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  • 1
    In: Hydrology and Earth System Sciences, Copernicus GmbH, Vol. 21, No. 8 ( 2017-08-23), p. 4169-4193
    Abstract: Abstract. Over recent decades, the global population has been rapidly increasing and human activities have altered terrestrial water fluxes to an unprecedented extent. The phenomenal growth of the human footprint has significantly modified hydrological processes in various ways (e.g. irrigation, artificial dams, and water diversion) and at various scales (from a watershed to the globe). During the early 1990s, awareness of the potential for increased water scarcity led to the first detailed global water resource assessments. Shortly thereafter, in order to analyse the human perturbation on terrestrial water resources, the first generation of large-scale hydrological models (LHMs) was produced. However, at this early stage few models considered the interaction between terrestrial water fluxes and human activities, including water use and reservoir regulation, and even fewer models distinguished water use from surface water and groundwater resources. Since the early 2000s, a growing number of LHMs have incorporated human impacts on the hydrological cycle, yet the representation of human activities in hydrological models remains challenging. In this paper we provide a synthesis of progress in the development and application of human impact modelling in LHMs. We highlight a number of key challenges and discuss possible improvements in order to better represent the human–water interface in hydrological models.
    Type of Medium: Online Resource
    ISSN: 1607-7938
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2017
    detail.hit.zdb_id: 2100610-6
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  • 2
    In: Hydrology and Earth System Sciences, Copernicus GmbH, Vol. 20, No. 9 ( 2016-09-08), p. 3631-3650
    Abstract: Abstract. In the current human-modified world, or Anthropocene, the state of water stores and fluxes has become dependent on human as well as natural processes. Water deficits (or droughts) are the result of a complex interaction between meteorological anomalies, land surface processes, and human inflows, outflows, and storage changes. Our current inability to adequately analyse and manage drought in many places points to gaps in our understanding and to inadequate data and tools. The Anthropocene requires a new framework for drought definitions and research. Drought definitions need to be revisited to explicitly include human processes driving and modifying soil moisture drought and hydrological drought development. We give recommendations for robust drought definitions to clarify timescales of drought and prevent confusion with related terms such as water scarcity and overexploitation. Additionally, our understanding and analysis of drought need to move from single driver to multiple drivers and from uni-directional to multi-directional. We identify research gaps and propose analysis approaches on (1) drivers, (2) modifiers, (3) impacts, (4) feedbacks, and (5) changing the baseline of drought in the Anthropocene. The most pressing research questions are related to the attribution of drought to its causes, to linking drought impacts to drought characteristics, and to societal adaptation and responses to drought. Example questions include (i) What are the dominant drivers of drought in different parts of the world? (ii) How do human modifications of drought enhance or alleviate drought severity? (iii) How do impacts of drought depend on the physical characteristics of drought vs. the vulnerability of people or the environment? (iv) To what extent are physical and human drought processes coupled, and can feedback loops be identified and altered to lessen or mitigate drought? (v) How should we adapt our drought analysis to accommodate changes in the normal situation (i.e. what are considered normal or reference conditions) over time? Answering these questions requires exploration of qualitative and quantitative data as well as mixed modelling approaches. The challenges related to drought research and management in the Anthropocene are not unique to drought, but do require urgent attention. We give recommendations drawn from the fields of flood research, ecology, water management, and water resources studies. The framework presented here provides a holistic view on drought in the Anthropocene, which will help improve management strategies for mitigating the severity and reducing the impacts of droughts in future.
    Type of Medium: Online Resource
    ISSN: 1607-7938
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2016
    detail.hit.zdb_id: 2100610-6
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  • 3
    In: Nature Geoscience, Springer Science and Business Media LLC, Vol. 9, No. 2 ( 2016-2), p. 89-91
    Type of Medium: Online Resource
    ISSN: 1752-0894 , 1752-0908
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2016
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    detail.hit.zdb_id: 2405323-5
    SSG: 16,13
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  • 4
    In: Environmental Research Letters, IOP Publishing, Vol. 17, No. 4 ( 2022-04-01), p. 044059-
    Abstract: Human activities both aggravate and alleviate streamflow drought. Here we show that aggravation is dominant in contrasting cases around the world analysed with a consistent methodology. Our 28 cases included different combinations of human-water interactions. We found that water abstraction aggravated all drought characteristics, with increases of 20%–305% in total time in drought found across the case studies, and increases in total deficit of up to almost 3000%. Water transfers reduced drought time and deficit by up to 97%. In cases with both abstraction and water transfers into the catchment or augmenting streamflow from groundwater, the water inputs could not compensate for the aggravation of droughts due to abstraction and only shift the effects in space or time. Reservoir releases for downstream water use alleviated droughts in the dry season, but also led to deficits in the wet season by changing flow seasonality. This led to minor changes in average drought duration (−26 to +38%) and moderate changes in average drought deficit (−86 to +369%). Land use showed a smaller impact on streamflow drought, also with both increases and decreases observed (−48 to +98%). Sewage return flows and pipe leakage possibly counteracted the effects of increased imperviousness in urban areas; however, untangling the effects of land use change on streamflow drought is challenging. This synthesis of diverse global cases highlights the complexity of the human influence on streamflow drought and the added value of empirical comparative studies. Results indicate both intended and unintended consequences of water management and infrastructure on downstream society and ecosystems.
    Type of Medium: Online Resource
    ISSN: 1748-9326
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2022
    detail.hit.zdb_id: 2255379-4
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  • 5
    In: Natural Hazards and Earth System Sciences, Copernicus GmbH, Vol. 16, No. 3 ( 2016-03-21), p. 801-819
    Abstract: Abstract. Drought is a natural hazard that can cause a wide range of impacts affecting the environment, society, and the economy. Providing an impact assessment and reducing vulnerability to these impacts for regions beyond the local scale, spanning political and sectoral boundaries, requires systematic and detailed data regarding impacts. This study presents an assessment of the diversity of drought impacts across Europe based on the European Drought Impact report Inventory (EDII), a unique research database that has collected close to 5000 impact reports from 33 European countries. The reported drought impacts were classified into major impact categories, each of which had a number of subtypes. The distribution of these categories and types was then analyzed over time, by country, across Europe and for particular drought events. The results show that impacts on agriculture and public water supply dominate the collection of drought impact reports for most countries and for all major drought events since the 1970s, while the number and relative fractions of reported impacts in other sectors can vary regionally and from event to event. The analysis also shows that reported impacts have increased over time as more media and website information has become available and environmental awareness has increased. Even though the distribution of impact categories is relatively consistent across Europe, the details of the reports show some differences. They confirm severe impacts in southern regions (particularly on agriculture and public water supply) and sector-specific impacts in central and northern regions (e.g., on forestry or energy production). The protocol developed thus enabled a new and more comprehensive view on drought impacts across Europe. Related studies have already developed statistical techniques to evaluate the link between drought indices and the categorized impacts using EDII data. The EDII is a living database and is a promising source for further research on drought impacts, vulnerabilities, and risks across Europe. A key result is the extensive variety of impacts found across Europe and its documentation. This insight can therefore inform drought policy planning at national to international levels.
    Type of Medium: Online Resource
    ISSN: 1684-9981
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2016
    detail.hit.zdb_id: 2069216-X
    detail.hit.zdb_id: 2064587-9
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  • 6
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2019
    In:  Nature Communications Vol. 10, No. 1 ( 2019-10-30)
    In: Nature Communications, Springer Science and Business Media LLC, Vol. 10, No. 1 ( 2019-10-30)
    Abstract: Present-day drought early warning systems provide the end-users information on the ongoing and forecasted drought hazard (e.g. river flow deficit). However, information on the forecasted drought impacts, which is a prerequisite for drought management, is still missing. Here we present the first study assessing the feasibility of forecasting drought impacts, using machine-learning to relate forecasted hydro-meteorological drought indices to reported drought impacts. Results show that models, which were built with more than 50 months of reported drought impacts, are able to forecast drought impacts a few months ahead. This study highlights the importance of drought impact databases for developing drought impact functions. Our findings recommend that institutions that provide operational drought early warnings should not only forecast drought hazard, but also impacts after developing an impact database.
    Type of Medium: Online Resource
    ISSN: 2041-1723
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
    detail.hit.zdb_id: 2553671-0
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  • 7
    Online Resource
    Online Resource
    Copernicus GmbH ; 2020
    In:  Natural Hazards and Earth System Sciences Vol. 20, No. 6 ( 2020-06-04), p. 1595-1608
    In: Natural Hazards and Earth System Sciences, Copernicus GmbH, Vol. 20, No. 6 ( 2020-06-04), p. 1595-1608
    Abstract: Abstract. Forecasting of drought impacts is still lacking in drought early-warning systems (DEWSs), which presently do not go beyond hazard forecasting. Therefore, we developed drought impact functions using machine learning approaches (logistic regression and random forest) to predict drought impacts with lead times up to 7 months ahead. The observed and forecasted hydrometeorological drought hazards – such as the standardized precipitation index (SPI), standardized precipitation evaporation index (SPEI), and standardized runoff index (SRI) – were obtained from the The EU-funded Enhancing Emergency Management and Response to Extreme Weather and Climate Events (ANYWHERE) DEWS. Reported drought impact data, taken from the European Drought Impact Report Inventory (EDII), were used to develop and validate drought impact functions. The skill of the drought impact functions in forecasting drought impacts was evaluated using the Brier skill score and relative operating characteristic metrics for five cases representing different spatial aggregation and lumping of impacted sectors. Results show that hydrological drought hazard represented by SRI has higher skill than meteorological drought represented by SPI and SPEI. For German regions, impact functions developed using random forests indicate a higher discriminative ability to forecast drought impacts than logistic regression. Moreover, skill is higher for cases with higher spatial resolution and less lumped impacted sectors (cases 4 and 5), with considerable skill up to 3–4 months ahead. The forecasting skill of drought impacts using machine learning greatly depends on the availability of impact data. This study demonstrates that the drought impact functions could not be developed for certain regions and impacted sectors, owing to the lack of reported impacts.
    Type of Medium: Online Resource
    ISSN: 1684-9981
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2020
    detail.hit.zdb_id: 2069216-X
    detail.hit.zdb_id: 2064587-9
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  • 8
    Online Resource
    Online Resource
    Copernicus GmbH ; 2019
    In:  Hydrology and Earth System Sciences Vol. 23, No. 3 ( 2019-03-26), p. 1725-1739
    In: Hydrology and Earth System Sciences, Copernicus GmbH, Vol. 23, No. 3 ( 2019-03-26), p. 1725-1739
    Abstract: Abstract. Quantifying the influence of human activities, such as reservoir building, water abstraction, and land use change, on hydrology is crucial for sustainable future water management, especially during drought. Model-based methods are very time-consuming to set up and require a good understanding of human processes and time series of water abstraction, land use change, and water infrastructure and management, which often are not available. Therefore, observation-based methods are being developed that give an indication of the direction and magnitude of the human influence on hydrological drought based on limited data. We suggest adding to those methods a “paired-catchment” approach, based on the classic hydrology approach that was developed in the 1920s for assessing the impact of land cover treatment on water quantity and quality. When applying the paired-catchment approach to long-term pre-existing human influences trying to detect an influence on extreme events such as droughts, a good catchment selection is crucial. The disturbed catchment needs to be paired with a catchment that is similar in all aspects except for the human activity under study, in that way isolating the effect of that specific activity. In this paper, we present a framework for selecting suitable paired catchments for the study of the human influence on hydrological drought. Essential elements in this framework are the availability of qualitative information on the human activity under study (type, timing, and magnitude), and the similarity of climate, geology, and other human influences between the catchments. We show the application of the framework on two contrasting case studies, one impacted by groundwater abstraction and one with a water transfer from another region. Applying the paired-catchment approach showed how the groundwater abstraction aggravated streamflow drought by more than 200 % for some metrics (total drought duration and total drought deficit) and the water transfer alleviated droughts with 25 % to 80 %, dependent on the metric. Benefits of the paired-catchment approach are that climate variability between pre- and post-disturbance periods does not have to be considered as the same time periods are used for analysis, and that it avoids assumptions considered when partly or fully relying on simulation modelling. Limitations of the approach are that finding a suitable catchment pair can be very challenging, often no pre-disturbance records are available to establish the natural difference between the catchments, and long time series of hydrological data are needed to robustly detect the effect of the human activities on hydrological drought. We suggest that the approach can be used for a first estimate of the human influence on hydrological drought, to steer campaigns to collect more data, and to complement and improve other existing methods (e.g. model-based or large-sample approaches).
    Type of Medium: Online Resource
    ISSN: 1607-7938
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2019
    detail.hit.zdb_id: 2100610-6
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  • 9
    In: Hydrological Sciences Journal, Informa UK Limited, Vol. 65, No. 3 ( 2020-02-17), p. 491-494
    Type of Medium: Online Resource
    ISSN: 0262-6667 , 2150-3435
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2020
    detail.hit.zdb_id: 2180448-5
    SSG: 14
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  • 10
    Online Resource
    Online Resource
    Informa UK Limited ; 2018
    In:  Hydrological Sciences Journal Vol. 63, No. 7 ( 2018-05-19), p. 979-990
    In: Hydrological Sciences Journal, Informa UK Limited, Vol. 63, No. 7 ( 2018-05-19), p. 979-990
    Type of Medium: Online Resource
    ISSN: 0262-6667 , 2150-3435
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2018
    detail.hit.zdb_id: 2180448-5
    SSG: 14
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