•Human water abstractions and irrigation impact future hydrological drought.•Projections for future hydrological drought should include human influences.•The impact of human water use on the future ...low-flow regime is significant.
Climate change will very likely impact future hydrological drought characteristics across the world. Here, we quantify the impact of human water use including reservoir regulation and climate change on future low flows and associated hydrological drought characteristics on a global scale. The global hydrological and water resources model PCR-GLOBWB is used to simulate daily discharge globally at 0.5° resolution for 1971–2099. The model was forced with the latest CMIP5 climate projections taken from five General Circulation Models (GCMs) and four emission scenarios (RCPs), under the framework of the Inter-Sectoral Impact Model Intercomparison Project.
A natural or pristine scenario has been used to calculate the impact of the changing climate on hydrological drought and has been compared to a scenario with human influences. In the latter scenario reservoir operations and human water use are included in the simulations of discharge for the 21st century. The impact of humans on the low flow regime and hydrological drought characteristics has been studied at a catchment scale.
Results show a significant impact of climate change and human water use in large parts of Asia, Middle East and the Mediterranean, where the relative contribution of humans on the changed drought severity can be close to 100%. The differences between Representative Concentration Pathways are small indicating that human water use is proportional to the changes in the climate. Reservoirs tend to reduce the impact of drought by water retention in the wet season, which in turn will lead to increased water availability in the dry season, especially for large regions in Europe and North America. The impact of climate change varies throughout the season for parts of Europe and North-America, while in other regions (e.g. North-Africa, Middle East and Mediterranean), the impact is not influenced by seasonal changes.
This study illustrates that the impact of human water use and reservoirs is nontrivial and can vary substantially per region and per season. Therefore, human influences should be included in projections of future drought characteristics, considering their large impact on the changing drought conditions.
Water scarcity is rapidly increasing in many regions. In a novel, multi-model assessment, we examine how human interventions (HI: land use and land cover change, man-made reservoirs and human water ...use) affected monthly river water availability and water scarcity over the period 1971 - 2010. Here we show that HI drastically change the critical dimensions of water scarcity, aggravating water scarcity for 8.8%(7.4 - 16.5 %) ) of the global population but alleviating it for another 8.3 % (6.4 -15.8 %). Positive impacts of HI mostly occur upstream, whereas HI aggravate water scarcity downstream; HI cause water scarcity to travel downstream. Attribution of water scarcity changes to HI components is complex and varies among the hydrological models. Seasonal variation in impacts and dominant HI components is also substantial. A thorough consideration of the spatially and temporally varying interactions among HI components and of uncertainties is therefore crucial for the success of water scarcity adaptation by HI.
The aridity Index under global warming Greve, P; Roderick, M L; Ukkola, A M ...
Environmental research letters,
12/2019, Letnik:
14, Številka:
12
Journal Article
Recenzirano
Odprti dostop
Aridity is a complex concept that ideally requires a comprehensive assessment of hydroclimatological and hydroecological variables to fully understand anticipated changes. A widely used (offline) ...impact model to assess projected changes in aridity is the aridity index (AI) (defined as the ratio of potential evaporation to precipitation), summarizing the aridity concept into a single number. Based on the AI, it was shown that aridity will generally increase under conditions of increased CO2 and associated global warming. However, assessing the same climate model output directly suggests a more nuanced response of aridity to global warming, raising the question if the AI provides a good representation of the complex nature of anticipated aridity changes. By systematically comparing projections of the AI against projections for various hydroclimatological and ecohydrological variables, we show that the AI generally provides a rather poor proxy for projected aridity conditions. Direct climate model output is shown to contradict signals of increasing aridity obtained from the AI in at least half of the global land area with robust change. We further show that part of this discrepancy can be related to the parameterization of potential evaporation. Especially the most commonly used potential evaporation model likely leads to an overestimation of future aridity due to incorrect assumptions under increasing atmospheric CO2. Our results show that AI-based approaches do not correctly communicate changes projected by the fully coupled climate models. The solution is to directly analyse the model outputs rather than use a separate offline impact model. We thus urge for a direct and joint assessment of climate model output when assessing future aridity changes rather than using simple index-based impact models that use climate model output as input and are potentially subject to significant biases.
Global hydrological models (GHMs) have become an established tool to simulate water resources worldwide. Most of the GHMs are however uncalibrated and typically use a set of basic hydrological ...parameters, that could potentially lead to unrealistic projections of the terrestrial water cycle. The calibration of hydrological models is usually performed by using and comparing modeled to observed discharge. Accurate station data and reliable time series data of discharge are, however, often not available for many parts of the world and classic calibration approaches are therefore not feasible. In this paper, we aim to develop a new calibration approach that requires no additional data, is easy to implement, and substantially improves model performance, especially in regions where uncalibrated model performance is rather poor. This is achieved by using the Budyko framework, which provides a conceptual representation of the long‐term water and energy balance. We use a state‐of‐the‐art GHM and calibrate the model within nine river catchments of different sizes and characteristics. Since observed river discharge is available for these catchments, we are able to compare the Budyko‐based calibration approach to a classic discharge‐based calibration scheme and the uncalibrated model version. In all catchments, the Budyko‐based calibration approach decreases biases and increases model performance compared to the uncalibrated model version although performance improvements obtained through a classic calibration approach are greater. Nonetheless, a Budyko‐based calibration is a valuable, intermediate approach between use of a basic set of a priori hydrological parameters and classical calibration against discharge data.
Key Points
Most global hydrological models are uncalibrated using predefined sets of basic hydrological parameters
We developed a simple calibration approach that requires no additional data and substantially improves model performance
The new approach is based on the Budyko framework providing a conceptual representation of the long‐term water and energy balance
Mountains are the water towers of the world, supplying a substantial part of both natural and anthropogenic water demands
. They are highly sensitive and prone to climate change
, yet their ...importance and vulnerability have not been quantified at the global scale. Here we present a global water tower index (WTI), which ranks all water towers in terms of their water-supplying role and the downstream dependence of ecosystems and society. For each water tower, we assess its vulnerability related to water stress, governance, hydropolitical tension and future climatic and socio-economic changes. We conclude that the most important (highest WTI) water towers are also among the most vulnerable, and that climatic and socio-economic changes will affect them profoundly. This could negatively impact 1.9 billion people living in (0.3 billion) or directly downstream of (1.6 billion) mountainous areas. Immediate action is required to safeguard the future of the world's most important and vulnerable water towers.
Target 6.4 of the recently adopted Sustainable Development Goals (SDGs) deals with the reduction of water scarcity. To monitor progress towards this target, two indicators are used: Indicator 6.4.1 ...measuring water use efficiency and 6.4.2 measuring the level of water stress (WS). This paper aims to identify whether the currently proposed indicator 6.4.2 considers the different elements that need to be accounted for in a WS indicator. WS indicators compare water use with water availability. We identify seven essential elements: 1) both gross and net water abstraction (or withdrawal) provide important information to understand WS; 2) WS indicators need to incorporate environmental flow requirements (EFR); 3) temporal and 4) spatial disaggregation is required in a WS assessment; 5) both renewable surface water and groundwater resources, including their interaction, need to be accounted for as renewable water availability; 6) alternative available water resources need to be accounted for as well, like fossil groundwater and desalinated water; 7) WS indicators need to account for water storage in reservoirs, water recycling and managed aquifer recharge. Indicator 6.4.2 considers many of these elements, but there is need for improvement. It is recommended that WS is measured based on net abstraction as well, in addition to currently only measuring WS based on gross abstraction. It does incorporate EFR. Temporal and spatial disaggregation is indeed defined as a goal in more advanced monitoring levels, in which it is also called for a differentiation between surface and groundwater resources. However, regarding element 6 and 7 there are some shortcomings for which we provide recommendations. In addition, indicator 6.4.2 is only one indicator, which monitors blue WS, but does not give information on green or green-blue water scarcity or on water quality. Within the SDG indicator framework, some of these topics are covered with other indicators.
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•SDG target 6.4 aims at reducing water scarcity.•Indicator 6.4.2 “Level of water stress”, relates water use to availability.•We identify 7 key elements that need to be considered for a water stress indicator.•Indicator 6.4.2 considers these 7 elements, but there is need for improvement.•We give clear recommendations for improvement.
Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate ...variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used.
To sustain growing food demand and increasing standard of living, global water use increased by nearly 6 times during the last 100 years, and continues to grow. As water demands get closer and closer ...to the water availability in many regions, each drop of water becomes increasingly valuable and water must be managed more efficiently and intensively. However, soaring water use worsens water scarcity conditions already prevalent in semi-arid and arid regions, increasing uncertainty for sustainable food production and economic development. Planning for future development and investments requires that we prepare water projections for the future. However, estimations are complicated because the future of the world's waters will be influenced by a combination of environmental, social, economic, and political factors, and there is only limited knowledge and data available about freshwater resources and how they are being used. The Water Futures and Solutions (WFaS) initiative coordinates its work with other ongoing scenario efforts for the sake of establishing a consistent set of new global water scenarios based on the shared socio-economic pathways (SSPs) and the representative concentration pathways (RCPs). The WFaS "fast track" assessment uses three global water models, namely H08, PCR-GLOBWB, and WaterGAP. This study assesses the state of the art for estimating and projecting water use regionally and globally in a consistent manner. It provides an overview of different approaches, the uncertainty, strengths and weaknesses of the various estimation methods, types of management and policy decisions for which the current estimation methods are useful. We also discuss additional information most needed to be able to improve water use estimates and be able to assess a greater range of management options across the water-energy-climate nexus.
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