scholarly journals Species-Specific Effects of Groundwater Level Alteration on Climate Sensitivity of Floodplain Trees

Forests ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1178
Author(s):  
Martin Šenfeldr ◽  
Pavel Horák ◽  
Jakub Kvasnica ◽  
Martin Šrámek ◽  
Hana Hornová ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Sensitivity ◽  
Groundwater Level ◽  
Floodplain Forest ◽  
Management Tool ◽  
Severe Drought ◽  
Adaptation To Climate Change ◽  
Growth Modulation ◽  
Groundwater Levels ◽  
Groundwater Availability

European floodplain forest is facing increasingly frequent and severe drought events related with ongoing climate change. Moreover, this ecosystem type was frequently affected by river regulation, leading to groundwater table lowering; however, river revitalization has, in some locations, achieved some restoration of groundwater levels. In this study, we investigated the growth–climate sensitivity and growth modulation after groundwater-level manipulation for Fraxinus angustifolia Vahl. and Quercus robur L. in one of the most important floodplain forest complexes in Central Europe. We constructed three different types of tree ring chronologies to reflect the high frequency variability, medium-low frequency variability, and basal area increment. We found F. angustifolia to be more sensitive than Q. robur to both drought and groundwater level fluctuations. Moreover, F. angustifolia showed more pronounced short-term and long-term growth decreases after artificial ground water level alteration than did Q. robur. We also found that the groundwater level increase due to river revitalization reduced the climate sensitivity for both F. angustifolia and Q. robur. The decrease in climate sensitivity associated with revitalization was more pronounced for F. angustifolia which, moreover, showed a greater basal growth after river revitalization. Our results suggest that F. angustifolia will be more threatened than Q. robur by the diminution in groundwater availability and increase in drought with ongoing climate change. They also show that river revitalization can be a suitable management tool to help the adaptation to climate change.

scholarly journals Meteorological, soil moisture, surface water, and groundwater data from the St Denis National Wildlife Area, Saskatchewan, Canada

2018 ◽  
Author(s):  
Edward K. P. Bam ◽  
Rosa Brannen ◽  
Sujata Budhathoki ◽  
Andrew M. Ireson ◽  
Chris Spence ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Surface Water ◽  
Climate Models ◽  
Multiple Scales ◽  
Full Range ◽  
Research Network ◽  
Groundwater Levels ◽  
Groundwater Availability ◽  
Surface Water And Groundwater

Abstract. Long-term meteorological, soil moisture, surface water, and groundwater data provide information on past climate change, most notably information that can be used to analyze past changes in precipitation and groundwater availability in a region. These data are also valuable to test, calibrate and validate hydrological and climate models. CCRN (Changing Cold Regions Network) is a collaborative research network that brought together a team of over 40 experts from 8 universities and 4 federal government agencies in Canada for 5 years (2013–18) through the Climate Change and Atmospheric Research (CCAR) Initiative of the Natural Sciences and Engineering Research Council of Canada (NSERC). The working group aimed to integrate existing and new data with improved predictive and observational tools to understand, diagnose and predict interactions amongst the cryospheric, ecological, hydrological, and climatic components of the changing Earth system at multiple scales, with a geographic focus on the rapidly changing cold interior of Western Canada. The St Denis National Wildlife Area database contains data for the prairie research site, St Denis National Wildlife Research Area, and includes atmosphere, soil, and groundwater. The meteorological measurements are observed every 5 seconds, and half-hourly averages (or totals) are logged. Soil moisture data comprise volumetric water content, soil temperature, electrical conductivity and matric potential for probes installed at depths of 5 cm, 20 cm, 50 cm, 100 cm, 200 cm and 300 cm in all soil profiles. Additional data on snow surveys, pond and groundwater levels, and water isotope isotopes collected on an intermittent basis between 1968 and 2018 are also presented including information on the dates and ground elevations (datum) used to construct hydraulic heads. The metadata table provides location information, information about the full range of measurements carried out on each parameter and GPS locations that are relevant to the interpretation of the records, as well as citations for both publications and archived data. The compiled data are available at https://doi.org/10.20383/101.0115.

Robust modelling to address UPH19 to predict future hydrological responses for water resources adaptation under climate change

2021 ◽  
Author(s):  
Francis Chiew ◽  
Hongxing Zheng ◽  
Jai Vaze
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Accurate Estimate ◽  
Severe Drought ◽  
Hydrological Models ◽  
Adaptation To Climate Change ◽  
Projected Range ◽  
Trade Offs ◽  
Eastern Australia ◽  
Robust Modelling

<p>This paper addresses the implications of UPH19 in extrapolating hydrological models to predict the future and assessing water resources adaptation to climate change. Many studies have now shown that traditional application of hydrological models calibrated against past observations will underestimate the range in the projected future hydrological impact, that is, it will underestimate the decline in runoff where a runoff decrease is projected, and underestimate the increase in runoff where a runoff increase is projected. This study opportunistically uses data from south-eastern Australia which recently experienced a long and severe drought lasting more than ten years and subsequent partial hydrological recovery from the drought. The paper shows that a more robust calibration of rainfall-runoff models to produce good calibration metrics in both the dry periods and wet periods, at the expense of the best calibration over the entire data period, can produce a more accurate estimate of the uncertainty in the projected future runoff, but cannot entirely eliminate the modelling limitation of underestimating the projected range in future runoff. This is because of the need to consider trade-offs between the calibration objectives, particularly in simulating the dry periods, versus enhanced bias that results from the consideration. Hydrological models must therefore also need to be adapted to reflect the non-stationary nature of catchment and vegetation responses in a changing climate under warmer conditions, higher CO<sub>2</sub> and changed precipitation patterns. This is an active area of research in UPH19, and some ideas relevant to this region will be presented.</p>

Ecosystem-based Adaptation to Climate Change: Experience from Smallholder Floodplain Forest Management

2015 ◽  
Vol 4 (0) ◽  
pp. 6
Author(s):  
Shikhasmita Nath ◽  
Arun Jyoti Nath ◽  
Rattan Lal ◽  
Ashesh Kumar Das
Keyword(s):  
Climate Change ◽  
Forest Management ◽  
Floodplain Forest ◽  
Adaptation To Climate Change

scholarly journals Testing the use of standardised indices and GRACE satellite data to estimate the European 2015 groundwater drought in near-real time

2017 ◽  
Vol 21 (4) ◽  
pp. 1947-1971 ◽  
Author(s):  
Anne F. Van Loon ◽  
Rohini Kumar ◽  
Vimal Mishra
Keyword(s):  
The Netherlands ◽  
Spatial Variability ◽  
Real Time ◽  
Groundwater Level ◽  
Meteorological Drought ◽  
Meteorological Conditions ◽  
Severe Drought ◽  
Near Surface ◽  
Groundwater Levels ◽  
Groundwater Drought

Abstract. In 2015, central and eastern Europe were affected by a severe drought. This event has recently been studied from meteorological and streamflow perspective, but no analysis of the groundwater situation has been performed. One of the reasons is that real-time groundwater level observations often are not available. In this study, we evaluate two alternative approaches to quantify the 2015 groundwater drought over two regions in southern Germany and eastern Netherlands. The first approach is based on spatially explicit relationships between meteorological conditions and historic groundwater level observations. The second approach uses the Gravity Recovery Climate Experiment (GRACE) terrestrial water storage (TWS) and groundwater anomalies derived from GRACE-TWS and (near-)surface storage simulations by the Global Land Data Assimilation System (GLDAS) models. We combined the monthly groundwater observations from 2040 wells to establish the spatially varying optimal accumulation period between the Standardised Groundwater Index (SGI) and the Standardized Precipitation Evapotranspiration Index (SPEI) at a 0.25° gridded scale. The resulting optimal accumulation periods range between 1 and more than 24 months, indicating strong spatial differences in groundwater response time to meteorological input over the region. Based on the estimated optimal accumulation periods and available meteorological time series, we reconstructed the groundwater anomalies up to 2015 and found that in Germany a uniform severe groundwater drought persisted for several months during this year, whereas the Netherlands appeared to have relatively high groundwater levels. The differences between this event and the 2003 European benchmark drought are striking. The 2003 groundwater drought was less uniformly pronounced, both in the Netherlands and Germany. This is because slowly responding wells (the ones with optimal accumulation periods of more than 12 months) still were above average from the wet year of 2002, which experienced severe flooding in central Europe. GRACE-TWS and GRACE-based groundwater anomalies did not capture the spatial variability of the 2003 and 2015 drought events satisfactorily. GRACE-TWS did show that both 2003 and 2015 were relatively dry, but the differences between Germany and the Netherlands in 2015 and the spatially variable groundwater drought pattern in 2003 were not captured. This could be associated with the coarse spatial scale of GRACE. The simulated groundwater anomalies based on GRACE-TWS deviated considerably from the GRACE-TWS signal and from observed groundwater anomalies. The uncertainty in the GRACE-based groundwater anomalies mainly results from uncertainties in the simulation of soil moisture by the different GLDAS models. The GRACE-based groundwater anomalies are therefore not suitable for use in real-time groundwater drought monitoring in our case study regions. The alternative approach based on the spatially variable relationship between meteorological conditions and groundwater levels is more suitable to quantify groundwater drought in near real-time. Compared to the meteorological drought and streamflow drought (described in previous studies), the groundwater drought of 2015 had a more pronounced spatial variability in its response to meteorological conditions, with some areas primarily influenced by short-term meteorological deficits and others influenced by meteorological deficits accumulated over the preceding 2 years or more. In drought management, this information is very useful and our approach to quantify groundwater drought can be used until real-time groundwater observations become readily available.

scholarly journals Deep Learning based assessment of groundwater level development in Germany until 2100

2021 ◽  
Author(s):  
Andreas Wunsch ◽  
Tanja Liesch ◽  
Stefan Broda
Keyword(s):  
Climate Change ◽  
Groundwater Level ◽  
Climate Models ◽  
Groundwater Resources ◽  
Groundwater Abstraction ◽  
Water Shortages ◽  
Entire Area ◽  
Groundwater Levels ◽  
The Past ◽  
Skill Scores

<p>Clear signs of climate stress on groundwater resources have been observed in recent years even in generally water-rich regions such as Germany. Severe droughts, resulting in decreased groundwater recharge, led to declining groundwater levels in many regions and even local drinking water shortages have occurred in past summers. We investigate how climate change will directly influence the groundwater resources in Germany until the year 2100. For this purpose, we use a machine learning groundwater level forecasting framework, based on Convolutional Neural Networks, which has already proven its suitability in modelling groundwater levels. We predict groundwater levels on more than 120 wells distributed over the entire area of Germany that showed strong reactions to meteorological signals in the past. The inputs are derived from the RCP8.5 scenario of six climate models, pre-selected and pre-processed by the German Meteorological Service, thus representing large parts of the range of the expected change in the next 80 years. Our models are based on precipitation and temperature and are carefully evaluated in the past and only wells with models reaching high forecasting skill scores are included in our study. We only consider natural climate change effects based on meteorological changes, while highly uncertain human factors, such as increased groundwater abstraction or irrigation effects, remain unconsidered due to a lack of reliable input data. We can show significant (p<0.05) declining groundwater levels for a large majority of the considered wells, however, at the same time we interestingly observe the opposite behaviour for a small portion of the considered locations. Further, we show mostly strong increasing variability, thus an increasing number of extreme groundwater events. The spatial patterns of all observed changes reveal stronger decreasing groundwater levels especially in the northern and eastern part of Germany, emphasizing the already existing decreasing trends in these regions</p>

scholarly journals Spatio-temporal impact of climate change on the groundwater system

2012 ◽  
Vol 16 (5) ◽  
pp. 1517-1531 ◽  
Author(s):  
J. Dams ◽  
E. Salvadore ◽  
T. Van Daele ◽  
V. Ntegeka ◽  
P. Willems ◽  
...  
Keyword(s):  
Climate Change ◽  
Groundwater Recharge ◽  
Groundwater Level ◽  
Climate Change Scenarios ◽  
Close Monitoring ◽  
Reference Period ◽  
Groundwater System ◽  
Groundwater Levels ◽  
Impact Of Climate Change ◽  
The Impact

Abstract. Given the importance of groundwater for food production and drinking water supply, but also for the survival of groundwater dependent terrestrial ecosystems (GWDTEs) it is essential to assess the impact of climate change on this freshwater resource. In this paper we study with high temporal and spatial resolution the impact of 28 climate change scenarios on the groundwater system of a lowland catchment in Belgium. Our results show for the scenario period 2070–2101 compared with the reference period 1960–1991, a change in annual groundwater recharge between −20% and +7%. On average annual groundwater recharge decreases 7%. In most scenarios the recharge increases during winter but decreases during summer. The altered recharge patterns cause the groundwater level to decrease significantly from September to January. On average the groundwater level decreases about 7 cm with a standard deviation between the scenarios of 5 cm. Groundwater levels in interfluves and upstream areas are more sensitive to climate change than groundwater levels in the river valley. Groundwater discharge to GWDTEs is expected to decrease during late summer and autumn as much as 10%, though the discharge remains at reference-period level during winter and early spring. As GWDTEs are strongly influenced by temporal dynamics of the groundwater system, close monitoring of groundwater and implementation of adaptive management measures are required to prevent ecological loss.

scholarly journals Future Flows Hydrology: an ensemble of daily river flow and monthly groundwater levels for use for climate change impact assessment across Great Britain

2013 ◽  
Vol 5 (1) ◽  
pp. 101-107 ◽  
Author(s):  
C. Prudhomme ◽  
T. Haxton ◽  
S. Crooks ◽  
C. Jackson ◽  
A. Barkwith ◽  
...  
Keyword(s):  
Climate Change ◽  
Great Britain ◽  
Groundwater Level ◽  
River Flow ◽  
Hydrological Modelling ◽  
Time Slice ◽  
Practical Recommendation ◽  
Hydrological Models ◽  
Groundwater Levels ◽  
Modelling Uncertainty

Abstract. The dataset Future Flows Hydrology was developed as part of the project "Future Flows and Groundwater Levels'' to provide a consistent set of transient daily river flow and monthly groundwater level projections across England, Wales and Scotland to enable the investigation of the role of climate variability on river flow and groundwater levels nationally and how this may change in the future. Future Flows Hydrology is derived from Future Flows Climate, a national ensemble projection derived from the Hadley Centre's ensemble projection HadRM3-PPE to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications. Three hydrological models and one groundwater level model were used to derive Future Flows Hydrology, with 30 river sites simulated by two hydrological models to enable assessment of hydrological modelling uncertainty in studying the impact of climate change on the hydrology. Future Flows Hydrology contains an 11-member ensemble of transient projections from January 1951 to December 2098, each associated with a single realisation from a different variant of HadRM3 and a single hydrological model. Daily river flows are provided for 281 river catchments and monthly groundwater levels at 24 boreholes as .csv files containing all 11 ensemble members. When separate simulations are done with two hydrological models, two separate .csv files are provided. Because of potential biases in the climate–hydrology modelling chain, catchment fact sheets are associated with each ensemble. These contain information on the uncertainty associated with the hydrological modelling when driven using observed climate and Future Flows Climate for a period representative of the reference time slice 1961–1990 as described by key hydrological statistics. Graphs of projected changes for selected hydrological indicators are also provided for the 2050s time slice. Limitations associated with the dataset are provided, along with practical recommendation of use. Future Flows Hydrology is freely available for non-commercial use under certain licensing conditions. For each study site, catchment averages of daily precipitation and monthly potential evapotranspiration, used to drive the hydrological models, are made available, so that hydrological modelling uncertainty under climate change conditions can be explored further. doi:10.5285/f3723162-4fed-4d9d-92c6-dd17412fa37b

scholarly journals Assessment of Climate Change Impact on Future Groundwater-Level Behavior Using SWAT Groundwater-Consumption Function in Geum River Basin of South Korea

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 949 ◽  
Author(s):  
Jiwan Lee ◽  
Chunggil Jung ◽  
Sehoon Kim ◽  
Seongjoon Kim
Keyword(s):  
Climate Change ◽  
South Korea ◽  
Ground Water ◽  
River Basin ◽  
Water Use ◽  
Groundwater Level ◽  
Climate Change Scenarios ◽  
Groundwater Levels ◽  
The Future ◽  
And Storage

This study was to evaluate the groundwater-level behavior in Geum River Basin (9645.5 km2) of South Korea with HadGEM3-RA RCP 4.5 and 8.5 climate change scenarios and future groundwater use data using the soil and water assessment tool (SWAT). Before evaluating future groundwater behavior, the SWAT model was calibrated and validated using the daily inflows and storage of two dams (DCD and YDD) in the basin for 11 years (2005–2015), the daily groundwater-level observation data at five locations (JSJS, OCCS, BEMR, CASS, and BYBY), and the daily inflow and storage of three weir locations (SJW, GJW, and BJW) for three years and five months (August 2012 to December 2015). The Nash–Sutcliffe efficiency (NSE) and the coefficient of determination (R2) of two dam inflows was 0.55–0.70 and 0.67–0.75. For the inflows of the three weirs, NSE was 0.57–0.77 and R2 was 0.62–0.81. The average R2 value for the groundwater levels of the five locations ranged from 0.53 to 0.61. After verifying the SWAT for hydrologic components, we evaluated the behavior of future groundwater levels by future climate change scenarios and estimated future ground water use by Korean water vision 2020 based on ground water use monitoring data. The future groundwater-level decreased by −13.0, −5.0, and −9.0 cm at three upstream locations (JSJS, OCCS, and BEMR) among the five groundwater-level observation locations and increased by +3.0 and +1.0 cm at two downstream locations (CASS and BYBY). The future groundwater level was directly affected by the groundwater recharge, which was dependent on the seasonal and spatial precipitations in the basin.

scholarly journals Drought Under Global Warming and Climate Change: An Empirical Study of the Loess Plateau

2019 ◽  
Vol 11 (5) ◽  
pp. 1281 ◽  
Author(s):  
Yang Li ◽  
Zhixiang Xie ◽  
Yaochen Qin ◽  
Haoming Xia ◽  
Zhicheng Zheng ◽  
...  
Keyword(s):  
Climate Change ◽  
Loess Plateau ◽  
Severe Drought ◽  
Observation Data ◽  
The Loess Plateau ◽  
Adaptation To Climate Change ◽  
Livestock Farming ◽  
Drought Intensity ◽  
Random Events ◽  
Autumn And Winter

The Loess Plateau is located at the transition zone between agriculture and livestock farming; its spatial and temporal pattern of drought is the key for an appropriate adaptation to climate change. This study investigated monthly meteorological observation data of 79 meteorological stations from 1955 to 2014 to calculate the standardized precipitation evapotranspiration index at different time scales. The spatial and temporal characteristics and persistence of drought were analyzed. The results showed the following: (i) The drought trend is most apparent in spring (0.096/10a) and lower in summer (0.036/10a) and autumn (0.009/10a). (ii) A higher drought level indicates a lower frequency of droughts occurrence and vice versa. The frequency of light drought was highest (11.36%), while that of extreme drought was lowest (0.12%). (iii) The mean drought intensity was highest in summer, followed by spring, autumn, and winter. The drought intensity was mainly light, showing a pattern of severe drought in the northwest and light drought in the southeast. (iv) The Loess Plateau will continue a trend of drought in the future, but the season of the continuous intensity will differ. Droughts in spring and summer are highly persistent, autumn drought trends continue but may slow, and winter droughts become random events.

scholarly journals Evaluating the Adaptation of Chinese Torreya Plantations to Climate Change

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 176 ◽  
Author(s):  
Xiongwen Chen ◽  
Jianzhi Niu
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Policy Development ◽  
Climate Adaptation ◽  
Annual Precipitation ◽  
Severe Drought ◽  
Monthly Precipitation ◽  
Adaptation To Climate Change ◽  
Drought Period ◽  
Air Temperatures

Studying the capacity of some plant species to adapt to climate change is essential for ecological research and agricultural policy development. Chinese Torreya (Torreya grandis ‘Merrillii’) has been an important crop tree in subtropical China for over a thousand years. It is necessary to characterize its adaptation to climate change. In this study, the average monthly temperature and precipitation from 1901 to 2017 in the six regions with Chinese Torreya plantations at different provinces were analyzed. The results indicated that the average annual air temperature across these regions had increased by about 2.0 °C, but no general trend in the annual precipitation and incidence of drought was found. The annual air temperature that Chinese Torreya plantations had experienced was 12.96–18.23 °C; the highest and the lowest average monthly air temperatures were 30.1 °C and −0.8 °C, respectively. The lowest and the highest annual precipitation were 874.56 mm and 2501.88 mm, respectively. Chinese Torreya trees endured a severe drought period in the 1920s. The monthly air temperature at Zhuji, which is the central production region, showed a significant correlation with the air temperature in the other five regions. The monthly precipitation in Hunan and Guizhou had no significant correlation with that of Zhuji. Chinese Torreya plantations have been grown in the regions with a similar climate distance index of air temperatures but different precipitation. This tree has a high capacity to adapt to climate change based on the climate dynamics across its range. This approach may provide a way to evaluate climate adaptation in other tree species. These results may provide helpful information for the development of Chinese Torreya plantations.

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