Application of copula modelling to the performance assessment of reconstructed watersheds

Nazemi, A.; Elshorbagy, Amin

doi:10.1007/s00477-011-0467-7

Cited by 48 publications

(20 citation statements)

References 70 publications

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“…Copulas have flexible structures in joining random variables (i.e., x i ) with different types of marginal distributions (i.e., u i ). This is a unique feature that has inspired several copula applications in hydrological studies [e.g., De Michele et al , ; Shiau , ; Li et al , ; Khedun et al , ; Madadgar and Moradkhani , ; Grimaldi et al , ; Salvadori et al , ; Salvadori et al , ; Nazemi and Elshorbagy , ]. Unlike copulas, other multivariate distributions such as Gaussian and Gamma distributions [ Kelly and Krzysztofowicz , ; Sharma , ; Yue et al , ] require all random variables coming from similar distributions.…”

Section: Methodsmentioning

confidence: 99%

Probabilistic estimates of drought impacts on agricultural production

Madadgar

AghaKouchak

Farahmand

et al. 2017

Geophysical Research Letters

169

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Increases in the severity and frequency of drought in a warming climate may negatively impact agricultural production and food security. Unlike previous studies that have estimated agricultural impacts of climate condition using single‐crop yield distributions, we develop a multivariate probabilistic model that uses projected climatic conditions (e.g., precipitation amount or soil moisture) throughout a growing season to estimate the probability distribution of crop yields. We demonstrate the model by an analysis of the historical period 1980–2012, including the Millennium Drought in Australia (2001–2009). We find that precipitation and soil moisture deficit in dry growing seasons reduced the average annual yield of the five largest crops in Australia (wheat, broad beans, canola, lupine, and barley) by 25–45% relative to the wet growing seasons. Our model can thus produce region‐ and crop‐specific agricultural sensitivities to climate conditions and variability. Probabilistic estimates of yield may help decision‐makers in government and business to quantitatively assess the vulnerability of agriculture to climate variations. We develop a multivariate probabilistic model that uses precipitation to estimate the probability distribution of crop yields. The proposed model shows how the probability distribution of crop yield changes in response to droughts. During Australia's Millennium Drought precipitation and soil moisture deficit reduced the average annual yield of the five largest crops.

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Section: Methodsmentioning

confidence: 99%

Probabilistic estimates of drought impacts on agricultural production

Madadgar

AghaKouchak

Farahmand

et al. 2017

Geophysical Research Letters

169

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“…In fact, traditional risk assessment methods that rely on only one variable may not accurately represent concurrent extremes and could lead to significant underestimation of the risk of extremes [ Gräler et al, ]. In recent years, multivariate copulas have been widely used for assessing the relationship between climate variables and extremes [ Serinaldi et al , ; Hao et al, ; Salvadori et al, ; AghaKouchak, ; Nazemi and Elshorbagy, ; Pan et al, ]. Multivariate copulas can be used for deriving probability occurrence and return period of dependent variables [ Grimaldi and Serinaldi, , ; Salvadori et al, ].…”

Section: Introductionmentioning

confidence: 99%

Global warming and changes in risk of concurrent climate extremes: Insights from the 2014 California drought

AghaKouchak

Cheng

Mazdiyasni

et al. 2014

Geophysical Research Letters

572

354

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Global warming and the associated rise in extreme temperatures substantially increase the chance of concurrent droughts and heat waves. The 2014 California drought is an archetype of an event characterized by not only low precipitation but also extreme high temperatures. From the raging wildfires, to record low storage levels and snowpack conditions, the impacts of this event can be felt throughout California. Wintertime water shortages worry decision-makers the most because it is the season to build up water supplies for the rest of the year. Here we show that the traditional univariate risk assessment methods based on precipitation condition may substantially underestimate the risk of extreme events such as the 2014 California drought because of ignoring the effects of temperature. We argue that a multivariate viewpoint is necessary for assessing risk of extreme events, especially in a warming climate. This study discusses a methodology for assessing the risk of concurrent extremes such as droughts and extreme temperatures.

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“…This is a valid approach, since it has been documented in the relevant literature, the latter techniques may cause severe under-estimation [24]. …”

Section: Methodsmentioning

confidence: 99%

Soil Landscape Pattern Changes in Response to Rural Anthropogenic Activity across Tiaoxi Watershed, China

et al. 2016

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Soil sealing (loss of soil resources due to extensive land covering for the purpose of house building, road construction etc.) and subsequent soil landscape pattern changes constitute typical environmental problems in many places worldwide. Previous studies concentrated on soil sealing in urbanized regions, whereas rural areas have not been given sufficient attention. Accordingly, this paper studies soil landscape pattern dynamics (i.e., landscape pattern changes in response to rural anthropogenic activities) in the Tiaoxi watershed (Zhejiang province, eastern China), in which surface sealing is by far the predominant component of human forcing with respect to environmental change. A novel approach of quantifying the impacts of rural anthropogenic activities on soil resources is presented. Specifically, quantitative relationships were derived between five soil landscape pattern metrics (patch density, edge density, shape index, Shannon’s diversity index and aggregation index) and three rural anthropogenic activity indicators (anthropogenic activity intensity, distance to towns, and distance to roads) at two landscape block scales (3 and 5 km) between 1985 and 2010. The results showed that the Tiaoxi watershed experienced extensive rural settlement expansion and high rates of soil sealing. Soil landscapes became more fragmented, more irregular, more isolated, and less diverse. Relationships between soil landscape pattern changes and rural anthropogenic activities differed with the scale (spatial and temporal) and variable considered. In particular, the anthropogenic activity intensity was found to be the most important indicator explaining social development intensity, whereas the other two proximity indicators had a significant impact at certain temporal interval. In combination with scale effects, spatial dependency (correlation) was shown to play a key role that should be carefully taken into consideration in any relevant environmental study. Overall, the findings of this work suggest that soil sealing can be a critical human forcing issue with considerable consequences deserving serious attention by the experts, the public and the government alike.

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Application of copula modelling to the performance assessment of reconstructed watersheds

Cited by 48 publications

References 70 publications

Probabilistic estimates of drought impacts on agricultural production

Probabilistic estimates of drought impacts on agricultural production

Global warming and changes in risk of concurrent climate extremes: Insights from the 2014 California drought

Soil Landscape Pattern Changes in Response to Rural Anthropogenic Activity across Tiaoxi Watershed, China

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