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Sensor-based soil water monitoring to more effectively manage agricultural water resources in coastal plain soils.

机译:基于传感器的土壤水监测可以更有效地管理沿海平原土壤中的农业水资源。

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摘要

Cotton (Gossypium hirsutum L.) is widely grown in the United States with 5.7 million ha grown nationally and 1.2 million ha grown in the humid southeastern states in 2005. From 1969 to 2003, agricultural irrigated farmland acreage and total water applied increased by over 40% and 11% respectively to include a total of 55.3 million acres in 2002. Combined with recent and more frequent drought periods and legal water conflicts between states, there has been an increased interest in more effective southeastern water management, thus making the need to develop improved irrigation scheduling methods and enhanced water use efficiency of cotton cultivars.;Several irrigation scheduling methods (soil moisture monitoring, pan evaporation, and climate based) tested at Clemson and elsewhere have shown that sensor-based irrigation significantly increased cotton yields and provided a monetary savings compared to other methods. There is however limited information on capacitance based soil moisture analysis techniques in the southeastern coastal plain soils and also limited locally developed crop coefficients used in scheduling the ET based treatments.;The first objective of this study was to determine and improve the feasibility of utilizing sensor-based soil water monitoring techniques in Southeastern Coastal Plain soils to more effectively manage irrigation and increase water use efficiency of several cotton cultivars. The second objective was to develop two weighing lysimeters equipped with wireless data acquisition system to determine a crop coefficient for cotton under southeastern humid conditions.;Two multi-sensor capacitance probes, AquaSpy(TM) and Sentek EnviroSCAN RTM, were calibrated in this study. It was found that positive linear calibrations can be used to describe the relationship between the soil volumetric moisture content (VMC) and sensor readings found for both probes and that multi-sensor capacitance probes can be used to accurately measure volumetric soil moisture contents, if installed and calibrated properly. It was determined that a direct installation method should be used rather than a slurry mix method. The slurry method was found to overestimate the VMC in sandy soils.;There were good correlations between In Season Estimated Yield (INSEY) as measured by the plant Normalized Difference Vegetation Index (NDVI) and the VMC of the soil. Results showed that when separated by irrigation regime, the relationship between INSEY and VMC follows good linear correlations. This was due to the health of the plant and its dependency on soil moisture.;There were strong correlations between irrigation depths applied and seed cotton yields. Highest water use efficiency values were 0.55 kg seed cotton/m3 water applied in 2008 (0.55 kg seed cotton/m 3 ET) and 0.788 kg/m3 water applied (0.66 kg/m 3 ET) in 2009.;Two weighing lysimeters were constructed to provide cotton and reference ET measurements. Evaporation pan and weather data from a local station were also used to provide a basis for calculating ET. Because the Penman-Monteith (P-M) method is widely known and trusted, a set of crop coefficients were developed based on P-M and cotton lysimeter data and determined to be 0.91, 1.24, and 0.72 for the initial, mid, and end stages for a Delta Pine 0949 BSRF cultivar.
机译:棉花(Gossypium hirsutum L.)在美国广泛种植,2005年全国种植570万公顷,东南部潮湿的州种植120万公顷。从1969年到2003年,农业灌溉农田的面积和总用水量增加了40倍以上%和11%,分别占2002年的5530万英亩。加之最近和更频繁的干旱时期以及各州之间法律上的水冲突,人们对更有效的东南部水资源管理越来越感兴趣,因此需要发展改进的灌溉调度方法并提高了棉花品种的水分利用效率。在克莱姆森和其他地方测试的几种灌溉调度方法(土壤湿度监测,锅蒸发和基于气候的方法)表明,基于传感器的灌溉显着提高了棉花产量,并提供了经济效益与其他方法相比节省了成本。然而,东南沿海平原土壤中基于电容的土壤水分分析技术的信息有限,并且在调度基于ET的处理中使用的局部作物系数也有限。;本研究的首要目标是确定并提高利用传感器的可行性东南沿海平原土壤中基于土壤的水监测技术,可以更有效地管理灌溉并提高几个棉花品种的水分利用效率。第二个目标是开发两个配备无线数据采集系统的称重测力计,以确定东南潮湿条件下棉花的作物系数。;本研究中,对两个多传感器电容式探头AquaSpy(TM)和Sentek EnviroSCAN RTM进行了校准。结果发现,可以使用正线性校准来描述土壤水分含量(VMC)和两个探头的传感器读数之间的关系,并且如果安装了多传感器电容探针,则可以用来精确测量土壤水分含量并正确校准。确定应该使用直接安装方法而不是浆液混合方法。研究发现,泥浆法高估了沙质土壤中的VMC。通过植物归一化植被指数(NDVI)测得的季节估算单产(INSEY)与土壤VMC之间具有良好的相关性。结果表明,当按灌溉制度分开时,INSEY和VMC之间的关系遵循良好的线性相关性。这归因于植物的健康及其对土壤水分的依赖性。灌溉深度与籽棉产量之间存在很强的相关性。最高用水效率值是2008年使用0.55千克籽棉/立方米水(0.55千克籽棉/ m 3 ET)和2009年使用0.788千克/立方米水(0.66 kg / m 3 ET)。提供棉花和参考ET测量值。来自本地站的蒸发皿和天气数据也被用来提供计算ET的基础。由于Penman-Monteith(PM)方法是众所周知且值得信赖的方法,因此根据PM和棉花溶渗仪数据开发了一套作物系数,并确定其初始,中期和结束阶段的系数分别为0.91、1.24和0.72。 Delta Pine 0949 BSRF品种。

著录项

  • 作者

    Bellamy, Christopher A.;

  • 作者单位

    Clemson University.;

  • 授予单位 Clemson University.;
  • 学科 Engineering Agricultural.;Engineering Electronics and Electrical.;Water Resource Management.;Remote Sensing.
  • 学位 M.S.
  • 年度 2009
  • 页码 154 p.
  • 总页数 154
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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