A generalized framework for deriving nonparametric standardized drought indicators

Farahmand, Alireza; AghaKouchak, Amir

doi:10.1016/j.advwatres.2014.11.012

Cited by 311 publications

(209 citation statements)

References 48 publications

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“…The latter is independent on assumptions about the distribution of the index and shows superior or similar results also for shorter time series (up to 100 years). These findings agree with Farahmand and AghaKouchak (2015) who used also paramedic approaches in their drought indices.…”

Section: Impact Of the Normalization Proceduressupporting

confidence: 81%

“…The latter is shown to be deficient in some regions, in particular in arid regions where the index values can be hardly fit to a gamma distribution and, thus, such fitting shall be carefully evaluated at each location. The quantile mapping is similar to the non-parametric approach used by Farahmand and AghaKouchak (2015). Overall, the framework combines and extends existing approaches for the memory and normalization step in a new way.…”

Section: Discussionmentioning

confidence: 98%

“…As for the PDSI, the SPI depends on various assumptions, in particular the fit of the precipitation data to a given probability density distribution (PDF) used within the procedure (Lloyd-Hughes and Saunders, 2002;Mishra and Singh, 2010;Wu et al, 2007). Recently, Farahmand and AghaKouchak (2015) suggested non-parametric normalization procedure for the SPI, which avoids this conceptual drawback. Another caveat of the SPI is that it is based only on precipitation and thus ignores other processes like evaporation, temperature, run-off or soilwater content, which are known to affect the water balance but are difficult to measure (Vicente-Serrano et al, 2010).…”

Section: C R a I B L E E T A Lmentioning

confidence: 99%

See 2 more Smart Citations

Drought indices revisited – improving and testing of drought indices in a simulation of the last two millennia for Europe

Raible¹,

Bärenbold²,

Gómez-Navarro

2017

Tellus A: Dynamic Meteorology and Oceanography

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Over the past decades, different drought indices have been suggested in the literature. This study tackles the problem of how to characterize droughts by defining a framework and proposing a generalized family of drought indices that is flexible regarding the use of different hydrological fluxes in the water balance. The sensitivity of various indices and its skill to represent drought conditions is evaluated using a regional model simulation for Europe spanning the last two millennia as test bed. The framework combines an exponentially damped memory with a normalization method based on quantile mapping. Both approaches are more robust and physically meaningful compared to the existing methods used to define drought indices. Still, the framework is flexible with respect to hydrological fluxes used for the water balance, enabling users to adapt the index formulation to the data availability of different locations. Based on it, indices using different hydrological fluxes in the water balance are compared with each other showing that a drought index considering only precipitation in the water balance is sufficient for western to central Europe. In the Mediterranean, temperature effects via evapotranspiration rather than potential evapotranspiration, need to be considered to produce meaningful indices representative of water deficit. In addition, our results indicate that in north-eastern Europe and Scandinavia, snow and run-off effects need to be considered simultaneously in the index definition to obtain accurate results.

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Section: Impact Of the Normalization Proceduressupporting

confidence: 81%

Section: Discussionmentioning

confidence: 98%

Section: C R a I B L E E T A Lmentioning

confidence: 99%

See 1 more Smart Citation

Drought indices revisited – improving and testing of drought indices in a simulation of the last two millennia for Europe

Raible¹,

Bärenbold²,

Gómez-Navarro

2017

Tellus A: Dynamic Meteorology and Oceanography

View full text Add to dashboard Cite

show abstract

“…For a specific distribution function, its parameters need to be estimated based on the data fed and tend to be impacted by the length of the data record period. In light of these observations, a generalized framework in deriving nonparametric standardized indices entitled Standardized Drought Analysis Toolbox (SDAT) is developed [57]. This approach uses the empirical Gringorten plotting position in deriving the marginal distribution of the target variable.…”

Section: Potential Predictorsmentioning

confidence: 99%

“…This method requires no assumption on a parametric distribution function and thus no parameter estimation. For a detailed description on the SDAT, the readers are referred to [57]. This study adopts SDAT in calculating nonparametric standardized indices for precipitation, runoff, and snow at designated time scales (e.g., October-March, April-June, April-July, 1 April).…”

Section: Potential Predictorsmentioning

confidence: 99%

Predictability of Seasonal Streamflow in a Changing Climate in the Sierra Nevada

He¹,

Russo²,

Anderson³

2016

Climate

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Remote sensing of drought: Progress, challenges and opportunities

AghaKouchak

Farahmand

Melton

et al. 2015

Reviews of Geophysics

669

372

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This review surveys current and emerging drought monitoring approaches using satellite remote sensing observations from climatological and ecosystem perspectives. We argue that satellite observations not currently used for operational drought monitoring, such as near-surface air relative humidity data from the Atmospheric Infrared Sounder mission, provide opportunities to improve early drought warning. Current and future satellite missions offer opportunities to develop composite and multi-indicator drought models. While there are immense opportunities, there are major challenges including data continuity, unquantified uncertainty, sensor changes, and community acceptability. One of the major limitations of many of the currently available satellite observations is their short length of record. A number of relevant satellite missions and sensors (e.g., the Gravity Recovery and Climate Experiment) provide only a decade of data, which may not be sufficient to study droughts from a climate perspective. However, they still provide valuable information about relevant hydrologic and ecological processes linked to this natural hazard. Therefore, there is a need for models and algorithms that combine multiple data sets and/or assimilate satellite observations into model simulations to generate long-term climate data records. Finally, the study identifies a major gap in indicators for describing drought impacts on the carbon and nitrogen cycle, which are fundamental to assessing drought impacts on ecosystems.

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A generalized framework for deriving nonparametric standardized drought indicators

Cited by 311 publications

References 48 publications

Drought indices revisited – improving and testing of drought indices in a simulation of the last two millennia for Europe

Drought indices revisited – improving and testing of drought indices in a simulation of the last two millennia for Europe

Predictability of Seasonal Streamflow in a Changing Climate in the Sierra Nevada

Remote sensing of drought: Progress, challenges and opportunities

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