scholarly journals A Review of Case Studies on Climate Change Impact on Hydrologic Cycle: An Indian Perspective

2021 ◽  
pp. 249-266
Author(s):  
P K Bhunya ◽  
Sanjay Kumar ◽  
Sunil Gurrapu ◽  
M K Bhuyan
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Groundwater Resources ◽  
Rainfall Events ◽  
Groundwater Levels ◽  
Groundwater Level Fluctuations ◽  
Change Impact ◽  
Heavy Rainfall Events ◽  
Flood Characteristics

In recent times, several studies focused on the global warming that may affect the hydrological cycle due to intensification of temporal and spatial variations in precipitation. Such climatic change is likely to impact significantly upon freshwater resources availability. In India, demand for water has already increased manifold over the years due to urbanization, agriculture expansion, increasing population, rapid industrialization and economic development. Numerous scientific studies also report increases in the intensity, duration, and spatial extents of floods, higher atmospheric temperatures, warmer sea, changes in precipitation patterns, and changing groundwater levels. This work briefly discusses about the present scenario regarding impact of climate change on water resources in India. Due to the insufficient resolution of climate models and their generally crude representation of sub-grid scale and convective processes, little confidence can be placed in any definite predictions of such effects, although a tendency for more heavy rainfall events seems likely, and a modest increase in frequency in floods. Thus to analyses this effect, this work considers real problems about the changing flood characteristics pattern in two river regions, and the effect of spatial and temporal pattern in rainfall. In addition to these, the work also examines the trend of groundwater level fluctuations in few blocks of Ganga–Yamuna and Sutlej-Yamuna Link interfluves region. As a whole, it examines the potential for sustainable development of surface water and groundwater resources within the constraints imposed by climate change.

scholarly journals What can we learn from long-term groundwater data to improve climate change impact studies?

2011 ◽  
Vol 8 (4) ◽  
pp. 7621-7655 ◽  
Author(s):  
S. Stoll ◽  
H. J. Hendricks Franssen ◽  
R. Barthel ◽  
W. Kinzelbach
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Climate Change Impact ◽  
Large Scale ◽  
Climate Models ◽  
Groundwater Resources ◽  
Groundwater Dynamics ◽  
Impact Studies ◽  
Change Impact

Abstract. Future risks for groundwater resources, due to global change are usually analyzed by driving hydrological models with the outputs of climate models. However, this model chain is subject to considerable uncertainties. Given the high uncertainties it is essential to identify the processes governing the groundwater dynamics, as these processes are likely to affect groundwater resources in the future, too. Information about the dominant mechanisms can be achieved by the analysis of long-term data, which are assumed to provide insight in the reaction of groundwater resources to changing conditions (weather, land use, water demand). Referring to this, a dataset of 30 long-term time series of precipitation dominated groundwater systems in northern Switzerland and southern Germany is collected. In order to receive additional information the analysis of the data is carried out together with hydrological model simulations. High spatio-temporal correlations, even over large distances could be detected and are assumed to be related to large-scale atmospheric circulation patterns. As a result it is suggested to prefer innovative weather-type-based downscaling methods to other stochastic downscaling approaches. In addition, with the help of a qualitative procedure to distinguish between meteorological and anthropogenic causes it was possible to identify processes which dominated the groundwater dynamics in the past. It could be shown that besides the meteorological conditions, land use changes, pumping activity and feedback mechanisms governed the groundwater dynamics. Based on these findings, recommendations to improve climate change impact studies are suggested.

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 What can we learn from long-term groundwater data to improve climate change impact studies?

2011 ◽  
Vol 15 (12) ◽  
pp. 3861-3875 ◽  
Author(s):  
S. Stoll ◽  
H. J. Hendricks Franssen ◽  
R. Barthel ◽  
W. Kinzelbach
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Climate Change Impact ◽  
Large Scale ◽  
Climate Models ◽  
Groundwater Resources ◽  
Groundwater Dynamics ◽  
Impact Studies ◽  
Change Impact

Abstract. Future risks for groundwater resources, due to global change are usually analyzed by driving hydrological models with the outputs of climate models. However, this model chain is subject to considerable uncertainties. Given the high uncertainties it is essential to identify the processes governing the groundwater dynamics, as these processes are likely to affect groundwater resources in the future, too. Information about the dominant mechanisms can be achieved by the analysis of long-term data, which are assumed to provide insight in the reaction of groundwater resources to changing conditions (weather, land use, water demand). Referring to this, a dataset of 30 long-term time series of precipitation dominated groundwater systems in northern Switzerland and southern Germany is collected. In order to receive additional information the analysis of the data is carried out together with hydrological model simulations. High spatio-temporal correlations, even over large distances could be detected and are assumed to be related to large-scale atmospheric circulation patterns. As a result it is suggested to prefer innovative weather-type-based downscaling methods to other stochastic downscaling approaches. In addition, with the help of a qualitative procedure to distinguish between meteorological and anthropogenic causes it was possible to identify processes which dominated the groundwater dynamics in the past. It could be shown that besides the meteorological conditions, land use changes, pumping activity and feedback mechanisms governed the groundwater dynamics. Based on these findings, recommendations to improve climate change impact studies are suggested.

scholarly journals Modelling the Impacts of Climate Change on Shallow Groundwater Conditions in Hungary

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 668
Author(s):  
Attila Kovács ◽  
András Jakab
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Groundwater Resources ◽  
Regional Climate ◽  
Shallow Groundwater ◽  
Predictive Modelling ◽  
Climate Impacts ◽  
Annual Rainfall ◽  
Groundwater Levels

The purpose of the present study was to develop a methodology for the evaluation of direct climate impacts on shallow groundwater resources and its country-scale application in Hungary. A modular methodology was applied. It comprised the definition of climate zones and recharge zones, recharge calculation by hydrological models, and the numerical modelling of the groundwater table. Projections of regional climate models for three different time intervals were applied for the simulation of predictive scenarios. The investigated regional climate model projections predict rising annual average temperature and generally dropping annual rainfall rates throughout the following decades. Based on predictive modelling, recharge rates and groundwater levels are expected to drop in elevated geographic areas such as the Alpokalja, the Eastern parts of the Transdanubian Mountains, the Mecsek, and Northern Mountain Ranges. Less significant groundwater level drops are predicted in foothill areas, and across the Western part of the Tiszántúl, the Duna-Tisza Interfluve, and the Szigetköz areas. Slightly increasing recharge and groundwater levels are predicted in the Transdanubian Hills and the Western part of the Transdanubian Mountains. Simulation results represent groundwater conditions at the country scale. However, the applied methodology is suitable for simulating climate change impacts at various scales.

scholarly journals Evaluation of Climate Change Impact on Groundwater Recharge in Groundwater Regions in Taiwan

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1153
Author(s):  
Shih-Jung Wang ◽  
Cheng-Haw Lee ◽  
Chen-Feng Yeh ◽  
Yong Fern Choo ◽  
Hung-Wei Tseng
Keyword(s):  
Climate Change ◽  
Groundwater Recharge ◽  
Climate Change Impact ◽  
Groundwater Resources ◽  
Regression Equations ◽  
Impact Of Climate Change ◽  
Groundwater Systems ◽  
Change Impact ◽  
The Impact ◽  
Assessment Results

Climate change can directly or indirectly influence groundwater resources. The mechanisms of this influence are complex and not easily quantified. Understanding the effect of climate change on groundwater systems can help governments adopt suitable strategies for water resources. The baseflow concept can be used to relate climate conditions to groundwater systems for assessing the climate change impact on groundwater resources. This study applies the stable baseflow concept to the estimation of the groundwater recharge in ten groundwater regions in Taiwan, under historical and climate scenario conditions. The recharge rates at the main river gauge stations in the groundwater regions were assessed using historical data. Regression equations between rainfall and groundwater recharge quantities were developed for the ten groundwater regions. The assessment results can be used for recharge evaluation in Taiwan. The climate change estimation results show that climate change would increase groundwater recharge by 32.6% or decrease it by 28.9% on average under the climate scenarios, with respect to the baseline quantity in Taiwan. The impact of climate change on groundwater systems may be positive. This study proposes a method for assessing the impact of climate change on groundwater systems. The assessment results provide important information for strategy development in groundwater resources management.

scholarly journals Regions of intensification of extreme snowfall under future warming

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lennart Quante ◽  
Sven N. Willner ◽  
Robin Middelanis ◽  
Anders Levermann
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Observational Data ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Global Climate Models ◽  
Average Intensity ◽  
High Latitudes ◽  
Future Warming

AbstractDue to climate change the frequency and character of precipitation are changing as the hydrological cycle intensifies. With regards to snowfall, global warming has two opposing influences; increasing humidity enables intense snowfall, whereas higher temperatures decrease the likelihood of snowfall. Here we show an intensification of extreme snowfall across large areas of the Northern Hemisphere under future warming. This is robust across an ensemble of global climate models when they are bias-corrected with observational data. While mean daily snowfall decreases, both the 99th and the 99.9th percentiles of daily snowfall increase in many regions in the next decades, especially for Northern America and Asia. Additionally, the average intensity of snowfall events exceeding these percentiles as experienced historically increases in many regions. This is likely to pose a challenge to municipalities in mid to high latitudes. Overall, extreme snowfall events are likely to become an increasingly important impact of climate change in the next decades, even if they will become rarer, but not necessarily less intense, in the second half of the century.

Assess 21st century Flash Drought in the United States using high resolution regional climate models

2021 ◽  
Author(s):  
Brandi Gamelin ◽  
Jiali Wang ◽  
V. Rao Kotamarthi
Keyword(s):  
Climate Change ◽  
United States ◽  
Soil Moisture ◽  
Climate Models ◽  
Wrf Model ◽  
The United States ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Regional Variability ◽  
Groundwater Levels

<p>Flash droughts are the rapid intensification of drought conditions generally associated with increased temperatures and decreased precipitation on short time scales.  Consequently, flash droughts are responsible for reduced soil moisture which contributes to diminished agricultural yields and lower groundwater levels. Drought management, especially flash drought in the United States is vital to address the human and economic impact of crop loss, diminished water resources and increased wildfire risk. In previous research, climate change scenarios show increased growing season (i.e. frost-free days) and drying in soil moisture over most of the United States by 2100. Understanding projected flash drought is important to assess regional variability, frequency and intensity of flash droughts under future climate change scenarios. Data for this work was produced with the Weather Research and Forecasting (WRF) model. Initial and boundary conditions for the model were supplied by CCSM4, GFDL-ESM2G, and HadGEM2-ES and based on the 8.5 Representative Concentration Pathway (RCP8.5). The WRF model was downscaled to a 12 km spatial resolution for three climate time frames: 1995-2004 (Historical), 2045-2054 (Mid), and 2085-2094 (Late).  A key characteristic of flash drought is the rapid onset and intensification of dry conditions. For this, we identify onset with vapor pressure deficit during each time frame. Known flash drought cases during the Historical run are identified and compared to flash droughts in the Mid and Late 21<sup>st</sup> century.</p>

scholarly journals Brief communication "Climatic covariates for the frequency analysis of heavy rainfall in the Mediterranean region"

2011 ◽  
Vol 11 (9) ◽  
pp. 2463-2468 ◽  
Author(s):  
Y. Tramblay ◽  
L. Neppel ◽  
J. Carreau
Keyword(s):  
Extreme Events ◽  
Heavy Rainfall ◽  
Climate Models ◽  
Extreme Event ◽  
Generalized Pareto Distribution ◽  
Climatic Conditions ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
The Future ◽  
Heavy Rainfall Events

Abstract. In Mediterranean regions, climate studies indicate for the future a possible increase in the extreme rainfall events occurrence and intensity. To evaluate the future changes in the extreme event distribution, there is a need to provide non-stationary models taking into account the non-stationarity of climate. In this study, several climatic covariates are tested in a non-stationary peaks-over-threshold modeling approach for heavy rainfall events in Southern France. Results indicate that the introduction of climatic covariates could improve the statistical modeling of extreme events. In the case study, the frequency of southern synoptic circulation patterns is found to improve the occurrence process of extreme events modeled via a Poisson distribution, whereas for the magnitude of the events, the air temperature and sea level pressure appear as valid covariates for the Generalized Pareto distribution scale parameter. Covariates describing the humidity fluxes at monthly and seasonal time scales also provide significant model improvements for the occurrence and the magnitude of heavy rainfall events. With such models including climatic covariates, it becomes possible to asses the risk of extreme events given certain climatic conditions at monthly or seasonal timescales. The future changes in the heavy rainfall distribution can also be evaluated using covariates computed by climate models.

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.

scholarly journals Hydrological processes and water resources management in a dryland environment IV: Long-term groundwater level fluctuations due to variation in rainfall

1999 ◽  
Vol 3 (3) ◽  
pp. 353-361 ◽  
Author(s):  
J. A. Butterworth ◽  
R. E. Schulze ◽  
L. P. Simmonds ◽  
P. Moriarty ◽  
F. Mugabe
Keyword(s):  
Groundwater Resources ◽  
Water Levels ◽  
Shallow Aquifer ◽  
Balance Model ◽  
Specific Yield ◽  
Evaporative Demand ◽  
Groundwater Levels ◽  
Groundwater Level Fluctuations ◽  
Modelling Methods

Abstract. To evaluate the effects of variations in rainfall on groundwater, long-term rainfall records were used to simulate groundwater levels over the period 1953-96 at an experimental catchment in south-east Zimbabwe. Two different modelling methods were adopted. Firstly, a soil water balance model (ACRU) simulated drainage from daily rainfall and evaporative demand; groundwater levels were predicted as a function of drainage, specific yield and water table height. Secondly, the cumulative rainfall departure method was used to model groundwater levels from monthly rainfall. Both methods simulated observed groundwater levels over the period 1992-96 successfully, and long-term simulated trends in historical levels were comparable. Results suggest that large perturbations in groundwater levels area a normal feature of the response of a shallow aquifer to variations in rainfall. Long-term trends in groundwater levels are apparent and reflect the effect of cycles in rainfall. Average end of dry season water levels were simulated to be almost 3 m higher in the late 1970s compared to those of the early 1990s. The simulated effect of prolonged low rainfall on groundwater levels was particularly severe during the period 1981-92 with a series of low recharge years unprecedented in the earlier record. More recently, above average rainfall has resulted in generally higher groundwater levels. The modelling methods described may be applied in the development of guidelines for groundwater schemes to help ensure safe long-term yields and to predict future stress on groundwater resources in low rainfall periods; they are being developed to evaluate the effects of land use and management change on groundwater resources.

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