Risk assessment of maize drought disaster in southwest China using the Environmental Policy Integrated Climate model

The East Asian monsoon has a tremendous impact on agricultural production in China. An assessment of the risk of drought disaster in maize-producing regions is therefore important in ensuring a reduction in such disasters and an increase in food security. A risk assessment model, EPIC(Environmental Policy Integrated Climate) model, for maize drought disasters based on the Erosion Productivity Impact Calculator crop model is proposed for areas with the topographic characteristics of the mountainous karst region in southwest China. This region has one of the highest levels of environmental degradation in China. The results showed that the hazard risk level for the maize zone of southwest China is generally high. Most hazard index values were between 0.4 and 0.5,accounting for 47.32% of total study area. However,the risk level for drought loss was low. Most of the loss rate was 0.1, accounting for 96.24% of the total study area. The three high-risk areas were mainlydistributed in the parallel ridge–valley areas in the east of Sichuan Province, the West Mountain area of Guizhou Province, and the south of Yunnan Province.These results provide a scientific basis and support for the reduction of agricultural drought disasters and an increase in food security in the southwest China maize zone.     

An Analytical Model For Threshold Crossing Rates Of Concentration Fluctuations In Dispersing Plumes

A simple analytical model is developed for the meanupcrossing rate of plume concentration fluctuations assuming that thisprocess can be well approximated by a lognormal process. The resultingexpression requires only the specification of the in-plume fluctuationintensity and in-plume Taylor micro-time scale and, hence, does notexplicitly involve the joint probability density function of theconcentration and its derivative. The analytical model provides agood fit to some field measurements of the mean upcrossing rate ina dispersing plume.     

THE HOLOCENE SEDIMENTAL CHARACTERISTIC AND PALEOCLIMATIC EVOLUTION OF EBINUR LAKE，XINJIANG

ＴＨＥＨＯＬＯＣＥＮＥＳＥＤＩＭＥＮＴＡＬＣＨＡＲＡＣＴＥＲＩＳＴＩＣＡＮＤＰＡＬＥＯＣＬＩＭＡＴＩＣＥＶＯＬＵＴＩＯＮＯＦＥＢＩＮＵＲＬＡＫＥ，ＸＩＮＪＩＡＮＧ吴敬禄，王苏民，吴艳宏ＴＨＥＨＯＬＯＣＥＮＥＳＥＤＩＭＥＮＴＡＬＣＨＡＲＡＣＴＥＲＩＳＴ...     

Intercalibration of Solar Soft X-Ray Broad Band Measurements from SOLRAD 9 through GOES-12

The two-band soft X-ray observations of solar flares made by the Naval Research Laboratory’s (NRL) SOLar RADiation (SOLRAD) satellites and by the Geostationary Orbiting Environmental Satellites (GOES) operated by the National Oceanic and Atmospheric Administration’s (NOAA) Space Weather Prediction Center have produced a nearly continuous record of solar flare observations over a period of more than forty years (1969 – 2011). However, early GOES observations (i.e., GOES-2) and later (GOES-8 and subsequent missions) are not directly comparable due to changes in the conversion of measured currents to integrated fluxes in the two spectral bands that were adopted: 0.05 – 0.3 (or 0.4) nm, which we refer to as XS and 0.1 – 0.8 nm (XL). Furthermore, additional flux adjustments, using overlapping data sets, were imposed to provide consistency of flare-flux levels from mission to mission. This article evaluates the results of these changes and compares experimental GOES-8/GOES-2 results with changes predicted from modeled flare spectra. The factors by which recent GOES observations can be matched to GOES-2 are then optimized by adapting a technique first used to extrapolate GOES X-ray fluxes above saturation using ionospheric VLF radio phase enhancements. A nearly 20% increase in published GOES-8 XL data would be required to match to GOES-2 XL fluxes, which were based on observed flare spectra. On the other hand, a factor of 1.07 would match GOES-8 and later flat-spectrum 0.1 – 0.8 nm fluxes to GOES-2 XL if the latter data were converted to a flat-spectrum basis. Finally, GOES-8 observations are compared to solar soft X-ray estimates made concurrently with other techniques. Published GOES-8 0.1 – 0.8 nm fluxes are found to be 0.59 of the mean of these other determinations. Rescaling GOES to a realistic flare spectrum and removing a 30% downward adjustment applied to the GOES-8 measurements during initial data processing would place GOES-8 and later GOES XL fluxes at 0.94 of this XL mean. GOES-2 on the same scale would lie at about 0.70 of this mean. Significant uncertainties in the absolute levels of broad band soft X-ray fluxes still remain, however.     

Impact factors identification of spatial heterogeneity of herbaceous plant diversity on five southern islands of Miaodao Archipelago in North China

Herbaceous plants are widely distributed on islands and where they exhibit spatial heterogeneity. Accurately identifying the impact factors that drive spatial heterogeneity can reveal typical island biodiversity patterns. Five southern islands in the Miaodao Archipelago, North China were studied herein. The spatial distribution of herbaceous plant diversity on these islands was analyzed, and the impact factors and their degree of impact on spatial heterogeneity were identified using CCA ordination and ANOVA. The results reveal 114 herbaceous plant species, belonging to 94 genera from 34 families in the 50 plots sampled. The total species numbers on different islands were significantly positively correlated with island area, and the average α diversity was correlated with human activities, while the β diversity among islands was more affected by island area than mutual distances. Spatial heterogeneity within islands indicated that the diversities were generally high in areas with higher altitude, slope, total nitrogen, total carbon, and canopy density, and lower moisture content, pH, total phosphorus, total potassium, and aspect. Among the environmental factors, pH, canopy density, total K, total P, moisture content, altitude, and slope had significant gross effects, but only canopy density exhibited a significant net effect. Terrain affected diversity by restricting plantation, plantation in turn influenced soil properties and the two together affected diversity. Therefore, plantation was ultimately the fundamental driving factor for spatial heterogeneity in herbaceous plant diversity on the five islands.     

乌鲁木齐河灌区水资源利用及可持续管理

通过对乌鲁木齐河灌区历年供水和用水状况分析,提出了该灌区水资源可持续利用的对策,并针对城市用水逐年增加与水资源供需矛盾日益突出的形势,从水份分析入手,从水资源可持续管理的角度,提出了水资源高效利用与管理的对策 。     

祁连山南坡灌丛草甸生物量变化与水热因子的关系研究

通过野外调研和室内实验,研究了祁连山南坡灌丛草甸地上生物量的生长季变化,并对地上生物量与水热因子的关系进行了探讨。结果表明：在不同区域群落结构有所不同,覆盖度越低,上层和下层的植物高度越低,丰富度和多样性越小。但均匀度还受草场退化阶段的影响,群落结构相对稳定,植物的均匀度越高;地上生物量的年内变化是单峰曲线,乌鞘岭和门源的地上生物量在7月份最大,祁连和野牛沟的地上生物量在9月份最大;地上生物量的积累与前1月和前2月的气温和降水正相关,与前4月的气温也正相关,并且对气温变化的敏感性大于降水,但与地温和土壤水分的相关性不明显,前1月表层地温较高对地上生物量的积累有积极作用;对于地上生物量积累,日气温、日相对湿度、降水量有直接正向作用,而日最高气温、日最低气温、日水汽压有直接负向作用,5 cm、20 cm地温和0~10 cm、20~30 cm土壤水分也有直接正向作用,而10 cm地温和10~20 cm土壤水分也有直接负向作用。     

Study on uncertainty of inversion and resolution limit in the presence of noise

This study analyzed the uncertainty of inversion and the resolution limit in the presence of noise by means of statistical experiments. The exhaustive method is adopted to obtain the global optimal solution in each experiment. We found that even with small level of noise, solutions fluctuate in a large range for the thin bed. The distribution of solutions in the presence of noise is closely related to the spread of the cost function in the absence of noise. As a result, the area of a certain neighborhood around the true solution on the spread of the cost function in the absence of noise is used to evaluate the uncertainty of inversion and the resolution limit in the presence of noise. In the case that the SNR (signal-to-noise ratio) is 5 in this study, solutions focus around the true solution with a very small uncertainty only when the bed thickness is greater than the reciprocal of the double predominant frequency of the convoluting wavelet.     

An inter-comparison of tidal solutions computed with a range of unstructured grid models of the Irish and Celtic Sea Regions

Three finite element codes, namely TELEMAC, ADCIRC and QUODDY, are used to compute the spatial distributions of the M₂, M₄ and M₆ components of the tide in the sea region off the west coast of Britain. This region is chosen because there is an accurate topographic dataset in the area and detailed open boundary M₂ tidal forcing for driving the model. In addition, accurate solutions (based upon comparisons with extensive observations) using uniform grid finite difference models forced with these open boundary data exist for comparison purposes. By using boundary forcing, bottom topography and bottom drag coefficients identical to those used in an earlier finite difference model, there is no danger of comparing finite element solutions for “untuned unoptimised solutions” with those from a “tuned optimised solution”. In addition, by placing the open boundary in all finite element calculations at the same location as that used in a previous finite difference model and using the same M₂ tidal boundary forcing and water depths, a like with like comparison of solutions derived with the various finite element models was possible. In addition, this open boundary was well removed from the shallow water region, namely the eastern Irish Sea where the higher harmonics were generated. Since these are not included in the open boundary, forcing their generation was determined by physical processes within the models. Consequently, an inter-comparison of these higher harmonics generated by the various finite element codes gives some indication of the degree of variability in the solution particularly in coastal regions from one finite element model to another. Initial calculations using high-resolution near-shore topography in the eastern Irish Sea and including “wetting and drying” showed that M₂ tidal amplitudes and phases in the region computed with TELEMAC were in good agreement with observations. The ADCIRC code gave amplitudes about 30 cm lower and phases about 8° higher. For the M₄ tide, in the eastern Irish Sea amplitudes computed with TELEMAC were about 4 cm higher than ADCIRC on average, with phase differences of order 5°. For the M₆ component, amplitudes and phases showed significant small-scale variability in the eastern Irish Sea, and no clear bias between the models could be found. Although setting a minimum water depth of 5 m in the near-shore region, hence removing wetting and drying, reduced the small-scale variability in the models, the differences in M₂ and M₄ tide between models remained. For M₆, a significant reduction in variability occurred in the eastern Irish Sea when a minimum 5-m water depth was specified. In this case, TELEMAC gave amplitudes that were 1 cm higher and phases 30° lower than ADCIRC on average. For QUODDY in the eastern Irish Sea, average M₂ tidal amplitudes were about 10 cm higher and phase 8° higher than those computed with TELEMAC. For M₄, amplitudes were approximately 2 cm higher with phases of order 15° higher in the northern part of the region and 15° lower in the southern part. For M₆ in the north of the region, amplitudes were 2 cm higher and about 2 cm lower in the south. Very rapid M₆ tidal-phase changes occurred in the near-shore regions. The lessons learned from this model inter-comparison study are summarised in the final section of the paper. In addition, the problems of performing a detailed model–model inter-comparison are discussed, as are the enormous difficulties of conducting a true model skill assessment that would require detailed measurements of tidal boundary forcing, near-shore topography and precise knowledge of bed types and bed forms. Such data are at present not available.