Modelling the effect of changing precipitation inputs on deep soil water utilization          下载免费PDF全文

Ji Qi  Daniel Markewitz  David Radcliffe 《水文研究》2018,32(5):672-686

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   

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing     

Peng Yue  Fan Gao  Boyi Shangguan  Zheren Yan 《International journal of geographical information science》2020,34(11):2243-2274

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.  相似文献   

PRELIMINARY STUDY ON THE FLOODING AND DROUGHT CLAMITY DURING PAST 1500 YEARS IN THE HAI′AN REGION，JIANGSU PROVINCE   总被引：1，自引：0，他引：1  

ZHANGQiang  CHENGJi 《中国地理科学(英文版)》2002,12(2):146-151

Collection and arrangement of the historical records of climatic changes and environment evolution,espectial-lyin the aspect of calamities,are made on the history documents of past 1500 years about Haiˊan region,Jiangsu Province.There existed two obvious flooding-drought frequently-occurring periods:one was from 1550 AD to 1850 AD and another was 100 AD to 1200AD.The period of 1550 AD to1850 AD is interrupted by two relatively arid and cold climatic periods:one was from 1630 AD to 1700 AD and another was 1750 AD to 1820 AD.The main characteristic of the calamity periods is that they occurred by turns,and sometimes,both drought and flooding occurred in the same year.The instability of the climatic changes in the Little Ice Age may be the main reason of the frequently-occurring flooding and drought in Haiˊan region.Research results also show that the frequently-occurring periods of flooding and drought is in close relationship with the solar activity,and therefore,occurrence of the flooding and drought may be in relation with the intensity of the solar activity.This hypothesis may need further study in the future.  相似文献   

An approximate method for evaluating the shear band thickness in saturated soils     

X. B. Lu  Wang Shuyun  Wang Yihua  Peng Cui 《国际地质力学数值与分析法杂志》2004,28(15):1533-1541

A formula for the thickness of a shear band formed in saturated soils under a simple shear or a combined stress state has been proposed. It is shown that the shear band thickness is dependent on the pore pressure properties of the material and the dilatancy rate, but is independent of the details of the combined stress state. This is in accordance with some separate experimental observations. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

Evolution of Electric Currents Associated with Two M-Class Flares     

Baolin Tan  Haisheng Ji  Guangli Huang  Tuanhui Zhou  Qiwu Song  Yu Huang 《Solar physics》2006,239(1-2):137-148

Using one-minute cadence vector magnetograms from Big Bear Solar Observatory (BBSO), we analyze the temporal behavior of derived longitudinal electric currents associated with two flares on July 26, 2002. One of the events is an M1.0 flare which occurred in active region NOAA 10044, while the other is an M8.7 flare in the adjacent region 10039. Rapid changes of magnetic fields in the form of flux emergence are found to be associated with both of these events. However, the temporal behavior of electric currents are very different. For the M1.0 flare, the longitudinal electric current density drops rapidly near the flaring neutral line; while for the M8.7 flare, the current density rapidly increases, confirming the picture of the current-carrying flux emergence. We offer a possible explanation for such a difference: magnetic reconnection at different heights for the two events, near the photosphere for the M1.0 flare, and higher up for the M8.7 flare.  相似文献   

GPS/LEO掩星观测的变分同化技术   总被引：6，自引：0，他引：6  

刘敏  郭鹏 《天文学进展》2006,24(1):27-42

在简单介绍GPS/LEO掩星探测大气的发展历史和科学意义之后,详细阐述了反演的基本原理;分析了标准反演中存在的问题,并说明一维变分同化(1DVAR)在反演方法中的重要性;给出了一维变分同化中价值函数的求解,以及各种同化因子;简单介绍了对当前气象学中普遍使用的四维变分同化(4DVAR);重点讨论了各种同化方法,以及使用各种同化因子的优缺点。最后,通过CHAMP卫星的观测实例分析,验证了GPS数据在数值天气预报(NWP)中的作用,以及相对于标准反演法一维变分对气象要素的改进。  相似文献   

Approach to Mountain Hazards in Tibet, China   总被引：1，自引：1，他引：0  

MADongtao TUJianjun CUIPeng LURuren 《山地科学学报》2004,1(2):143-154

Tibet is located at the southwest boundary of China. It is the main body of the Qinghai-Tibet Plateau, the highest and the youngest plateau in the world. Owing to complicated geology, Neo-tectonic movements, geomorphology, climate and plateau environment, various mountain hazards, such as debris flow, flash flood, landslide, collapse, snow avalanche and snow drifts, are widely distributed along the Jinsha River (the upper reaches of the Yangtze River), the Nu River and the Lancang River in the east, and the Yarlungzangbo River, the Pumqu River and the Poiqu River in the south and southeast of Tibet. The distribution area of mountain hazards in Tibet is about 589,000 km^2, 49.3% of its total territory. In comparison to other mountain regions in China, mountain hazards in Tibet break out unexpectedly with tremendously large scale and endanger the traffic lines, cities and towns, farmland, grassland, mountain environment, and make more dangers to the neighboring countries, such as Nepal, India, Myanmar and Bhutan. To mitigate mountain hazards, some suggestions are proposed in this paper, such as strengthening scientific research, enhancing joint studies, hazards mitigation planning, hazards warning and forecasting, controlling the most disastrous hazards and forbidding unreasonable human exploring activities in mountain areas.  相似文献   

Book review     

Jiří Podolský 《Astrophysics and Space Science》1990,164(2):333-336

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Optical monitoring of the quasar 4C 38.41     

B. Peng  J. Wu  X. Zhou 《Monthly notices of the Royal Astronomical Society》2003,346(2):483-488

The results of a photometric monitoring of the quasar 4C 38.41, performed at the optical R and B bands in 2002 February–March, are presented. With a 60/90 cm Schmidt telescope at the Xinglong station of the National Astronomical Observatories of China, we observed the source exhibiting amplitude variations of up to 0.78 mag in both bands during the whole campaign. Intraday and even intranight variations are detected as well. A typical variability time-scale of about 36 d is derived from our 2-month observations at the optical bands, which is identical to that found at a radio wavelength of 92 cm, suggesting a common origin for the variations in 4C 38.41 from optical to radio bands.  相似文献   

SIMULATION AND PREDICTION OF DEBRIS FLOW USING ARTIFICIAL NEURAL NETWORK     

WANGXie-kang HUANGEr CUIPeng 《中国地理科学(英文版)》2003,13(3):262-266

Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural haz-ard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting de-bris flow have been proposed, however, the accuracy of these methods is not high enough for practical use because of the stochastic and non-linear characteristics of debris flow. Artificial neural network has proven to be feasible and use-fill in developing models for nonlinear systems. On the other hand, predicting the future behavior based on a time se-ries of collected historical data is also an important tool in many scientific applications. In this study we present a three-layer feed-forward neural network model to forecast surge of debris flow according to the time series data collect-ed in the Jiangjia Ravine, situated in north part of Yunnan Province of China. The simulation and prediction of debris flow using the proposed approach shows this model is feasible, however, further studies are needed.  相似文献