Spatial and temporal dust source variability in northern China identified using advanced remote sensing analysis

The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi‐scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust‐producing sources. The representation of intra‐annual and inter‐annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter‐annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas. Copyright © 2012 John Wiley & Sons, Ltd.     

A) A. I. H. S. / A) A. I. H. S.

Abstract

A new method is presented to generate stationary multi-site hydrological time series. The proposed method can handle flexible time-step length, and it can be applied to both continuous and intermittent input series. The algorithm is a departure from standard decomposition models and the Box-Jenkins approach. It relies instead on the recent advances in statistical science that deal with generation of correlated random variables with arbitrary statistical distribution functions. The proposed method has been tested on 11 historic weekly input series, of which the first seven contain flow data and the last four have precipitation data. The article contains an extensive review of the results.

Editor D. Koutsoyiannis

Citation Ilich, N., 2014. An effective three-step algorithm for multi-site generation of stochastic weekly hydrological time series. Hydrological Sciences Journal, 59 (1), 85–98.     

Statistical interpretation of the daily variation of urban water consumption in Beijing,China

Abstract

The efficient planning and design of water networks, as well as the management and strategies of existing water supply systems, require accurate short-term water demand forecasts. In this study, a statistical model for the estimation of daily urban water consumption was developed. The model was applied to analyse and forecast the daily water consumption in the main district of Beijing, China, from 2006 to 2010. The model exhibited good performance with a coefficient of determination, R², greater than 0.9 in both the calibration and validation periods. The results indicate that: (a) the 7-day moving average temperature is an efficient variable that can be used to depict water-use variation in a year; (b) a daily maximum temperature of 31.1°C and the occurrence of precipitation are two thresholds of water-use behaviour; and (c) the current day’s water consumption has a strong correlation with the consumption of one, two and seven days ago.

Editor Z.W. Kundzewicz; Associate editor D. Yang

Citation Zhang, D.W., et al., 2013. Statistical interpretation of the daily variation of urban water consumption in Beijing, China. Hydrological Sciences Journal, 59 (1), 181–192.     

Estimation of the temporal autocorrelation structure by the collocation technique with an emphasis on soil moisture studies

Abstract

The collocation technique has become a popular tool in oceanography and hydrology for estimating the error variances of different data sources such as in situ sensors, models and remote sensing products. It is also possible to determine calibration constants, for example to account for an off-set between the data sources. So far, the temporal autocorrelation structure of the errors has not been studied, although it is known that it has detrimental effects on the results of the collocation technique, in particular when calibration constants are also determined. This paper shows how the (triple) collocation estimators can be adapted to retrieve the autocovariance functions; the statistical properties as well as the structural deficencies are described. The coupling between the autocorrelation of the error and the estimation of calibration constants is studied in detail, due to its importance for analysing temporal changes. In soil moisture applications, such time variations can be induced, for example, by seasonal changes in the vegetation cover, which affect both models and remote sensing products. The limitations of the proposed technique associated with these considerations are analysed using remote sensing and in situ soil moisture data. The variability of the inter-sensor calibration and the autocovariance are shown to be closely related to temporal patterns of the data.

Editor D. Koutsoyiannis

Citation Zwieback, S., Dorigo, W., and Wagner, W., 2013. Estimation of the temporal autocorrelation structure by the collocation technique with an emphasis on soil moisture studies. Hydrological Sciences Journal, 58 (8), 1729–1747.     

On the quest for chaotic attractors in hydrological processes

Abstract

In the last two decades, several researchers have claimed to have discovered low-dimensional determinism in hydrological processes, such as rainfall and runoff, using methods of chaotic analysis. However, such results have been criticized by others. In an attempt to offer additional insights into this discussion, it is shown here that, in some cases, merely the careful application of concepts of dynamical systems, without doing any calculation, provides strong indications that hydrological processes cannot be (low-dimensional) deterministic chaoti. Furthermore, it is shown that specific peculiarities of hydrological processes on fine time scales, such as asymmetric, J-shaped distribution functions, intermittency, and high autocorrelations, are synergistic factors that can lead to misleading conclusions regarding the presence of (low-dimensional) deterministic chaos. In addition, the recovery of a hypothetical attractor from a time series is put as a statistical estimation problem whose study allows, among others, quantification of the required sample size; this appears to be so huge that it prohibits any accurate estimation, even with the largest available hydrological records. All these arguments are demonstrated using appropriately synthesized theoretical examples. Finally, in light of the theoretical analyses and arguments, typical real-world hydrometeorological time series, such as relative humidity, rainfall, and runoff, are explored and none of them is found to indicate the presence of chaos.     

Regulating Environmental Factors of Nutrients Release from Wheat Straw Biochar for Sustainable Agriculture

One mechanism by which biochar application enhances soil nutrient availability is through direct nutrients release from biochar. However, factors controlling the release processes are poorly understood. In this study, the effects of pH, biochar to water ratio, temperature, ionic strength, and equilibration time on the release of PO, NO, NH, K⁺, Na⁺, Ca²⁺, and Mg²⁺ from biochar were evaluated in simulated experiments. The release of PO, K⁺, Ca²⁺, and Mg²⁺ was significantly affected by extraction pH, suggesting that their release from biochar was pH dependent or an H⁺‐consuming process. Correlation analysis indicated that PO and Ca²⁺, PO and Mg²⁺, and Ca²⁺ and Mg²⁺ were co‐solubilized with increasing soil acidity. To a lesser extent, the recovery of the nutrients was also affected by the ratio of biochar to water: more nutrients were soluble with more water supply. In contrast, the release of Na was not affected by pH while the concentration increased with decreasing biochar to water ratio. Meanwhile, other factors (temperature, ionic strength, and equilibration time) had less effect on nutrient release from biochar. Under the influence of pH, the patterns of NO and PO release from biochar were different: extractable NO concentration was not affected by the pH but more PO was released in strongly acidic conditions. Our data suggested that P was mainly retained in inorganic forms while N was in organic forms in biochar. We conclude that environmental factors have marked influences on nutrients release from biochar.     

Mass Balance Study on Phosphorus Removal in Constructed Wetland Microcosms Treating Polluted River Water

A number of studies have showed that the mass removal rates of phosphorus (P) in different constructed wetlands (CWs) varied significantly, and it is essential to quantify the contributions of major P removal processes in order to improve system design. The objective of this study was to investigate the effects of vegetation, hydraulic retention time (HRT), and water temperature on P removal from polluted river water and to quantify the contributions of different P removal pathways in surface CWs. Results showed that the average total P removal rates ranged between 2.69 and 20.84 mg/(m² day) in different seasons and were influenced significantly by vegetation, HRT, and water temperature. According to the mass balance approach, plant uptake removed 4.81–22.33% of P input, while media storage contributed 36.16–49.66%. Other P removal processes such as microbiota uptake removed around 0.26–4.13%. Media storage and plant uptake were identified as the main P removal processes in surface CWs treating polluted river water. This illustrated the importance of selecting media and plants in CWs for future practical application.     

Development of time series stacks of Landsat images for reconstructing forest disturbance history

Abstract

Forest dynamics is highly relevant to a broad range of earth science studies, many of which have geographic coverage ranging from regional to global scales. While the temporally dense Landsat acquisitions available in many regions provide a unique opportunity for understanding forest disturbance history dating back to 1972, large quantities of Landsat images will need to be analysed for studies at regional to global scales. This will not only require effective change detection algorithms, but also highly automated, high level preprocessing capabilities to produce images with subpixel geolocation accuracies and best achievable radiometric consistency, a status called imagery-ready-to-use (IRU). This paper describes a streamlined approach for producing IRU quality Landsat time series stacks (LTSS). This approach consists of an image selection protocol, high level preprocessing algorithms and IRU quality verification procedures. The high level preprocessing algorithms include updated radiometric calibration and atmospheric correction for calculating surface reflectance and precision registration and orthorectification routines for improving geolocation accuracy. These automated routines have been implemented in the Landsat Ecosystem Disturbance Adaptive System (LEDAPS) designed for processing large quantities of Landsat images. Some characteristics of the LTSS developed using this approach are discussed.     

考虑关断时间的回线源激发TEM三维时域有限差分正演

从麦克斯韦旋度方程出发可以直接导出瞬变电磁场扩散方程,然而扩散方程不含电场对时间的一阶导数,不能构成显式的时域有限差分方程,借鉴du Fort-Frankel有限差分离散方法引入虚拟位移电流项构建显式时域有限差分方程.对Wang和Hohmann的经典时域算法进行了两点改进:第一,通过将矩形回线源电流密度加入麦克斯韦方程组的安培环路定理方程,实现回线源瞬变电磁激发源加入;第二,在计算中考虑关断时间.第一点改进使时域有限差分方程考虑了一次场的计算,并且源的计算不再依赖均匀半空间模型响应作为初始条件,使算法能够适应表层电阻率不均匀时的三维复杂模型.由于实际观测中不可能出现阶跃电流的关断形式,第二点改进可以方便设置发射电流下降沿.采用改进的三维时域有限差分正演算法对均匀半空间模型、四类三层模型、均匀半空间中含有低阻块体模型进行了计算并分别与解析解、线性数字滤波解、积分方程解和Wang的三维时域有限差分解进行了对比验证.以H模型为例,采用建立的三维时域有限差分正演算法计算了不同关断时间的斜阶跃脉冲回线源瞬变电磁中心点感应电动势衰减曲线.以实际地质资料为基础,构建包含两层采空区的三维复杂模型,以1 μs的极短关断时间进行了复杂模型定回线源瞬变电磁响应计算,并计算了该复杂模型的视电阻率曲线.