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Wolkeba FT, Mekonnen MM, Brauman KA, Kumar M. Indicator metrics and temporal aggregations introduce ambiguities in water scarcity estimates. Sci Rep 2024; 14:15182. [PMID: 38956151 PMCID: PMC11219772 DOI: 10.1038/s41598-024-65155-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Accepted: 06/17/2024] [Indexed: 07/04/2024] Open
Abstract
Water scarcity is a global challenge affecting billions of people worldwide. This study systematically assesses differences in the estimation of the global population exposed to water scarcity based on 7 water scarcity indicators and 11 Environmental Flow Requirements (EFR) evaluated at various spatial and temporal resolutions. All indicators show an increase in water scarcity since 1901. However, considering monthly average water scarcity estimates spatially aggregated at the basin scale found 35% less population exposed than estimates based on a distributed grid over the landscape. Estimates temporally disaggregated to consider water scarcity for at least one month a year found 50% (tenfold) larger population exposed compared to average monthly (annual) estimates. The study illustrates that estimates of the impacts of water scarcity are an artifact of how water scarcity is defined and calculated. This suggests caution is needed when relying on a single method and emphasizes the importance of considering the diversity of factors that can influence estimates of impact when assessing water scarcity.
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Affiliation(s)
- Fitsume T Wolkeba
- Department of Civil, Construction, and Environmental Engineering, University of Alabama, Tuscaloosa, AL, USA.
| | - Mesfin M Mekonnen
- Department of Civil, Construction, and Environmental Engineering, University of Alabama, Tuscaloosa, AL, USA.
| | - Kate A Brauman
- Global Water Security Center, Alabama Water Institute, University of Alabama, Tuscaloosa, AL, USA
| | - Mukesh Kumar
- Department of Civil, Construction, and Environmental Engineering, University of Alabama, Tuscaloosa, AL, USA
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Abstract
Bluecat is a recently proposed methodology to upgrade a deterministic model (D-model) into a stochastic one (S-model), based on the hypothesis that the information contained in a time series of observations and the concurrent predictions made by the D-model is sufficient to support this upgrade. The prominent characteristics of the methodology are its simplicity and transparency, which allow its easy use in practical applications, without sophisticated computational means. In this paper, we utilize the Bluecat methodology and expand it in order to be combined with climate model outputs, which often require extrapolation out of the range of values covered by observations. We apply the expanded methodology to the precipitation and temperature processes in a large area, namely the entire territory of Italy. The results showcase the appropriateness of the method for hydroclimatic studies, as regards the assessment of the performance of the climate projections, as well as their stochastic conversion with simultaneous bias correction and uncertainty quantification.
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Gao X, Lv M, Liu Y, Sun B. Precipitation projection over Daqing River Basin (North China) considering the evolution of dependence structures. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:5415-5430. [PMID: 34417694 PMCID: PMC8379070 DOI: 10.1007/s11356-021-16066-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Accepted: 08/16/2021] [Indexed: 06/13/2023]
Abstract
Understanding dynamic future changes in precipitation can provide prior information for nonpoint source pollution simulations under global warming. However, the evolution of the dependence structure and the unevenness characteristics of precipitation are rarely considered. This study applied a two-stage bias correction to daily precipitation and max/min temperature data in the Daqing River Basin (DQRB) with the HadGEM3-RA climate model. Validated from 1981 to 2015, future scenarios under two emission paths covering 2031-2065 and 2066-2100 were projected to assess variations in both the amount and unevenness of precipitation. The results suggested that, overall, the two-stage bias correction could reproduce the marginal distributions of variables and the evolution process of the dependence structure. In the future, the amount of precipitation in the plains is expected to increase more than that in the mountains, while precipitation unevenness, as measured by relative entropy, shows a slight increase in the mountains and a decrease in the plains, with enhanced seasonality. Conditioned on rising temperatures, high-/low-intensity precipitation tends to intensify/weaken precipitation unevenness. Additionally, the potential application of the bias correction method used herein and the possible impacts of uneven precipitation on nonpoint source pollution are given for further analyses. This study can provide useful information for future nonpoint source pollution simulations in the DQRB.
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Affiliation(s)
- Xueping Gao
- State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin, 300072, China
| | - Mingcong Lv
- State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin, 300072, China
| | - Yinzhu Liu
- State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin, 300072, China.
| | - Bowen Sun
- State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin, 300072, China
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Bradford JB, Andrews CM, Robles MD, McCauley LA, Woolley TJ, Marshall RM. Landscape-scale restoration minimizes tree growth vulnerability to 21 st century drought in a dry forest. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2021; 31:e2238. [PMID: 33067874 DOI: 10.1002/eap.2238] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 07/29/2020] [Accepted: 08/17/2020] [Indexed: 06/11/2023]
Abstract
Increasing aridity is a challenge for forest managers and reducing stand density to minimize competition is a recognized strategy to mitigate drought impacts on growth. In many dry forests, the most widespread and common forest management programs currently being implemented focus on restoration of historical stand structures, primarily to minimize fire risk and enhance watershed function. The implications of these restoration projects for drought vulnerability are not well understood. Here, we examined how planned restoration treatments in the Four Forests Restoration Initiative, the largest forest restoration project in the United States, would alter landscape-scale patterns of forest growth and drought vulnerability throughout the 21st century. Using drought-growth relationships developed within the landscape, we considered a suite of climate and treatment scenarios and estimated average forest growth and the proportion of years with extremely low growth as a measure of vulnerability to long-term decline. Climatic shifts projected for this landscape include higher temperatures and shifting seasonal precipitation that promotes lower soil moisture availability in the early growing season and greater hot-dry stress, conditions negatively associated with tree growth. However, drought severity and the magnitude of future growth declines were moderated by the thinning treatments. Compared to historical conditions, proportional growth in mid-century declines by ~40% if thinning ceases or continues at the status quo pace. By comparison, proportional growth declines by only 20% if the Four Forest Restoration Initiative treatments are fully implemented, and <10% if stands are thinned even more intensively than currently planned. Furthermore, restoration treatments resulted in dramatically fewer years with extremely low growth in the future, a recognized precursor to forest decline and eventual tree mortality. Benefits from density reduction for mitigating drought-induced growth declines are more apparent in mid-century and under RCP4.5 than under RCP8.5 at the end of the century. Future climate is inherently uncertain, and our results only reflect the climate projections from the representative suite of models examined. Nevertheless, these results indicate that forest restoration projects designed for other objectives also have substantial benefits for minimizing future drought vulnerability in dry forests and provide additional incentive to accelerate the pace of restoration.
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Affiliation(s)
- John B Bradford
- U.S. Geological Survey, Southwest Biological Science Center, Flagstaff, Arizona, 86011, USA
| | - Caitlin M Andrews
- U.S. Geological Survey, Southwest Biological Science Center, Flagstaff, Arizona, 86011, USA
| | - Marcos D Robles
- The Nature Conservancy, Center for Science and Public Policy, 1510 E Ft Lowell Road, Tucson, Arizona, 85719, USA
| | - Lisa A McCauley
- The Nature Conservancy, Center for Science and Public Policy, 1510 E Ft Lowell Road, Tucson, Arizona, 85719, USA
| | - Travis J Woolley
- The Nature Conservancy, Center for Science and Public Policy, 1510 E Ft Lowell Road, Tucson, Arizona, 85719, USA
| | - Robert M Marshall
- The Nature Conservancy, Center for Science and Public Policy, 1510 E Ft Lowell Road, Tucson, Arizona, 85719, USA
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Gleason KE, Bradford JB, D'Amato AW, Fraver S, Palik BJ, Battaglia MA. Forest density intensifies the importance of snowpack to growth in water-limited pine forests. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2021; 31:e02211. [PMID: 32750183 DOI: 10.1002/eap.2211] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 05/30/2020] [Accepted: 06/15/2020] [Indexed: 06/11/2023]
Abstract
Warming climate and resulting declines in seasonal snowpack have been associated with drought stress and tree mortality in seasonally snow-covered watersheds worldwide. Meanwhile, increasing forest density has further exacerbated drought stress due to intensified tree-tree competition. Using a uniquely detailed data set of population-level forest growth (n = 2,495 sampled trees), we examined how inter-annual variability in growth relates to snow volume across a range of forest densities (e.g., competitive environments) in sites spanning a broad aridity gradient across the United States. Forest growth was positively related to snowpack in water-limited forests located at low latitude, and this relationship was intensified by forest density. However, forest growth was negatively related to snowpack in a higher latitude more energy-limited forest, and this relationship did not interact with forest density. Future reductions in snowpack may have contrasting consequences, as growth may respond positively in energy-limited forests and negatively in water-limited forests; however, these declines may be mitigated by reducing stand density through forest thinning.
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Affiliation(s)
- Kelly E Gleason
- Department of Environmental Science and Management, Portland State University, 1719 SW 10th Avenue, Portland, Oregon, 97201, USA
- Southwest Biological Science Center, U.S. Geological Survey, Flagstaff, Arizona, 86001, USA
| | - John B Bradford
- Southwest Biological Science Center, U.S. Geological Survey, Flagstaff, Arizona, 86001, USA
| | - Anthony W D'Amato
- Rubenstein School of Environment and Natural Resources, University of Vermont, 204E Aiken Center, Burlington, Vermont, 05405, USA
| | - Shawn Fraver
- School of Forest Resources, University of Maine, 5755 Nutting Hall, Orono, Maine, 04469-5755, USA
| | - Brian J Palik
- USDA Forest Service, Northern Research Station, 1831 Highway 169 E, Grand Rapids, Minnesota, 80526, USA
| | - Michael A Battaglia
- USDA Forest Service, Rocky Mountain Research Station, 240 West Prospect Road, Fort Collins, Colorado, 80526, USA
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Watershed-Scale, Probabilistic Risk Assessment of Water Resources Impacts from Climate Change. WATER 2020. [DOI: 10.3390/w13010040] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
A framework for the assessment of relative risk to watershed-scale water resources from systemic changes is presented. It is composed of two experiments, or pathways, within a Monte Carlo structure and provides quantification of prediction uncertainty. One simulation pathway is the no change, or null hypothesis, experiment, and the other provides simulation of the hypothesized system change. Each pathway uses a stochastic weather generator and a deterministic water balance model. For climate change impact analysis, the framework is calibrated so that the differences between thirty-year average precipitation and temperature pathway values reproduce climate trends. Simulated weather provides forcing for identical water balance models. Probabilistic time histories of differences in actual evapotranspiration, runoff, and recharge provide likelihood per magnitude change to water resources availability. The framework is applied to a semi-arid watershed in Texas. Projected climate trends for the site are a 3 °C increase in average temperature and corresponding increase in potential evapotranspiration, no significant change in average annual precipitation, and a semi-arid classification from 2011–2100. Two types of water balance model are used in separate applications: (1) monthly water balance and (2) daily distributed parameter. Both implementations predict no significant change, on average, to actual evapotranspiration, runoff, or recharge from 2011–2100 because precipitation is unchanged on average. Increases in extreme event intensity are represented for future conditions producing increased water availability during infrequent events.
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Bradford JB, Schlaepfer DR, Lauenroth WK, Palmquist KA. Robust ecological drought projections for drylands in the 21st century. GLOBAL CHANGE BIOLOGY 2020; 26:3906-3919. [PMID: 32342577 DOI: 10.1111/gcb.15075] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 02/20/2020] [Accepted: 02/28/2020] [Indexed: 05/26/2023]
Abstract
Dryland ecosystems may be especially vulnerable to expected 21st century increases in temperature and aridity because they are tightly controlled by moisture availability. However, climate impact assessments in drylands are difficult because ecological dynamics are dictated by drought conditions that are difficult to define and complex to estimate from climate conditions alone. In addition, precipitation projections vary substantially among climate models, enhancing variation in overall trajectories for aridity. Here, we constrain this uncertainty by utilizing an ecosystem water balance model to quantify drought conditions with recognized ecological importance, and by identifying changes in ecological drought conditions that are robust among climate models, defined here as when >90% of models agree in the direction of change. Despite limited evidence for robust changes in precipitation, changes in ecological drought are robust over large portions of drylands in the United States and Canada. Our results suggest strong regional differences in long-term drought trajectories, epitomized by chronic drought increases in southern areas, notably the Upper Gila Mountains and South-Central Semi-arid Prairies, and decreases in the north, particularly portions of the Temperate and West-Central Semi-arid Prairies. However, we also found that exposure to hot-dry stress is increasing faster than mean annual temperature over most of these drylands, and those increases are greatest in northern areas. Robust shifts in seasonal drought are most apparent during the cool season; when soil water availability is projected to increase in northern regions and decrease in southern regions. The implications of these robust drought trajectories for ecosystems will vary geographically, and these results provide useful insights about the impact of climate change on these dryland ecosystems. More broadly, this approach of identifying robust changes in ecological drought may be useful for other assessments of climate impacts in drylands and provide a more rigorous foundation for making long-term strategic resource management decisions.
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Affiliation(s)
- John B Bradford
- Southwest Biological Science Center, U.S. Geological Survey, Flagstaff, AZ, USA
| | - Daniel R Schlaepfer
- Southwest Biological Science Center, U.S. Geological Survey, Flagstaff, AZ, USA
- School of Forestry and Environmental Studies, Yale University, New Haven, CT, USA
| | - William K Lauenroth
- School of Forestry and Environmental Studies, Yale University, New Haven, CT, USA
| | - Kyle A Palmquist
- Department of Biological Sciences, Marshall University, Huntington, WV, USA
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