Modelling the effect of changing precipitation inputs on deep soil water utilization

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.     

Revisiting Sustainable Development of Dry Valleys in Hengduan Mountains Region

Dry valleys are a striking geographic landscape in Hengduan Mountains Region and are characterized by low rainfall, desert type of vegetation and fragile environment. Past efforts and resources have been concentrated mainly on rehabilitation of degraded ecosystem and fragile environment, particularly reforestation, while socio-economic development has been largely overlooked. Despite successes in pocket areas, the overall trend of unsustainability and environmental deterioration are continuing. It is important to understand that uplift of the Tibetan Plateau is the root cause of development of dry valleys, and development and formation of dry valleys is a natural process. Human intervention has played a secondary role in development of dry valleys and degradation of dry valleys though human intervention in many cases has speeded up environmental degradation of the dry valleys. It is important to understand that dry valleys are climatic enclaves and an integrated approach that combines rehabilitation of degraded ecosystems and socio-economic development should be adopted if the overall goal of sustainable development of dry valleys is to be achieved. Promotion of niche-based cash crops, rural energy including hydropower, solar energy, biogas and fuelwood plantation is recommended as the priority activities.     

Precipitation patterns in flood season over China associated with the El Niño/Southern Osciliation

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.     

Identification of physical processes inherent in artificial neural network rainfall runoff models

The emergence of artificial neural network (ANN) technology has provided many promising results in the field of hydrology and water resources simulation. However, one of the major criticisms of ANN hydrologic models is that they do not consider/explain the underlying physical processes in a watershed, resulting in them being labelled as black‐box models. This paper discusses a research study conducted in order to examine whether or not the physical processes in a watershed are inherent in a trained ANN rainfall‐runoff model. The investigation is based on analysing definite statistical measures of strength of relationship between the disintegrated hidden neuron responses of an ANN model and its input variables, as well as various deterministic components of a conceptual rainfall‐runoff model. The approach is illustrated by presenting a case study for the Kentucky River watershed. The results suggest that the distributed structure of the ANN is able to capture certain physical behaviour of the rainfall‐runoff process. The results demonstrate that the hidden neurons in the ANN rainfall‐runoff model approximate various components of the hydrologic system, such as infiltration, base flow, and delayed and quick surface flow, etc., and represent the rising limb and different portions of the falling limb of a flow hydrograph. Copyright © 2004 John Wiley & Sons, Ltd.     

Silicon limitation on primary production and its destiny in Jiaozhou Bay, China——Ⅳ：Study on cross-bay transect from estuary to ocean

The authors analyzed the data collected in the Ecological Station Jiaozhou Bay from May 1991 to November 1994, including 12 seasonal investigations, to determine the characteristics, dynamic cycles and variation trends of the silicate in the bay. The results indicated that the rivers around Jiaozhou Bay provided abundant supply of silicate to the bay. The silicate concentration there depended on river flow variation. The horizontal variation of silicate concentration on the transect showed that the silicate concentration decreased with distance from shorelines. The vertical variation of it showed that silicate sank and deposited on the sea bottom by phytoplankton uptake and death, and zooplankton excretion. In this way, silicon would endlessly be transferred from terrestrial sources to the sea bottom. The silicon took up by phytoplankton and by other biogeochemical processes led to insufficient silicon supply for phytoplankton growth. In this paper, a 2D dynamic model of river flow versus silicate concentration was established by which silicate concentrations of 0.028–0.062 μmol/L in seawater was yielded by inputting certain seasonal unit river flows (m³/s), or in other words, the silicate supply rate; and when the unit river flow was set to zero, meaning no river input, the silicate concentrations were between 0.05–0.69 μmol/L in the bay. In terms of the silicate supply rate, Jiaozhou Bay was divided into three parts. The division shows a given river flow could generate several different silicon levels in corresponding regions, so as to the silicon-limitation levels to the phytoplankton in these regions. Another dynamic model of river flow versus primary production was set up by which the phytoplankton primary production of 5.21–15.55 (mgC/m²·d)/(m³/s) were obtained in our case at unit river flow values via silicate concentration or primary production conversion rate. Similarly, the values of primary production of 121.98–195.33 (mgC/m²·d) were achieved at zero unit river flow condition. A primary production conversion rate reflects the sensitivity to silicon depletion so as to different phytoplankton primary production and silicon requirements by different phytoplankton assemblages in different marine areas. In addition, the authors differentiated two equations (Eqs. 1 and 2) in the models to obtain the river flow variation that determines the silicate concentration variation, and in turn, the variation of primary production. These results proved further that nutrient silicon is a limiting factor for phytoplankton growth. This study was funded by NSFC (No. 40036010), and the Director's Fund of the Beihai Sea Monitoring Center, the State Oceanic Administration.     

Is Precipitation the Dominant Controlling Factor of High Inorganic Nitrogen Content in the Changjiang River and Its Mouth？

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.     

区域GPS网实时计算可降水量的若干问题

目前地基GPS气象学测得的可降水量 (PWV )精度好于 2mm ,但在利用区域GPS网实时计算每个测站上空的PWV时 ,要涉及到很多常规GPS资料处理时所忽略的问题 ,如需考虑数据处理软件和计算方式的选择、站坐标的确定和约束、轨道的使用方法、网外辅助站最佳数量的确定、海潮对实时计算PWV的影响以及实时应用于气象服务时的端部效应等问题。利用上海GPS综合应用网获取的 2 0 0 2年 6、7月份长江三角洲地区入梅前后的数据 ,分析了利用区域性的GPS网实时计算高精度的PWV时要解决的各种问题 ,探讨了其数据处理方案     

Deep Processes of Basin Evolution:A Case Study of the Southern Songliao Basin and Adjacent Area,NE China in Mesozoic-Cenozoic

1IntroductionOne of the key factors related to basin geody-namics is deep process controlling formation and evolution of sedimentary basin. Depth and tempera-ture of asthenosphere,existence of mantle plume,occurrence of mantle melting,and amounts of melts under depressurization during thinning of lithosphere are controlling factors influenced formation and characteristics of extensional basin directly (Li,1994). Rifting is probably governed by frictional forces exerted on the base of litho…     

用层次分析法决策地下水库回灌方案的排序问题

本文引用了一种新的系统分析方法(层次分析法)对地下水库人工回灌的复杂系统进行了择优排序研究,取得了满意的结果。实践证明,层次分析法对于地下水库人工回灌方案的择优是一种简捷实用的决策方法。     

气候变化对塔里木河来自天山的地表径流影响

塔里木河水资源主要来自天山南坡两条源流,选择西段阿克苏河和中段开都河-孔雀河作为研究区.1956-2003年研究河源山区气温呈持续升温且降水波动增加的趋势,其中1995-2003年升温强劲,升温速率高出48 a期间平均的3倍以上;降水自1986年后持续增加,20世纪90年代较80年代增幅达18%,并显示出河源山区湿岛向塔里木盆地扩展.因高山缺少气象观测,出山径流过程变化可以综合反映中高山带的气候变化.塔里木河来自天山的地表径流在1986-2003年间持续增长,以冰川融水补给为主的库玛拉克河,1994年以来年径流量增加已在前期平均值基础上提升了一个台阶;开都河以降水径流补给为主,1986-2002年出现了观测记录以来的丰水期,并使1986年后博斯腾湖水位快速上升,恢复到1958年记录的最高水位以上.两河年径流变化趋势基本相似,但也显示有西、中段的气候变化局部差异,出现丰枯水期的不一致;然而,在近16 a升温过程中,年径流增长幅度和快慢相近.