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气象因素与土壤性质耦合效应对土壤电导的影响
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摘要
土壤电导是土壤的基本属性,它与土壤性质(电解质构成、浓度、土壤胶体类型、土壤质地、土壤结构、土壤含水量、土壤温度),以及气象因素(降水、温度、湿度、蒸发、风速、气压、日照)等密切相关。土壤电导特性指标常常用土壤电导率或者土壤电导率的倒数——土壤电阻率来表示,而土壤电阻率是防雷接地工程技术的基础,是判断土壤腐蚀性的一个重要评价标准,也是反映土壤肥力特性的基础指标。所以土壤电导特性在雷电灾害风险评估、雷电防护工程、地下金属设施的防腐工程、精细农业等方面都有重要应用。因此研究气象因素与土壤性质耦合效应对防雷接地工程、地下金属设施防腐工程、精细农业等方面所涉及固定区域固定地点稳定土壤电导的影响,其实质就是研究气象因素与土壤温度、土壤含水量的耦合效应对土壤电阻率的影响。但是,目前土壤电导研究主要集中在土壤自身的物理化学特性对土壤电导影响的研究,研究的手段主要是实验或野外人工测量土壤电导与土壤的物理化学特性来分析土壤电导与土壤的物理化学特性的关系;还未见有关土壤电导特性、土壤含水量、土壤温度和气象因素等连续自动监测的野外观测试验和应用长时间野外观测试验的海量资料分析研究土壤含水量、土壤温度和气象因素对土壤电导影响方面的报道。所以本研究主要是开展土壤电阻率自动测量装置研制,在此基础上对土壤电导性、土壤含水量、土壤温度、气象因素等进行连续监测,最终阐明气象因素与土壤性质的耦合效应对土壤电导的影响。
     本研究选择了重庆市合川区气象局观测场作为气象因素与土壤含水量特性、土壤温度特性耦合效应对土壤电导影响研究的野外试验场地,应用观测场已有的观测仪器设备和自主研制并通过了中国气象局综合观测司组织专家鉴定验收的土壤电阻率自动测量装置,开展了降水、温度、湿度、风、气压、蒸发、水汽压、日照和土壤电阻率、土壤温度、土壤含水量以及降水酸碱度(pH值)、降水电导率(K值)的野外观测试验,并通过一年观测试验资料的分析研究,获得了以下主要研究结果:
     (1)研制了多通道土壤电阻率自动测量装置,开发了土壤电阻率自动测量系统远程控制软件,实现了对土壤电阻率自动测量系统的远程控制操作,建立了土壤电阻率每间隔1小时的连续性接地特征参数的数据库;提供了土壤电阻率、土壤电导率、接地电阻远程自动测试装置及方法;解决了传统的野外土壤电阻率、土壤电导率、接地电阻测量仪器设备需要工程技术人员现场进行测试还未实现无人状态下的远程自动监测的技术难题,实现了土壤电阻率、土壤电导率、接地电阻的多通道、长期、连续、稳定、自动测量;同时土壤电阻率自动测量装置提供了对降阻剂产品在使用过程中是否具有降阻效能、是否有腐蚀性等的连续自动监测手段,为气象主管机构依法按照《接地降阻剂》(QX/T 104-2009)行使防雷安全社会管理职能之降阻剂产品管理奠定了基础。
     (2)研究发现,气象因素主要是通过影响土壤温度、土壤含水量的途径来影响土壤电阻率,是间接影响因素;而土壤温度、土壤含水量是影响土壤电阻率的直接因素,其中不同深度土壤含水量是影响不同深度土壤层电阻率的最主要因素,也是最敏感因素。各气象因素中降水、气温、日照是影响不同深度土壤层电阻率的主要因素,而其他气象因素是影响土壤电阻率的协变因素。降水是影响土壤电阻率的最敏感因素,尤其当前小时的降水量对土壤电阻率变化的影响最显著,随着日、小时时间尺度的降水量的增加,不同深度土壤层日、小时时间尺度的电阻率随着降低,但其土壤电阻率降低的趋势减弱,甚至出现升高的趋势,只有适当降水量,才可能使土壤电阻率降至最低。在雨季(5-9月),对不同深度土壤层电阻率的影响以月降水量为主,在非雨季(1-4月、10-12月),对不同深度土壤层电阻率的影响以月平均气温为主;月降水量对不同深度的土壤层电阻率月平均值的影响具有明显的时间滞后性,滞后时间在土壤浅层为1个月、在土壤深层为2个月;不同深度的土壤层的月平均电阻率变化趋势比土壤温度变化趋势具有明显的时间滞后性,0-15cm、0-30cm、0-80cm土壤层月平均电阻率变化趋势比气温变化趋势滞后1个月,0-160cm、0-320cm土壤层月平均电阻率变化趋势比气温变化趋势滞后4个。
     (3)通过降水过程时间和降水量耦合效应对土壤电阻率恢复到降水前值的恢复时间影响的研究,得到了“降水量小于0.1mm的降水,其恢复时间为0小时;降水过程时间小于1小时或降水量小于2.0 mm的降水,其恢复时间不大于24小时;降水过程时间在2-10小时之间或降水量在2.1~5.0 mm之间的降水,其恢复时间不大于72小时;降水过程时间大于11小时或者降水量大于5.1mm的降水,其恢复时间大于72小时,小于232小时”研究成果,解决了雷电灾害风险评估、雷电防护工程、地下金属设施防腐工程的土壤电阻率测量时,降水后,时隔多少时间进行土壤电阻率、土壤电导率、接地电阻测量才能消除降水影响,从而获得可靠而有效的土壤电阻率、土壤电导率、接地电阻测量值的技术难题,为气象主管机构依法科学、客观评估建筑(构)物防雷接地装置安全性能、各种设施与仪器设备接地装置安全性能提供了科学依据。
     (4)通过日降水pH值及其电导率(K值)观测资料和不同深度土壤层电阻率自动监测资料研究分析降水粒子电荷对土壤电阻率的影响,得到“在同一区域固定地点不同深度土壤层的日平均电阻率与日降水K值的相关呈现显著的正相关性,是由于日降水量与不同深度土壤层的日平均电阻率的显著负相关性和日降水量与降水K值的显著负相关性综合作用的结果,因此日降水中带电离子浓度改善土壤的导电能力远远弱于日降水量改善土壤的导电能力,日降水酸碱度及其电导率对土壤电阻率的影响与日降水量对土壤电阻率的影响相比可以忽略不计”的重要研究成果,从而发现了“目前降阻剂产品研发中仅仅依靠降阻剂产品为土壤提供有限的带电离子改善土壤电阻率来降低接地电阻的技术路线”的问题,提出了降阻剂产品研发的“低电阻效率、吸收水分、保持水分”三大降阻原则,为降阻剂产品研发制定正确的研发技术路线提供了科学依据。
     (5)通过气象因素与土壤温度特性、土壤含水量特性的耦合效应对土壤电阻率的影响分析,发现了气象因素、土壤温度、土壤含水量共同的耦合效应对不同深度土壤层电阻率影响的回归模型的贡献远比气象因素、土壤温度、土壤含水量单独对不同深度土壤层电阻率影响的回归模型的贡献显著,比土壤温度、土壤含水量二者的耦合效应对不同深度土壤层电阻率影响的回归模型的贡献显著,比气象因素、土壤温度二者的耦合效应对不同深度土壤层电阻率影响的回归模型的贡献显著,比降水单独对不同深度土壤层电阻率影响的回归模型的贡献显著。得到了“依据不同资料评估土壤电阻率时,应采用不同的最佳回归模型。因此0-15cm土壤层的日平均电阻率尽可能依据日平均(日值)气象因素和不同深度土壤日平均温度的耦合效应对不同深度土壤层日平均电阻率影响的回归模型估算土壤层的日平均电阻率,0-30cm、0-80cm、0-160cm和0-320cm土壤层的日、时时间尺度电阻率尽可能依据日、时时间尺度气象因素、不同深度土壤日、时时间尺度温度及日、时时间尺度土壤含水量共同的耦合效应影响不同深度土壤层日、时时间尺度电阻率的回归模型估算土壤层的日、时时间尺度电阻率,0-80cm土壤层的日平均电阻率变化可依据日平均含水量变化或者日平均含水量变化及土壤温度变化的耦合效应影响不同深度土壤层日平均电阻率变化的回归模型估算,0-30cm土壤层的日平均电阻率变化尽可能依据日平均(日值)气象因素变化、不同深度处的日平均土壤温度变化及日平均土壤含水量变化共同的耦合效应对不同深度土壤层日平均电阻率变化影响的回归模型估算土壤层的日平均电阻率变化。”研究成果。建立了利用目前气象观测站现有气象因素观测资料、不同深度土壤温度及其含水量观测资料估算不同深度土壤层电阻率的回归数学模型,为开展雷电灾害风险评估、防雷工程设计、大型地下金属设施的防腐工程设计,以及土壤肥力研究等方面估算不同深度土壤层电阻率提供了一种可靠数学计算方法,解决了实际工作中缺少土壤电阻率、土壤电导率历史观测资料的难题。
As a basic attribute of soil, soil conductivity is closely related to soil properties (electrolyte composition, concentration, soil colloid type, soil texture, soil structure, soil moisture content and soil temperature) and meteorological factors (rainfall, temperature, moisture, evaporation, wind speed, air pressure and sunshine), etc. Soil conductivity index is usually expressed as soil conductivity or its reciprocal-soil resistivity, while soil resistivity is the fundamental to lightning grounding, being an important evaluation standard for determining soil corrosivity, and a basic indicator of soil fertility. Therefore, soil conductivity is widely applied in lightning disaster risk assessment, lightning protection, anticorrosive engineering of underground metal facilities and fine agriculture, etc. Therefore, the study on the coupling effect between meteorological factors and soil properties on soil conductivity is to study the coupling effect between meteorological factors, soil temperature and soil moisture content on soil resistivity. However, currently the study on soil conductivity is concentrated on the impact of the physical and chemical properties of soil on soil conductivity, and research measures primarily include experiments or field measuring of soil conductivity and physical and chemical properties of soil to analyze the relations between soil conductivity and its physical and chemical properties, without such reports as continuous and automatic field observation of soil conductivity, soil moisture content, soil temperature and meteorological factors, and the use of mass data of long-term field observation to analyze and study the impact of soil moisture content, soil temperature and meteorological factors on soil conductivity. Therefore, this study primarily develops the automatic measuring device of soil resistivity, based on which the continuous monitoring of soil conductivity, soil moisture content, soil temperature and meteorological factors will be possible, thus eventually interpreting the coupling effect between meteorological factors and soil properties on soil conductivity.
     This study selects the observation field of the Meteorological Bureau of Hechuan District, Chongqing as the field test site for the, study on the coupling effect between meteorological factors, soil moisture content and soil temperature on soil conductivity. By using existing observation instruments and devices on the observation field and a independently developed automatic soil resistivity measuring device, field observation tests of rainfall, temperature, moisture, wind, air pressure, evaporation, vapor pressure, sunshine and soil resistivity, soil temperature, soil moisture content, rainfall pH value and rainfall conductivity (K value) are conducted, and through analysis and study of the observation test data in a year, the following major findings are obtained:
     (1) A multichannel soil resistivity automatic measuring device is developed. Remote control software of automatic soil resistivity measuring system is developed for the remote control of the automatic soil resistivity measuring system. Characteristic parameter database of continuous grounding for soil resistivity with an interval of one hour is established. Remote automatic test devices and methods for soil resistivity, soil conductivity and grounding resistance are provided. Unattended remote automatic monitoring is achieved to replace traditional filed soil resistivity, soil conductivity and grounding resistance measuring instruments and devices that require site tests by engineers (which was very difficult before), achieving multichannel, long-term, continuous, stable and automatic measuring of soil resistivity, soil conductivity and grounding resistance. Meanwhile, the automatic soil resistivity measuring device provides continuous automatic monitoring of the resistance reduction function and corrosiveness of resistance reducers, facilitating meteorological departments to manage resistance reducers as per Grounding Resistance Reducer (QX/T 104-2009).
     (2) The study finds that meteorological factors affect soil resistivity by affecting soil temperature and soil moisture content, and are indirect acting factors, while soil temperature and soil moisture content are factors directly affecting soil resistivity, of which moisture contents of soil of different depths are the major factor affecting the resistivity of soil layers of different depths, and are the most sensitive factor. Regarding meteorological factors, rainfall, temperature and sunshine are the major factors affecting the resistivity of soil layers of different depths, while other meteorological factors are covariant factors affecting soil resistivity. Rainfall is the most sensitive factor affecting soil resistivity. In particular, the rainfall of the current hour has most remarkable impact,on soil resistivity variation. With the increase of rainfall by day/ hour, the resistivity of soil layers of different depths will decrease, but the decrease trend of its soil resistivity will weaken, and even an increase trend will appear. Only a proper rainfall can reduce the soil resistivity to its minimum. In raining seasons (May to September), monthly rainfall is the major factor affecting the resistivity of soil layers of different depths. In non-raining seasons (January to April, October to December), monthly average temperature is the major factor affecting the resistivity of soil layers of different depths. Monthly rainfall affects the monthly average resistivity of soil layers of different depths with a remarkable hysteretic nature, being one month for the shallow layer of soil, and two months for the deep layer of soil. The monthly average resistivity variation trend of soil layers of different depths remarkably lag behind soil temperature variation. The monthly average resistivity variation trend of soil layers of 0-15cm,0-30cm and 0-80cm deep is one month later than temperature variation; the monthly average resistivity variation trend of soil layers of 0-160cm and 0-320cm deep is four months later than temperature variation.
     (3) Through the study on the coupling effect between rainfall process time and rainfall on the recovery time of soil resistivity to its value before the rainfall, the following findings are obtained:"When the rainfall is less than 0.1 mm, its recovery time is 0 hour. When the rainfall process time is less than one hour or the rainfall is less than 2.0 mm, its recovery time will not be greater than 24 hours. When the rainfall process time is 2-10 hours or the rainfall is 2.1-5.0 mm, its recovery time will not be greater than 72 hours. When the rainfall process time is greater than 11 hours or the rainfall is greater than 5.1mm, its recovery time will be greater than 72 hours and less than 232 hours", tackling the problem that for soil resistivity measuring of lightning disaster risk assessment, lightning protection and anticorrosive engineering of underground metal facility, how long after the rainfall that soil resistivity, soil conductivity and grounding resistance measuring can be conducted to eliminate rainfall influence and obtain reliable and valid measured value of soil resistivity, soil conductivity and grounding resistance, scientifically supporting the security assessment of lightning protection and grounding devices for buildings (structures) as well as grounding devices for facilities and instruments.
     (4) Through the study and analysis of the impact of rainfall particle charges on soil resistivity by using the observation data of daily rainfall pH value and its conductivity (K value) and the automatic monitoring data of the resistivity of soil layers of different depths, the following findings are obtained:"At a fixed place of the same area, the remarkable positive correlation between the average daily resistivity of soil layers of different depths and the K value of daily rainfall is a result of the combined action of the remarkable negative correlation between daily rainfall and average daily resistivity of soil layers of different depths, and the remarkable negative correlation between daily rainfall and K value of rainfall. Therefore, the concentration of charged ions in daily rainfall improves far less conductivity that daily rainfall does, and the impact of pH value of daily rainfall and its conductivity on soil resistivity, as compared with the impact of dailyrainfall on soil resistivity, can be neglected", thus finding the problem that "currently in the R&D of resistance reducers, only resistance reducers are used to provide soil with limited charged ions to improve soil,resistivity, thus reducing grounding resistance", and proposing three major resistance reduction principles of "low resistivity, water absorption and water retention" for the R&D of resistance reducers.
     (5) Through the analysis of the coupling effect between meteorological factors, soil temperature and soil moisture content on soil resistivity, it is found that the regression model of such coupling effect on the resistivity of soil layers of different depth contributes far more than the regression model of the individual impact of any of meteorological factors, soil temperature and soil moisture content on the resistivity of soil layers of different depths does, and contributes more remarkably than the coupling effect between soil temperature and soil moisture content, than the coupling effect between meteorological factors and soil temperature, and than the individual impact of rainfall on the resistivity of soil layers of different depths. And, the following findings are obtained:"The different best regression model should be taken when evaluates soil resistivity according to different data.That means for average daily resistivity of soil layer of 0-15cm, average daily resistivity of soil layers shall be estimated by maximally using the regression model of the coupling effect between average daily (daily value) meteorological factors and the average daily temperature of soil of different depths on average daily resistivity of soil layers of different depths. The daily and hourly resistivity of soil layers of 0-30cm,0-80cm,0-160cm and 0-320cm shall be estimated by maximally using the regression model of the coupling effect between daily and hourly meteorological factors, and the coupling effect between daily and hourly temperature of soil of different depths and daily and hourly soil moisture content on the daily and hourly resistivity of soil layers of different depths. The average daily resistivity variation of soil layer of 0-80cm can be estimated by using the regression model of the coupling effect between average daily moisture content variation or average daily moisture content variation and soil temperature variation on the average daily resistivity variation of soil layers of different depths. The average daily resistivity variation of soil layer of 0-30cm shall be estimated by maximally using the regression model of the coupling effect of average daily (daily value) meteorological factors variation, and the coupling effect between average daily soil temperature variation in different depths and average daily soil moisture content variation on the average daily resistivity variation of soil layers of different depths." The regression model to estimate the resistivity of soil layers of different depths by using the observation data of meteorological factors from weather stations, soil temperature in different depths and the observation data of moisture contents is established, providing a reliable computational method for the estimation of the resistivity of soil layers of different depths for lightning disaster risk assessment, lightning protection, anticorrosive engineering of large underground metal facilities and the study on soil fertility, thus providing historical observation data of soil resistivity and soil conductivity.
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