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Copula-based identification of the non-stationarity of the relation between runoff and sediment load
It is important to identify the non-stationarity in the relation between runoff and sediment load under the backdrop of the changing environment. This relation helps to further understand the mechanisms of runoff and sediment yield. A copula-based method was used to detect possible change points in the relation between runoff and sediment load in the Wei River Basin (WRB), China, where soil erosion is a very severe issue. The modified Mann-Kendall trend test method was applied to obtain the trends of runoff and sediment load spanning 1960–2010 at monthly and annual timescales. Finally, the causes of the identified non-stationarity of the relation between runoff and sediment load were roughly analyzed from the perspective of climate change and human activities. Results indicated that:(1) the runoff and sediment load in the Jinghe and Wei rivers were generally characterized by noticeably decreasing trends at both monthly and annual timescales;(2) both the Jinghe and Wei rivers had a common change point (2002), implying that the stationarity of the relation between runoff and sediment load in the Jinghe and Wei River was invalid; (3) human activities including increasing water consumption and growing application of soil conservation practices are dominant factors resulting in non-stationarity in the rela-tion between runoff and sediment load in the WRB. This study provides a new idea for identifying the non-stationarity of multivariate relation in the hydro-meteorological field under the background of the changing environment. 相似文献
2.
Statistical assessment of trends and oscillations in rainfall dynamics: Analysis of long daily Italian series 总被引：1，自引：0，他引：1
Since the 18th century systematic measurements of rainfall have been collected in Italy. The daily rainfall series observed in Milan (1835–2001), Genoa (1833–2000), Bologna (1813–2001) and Palermo (1797–1999) are examples of available long rainfall records. These data series can help analyzing the evolution of precipitation. The present paper deals with long term evolution of: (i) annual rainfall amount; (ii) annual number of rainy events; (iii) intensity of rainfall, (iv) inter-annual rainfall partitioning, i.e. the duration of wet and dry periods, and (v) maximum annual values of daily rainfall amount, duration of wet and dry periods. The evolution is studied analyzing the first two order statistics and the 30-year return period quantiles via moving window analysis. Confidence intervals are introduced to check the statistical significance of the estimated statistics and quantiles. The results are compared with those provided by the traditional Mann-Kendall test. The analysis shows how the annual precipitation exhibits a negative trend in the first half of 20th century, with a subsequent positive trend in northern Italy (Genoa, Milan and Bologna). Conversely, the dataset for Palermo (southern Italy) displays only a negative trend. Because the number of precipitation episodes is found to decrease in the investigated period, the average rain rate is significantly increasing especially in northern Italy. This is also associated with shorter duration of rain episodes with an evident effect on rainfall extremes. Dry periods tend to be longer with increasing variability. The Mann-Kendall test and its progressive form have shown to be well suited for monotonic trend, but the confidence interval analysis, introduced here, is more appropriate if oscillations are significant. 相似文献
4.
Binbin Lu Martin Charlton Chris Brunsdon Paul Harris 《International journal of geographical information science》2016,30(2):351-368
In this study, the geographically weighted regression (GWR) model is adapted to benefit from a broad range of distance metrics, where it is demonstrated that a well-chosen distance metric can improve model performance. How to choose or define such a distance metric is key, and in this respect, a ‘Minkowski approach’ is proposed that enables the selection of an optimum distance metric for a given GWR model. This approach is evaluated within a simulation experiment consisting of three scenarios. The results are twofold: (1) a well-chosen distance metric can significantly improve the predictive accuracy of a GWR model; and (2) the approach allows a good approximation of the underlying ‘optimal distance metric’, which is considered useful when the ‘true’ distance metric is unknown. 相似文献
5.
An important issue of using the multiple-point (MP) statistical approach for reservoir modeling concerns the integration of
auxiliary constraints derived, for instance, from seismic information. There exist two methods in the literature for these
non-stationary MP simulations. One is based on an analytical approximation (the “τ-model”) of the conditional probabilities that involve auxiliary data. The degree of approximation with this method depends
on the parameter τ, whose inference is difficult in practice. The other method is based on the inference of these conditional probabilities
directly from training images. This method classifies the auxiliary data into a few classes. This classification is in general
arbitrary and therefore inconvenient in practice, especially in the case of continuous auxiliary constraints. In this paper,
we propose an alternative method for performing non-stationary MP simulations. This method accounts for the data support in
the modeling procedure and allows, in particular, continuous auxiliary data to be integrated into MP simulations. This method
avoids the major limitations of the previous methods, namely the use of an approximate analytical model and the reduction
of the auxiliary data into a limited number of classes. This method can be easily implemented in the existing MP simulation
codes. Numerical tests show good performance of this method both in reproducing the geometrical features of the training image
and in honouring the auxiliary data. 相似文献
6.
Andrew R. Bell Daniel E. Osgood Benjamin I. Cook Kevin J. Anchukaitis Geoffrey R. McCarney Arthur M. Greene Brendan M. Buckley Edward R. Cook 《Global Environmental Change》2013,23(4):774-781
Proxy-based climate reconstructions can extend instrumental records by hundreds of years, providing a wealth of climate information at high temporal resolution. To date, however, their usefulness for informing climate risk and variability in policy and social applications has been understudied. Here, we apply tree-ring based reconstructions of drought for the last 700 years in a climate index insurance framework to show that additional information from long climate reconstructions significantly improves our understanding of the underlying climate distributions and variability. We further show that this added information can be used to better characterize risk to insurance providers, in many cases providing meaningful reductions in long-term contract costs to farmers in stand-alone policies. The impact of uncertainty on insurance premiums can also be reduced when insurers diversify portfolios, and the availability of long-term climate information from tree rings across a broad geographic range provides an opportunity to characterize spatial correlation in climate risk across geographic regions. Our results are robust to the range of climate variability experienced over the last 400 years and in model simulations of the twenty-first century, even within the context of changing baselines due to low frequency variability and secular climate trends. These results demonstrate the utility of longer-term climate histories in index insurance applications. Furthermore, they make the case from a climate-variability perspective for the continued importance of such approaches to improving the instrumental climate record, even into a non-stationary climate future. 相似文献
7.
应用基于GEV(Generalized Extreme Value)分布的平稳/非平稳极值概率模型,拟合中国区域489站自建站至2013年极端最高、最低温度和日最大降水量的年极值序列,并导出极值的重现水平及其变率随重现期和时间变化的一般表达式。着重分析了气候极值的"常态"(重现期为2年)与"极端态"(重现期为50年)的变化趋势及其线性变率的空间格局。详细探讨了极值的常态与极端态变化趋势相反的原因以及可能的影响。结果表明,极端最高温度在东部季风区普遍适用平稳模型;在其他地区更适用非平稳模型,其常态和极端态都以增温为主。极端最低温度在全国范围内普遍适用非平稳模型,其常态和极端态也都以增温为主,但在东北局部地区极端态呈现与常态相反的降温趋势。日最大降水量则在全国范围内普遍适用平稳模型。当GEV分布的尺度参数随时间变化时,与极值的常态相比,极端态的变率范围要大得多,并可能导致两者的变率异号的情形;尤其是当气候极值的常态日趋平缓而极端态却日益极端时,可能导致更为剧烈的灾害性天气。 相似文献
8.
I. Cordery R. Mehrotra M. J. Nazemosadat 《Stochastic Environmental Research and Risk Assessment (SERRA)》2007,21(6):765-771
In modern hydrological practice large confidence is placed on modelling results that are used for planning and design. This
is especially the case where the modelling results have been carefully verified against independent data. An underlying assumption
of the calibration/verification process is that the whole data series is stationarity. Standard parametric and non-parametric
tests are available for examining the stationary of hydrologic time series but it has been shown here that these may be inadequate
for that purpose unless applied with care. Annual, seasonal, monthly and daily time series of precipitation and climate data
were examined considering parts of the series formed using sequential windows. Seven standard parametric and non-parametric
tests were applied to these relatively long series and while it was shown that some tests suggested that all series were stationary,
most series were shown to be non-stationary in more than one of the tests, some of them at very high levels of significance.
This apparently hidden non-stationarity could have very large effects on water resources modelling. These effects would have
considerable influence in calibration and verification of models and in simulation of long series of water resources characteristics
and could be especially important as the effects of climate change become more pervasive. 相似文献
9.
Is the wind wave frequency spectrum outdated 总被引：2，自引：0，他引：2
This paper presents a detailed examination of the practice of using the frequency spectrum to characterize wind waves. In particular, the issue of stationarity and Gaussian random process in connection with wind wave studies is addressed. We describe a test for nonstationarity based on the wavelet spectrum. When this test is applied to wind wave time series, the results significantly diverge from those expected for a Gaussian random process, thus casting critical doubts on the conventional concept of the wind wave frequency spectrum. 相似文献
10.
Non-stationary spatial covariance structure estimation in oversampled domains by cluster differences scaling with spatial constraints 总被引：2，自引：2，他引：0
J. F. Vera R. Macías J. M. Angulo 《Stochastic Environmental Research and Risk Assessment (SERRA)》2008,22(1):95-106
In the analysis of spatiotemporal processes underlying environmental studies, the estimation of the non-stationary spatial
covariance structure is a well known issue in which multidimensional scaling (MDS) provides an important methodological approach
(Sampson and Guttorp in J Am Stat Assoc 87:108–119, 1992). It is also well known that approximating dispersion by a non-metric
MDS procedure offers, in general, low precision when accurate differences in spatial dispersion are needed for interpolation
purposes, specially if a low dimensional configuration is employed besides a high number of stations in oversampled domains.
This paper presents a modification, consisting of including geographical spatial constraints, of Heiser and Groenen’s (Psychometrika
62:63–83, 1997) cluster differences scaling algorithm by which not the original stations but the cluster centres can be represented,
while the stations and clusters retain their spatial relationships. A decomposition of the sum of squared dissimilarities
into contributions from several sources of variation can be employed for an exploratory diagnosis of the model. Real data
are analyzed and differences between several cluster-MDS strategies are discussed. 相似文献
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