in biogeochemical cycling were evaluated in two soils (a loam and a sandy loam at 0–10 cm) with a management history of monoculture (continuous cotton) or rotation (cotton and sorghum or millet). Samplings occurred under the most extreme drought and heat conditions (July 2011), after precipitation resulted in a reduction in a drought severity index (March 2012), and 12 months after the initial sampling (July 2012; loam only). Eight out of ten EAs, were significantly higher in July 2011 compared to March 2012 for some combinations of soil type and management history. Among these eight EAs, enzymes key to C (β-glucosidase, β-glucosaminidase) and P cycling (phosphodiesterase, acid and alkaline phosphatases) were significantly higher (19–79%) in July 2011 than in March 2012 for both management histories regardless of the soil type (P > 0.05). When comparing all sampling times, the activities of alkaline phosphatase, aspartase and urease (rotation only) showed this trend: July 2011 > March 2012 > July 2012. Activities of phosphodiesterase, acid phosphatase, α-galactosidase, β-glucosidase and β-glucosaminidase were higher in July 2011 than July 2012 in at least one of the two management histories. Total C was reduced significantly from July 2011 to March 2012 in the rotation for both soils. Only the activities of arylsulfatase (avg. 36%) and asparaginase showed an increase from July 2011 to March 2012 for both soil types, which may indicate they have a different origin/location than the other enzymes. EAs continued to be a fingerprint of the soil management history (i.e., higher EAs in the rotation than in monoculture) during the drought/heat wave. This study provided some of the first evidence of the adverse effects of a natural, extreme drought and heat wave on soil quality in agroecosystems as indicated by EAs involved in biogeochemical cycling.