Comparison of direct statistical and indirect statistical-deterministic frameworks in downscaling river low-flow indices

ABSTRACT

This work explores the ability of two methodologies in downscaling hydrological indices characterizing the low flow regime of three salmon rivers in Eastern Canada: Moisie, Romaine and Ouelle. The selected indices describe four aspects of the low flow regime of these rivers: amplitude, frequency, variability and timing. The first methodology (direct downscaling) ascertains a direct link between large-scale atmospheric variables (the predictors) and low flow indices (the predictands). The second (indirect downscaling) involves downscaling precipitation and air temperature (local climate variables) that are introduced into a hydrological model to simulate flows. Synthetic flow time series are subsequently used to calculate the low flow indices. The statistical models used for downscaling low flow hydrological indices and local climate variables are: Sparse Bayesian Learning and Multiple Linear Regression. The results showed that direct downscaling using Sparse Bayesian Learning surpassed the other approaches with respect to goodness of fit and generalization ability.

Editor D. Koutsoyiannis; Associate editor K. Hamed     

Differences in throughfall drop size distributions in the presence and absence of foliage

ABSTRACT

Throughfall drop size distributions (DSDs) are important for plant–soil interactions. This is the first known study to quantify differences in throughfall DSDs with the presence and absence of foliage. Employing a disdrometer, three parameters solely representing throughfall drip were measured and calculated: maximum drop diameter (D_MAX), median volume diameter of drops (D₅₀D_R) and relative volume percentage of drops (pD_R). Beneath Liriodendron tulipifera L. in Maryland (USA), D_MAX, D₅₀D_R and pD_R were substantially larger when the canopy was unfoliated. In fact, the presence or absence of foliage was one of the primary factors affecting all three throughfall DSDs along with air temperature, according to the boosted regression tree analysis. Experimental results were attributed to differing physical properties of intercepted water between foliated and unfoliated periods and differential water behavior on leaves and bark. Future work should examine the effects of concentrated drip points on the development of throughfall-induced hot spots.

Editor M.C. Acreman; Associate editor F. Hattermann     

Historical trends in Florida temperature and precipitation

Because of its low topographic relief, unique hydrology, and the large interannual variability of precipitation, Florida is especially vulnerable to climate change. In this paper, we investigate a comprehensive collection of climate metrics to study historical trends in both averages and extremes of precipitation and temperature in the state. The data investigated consist of long‐term records (1892–2008) of precipitation and raw (unadjusted) temperature at 32 stations distributed throughout the state. To evaluate trends in climate metrics, we use an iterative pre‐whitening method, which aims to separate positive autocorrelation from trend present in time series. Results show a general decrease in wet season precipitation, most evident for the month of May and possibly tied to a delayed onset of the wet season. In contrast, there seems to be an increase in the number of wet days during the dry season, especially during November through January. We found that the number of dog days (above 26.7 °C) during the year and during the wet season has increased at many locations. For the post‐1950 period, a widespread decrease in the daily temperature range (DTR) is observed mainly because of increased daily minimum temperature (Tmin). Although we did not attempt to formally attribute these trends to natural versus anthropogenic causes, we find that the urban heat island effect is at least partially responsible for the increase in Tmin and its corresponding decrease in DTR at urbanized stations compared with nearby rural stations. In the future, a formal trend attribution study should be conducted for the region. Copyright © 2012 John Wiley & Sons, Ltd.     

Evaluation of the response modification coefficient and collapse potential of special concentrically braced frames

Special concentrically braced frames (SCBFs) are commonly used for seismic design of buildings. Their large elastic stiffness and strength efficiently sustains the seismic demands during smaller, more frequent earthquakes. During large, infrequent earthquakes, SCBFs exhibit highly nonlinear behavior due to brace buckling and yielding and the inelastic behavior induced by secondary deformation of the framing system. These response modes reduce the system demands relative to an elastic system without supplemental damping using a response modification coefficient, commonly termed the R factor. More recently, procedures put forth in FEMAP695 have been made to quantify the R factor through a formalized procedure that accounts for collapse potential. The primary objective of the research in this paper was to evaluate the approach for SCBFs. An improved model for SCBFs that permits simulation of brace fracture was used to conduct response history analyses. A series of three‐story, nine‐story and 20‐story SCBFs were designed and evaluated. Initially, the FEMAP695 method was conducted to estimate collapse and the corresponding R factor. An alternate procedure for scaling the multiple acceleration records to the seismic design hazard was also evaluated. The results show significant variation between the two methods. Of the three variations of buildings studied, the largest vulnerability was identified for the three‐story building. To achieve a consistent margin of safety against collapse, a significantly lower R factor is required for the low‐rise SCBFs (three‐story), whereas the mid‐rise and high‐rise SCBFs (nine‐story and 20‐story) may continue to use the current value of 6, as provided in ASCE‐07. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

Spatial interaction between collapsed pipes and landslides in hilly regions with loess‐derived soils

While most studies focus on the effect of soil pipes on hillslope stability, this present study investigates the impact of landsliding on pipe development. It is hypothesized that poorly drained active and dormant landslides change the hillslope hydrology through (i) surface flow obstruction, by changing topography, as well as (ii) subsurface flow obstruction by tilting less‐permeable clay‐rich substrates. Hence, new preferential flow paths are created at reverse slopes within the landslide zone and at the boundary of the landslide, enhancing pipe formation. This study aims at a better understanding of the interaction between collapsed pipe (CP) occurrence and landslide (LS) occurrence in the Flemish Ardennes (Belgium) by comparing their respective spatial patterns. At least 24.5% of the 139 sites with CP were related to the occurrence of an observed LS. Poorly drained LS may create favourable conditions for pipe development. Outside LS, natural and anthropogenic (e.g. broken field drains, road drainage) causes may result in concentrated subsurface flow, resulting in pipe development. No evidence was found that pipe development enhanced LS, probably because the subsurface drainage discharge generated upslope of the LS is too low. Even when pipes become blocked, it is more likely that new pipes develop and new collapses occur than they trigger or reactivate LS. A conceptual model is presented summarizing all elements that influence piping erosion in the Flemish Ardennes, including the role of LS. Copyright © 2012 John Wiley & Sons, Ltd.     

中国大陆地震地下流体异常特征研究

根据《中国震例》(1966~1999年)在中国大陆发生M_S≥5.0地震188次震例资料 , 将其中与流体异常相关的126个震例中的803项流体异常按异常出现、 异常转折至发震随时间变化和异常数量随震中距距离变化分布的时、 空特征进行统计、 分析。 研究结果表明, 无论是趋势性异常还是短临异常, 在不同的时间段中, 异常数量呈现出明显的阶段性分布特征; 异常数量空间分布会随震中距的变化而不同。 在统计研究中还表明, 两者在时、 空分布方面有较好的一致性。     

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.     

气温对太湖蓝藻复苏和休眠进程的影响

利用2005 2014年每日的卫星数据、气象站和浮标站观测资料研究复苏期和休眠期的平均气温、稳定通过界限温度初终日、周有效积温与太湖蓝藻休眠和复苏时间的关系,探讨气温是否是影响蓝藻休眠和复苏时间进程的关键因子.分析结果显示:太湖蓝藻复苏早晚与春季(3 5月)气温密切相关,春季气温越高,蓝藻复苏时间越早;太湖蓝藻休眠时间与秋、冬季(11次年1月)气温密切相关,秋、冬季气温越高,蓝藻休眠时间越晚.此外根据分析结果发现,太湖首次出现蓝藻水华的时间一般是气温稳定通过9℃初日之后的1个月左右,但上一周期的休眠与下一周期的复苏之间气温异常偏高会导致蓝藻水华首次出现时间早于稳定通过9℃初日;最后一次蓝藻水华出现时间与气温稳定通过4℃的终日相近;在复苏期,湖水中的叶绿素a浓度随周有效积温变化而变化,二者相关系数为0.9.