Evaluation of the drought management measures in a semi-arid agricultural watershed

In the context of proactive drought management plans, a key element consists of analyzing, selecting and allocating measures aimed at increasing resistance to droughts and reducing its potential impacts on the society, environment and economy. Currently, these measures, known as preventive drought management measures (Fatulov&#225; et al., 2015), are embedded within measures for flood management, catchment management plans, rural development plans, among others. This situation raises two issues. Firstly, information about potential preventive drought management measures (PDMM) is commonly fragmented and it is not a trivial task find or select measures that could be implemented as PDDM. Secondly, even though the same measure can be implemented from different management perspectives (Flood management, land degradation management, catchment management, rural development plans,) its applicability, advantages and limitations, may change according to the management perspective.Considering the above, this study attempts to provide a review of PDMM that includes: measure description, applicability, limitations, mathematical representation (For further implementation in modelling systems) and classification, from a drought management perspective. It is worth to mention that this study is focused on hydrologically based measures, applicable for agricultural and hydrological drought management.The research methodology is divided in three phases. The first phase consists of identifying drivers that trigger and/or enhance agricultural and hydrological droughts. This analysis is carried out from a hydrological angle, where land surface processes and human activities are potential drivers agricultural and hydrological droughts (Van Loon et al., 2016). The second phase examines an extensive list of technical documents, books, books sections, journal articles and case studies in order to identify those measures that could manage or mitigate the impact of potential drivers of agricultural and hydrological droughts. In this phase, PDMM are described in terms of applicability, advantages, limitations and mathematical representation for further implementation in modelling systems. Based on the analysis of the PDMM, the third phase of the study focusses on their classification, into three categories: nature-based solutions, grey infrastructure and changes in human water consumption

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

Hydrology and Earth System Sciences ◽

10.5194/hess-22-2409-2018 ◽

2018 ◽

Vol 22 (4) ◽

pp. 2409-2424 ◽

Cited By ~ 6

Author(s):

Marta Zaniolo ◽

Matteo Giuliani ◽

Andrea Francesco Castelletti ◽

Manuel Pulido-Velazquez

Keyword(s):

Ad Hoc ◽

Management Plan ◽

Efficient Solutions ◽

Automatic Design ◽

Drought Management ◽

Water Resource System ◽

Management Measures ◽

Pumping Wells ◽

State Index ◽

Available Information

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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