Spatial variability of the response to climate change in regional groundwater systems – Examples from simulations in the Deschutes Basin, Oregon

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.

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Spatial variability of topsoil δ13C across Qinghai-Tibet Plateau

10.5194/egusphere-egu21-5768 ◽

2021 ◽

Author(s):

Yunsen Lai ◽

Shaoda Li ◽

Xiaolu Tang ◽

Xinrui Luo ◽

Liang Liu ◽

...

Keyword(s):

Climate Change ◽

Machine Learning ◽

Spatial Variability ◽

Soil Carbon ◽

Tibet Plateau ◽

Learning Approach ◽

Carbon Turnover ◽

Machine Learning Approach ◽

Qinghai Tibet Plateau ◽

Soil Carbon Turnover

Soil carbon isotopes (&#948;13C) provide reliable insights at the long-term scale for the study of soil carbon turnover and topsoil &#948;13C could well reflect organic matter input from the current vegetation. Qinghai-Tibet Plateau (QTP) is called &#8220;the third pole of the earth&#8221; because of its high elevation, and it is one of the most sensitive and critical regions to global climate change worldwide. Previous studies focused on variability of soil &#948;13C at in-site scale. However, a knowledge gap still exists in the spatial pattern of topsoil &#948;13C in QTP. In this study, we first established a database of topsoil &#948;13C with 396 observations from published literature and applied a Random Forest (RF) algorithm (a machine learning approach) to predict the spatial pattern of topsoil &#948;13C using environmental variables. Results showed that topsoil &#948;13C significantly varied across different ecosystem types (p < 0.05).&#160; Topsoil &#948;13C was -26.3 &#177; 1.60 &#8240; for forest, 24.3 &#177; 2.00 &#8240; for shrubland, -23.9 &#177; 1.84 &#8240; for grassland, -18.9 &#177; 2.37 &#8240; for desert, respectively. RF could well predict the spatial variability of topsoil &#948;13C with a model efficiency (pseudo R2) of 0.65 and root mean square error of 1.42. The gridded product of topsoil &#948;13C and topsoil &#946; (indicating the decomposition rate of soil organic carbon, calculated by &#948;13C divided by logarithmically converted SOC) with a spatial resolution of 1000 m were developed. Strong spatial variability of topsoil &#948;13C was observed, which increased gradually from the southeast to the northwest in QTP. Furthermore, a large variation was found in &#946;, ranging from -7.87 to -81.8, with a decreasing trend from southeast to northwest, indicating that carbon turnover rate was faster in northwest QTP compared to that of southeast. This study was the first attempt to develop a fine resolution product of topsoil &#948;13C for QTP using a machine learning approach, which could provide an independent benchmark for biogeochemical models to study soil carbon turnover and terrestrial carbon-climate feedbacks under ongoing climate change.

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Alaskan soil carbon stocks: spatial variability and dependence on environmental factors

Biogeosciences Discussions ◽

10.5194/bgd-9-5695-2012 ◽

2012 ◽

Vol 9 (5) ◽

pp. 5695-5718 ◽

Cited By ~ 1

Author(s):

U. Mishra ◽

W. J. Riley

Keyword(s):

Climate Change ◽

Spatial Variability ◽

Soil Carbon ◽

Active Layer ◽

High Latitude ◽

Future Climate Change ◽

Climate Change Scenarios ◽

Intergovernmental Panel ◽

Soil Wetness ◽

Soc Stocks

Abstract. The direction and magnitude of soil organic carbon (SOC) changes in response to climate change depend on the spatial and vertical distributions of SOC. We estimated spatially-resolved SOC stocks from surface to C horizon, distinguishing active-layer and permafrost-layer stocks, based on geospatial analysis of 472 soil profiles and spatially referenced environmental variables for Alaska. Total Alaska state-wide SOC stock was estimated to be 77 Pg, with 61% in the active-layer, 27% in permafrost, and 12% in non-permafrost soils. Prediction accuracy was highest for the active-layer as demonstrated by highest ratio of performance to deviation (1.5). Large spatial variability was predicted, with whole-profile, active-layer, and permafrost-layer stocks ranging from 1–296 kg C m−2, 2–166 kg m−2, and 0–232 kg m−2, respectively. Temperature and soil wetness were found to be primary controllers of whole-profile, active-layer, and permafrost-layer SOC stocks. Secondary controllers, in order of importance, were: land cover type, topographic attributes, and bedrock geology. The observed importance of soil wetness rather than precipitation on SOC stocks implies that the poor representation of high-latitude soil wetness in Earth System Models may lead to large uncertainty in predicted SOC stocks under future climate change scenarios. Under strict caveats described in the text and assuming temperature changes from the A1B Intergovernmental Panel on Climate Change emissions scenario, our geospatial model indicates that the equilibrium average 2100 Alaska active-layer depth could deepen by 11 cm, resulting in a thawing of 13 Pg C currently in permafrost. The equilibrium SOC loss associated with this warming would be highest under continuous permafrost (31%), followed by discontinuous (28%), isolated (24.3%), and sporadic (23.6%) permafrost areas. Our high resolution mapping of soil carbon stock reveals the potential vulnerability of high-latitude soil carbon and can be used as a basis for future studies of anthropogenic and climatic perturbations.

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Rapid climate change results in long-lasting spatial homogenization of phylogenetic diversity

Nature Communications ◽

10.1038/s41467-020-18343-6 ◽

2020 ◽

Vol 11 (1) ◽

Cited By ~ 1

Author(s):

Bianca Saladin ◽

Loïc Pellissier ◽

Catherine H. Graham ◽

Michael P. Nobis ◽

Nicolas Salamin ◽

...

Keyword(s):

Climate Change ◽

Spatial Variability ◽

Phylogenetic Diversity ◽

Climate Changes ◽

Northern Europe ◽

Seed Plants ◽

Climate Oscillations ◽

The Past ◽

Rapid Climate Change ◽

Insight Into

Abstract Scientific understanding of biodiversity dynamics, resulting from past climate oscillations and projections of future changes in biodiversity, has advanced over the past decade. Little is known about how these responses, past or future, are spatially connected. Analyzing the spatial variability in biodiversity provides insight into how climate change affects the accumulation of diversity across space. Here, we evaluate the spatial variation of phylogenetic diversity of European seed plants among neighboring sites and assess the effects of past rapid climate changes during the Quaternary on these patterns. Our work shows a marked homogenization in phylogenetic diversity across Central and Northern Europe linked to high climate change velocity and large distances to refugia. Our results suggest that the future projected loss in evolutionary heritage may be even more dramatic, as homogenization in response to rapid climate change has occurred among sites across large landscapes, leaving a legacy that has lasted for millennia.

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Spatial variability of climate change impacts on yield of rice and wheat in the Indian Ganga Basin

The Science of The Total Environment ◽

10.1016/j.scitotenv.2013.05.080 ◽

2013 ◽

Vol 468-469 ◽

pp. S132-S138 ◽

Cited By ~ 40

Author(s):

Ashok Mishra ◽

R. Singh ◽

N.S. Raghuwanshi ◽

C. Chatterjee ◽

Jochen Froebrich

Keyword(s):

Climate Change ◽

Spatial Variability ◽

Climate Change Impacts ◽

Ganga Basin

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Effects of climate change on coastal groundwater systems: A modeling study in the Netherlands

Water Resources Research ◽

10.1029/2009wr008719 ◽

2010 ◽

Vol 46 (10) ◽

Cited By ~ 157

Author(s):

G. H. P. Oude Essink ◽

E. S. van Baaren ◽

P. G. B. de Louw

Keyword(s):

Climate Change ◽

The Netherlands ◽

Coastal Groundwater ◽

Groundwater Systems ◽

Modeling Study

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Vine vigor, yield and grape quality assessment by airborne remote sensing over three years: Analysis of unexpected relationships in cv. Tempranillo

Spanish Journal of Agricultural Research ◽

10.5424/sjar/2015132-7809 ◽

2015 ◽

Vol 13 (2) ◽

pp. e0903 ◽

Cited By ~ 17

Author(s):

Irene Bonilla ◽

Fernando Martinez de Toda ◽

Jose Antonio Martínez-Casasnovas

Keyword(s):

Climate Change ◽

Remote Sensing ◽

Spatial Variability ◽

Vegetative Growth ◽

Multispectral Imagery ◽

Climate Conditions ◽

Ripening Process ◽

Stable Pattern ◽

Grape Quality ◽

High Spatial Variability

The prediction of grape composition is becoming more important due to the need of reducing the current levels of alcohol and pH of the wines, a problem that is exacerbated by climate change. This work presents a 3-year study of the spatial variability of grape composition in a rainfed Tempranillo vineyard located in Rioja (Spain). It is based on the acquisition of multispectral imagery at véraison (start of the ripening process); and zoning based on NDVI, to assess its performance for zonal management. The results reveal a high spatial variability within the plot, with a stable pattern over the years, even with very different climate conditions. NDVI was a good predictor of vegetative growth variables. However, the prediction of grape composition was more complex. Unexpectedly, anthocyanins were found to be higher in the highest vigor zone, which is probably related to the effects of climate change. This unexpected relationship is particularly discussed in the article.

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Climate change impacts on solar power generation and its spatial variability in Europe based on CMIP6

Earth System Dynamics ◽

10.5194/esd-12-1099-2021 ◽

2021 ◽

Vol 12 (4) ◽

pp. 1099-1113

Author(s):

Xinyuan Hou ◽

Martin Wild ◽

Doris Folini ◽

Stelios Kazadzis ◽

Jan Wohland

Keyword(s):

Climate Change ◽

Power Generation ◽

Spatial Variability ◽

Cloud Cover ◽

Climate Change Impacts ◽

Solar Pv ◽

Clear Sky ◽

Generation Structure ◽

Recent Climate ◽

Pv Power Generation

Abstract. Solar photovoltaics (PV) plays an essential role in decarbonizing the European energy system. However, climate change affects surface solar radiation and will therefore directly influence future PV power generation. We use scenarios from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) for a mitigation (SSP1-2.6) and a fossil-fuel-dependent (SSP5-8.5) pathway in order to quantify climate risk for solar PV in Europe as simulated by the Global Solar Energy Estimator (GSEE). We find that PV potential increases by around 5 % in the mitigation scenario, suggesting a positive feedback loop between climate change mitigation and PV potential. While increased clear-sky radiation and reduced cloud cover go hand in hand in SSP1-2.6, the effect of a decrease in clear-sky radiation is outweighed by a decrease in cloud cover in SSP5-8.5, resulting in an increase in all-sky radiation. Moreover, we find that the seasonal cycle of PV generation changes in most places, as generation grows more strongly in winter than in summer (SSP1-2.6) or increases in summer and declines in winter (SSP5-8.5). We further analyze climate change impacts on the spatial variability of PV power generation. Similar to the effects anticipated for wind energy, we report an increase in the spatial correlations of daily PV production with large inter-model agreement yet relatively small amplitude, implying that PV power balancing between different regions in continental Europe will become more difficult in the future. Thus, based on the most recent climate simulations, this research supports the notion that climate change will only marginally impact renewable energy potential, while changes in the spatiotemporal generation structure are to be expected and should be included in power system design.

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The Use of Environmental Isotope Techniques together with Conventional Methods in Regional Groundwater Studies

Hydrology Research ◽

10.2166/nh.1976.0007 ◽

1976 ◽

Vol 7 (2) ◽

pp. 81-94

Author(s):

Guttormur Sigbjarnarson ◽

Pall Theodorsson ◽

Bragi Arnason

Keyword(s):

Groundwater Flow ◽

Flow Pattern ◽

Environmental Isotopes ◽

Geological Exploration ◽

Environmental Isotope ◽

Mountain Ranges ◽

Geological Conditions ◽

Groundwater Systems ◽

Regional Groundwater ◽

Perched Aquifers

Regional hydrological investigations of the subsurface drainage in the neovolcanic area around lake Thorisvatn on the central Icelandic plateau have been carried out as well as geological exploration. Environmental isotopes, deuterium and tritium, proved decisive in finding the groundwater flow pattern and in separating the different groundwater systems and explaining local deviations as barriers and perched aquifers. The regional groundwater flow is only slightly dependent on the. topography but highly on the geological conditions, as it virtually flows under mountain ranges as well as under the river Tungnaa.

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