A drought index accounting for snow

Staudinger, Maria; Stahl, Kerstin; Seibert, Jan

doi:10.1002/2013wr015143

Cited by 97 publications

(84 citation statements)

References 39 publications

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“…More comprehensive indexes can also include snowpack extent, reservoir storage, and groundwater level (Shafer and Dezman, 1982;Keyantash and Dracup, 2004;Staudinger et al, 2014). This drought takes place after a prolonged time of low precipitation and deficient soil moisture and its effects are witnessed in the long-term (6-12 months; Zargar et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Automatic design of basin-specific drought indexes for highly regulated water systems

Zaniolo

Giuliani

Castelletti

et al. 2018

Hydrol. Earth Syst. Sci.

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Abstract. Socio-economic costs of drought are progressively increasing worldwide due to undergoing alterations of hydro-meteorological regimes induced by climate change. Although drought management is largely studied in the literature, traditional drought indexes often fail at detecting critical events in highly regulated systems, where natural water availability is conditioned by the operation of water infrastructures such as dams, diversions, and pumping wells. Here, ad hoc index formulations are usually adopted based on empirical combinations of several, supposed-to-be significant, hydro-meteorological variables. These customized formulations, however, while effective in the design basin, can hardly be generalized and transferred to different contexts. In this study, we contribute FRIDA (FRamework for Index-based Drought Analysis), a novel framework for the automatic design of basin-customized drought indexes. In contrast to ad hoc empirical approaches, FRIDA is fully automated, generalizable, and portable across different basins. FRIDA builds an index representing a surrogate of the drought conditions of the basin, computed by combining all the relevant available information about the water circulating in the system identified by means of a feature extraction algorithm. We used the Wrapper for Quasi-Equally Informative Subset Selection (W-QEISS), which features a multi-objective evolutionary algorithm to find Pareto-efficient subsets of variables by maximizing the wrapper accuracy, minimizing the number of selected variables, and optimizing relevance and redundancy of the subset. The preferred variable subset is selected among the efficient solutions and used to formulate the final index according to alternative model structures. We apply FRIDA to the case study of the Jucar river basin (Spain), a drought-prone and highly regulated Mediterranean water resource system, where an advanced drought management plan relying on the formulation of an ad hoc "state index" is used for triggering drought management measures. The state index was constructed empirically with a trial-and-error process begun in the 1980s and finalized in 2007, guided by the experts from the Confederación Hidrográfica del Júcar (CHJ). Our results show that the automated variable selection outcomes align with CHJ's 25-year-long empirical refinement. In addition, the resultant FRIDA index outperforms the official State Index in terms of accuracy in reproducing the target variable and cardinality of the selected inputs set.

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Section: Introductionmentioning

confidence: 99%

Automatic design of basin-specific drought indexes for highly regulated water systems

Zaniolo

Giuliani

Castelletti

et al. 2018

Hydrol. Earth Syst. Sci.

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“…Droughts are especially important in regions where economic activities are highly dependent on water resources [4], such as in mountain regions which traditionally provide water resources and services to local communities and lowland residents [5]. For example, the Andean basins, which have been identified as excellent providers of water for multiple uses [6,7], could be affected by droughts and climate change, putting the water supply at risk and augmenting the vulnerability of the basin's water resources systems and eco-services [8][9][10][11]. The increasing tendency of water shortage is a concern of water managers [11], wrestling with questions such as which drought indicator [12] and threshold of the indicators should be used to qualify the drought status.…”

Section: Introductionmentioning

confidence: 99%

“…The increasing tendency of water shortage is a concern of water managers [11], wrestling with questions such as which drought indicator [12] and threshold of the indicators should be used to qualify the drought status. In fact, drought characterization requires indicators that are generally applicable, but specific enough to capture the type of drought relevant to the region and the variables of interest [10]. Droughts may occur at different moments in the hydrological year, with the consequence that hydrologic variables might experience quite different levels of drought, complicating the overall assessment of the drought status [13].…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Forecasting of Drought Events Using Markov Chain- and Bayesian Network-Based Models: A Case Study of an Andean Regulated River Basin

Avilés

Célleri

Solera

et al. 2016

Water

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Abstract:The scarcity of water resources in mountain areas can distort normal water application patterns with among other effects, a negative impact on water supply and river ecosystems. Knowing the probability of droughts might help to optimize a priori the planning and management of the water resources in general and of the Andean watersheds in particular. This study compares Markov chain-(MC) and Bayesian network-(BN) based models in drought forecasting using a recently developed drought index with respect to their capability to characterize different drought severity states. The copula functions were used to solve the BNs and the ranked probability skill score (RPSS) to evaluate the performance of the models. Monthly rainfall and streamflow data of the Chulco River basin, located in Southern Ecuador, were used to assess the performance of both approaches. Global evaluation results revealed that the MC-based models predict better wet and dry periods, and BN-based models generate slightly more accurately forecasts of the most severe droughts. However, evaluation of monthly results reveals that, for each month of the hydrological year, either the MC-or BN-based model provides better forecasts. The presented approach could be of assistance to water managers to ensure that timely decision-making on drought response is undertaken.

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“…In such contexts, an accurate characterization of snow availability and its evolution in time can be extremely valuable for a variety of operational purposes, from avalanche prediction (e.g., Perona et al, 2012;Schweizer et al, 2009), water-systems operations through medium to longterm streamflow forecast (e.g., Wood and Lettenmaier, 2006;Anghileri et al, 2016), or drought risk management (e.g., Staudinger et al, 2014). The projected temperature increase induced by climate change, with consequent reductions of large volumes of snowpacks and acceleration of the water cycle in many mountainous areas, will further amplify the importance of better understanding snow dynamics (Barnett et al, 2005;Kunkel et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Using crowdsourced web content for informing water systems operations in snow-dominated catchments

Giuliani

Castelletti

Fedorov

et al. 2016

Hydrol. Earth Syst. Sci.

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Abstract. Snow is a key component of the hydrologic cycle in many regions of the world. Despite recent advances in environmental monitoring that are making a wide range of data available, continuous snow monitoring systems that can collect data at high spatial and temporal resolution are not well established yet, especially in inaccessible high-latitude or mountainous regions. The unprecedented availability of user-generated data on the web is opening new opportunities for enhancing real-time monitoring and modeling of environmental systems based on data that are public, low-cost, and spatiotemporally dense. In this paper, we contribute a novel crowdsourcing procedure for extracting snow-related information from public web images, either produced by users or generated by touristic webcams. A fully automated process fetches mountain images from multiple sources, identifies the peaks present therein, and estimates virtual snow indexes representing a proxy of the snow-covered area. Our procedure has the potential for complementing traditional snow-related information, minimizing costs and efforts for obtaining the virtual snow indexes and, at the same time, maximizing the portability of the procedure to several locations where such public images are available. The operational value of the obtained virtual snow indexes is assessed for a real-world water-management problem, the regulation of Lake Como, where we use these indexes for informing the daily operations of the lake. Numerical results show that such information is effective in extending the anticipation capacity of the lake operations, ultimately improving the system performance.

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A drought index accounting for snow

Cited by 97 publications

References 39 publications

Automatic design of basin-specific drought indexes for highly regulated water systems

Automatic design of basin-specific drought indexes for highly regulated water systems

Probabilistic Forecasting of Drought Events Using Markov Chain- and Bayesian Network-Based Models: A Case Study of an Andean Regulated River Basin

Using crowdsourced web content for informing water systems operations in snow-dominated catchments

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