Spatial Variability of Nitrate and Ammonium in Pleistocene Aquifer of Central Yangtze River Basin

It becomes increasingly important and challenging for nitrogen pollution prevention to identify key controls for spatial variability of nitrogen in groundwater that could be affected by multiple factors, including anthropogenic input, groundwater flow, and local geochemistry. This study characterized spatial variability of both nitrate and ammonium in the Pleistocene aquifer of central Yangtze River Basin and assessed the effect of various factors in controlling nitrate and ammonium levels based on multiple statistical approaches (correlation, geostatistics, multiple liner regression). The results indicate that nitrate is mostly influenced by Cl⁻ that represents anthropogenic input, while Eh representing local redox state is a secondary variable influencing nitrate concentrations. The groundwater with elevated nitrate concentrations are estimated to occur mainly in areas with higher-permeability near-surface sediments which can facilitate more anthropogenic nitrate transport and less nitrate removal owing to more oxidized state. Ammonium is mostly correlated to Eh, followed by dissolved organic carbon (DOC), but only DOC improves significantly the accuracy of co-kriging prediction model. The groundwater with elevated ammonium concentrations are estimated to occur mainly in areas with more organic-rich sediments within or around the aquifer which can facilitate more ammonium release owing to natural organic matter consumption accompanying strong reducing conditions. The regional groundwater flow is not a factor significantly controlling nitrate or ammonium levels owing to flat topography and sluggish lateral flow.     

Dunefield Activity and Interactions with Climatic Variability in the Southwest Kalahari Desert

An analysis is undertaken of the temporal variability of climatic parameters that influence dunefield aeolian activity. Data from seven meteorological stations in the southwestern Kalahari Desert are used, spanning the period 1960–1992. Erosivity is considered through analysis of wind data, and erodibility through analysis of precipitation and potential evapotranspiration, which together influence dune surface plant growth. The data are integrated using Lancaster's ‘mobility’ index which provides a measure of potential dune surface sand transport. This is renamed ‘potential dune surface activity index’, to reflect the actual characteristic that is measured. The subsequent analysis indicates that dunefield activity is episodic and temporally variable, that both erosivity and erodibility vary through time, and that present levels of activity cannot be characterized by a single simple state. © 1997 by John Wiley & Sons, Ltd.     

The Safe Yield and Climatic Variability: Implications for Groundwater Management

Methods for calculating the safe yield are evaluated in this paper using a high‐quality and long historical data set of groundwater recharge, discharge, extraction, and precipitation in a karst aquifer. Consideration is given to the role that climatic variability has on the determination of a climatically representative period with which to evaluate the safe yield. The methods employed to estimate the safe yield are consistent with its definition as a long‐term average extraction rate that avoids adverse impacts on groundwater. The safe yield is a useful baseline for groundwater planning; yet, it is herein shown that it is not an operational rule that works well under all climatic conditions. This paper shows that due to the nature of dynamic groundwater processes it may be most appropriate to use an adaptive groundwater management strategy that links groundwater extraction rates to groundwater discharge rates, thus achieving a safe yield that represents an estimated long‐term sustainable yield. An example of the calculation of the safe yield of the Edwards Aquifer (Texas) demonstrates that it is about one‐half of the average annual recharge.     

Climatic characteristics of the tropopause over the Arctic Basin

On the basis of stationary aerological observations and measurements at Russian –North Pole drifting stations taken during 1954–1991, tropopause climate parameters (height and temperature at its upper and lower bounds) are determined. Long-term trends of these parameters over the Arctic Ocean are revealed.     

时变功率谱空间变化性分析

基于我国台湾地区SMART-1密集台阵强震记录资料和Kameda的时变功率谱模型,利用多重滤波技术和非线性最小二乘法拟合得到每条记录的Kameda模型参数值;通过分析模型参数随频率变化的散点图分布规律,建立了时变功率谱模型参数随频率变化的随机模型。采用随机振动理论和多元统计分析方法,分析了沿波传播方向距离、垂直于波传播方向距离及测点所在位置土层厚度等局部空间位置变化对时变功率谱模型参数的影响规律,探讨了时变功率谱模型参数的空间分布形式,建立了各模型参数随空间坐标变化的随机预测模型,从而为重大工程多点输入地震动参数的确定和多点输入加速度时程的合成提供实用模型。     

Factors Influencing Variability in Groundwater Monitoring Data Sets

“Random” variability in groundwater monitoring data sets reduces the ability to identify long‐term concentration trends. This, in turn, increases the time and cost required to evaluate the effectiveness of natural attenuation and other groundwater remedies. To better understand the factors influencing variability in groundwater monitoring results, we have analyzed three large groundwater monitoring data sets. For the three data sets, the long‐term trend in contaminant concentration in each well accounted for an average of 30% to 40% of the overall variation in contaminant concentration. Understanding the causes of the remaining variability would support the development of improved groundwater monitoring methods. All three data sets show large differences in the temporal monitoring records between individual wells (e.g., coefficient of variation for monitoring results from individual wells ranges from 0.08 to 4.6) indicating that well and aquifer factors are more important contributors to variability than sample collection and analysis factors. However, the depth to groundwater (R² = 0.020) and distance between water level and screened interval (R² = 0.049) accounted for only a portion of the differences in variability between wells and other aquifer characteristics evaluated and were not correlated with the observed variability in monitoring results. Unidentified factors were apparently much more important contributors to variability than these factors. The monitoring data sets exhibited two distinct timescales for variability: Time‐independent variability that was apparent even when wells were re‐sampled within a few days and a long‐term variability likely associated with the long‐term concentration trend. The observation of time‐independent variability suggests that frequent monitoring of contaminated monitoring wells serves primarily to characterize sources of variability unrelated to the long‐term trend of primary interest.     

Variability in the composition and export of silica in the Huanghe River Basin

Concentrations of suspended particle material(SPM), dissolved silicate(DSi), biogenic silica(BSi), phytoliths(plant produced siliceous microscopic structures), and other parameters were analyzed to examine the influence of both natural processes and human activities on silica delivery to the estuary of the Huanghe River(Yellow River). Our results indicate that the concentrations of DSi in the river decreased significantly since 1986. Approximately 34% of dissolved silica was trapped in the basin between 1986 and 2010 due to a reduction of soil erosion. Phytoliths comprised 67.2%–96.3% of BSi, with the smoothing bar type being the dominant form. Concentrations of BSi are significantly higher in the Huanghe River compared to other major rivers throughout the world due to its high sediment yield. We also found that the ratios of BSi/(BSi+DSi) and BSi/SPM were approximately 0.5 and 0.003 at Lijin near the river mouth, indicating that BSi carried in suspension by the Huanghe River was an important component of the rivers silica load. Significant amounts of BSi were also composed of phytoliths in Bohai Sea sediments near the Huanghe River estuary with the smoothing bar form again being the most abundant. The relatively high specific fluxes of BSi in the Huanghe River reflect its high turbidity and high erosion rates in the basin. The high sediment load originating on the Loess Plateau is likely responsible for the higher BSi flux, in agreement with a general trend of increasing BSi flux with increasing sediment flux in global river systems. This study demonstrates that BSi transported by rivers can be composed largely of phytoliths originating from the erosion of topsoils. The flux of phytoliths in river's suspended sediment load may therefore represent a significant contribution to the biogeochemical cycle of silica in coastal waters.     

Statistical Variability and Tokunaga Branching of Aftershock Sequences Utilizing BASS Model Simulations

Aftershock statistics provide a wealth of data that can be used to better understand earthquake physics. Aftershocks satisfy scale-invariant Gutenberg–Richter (GR) frequency–magnitude statistics. They also satisfy Omori’s law for power-law seismicity rate decay and Båth’s law for maximum-magnitude scaling. The branching aftershock sequence (BASS) model, which is the scale-invariant limit of the epidemic-type aftershock sequence model (ETAS), uses these scaling laws to generate synthetic aftershock sequences. One objective of this paper is to show that the branching process in these models satisfies Tokunaga branching statistics. Tokunaga branching statistics were originally developed for drainage networks and have been subsequently shown to be valid in many other applications associated with complex phenomena. Specifically, these are characteristic of a universality class in statistical physics associated with diffusion-limited aggregation. We first present a deterministic version of the BASS model and show that it satisfies the Tokunaga side-branching statistics. We then show that a fully stochastic BASS simulation gives similar results. We also study foreshock statistics using our BASS simulations. We show that the frequency–magnitude statistics in BASS simulations scale as the exponential of the magnitude difference between the mainshock and the foreshock, inverse GR scaling. We also show that the rate of foreshock occurrence in BASS simulations decays inversely with the time difference between foreshock and mainshock, an inverse Omori scaling. Both inverse scaling laws have been previously introduced empirically to explain observed foreshock statistics. Observations have demonstrated both of these scaling relations to be valid, consistent with our simulations. ETAS simulations, in general, do not generate Båth’s law and do not generate inverse GR scaling.     

Groundwater Quality: Analysis of Its Temporal and Spatial Variability in a Karst Aquifer

This study develops an approach based on hierarchical cluster analysis for investigating the spatial and temporal variation of water quality governing processes. The water quality data used in this study were collected in the karst aquifer of Yucatan, Mexico, the only source of drinking water for a population of nearly two million people. Hierarchical cluster analysis was applied to the quality data of all the sampling periods lumped together. This was motivated by the observation that, if water quality does not vary significantly in time, two samples from the same sampling site will belong to the same cluster. The resulting distribution maps of clusters and box‐plots of the major chemical components reveal the spatial and temporal variability of groundwater quality. Principal component analysis was used to verify the results of cluster analysis and to derive the variables that explained most of the variation of the groundwater quality data. Results of this work increase the knowledge about how precipitation and human contamination impact groundwater quality in Yucatan. Spatial variability of groundwater quality in the study area is caused by: a) seawater intrusion and groundwater rich in sulfates at the west and in the coast, b) water rock interactions and the average annual precipitation at the middle and east zones respectively, and c) human contamination present in two localized zones. Changes in the amount and distribution of precipitation cause temporal variation by diluting groundwater in the aquifer. This approach allows to analyze the variation of groundwater quality controlling processes efficiently and simultaneously.     

Spatial and Temporal Variability of Biogenic Elements Flow and Water Quality in a Small River

Regularities of the formation of biogenic elements flow and water quality in the Istra River (downstream of the Istrinskoye Reservoir) and its tributaries are revealed. Temporal variability in water quality parameters is shown to be closely related to fluctuations in the river water abundance, whereas spatial variability is determined by different intensity of anthropogenic load on river watersheds. It was found that the mean annual (for the period of 1991–1995) concentrations of nitrogen and phosphorus mineral compounds do not always meet the requirements of drinking water supply. A method of estimating the environmental state of the main river, taking into account biogenic elements input from its basin is suggested.     

Spatial Variability of Surface Soil Moisture in a Depression Area of Karst Region

An understanding of soil moisture variability is necessary to characterize the linkages between a region's hydrology, ecology, and physiography. In subtropical karst region, the spatial variability of surface soil moisture is still unclear for the rocky ecological environment and intensive land uses. The purpose of this study was to characterize the variation and patterns of soil moisture content at depth of 0–16 cm and to investigate their influencing factors in a karst depression area of southwest China. Soil moisture content was measured at 20 m intervals by intensive sampling on March 11 (dry season) and August 30 (rainy season) in 2005, respectively. Surface soil moisture presented a moderate variability in the depression area at the sampling times. The variability was relatively higher in dry season with lower mean soil moisture, but lower in rainy season with higher mean soil moisture after heavy rain event. Similar results were also obtained from the mosaic patterns of soil moisture generated by ordinary Kriging interpolation with low standard deviations. This suggested that more soil samples might be required and the sampling interval should be shortened in dry season compared with rainy season. The dominant influencing factors on the variability of surface soil moisture were rainfall and land use types. However, altitude, bare‐rock ratio, and soil organic carbon were also important factors, and exerted jointly to control and redistribute the surface soil moisture either in dry or rainy season in the depression area. Such information provided some insights for the study on eco‐hydrological processes of vegetation restoration in the karst degraded ecosystem of southwest China.