The development of the root system of corn in soil profile is an indispensable parameter for the estimation of corn growth.The distribution of the root system can be used to evaluate the influence of climate on vegetative growth. This constitutes a creative scientific management and development system of water-saving agriculture. In the Gucheng Agro-meteorological Field Experimental Station of Chinese Academy of Meteorological Sciences, root length, root areal reach, root depth and root dry-weight of "Tunyu 46" corn were observed using clod sampling method and installed underground surface glazing. Observation data on the spatial and temporal distribution characters of the root system in the soil profile were then analyzed. The results show that root dry-weight and root length decrease with increasing soil depth. In spin silk period, root length in the 40 cm, 80 cm, and 120 cm soil layer is respectively 51.5%, 76.2% and 90.5% of total root length. Root length to total root length ratio in various soil layers is similar for both spin silk and late milk maturity periods. Root thickness decreases in upper soil layer and increases in lower soil layer with increasing soil depth. In the late milk maturity period, root depth may reach 230 cm, and total combined root length can reach 8.288 km•m −2 .Clearly thus, root depth and the total root length of "Tunyu 46" are larger than those of other corn varieties. Root distribution characteristics show that the root system of "Tunyu 46" is a lot more developed and robust for defending drought. Based on data obtained from the installed glazing, root depth is much deeper than that observed far from the glazing.
Atmospheric precipitable water vapor of Poyang Lake area can be estimated using the ground-based global positioning system technology and the atmospheric precipitable water vapor change characteristics during the rainfall process can be analyzed. At the same time we can use National Centers for Environmental Prediction reanalysis data and high-density grid data analysis of weather system, water vapor transmission, convergence and precipitation power mechanism. The atmospheric precipitable water vapor and rainfall contrast analysis show that rainfall and precipitable water vapor are not directly in corresponding relation, and their values are not always mutually corresponded. The value of rainfall is closely related with the water vapor transfer and water vapor convergence. In front of the rainfall the increasing process of GPS/PWV changes continuously, and increases suddenly in about 1 h before the rainfall. The rainfall is not always smaller than the biggest value of GPS/PWV, and has the possibility to be bigger than the GPS/PWV values. GPS delivered PWV could be used to improve the near real time forecast/short term forecast of precipitation.
The root minirhizotron technique (MT) has been used to monitor nondestructively the root growth of field crops. The objective of this study was to compare the ability of MT to measure the root length density (RLD) of maize (Zea mays L.) as compared to the quadrate monolith method (QMM). The experiment was conducted at the Gucheng Ecological-Meteorological Experiment Station in China during the summer of 2007. RLD was estimated using MT and QMM. Results showed that the vertical distribution of RLD decreased top-down gradually, starting at the top of the root zone. The growth rate of RLD decreased as soil depth increased based on both methods. RLD was underestimated by MT at depths between 0 and 40 cm at the milk and maturity stages and overestimated by MT at depths between 0 and 20 cm at the jointing and tasseling stages. There was a significant correlation (r 2 = 0.715, α = 0.05) between RLD estimates based on QMM and MT. The results of this study indicate that properly calibrated MT is a reliable method to screen nondestructively the root growth of maize.
Fast quality control (FQC) is important to deal with high-frequency observation records at meteorological station networks in time, and may check whether the records fall within a range of acceptable values. Threshold tests in the previous quality control methods for monthly, daily, or hourly observation data do not work well for 0.5 Hz data at a single station. In this study, we develop an algorithm for the automatic determination of maximum and minimum minute thresholds for 0.5 Hz temperature data in the data collection phase of the newly built stations. The fast threshold test based on the percentile threshold (0.1–99.9%) and standard deviation scheme is able to efficiently identify the incorrect data in the current minute. A visual graph is generated every minute, and the time series of the data records and the thresholds are displayed by the automated graphical procedures. The observations falling outside the thresholds are flagged and then a manual check is performed. This algorithm has the higher efficiency and lower computational requirement in identifying out the obvious outliers of 0.5 Hz data in real or near-real time observation. Meanwhile, this algorithm can also find problems in observation instruments. This method is applied to the quality control of 0.5 Hz data at two Tianjin experiment stations and hourly data at one Shenyang experiment station. The results show that this fast threshold test may be a viable option in the data collection phase. The advantage of this method is that the computation requires less memory and the computational burden is reduced for real or near-real time observations, so it may be extended to test other meteorological variables measured by high-frequency measurement systems.
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