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1.
Forests in the Southeastern United States are predicted to experience future changes in seasonal patterns of precipitation inputs as well as more variable precipitation events. These climate change‐induced alterations could increase drought and lower soil water availability. Drought could alter rooting patterns and increase the importance of deep roots that access subsurface water resources. To address plant response to drought in both deep rooting and soil water utilization as well as soil drainage, we utilize a throughfall reduction experiment in a loblolly pine plantation of the Southeastern United States to calibrate and validate a hydrological model. The model was accurately calibrated against field measured soil moisture data under ambient rainfall and validated using 30% throughfall reduction data. Using this model, we then tested these scenarios: (a) evenly reduced precipitation; (b) less precipitation in summer, more in winter; (c) same total amount of precipitation with less frequent but heavier storms; and (d) shallower rooting depth under the above 3 scenarios. When less precipitation was received, drainage decreased proportionally much faster than evapotranspiration implying plants will acquire water first to the detriment of drainage. When precipitation was reduced by more than 30%, plants relied on stored soil water to satisfy evapotranspiration suggesting 30% may be a threshold that if sustained over the long term would deplete plant available soil water. Under the third scenario, evapotranspiration and drainage decreased, whereas surface run‐off increased. Changes in root biomass measured before and 4 years after the throughfall reduction experiment were not detected among treatments. Model simulations, however, indicated gains in evapotranspiration with deeper roots under evenly reduced precipitation and seasonal precipitation redistribution scenarios but not when precipitation frequency was adjusted. Deep soil and deep rooting can provide an important buffer capacity when precipitation alone cannot satisfy the evapotranspirational demand of forests. How this buffering capacity will persist in the face of changing precipitation inputs, however, will depend less on seasonal redistribution than on the magnitude of reductions and changes in rainfall frequency.  相似文献   
2.
The Three Gorges Project is the world's largest water conservancy project. According to the design standards for the 1,000‐year flood, flood diversion areas in the Jingjiang reach of the Yangtze River must be utilized to ensure the safety of the Jingjiang area and the city of Wuhan. However, once these areas are used, the economic and life loss in these areas may be very great. Therefore, it is vital to reduce this loss by developing a scheme that reduces the use of the flood diversion areas through flood regulation by the Three Gorges Reservoir (TGR), under the premise of ensuring the safety of the Three Gorges Dam. For a 1,000‐year flood on the basis of a highly destructive flood in 1954, this paper evaluates scheduling schemes in which flood diversion areas are or are not used. The schemes are simulated based on 2.5‐m resolution reservoir topography and an optimized model of dynamic capacity flood regulation. The simulation results show the following. (a) In accord with the normal flood‐control regulation discharge, the maximum water level above the dam should be not more than 175 m, which ensures the safety of the dam and reservoir area. However, it is necessary to utilize the flood diversion areas within the Jingjiang area, and flood discharge can reach 2.81 billion m3. (b) In the case of relying on the TGR to impound floodwaters independently rather than using the flood diversion areas, the maximum water level above the dam reaches 177.35 m, which is less than the flood check level of 180.4 m to ensure the safety of the Three Gorges Dam. The average increase of the TGR water level in the Chongqing area is not more than 0.11 m, which indicates no significant effect on the upstream reservoir area. Comparing the various scheduling schemes, when the flood diversion areas are not used, it is believed that the TGR can execute safe flood control for a 1,000‐year flood, thereby greatly reducing flood damage.  相似文献   
3.
The precipitation patterns in flood season over China associated with the El Niño/Southern Oscillation (ENSO) are investigated, especially in the eastern China, using the rather long period rainfall data in this century. The results show that there were remarkable differences between the precipitation patterns in flood seasons of ENSO warm phase (El Niño year) and cold phase (La Niña year), as well as between the patterns in El Niño years and their following years. The most parts of China received below normal rainfall in flood season of the onset years of El Niño events, but the coastal area of Southeast China received above normal amounts. Comparatively, the most parts of China received above normal rainfall in flood season of the following years of El Niño events, but the eastern part of the reaches among the Huanghe (Yellow) River, the Huaihe River and the Haihe River, and the Northeast China received less. During ENSO cold phase, the reaches of the Changjiang (Yangtze) River and the North China received more amounts than normal rainfall in flood season of the onset years of La Niña events, and the other regions of China received less. In the following years of La Niña events, the coastal area of the Southeast China, the most part of the Northeast China and the regions between the Huanghe River and the Huaihe River received more precipitation during flood seasons, but the other parts received below normal precipitation.  相似文献   
4.
三峡重庆库区深部地球物理特征与断裂构造   总被引:1,自引:0,他引:1  
为了深入研究三峡重庆库区岩石圈动力学特征及其对断裂构造活动的控制和影响.并为之提供基础资料,为三峡重庆库区地震、地质灾害的监测与防治提供基础依据,在已有地球物理资料的基础上,从综合地球物理研究角度出发,通过实测地震测线资料的再解释.采用新的处理技术方法,对本区的东西向主剖面和南北向支测线的地震测深资料进行二维射线追踪处理、Pg波成像;选用场分离技术、位移数字成像技术重新处理了重力和航磁资料,通过联合反演来建立深部二维构造剖面,对剖面所揭示的基底构造特征和地壳结构特征、主要断裂构造特征以及莫霍面的起伏特征进行了精细分析和细致研究.从地球物理平面场特征出发建立了岩石圈构造三维框架。研究结果表明,这样的研究思路准确、方法得当.结论可靠;沿该剖面,把可解译的断裂分为Ⅲ级:Ⅰ级为超岩石圈断裂;Ⅱ级为壳断裂;Ⅲ级为盖层断裂。依据地球物理特征,准确揭示了库区的断裂构造特征,达到了预期效果。  相似文献   
5.
本文使用天气学方法,从影响雅砻江区域主汛期降水量的长期预报有关因子出发,再运用数理统计方法反复筛选,仅取3个主要因子:西部青藏高原8个站冬春积温,北部冬季极涡面积指数,南部冬季印缅槽平均强度,建立逐步回归预报方程。结果显示:对主汛期6~9月降水量预报拟合准确率为16/17即约94%。回归分析中发现:尽管西太平洋副热带高压对盆地西部降水有很大影响,盛夏且与高原积温有较密切相关,但由放大范围长时段的青藏高原积温,对于雅砻江区域主汛期降水量的影响超过西太平洋副热高压,因而在逐步回归过程中,副高因子仍被剔除.  相似文献   
6.
企鹅珍珠贝人工苗生长的初步观察   总被引:3,自引:0,他引:3  
为了解企鹅珍珠贝生长规律,观察了壳高2.5~5.0mm的出池幼苗,按月测量其生长参数和成活率,以及环境因子。结果表明,企鹅珍珠贝生长最快的月份为7~11月和次年4~6月,壳长,壳高和壳宽月均增加量分别为3.8~13.0mm、4.7~11.2mm、2.3~3.8mm,月成活率97.8%~98.6%。企鹅珍珠贝生长最慢月份是11月至次年3月。  相似文献   
7.
The main reasons for the high content of inorganic N and its increase by several times in the Changjiang River and its mouth during the last 40 years were analysed in this work. The inorganic N in precipitation in the Changjiang River catchment mainly comes from gaseous loss of fertilizer N, N resulting from the increases of population and livestock, and from high temperature combustions of fossil fuels. N from precipitation is the first N source in the Changjiang River water and the only direct cause of high content of inorganic N in the Changjiang River and its mouth. The lost N in gaseous form and from agriculture non-point sources fertilizer comprised about 60% of annual consumption of fertilizer N in the Changjiang River catchment and were key factors controlling the high content of inorganic N in the Changjiang River mouth. The fate of the N in precipitation and other N sources in the Changjiang River catchment are also discussed in this paper.  相似文献   
8.
Concentrations of trace elements and heavy metals (Al, As, Ba, Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Sb, Se, Sr, V and Zn) in the Danjiangkou Reservoir, the water source area of the Middle Route of China’s interbasin South to North Water Transfer Project, were analyzed using an Inductively Coupled Plasma Atomic Emission Spectrometer (ICP-AES) and compared with the national and international standards for drinking water. The results indicated that concentrations of As, Pb, Sb and Se in the Reservoir exceeded the standards and they would pose health risk for residents in the region and the water receiving areas of the interbasin water transfer project. Spatial and temporal variability of the trace elements and heavy metals in the Reservoir implies their mixed sources of natural processing and anthropogenic activities in the upper drainage of the Reservoir. The research results would help develop water resource management and conservation strategy for the interbasin water transfer project.  相似文献   
9.
Neural network prediction of nitrate in groundwater of Harran Plain, Turkey   总被引:2,自引:0,他引:2  
Monitoring groundwater quality by cost-effective techniques is important as the aquifers are vulnerable to contamination from the uncontrolled discharge of sewage, agricultural and industrial activities. Faulty planning and mismanagement of irrigation schemes are the principle reasons of groundwater quality deterioration. This study presents an artificial neural network (ANN) model predicting concentration of nitrate, the most common pollutant in shallow aquifers, in groundwater of Harran Plain. The samples from 24 observation wells were monthly analysed for 1 year. Nitrate was found in almost all groundwater samples to be significantly above the maximum allowable concentration of 50 mg/L, probably due to the excessive use of artificial fertilizers in intensive agricultural activities. Easily measurable parameters such as temperature, electrical conductivity, groundwater level and pH were used as input parameters in the ANN-based nitrate prediction. The best back-propagation (BP) algorithm and neuron numbers were determined for optimization of the model architecture. The Levenberg–Marquardt algorithm was selected as the best of 12 BP algorithms and optimal neuron number was determined as 25. The model tracked the experimental data very closely (R = 0.93). Hence, it is possible to manage groundwater resources in a more cost-effective and easier way with the proposed model application.  相似文献   
10.
Geospatial technology is increasing in demand for many applications in geosciences. Spatial variability of the bed/hard rock is vital for many applications in geotechnical and earthquake engineering problems such as design of deep foundations, site amplification, ground response studies, liquefaction, microzonation etc. In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 km2. In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, Geostatistical model based on Ordinary Kriging technique, Artificial Neural Network (ANN) and Support Vector Machine (SVM) models have been developed. In Ordinary Kriging, the knowledge of the semi-variogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of the Bangalore, where field measurements are not available. A new type of cross-validation analysis developed proves the robustness of the Ordinary Kriging model. ANN model based on multi layer perceptrons (MLPs) that are trained with Levenberg–Marquardt backpropagation algorithm has been adopted to train the model with 90% of the data available. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing loss function has been used to predict the reduced level of rock from a large set of data. In this study, a comparative study of three numerical models to predict reduced level of rock has been presented and discussed.  相似文献   
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