In less than two decades, UASs (unmanned aerial systems) have revolutionized the field of hydrology, bridging the gap between traditional satellite observations and ground-based measurements and allowing the limitations of manned aircraft to be overcome. With unparalleled spatial and temporal resolutions and product-tailoring possibilities, UAS are contributing to the acquisition of large volumes of data on water bodies, submerged parameters and their interactions in different hydrological contexts and in inaccessible or hazardous locations. This paper provides a comprehensive review of 122 works on the applications of UASs in surface water and groundwater research with a purpose-oriented approach. Concretely, the review addresses: (i) the current applications of UAS in surface and groundwater studies, (ii) the type of platforms and sensors mainly used in these tasks, (iii) types of products generated from UAS-borne data, (iv) the associated advantages and limitations, and (v) knowledge gaps and future prospects of UASs application in hydrology. The first aim of this review is to serve as a reference or introductory document for all researchers and water managers who are interested in embracing this novel technology. The second aim is to unify in a single document all the possibilities, potential approaches and results obtained by different authors through the implementation of UASs.
The uncertainty in traditional hydrological modeling is a challenge that has not yet been overcome. This research aimed to provide a new method called the hybrid causal–hydrological (HCH) method, which consists of the combination of traditional rainfall–runoff models with novel hydrological approaches based on artificial intelligence, called Bayesian causal modeling (BCM). This was implemented by building nine causal models for three sub-basins of the Barbate River Basin (SW Spain). The models were populated by gauging (observing) short runoff series and from long and short hydrological runoff series obtained from the Témez rainfall–runoff model (T-RRM). To enrich the data, all series were synthetically replicated using an ARMA model. Regarding the results, on the one hand differences in the dependence intensities between the long and short series were displayed in the dependence mitigation graphs (DMGs), which were attributable to the insufficient amount of data available from the hydrological records and to climate change processes. The similarities in the temporal dependence propagation (basin memory) and in the symmetry of DMGs validate the reliability of the hybrid methodology, as well as the results generated in this study. Consequently, water planning and management can be substantially improved with this approach.
Reversing the chemical and quantitative impacts derived from human activity on aquifers demands a multidisciplinary approach. This requires, firstly, to update the hydrogeological knowledge of the groundwater systems, which is pivotal for the sustainable use of this resource, and secondly, to integrate the social, economic and administrative reality of the region. The present work focuses on the Benalup aquifer, whose exploitation plays a major role in the economy of the area, based mainly on irrigated agriculture. This activity has had negative consequences for the aquifer in quantitative and chemical terms, leading to its declaration as in poor condition. The study presented here shows the results obtained from the application of hydrogeological techniques, remote sensing and citizen participation tools, which have allowed us to deepen and improve the current knowledge of the system’s hydrogeological, geometric, administrative and social aspects. Additionally, the lessons learned from this case study are analyzed. The deficiencies detected are discussed, and alternatives aimed at the sustainable use of groundwater are proposed, such as the possibility of a joint use of surface and groundwater resources, the creation of a Water User Association responsible for the management of groundwater and the need for greater efforts aimed at educating and raising awareness of water conservation among citizens.
The standardized precipitation index (SPI) provides reliable estimations about the intensity, magnitude and spatial extent of droughts in a variety of time scales based on long-term precipitation series. In this work, we assess the evolution of monthly precipitation in the Barbate River basin (S. Iberian Peninsula) between 1910/11 and 2017/18 through the generation of a representative precipitation series for the 108-year period and the subsequent application of the SPI. This extensive series was obtained after processing all the precipitation data (67 stations) available within and nearby the basin and subsequent complex gap-filling stages. The SPI identified 26 periods of drought, 12 of them severe and 6 extreme, with return periods of 9 and 18 years, respectively. Complementary analysis evidenced changes in precipitation cyclicity, with periodicities of 5 and 7–8 years during the first and second half of the study period, respectively. Additionally, the amplitude of pluviometric oscillations increased during the second half of the period, and extreme events were more frequent. While the decade 1940–1950 was very dry, with precipitation 11% below the basin’s average, 1960–1970 was very humid, with precipitation 23% above average. Contrary to the results of climate change projections specific to this area, a clear downward trend in precipitation is not detected.
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