The potential effects of anthropogenic climate change on evaporation from water storage reservoirs within the Lockyer Catchment, south-east Queensland, Australia

2016 ◽  
Vol 67 (10) ◽  
pp. 1512 ◽  
Author(s):  
Ryan McGloin ◽  
Hamish McGowan ◽  
David McJannet
Keyword(s):  
Climate Change ◽  
Water Storage ◽  
Annual Runoff ◽  
Anthropogenic Climate Change ◽  
Annual Rainfall ◽  
Air Temperatures ◽  
Storage Reservoirs ◽  
The Future ◽  
Long Term Trends

In order to effectively manage water storage reservoirs, it is essential to be able to anticipate how components of the water balance will react to predicted long-term trends in climate. This study examines the potential impacts of anthropogenic climate change on evaporation from small reservoirs in the Lockyer catchment, a productive agricultural region in south-east Queensland, Australia. Future projections of evaporation, made using the most likely future emissions scenario, suggested that evaporation is expected to increase by ~6% by the year 2050. In addition, rainfall is expected to decrease by ~8%. These projected increases in evaporation and reductions in rainfall, combined with the knowledge that changes in annual rainfall are known to be amplified in annual runoff, mean that the availability of water resources in the Lockyer catchment region may be greatly diminished in the future. In addition, increases in water scarcity, combined with higher future air temperatures and population growth, are likely to result in a greater demand for irrigation in the future.

scholarly journals Long-term trends of climate change and its impact on crop growing season on Montreal Island

2016 ◽  
Vol 8 (1) ◽  
pp. 78-88
Author(s):  
Erika Bouchard ◽  
Zhiming Qi
Keyword(s):  
Climate Change ◽  
Daily Rainfall ◽  
Growing Season ◽  
Annual Rainfall ◽  
Climate Trends ◽  
Growing Season Length ◽  
Mk Test ◽  
Long Term Trends ◽  
Increasing Trends

Long-term trends in air temperature and precipitation under climate change were analyzed for two meteorological stations on the Island of Montreal: McGill (1872–1986) and Pierre-Elliott-Trudeau (P-E-T, formerly Dorval) Airport (1942–2014). A linear trendline analysis, the Mann–Kendall (MK) test and the two-sample Kolmogorov–Smirnov (KS) test were conducted to assess specific climate trends. On a 100-year basis, temperature increased 1.88°C (34%) and 1.18°C (19%) at the McGill and P-E-T Airport sites, respectively, while annual rainfall increased 23.9 mm y−1 (2.3%) and 138.8 mm y−1 (15%) over the same period. The frequency of 50% (every other year) and 95% (every year) annual maximum daily rainfall events showed decreasing trends for the McGill station, but increasing trends for the P-E-T Airport station. Growing degree-days and growing season length are prone to being influenced by climate change and are critical to managing agricultural activities in the Montreal region; both showed increasing trends. At the same time, the onset of the growing season occurred earlier as time progressed.

scholarly journals Maps, trends, and temperature sensitivities—phenological information from and for decreasing numbers of volunteer observers

2021 ◽  
Author(s):  
Ye Yuan ◽  
Stefan Härer ◽  
Tobias Ottenheym ◽  
Gourav Misra ◽  
Alissa Lüpke ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Strong Decrease ◽  
Temperature Changes ◽  
Interpolation Accuracy ◽  
Observation Network ◽  
Shiny App ◽  
Long Term Trends ◽  
Autumn And Winter

AbstractPhenology serves as a major indicator of ongoing climate change. Long-term phenological observations are critically important for tracking and communicating these changes. The phenological observation network across Germany is operated by the National Meteorological Service with a major contribution from volunteering activities. However, the number of observers has strongly decreased for the last decades, possibly resulting in increasing uncertainties when extracting reliable phenological information from map interpolation. We studied uncertainties in interpolated maps from decreasing phenological records, by comparing long-term trends based on grid-based interpolated and station-wise observed time series, as well as their correlations with temperature. Interpolated maps in spring were characterized by the largest spatial variabilities across Bavaria, Germany, with respective lowest interpolated uncertainties. Long-term phenological trends for both interpolations and observations exhibited mean advances of −0.2 to −0.3 days year−1 for spring and summer, while late autumn and winter showed a delay of around 0.1 days year−1. Throughout the year, temperature sensitivities were consistently stronger for interpolated time series than observations. Such a better representation of regional phenology by interpolation was equally supported by satellite-derived phenological indices. Nevertheless, simulation of observer numbers indicated that a decline to less than 40% leads to a strong decrease in interpolation accuracy. To better understand the risk of declining phenological observations and to motivate volunteer observers, a Shiny app is proposed to visualize spatial and temporal phenological patterns across Bavaria and their links to climate change–induced temperature changes.

scholarly journals Forest insects and climate change: long-term trends in herbivore damage

2013 ◽  
Vol 3 (12) ◽  
pp. 4183-4196 ◽  
Author(s):  
Maartje J. Klapwijk ◽  
György Csóka ◽  
Anikó Hirka ◽  
Christer Björkman
Keyword(s):  
Climate Change ◽  
Herbivore Damage ◽  
Forest Insects ◽  
Long Term Trends

Projecting conflict risk following the Shared Socioeconomic pathways: what role for water stress and climate?

2021 ◽  
Author(s):  
Sophie de Bruin ◽  
Jannis Hoch ◽  
Nina von Uexkull ◽  
Halvard Buhaug ◽  
Nico Wanders
Keyword(s):  
Climate Change ◽  
At Risk ◽  
Machine Learning Techniques ◽  
Mitigation Measures ◽  
Related Factors ◽  
Socioeconomic Impacts ◽  
Learning Techniques ◽  
The Future ◽  
Conflict Risk

<p>The socioeconomic impacts of changes in climate-related and hydrology-related factors are increasingly acknowledged to affect the on-set of violent conflict. Full consensus upon the general mechanisms linking these factors with conflict is, however, still limited. The absence of full understanding of the non-linearities between all components and the lack of sufficient data make it therefore hard to address violent conflict risk on the long-term. </p><p>Although it is neither desirable nor feasible to make exact predictions, projections are a viable means to provide insights into potential future conflict risks and uncertainties thereof. Hence, making different projections is a legitimate way to deal with and understand these uncertainties, since the construction of diverse scenarios delivers insights into possible realizations of the future.  </p><p>Through machine learning techniques, we (re)assess the major drivers of conflict for the current situation in Africa, which are then applied to project the regions-at-risk following different scenarios. The model shows to accurately reproduce observed historic patterns leading to a high ROC score of 0.91. We show that socio-economic factors are most dominant when projecting conflicts over the African continent. The projections show that there is an overall reduction in conflict risk as a result of increased economic welfare that offsets the adverse impacts of climate change and hydrologic variables. It must be noted, however, that these projections are based on current relations. In case the relations of drivers and conflict change in the future, the resulting regions-at-risk may change too.   By identifying the most prominent drivers, conflict risk mitigation measures can be tuned more accurately to reduce the direct and indirect consequences of climate change on the population in Africa. As new and improved data becomes available, the model can be updated for more robust projections of conflict risk in Africa under climate change.</p>

scholarly journals Examining the Climatology of Shortwave Radiation in the Northeastern United States

2017 ◽  
Vol 56 (10) ◽  
pp. 2869-2881
Author(s):  
Janel Hanrahan ◽  
Alexandria Maynard ◽  
Sarah Y. Murphy ◽  
Colton Zercher ◽  
Allison Fitzpatrick
Keyword(s):  
Climate Change ◽  
United States ◽  
Renewable Energy ◽  
Renewable Energy Sources ◽  
Predictor Variable ◽  
Shortwave Radiation ◽  
Northeastern United States ◽  
Weather Patterns ◽  
Long Term Trends

AbstractAs demand for renewable energy grows, so does the need for an improved understanding of renewable energy sources. Paradoxically, the climate change mitigation strategy of fossil fuel divestment is in itself subject to shifts in weather patterns resulting from climate change. This is particularly true with solar power, which depends on local cloud cover. However, because observed shortwave radiation data usually span a decade or less, persistent long-term trends may not be identified. A simple linear regression model is created here using diurnal temperature range (DTR) during 2002–15 as a predictor variable to estimate long-term shortwave radiation (SR) values in the northeastern United States. Using an extended DTR dataset, SR values are computed for 1956–2015. Statistically significant decreases in shortwave radiation are identified that are dominated by changes during the summer months. Because this coincides with the season of greatest insolation and the highest potential for energy production, financial implications may be large for the solar energy industry if such trends persist into the future.

scholarly journals Estimation of Water Storage Changes in Small Endorheic Lakes in Northern Kazakhstan; The Effect of Climate Change and Anthropogenic Influences 

2017 ◽  
Author(s):  
Vadim Yapiyev ◽  
Kanat Samarkhanov ◽  
Dauren Zhumabayev ◽  
Nazym Tulegenova ◽  
Saltanat Jumassultanova ◽  
...  
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Water Resources ◽  
Water Balance ◽  
Climate Model ◽  
Human Impacts ◽  
Water Storage ◽  
Minor Importance ◽  
Climatic Data

Both climate change and anthropogenic activities contribute to the deterioration of terrestrial water resources and ecosystems worldwide. Central Asian endorheic basins are among the most affected regions through both climate and human impacts. Here, we used a digital elevation model, digitized bathymetry maps and Landsat images to estimate the areal water cover extent and volumetric storage changes in small terminal lakes in Burabay National Nature Park (BNNP), located in Northern Central Asia (CA), for the period of 1986 to 2016. Based on the analysis of long-term climatic data from meteorological stations, short-term hydrometeorological network observations, gridded climate datasets (CRU) and global atmospheric reanalysis (ERA Interim), we have evaluated the impacts of historical climatic conditions on the water balance of BNNP lake catchments. We also discuss the future based on regional climate model projections. We attribute the overall decline of BNNP lakes to long-term deficit of water balance with lake evaporation loss exceeding precipitation inputs. Direct anthropogenic water abstraction has a minor importance in water balance. However, the changes in watersheds caused by the expansion of human settlements and roads disrupting water drainage may play a more significant role in lake water storage decline. More precise water resources assessment at the local scale will be facilitated by further development of freely available higher spatial resolution remote sensing products. In addition, the results of this work can be used for the development of lake/reservoir evaporation models driven by remote sensing and atmospheric reanalysis data without the direct use of ground observations.

scholarly journals An evaluation of the effect of future climate on runoff in the Dongjiang River basin, South China

2015 ◽  
Vol 368 ◽  
pp. 257-262
Author(s):  
K. Lin ◽  
W. Zhai ◽  
S. Huang ◽  
Z. Liu
Keyword(s):  
Climate Change ◽  
River Basin ◽  
South China ◽  
Annual Runoff ◽  
Future Climate ◽  
Weather Data ◽  
Future Climate Change ◽  
Dongjiang River ◽  
The Future ◽  
The Impact

Abstract. The impact of future climate change on the runoff for the Dongjiang River basin, South China, has been investigated with the Soil and Water Assessment Tool (SWAT). First, the SWAT model was applied in the three sub-basins of the Dongjiang River basin, and calibrated for the period of 1970–1975, and validated for the period of 1976–1985. Then the hydrological response under climate change and land use scenario in the next 40 years (2011–2050) was studied. The future weather data was generated by using the weather generators of SWAT, based on the trend of the observed data series (1966–2005). The results showed that under the future climate change and LUCC scenario, the annual runoff of the three sub-basins all decreased. Its impacts on annual runoff were –6.87%, –6.54%, and –18.16% for the Shuntian, Lantang, and Yuecheng sub-basins respectively, compared with the baseline period 1966–2005. The results of this study could be a reference for regional water resources management since Dongjiang River provides crucial water supplies to Guangdong Province and the District of Hong Kong in China.

scholarly journals A Hydrological Modeling Approach for Assessing the Impacts of Climate Change on Runoff Regimes in Slovakia

Water ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 3358
Author(s):  
Patrik Sleziak ◽  
Roman Výleta ◽  
Kamila Hlavčová ◽  
Michaela Danáčová ◽  
Milica Aleksić ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Hydrological Modeling ◽  
Performance Metrics ◽  
Climate Change Scenarios ◽  
Reference Period ◽  
Changing Climate ◽  
Time Horizons ◽  
The Future

The changing climate is a concern with regard to sustainable water resources. Projections of the runoff in future climate conditions are needed for long-term planning of water resources and flood protection. In this study, we evaluate the possible climate change impacts on the runoff regime in eight selected basins located in the whole territory of Slovakia. The projected runoff in the basins studied for the reference period (1981–2010) and three future time horizons (2011–2040, 2041–2070, and 2071–2100) was simulated using the HBV (Hydrologiska Byråns Vattenbalansavdelning) bucket-type model (the TUW (Technische Universität Wien) model). A calibration strategy based on the selection of the most suitable decade in the observation period for the parameterization of the model was applied. The model was first calibrated using observations, and then was driven by the precipitation and air temperatures projected by the KNMI (Koninklijk Nederlands Meteorologisch Instituut) and MPI (Max Planck Institute) regional climate models (RCM) under the A1B emission scenario. The model’s performance metrics and a visual inspection showed that the simulated runoff using downscaled inputs from both RCM models for the reference period represents the simulated hydrological regimes well. An evaluation of the future, which was performed by considering the representative climate change scenarios, indicated that changes in the long-term runoff’s seasonality and extremality could be expected in the future. In the winter months, the runoff should increase, and decrease in the summer months compared to the reference period. The maximum annual daily runoff could be more extreme for the later time horizons (according to the KNMI scenario for 2071–2100). The results from this study could be useful for policymakers and river basin authorities for the optimum planning and management of water resources under a changing climate.

Long-term trends in seasonal plankton dynamics in Lake Mead (Nevada-Arizona, USA) and implications for climate change

Hydrobiologia ◽  
2018 ◽  
Vol 822 (1) ◽  
pp. 85-109 ◽  
Author(s):  
John R. Beaver ◽  
Janet E. Kirsch ◽  
Claudia E. Tausz ◽  
Erin E. Samples ◽  
Thomas R. Renicker ◽  
...  
Keyword(s):  
Climate Change ◽  
Lake Mead ◽  
Plankton Dynamics ◽  
Long Term Trends

The «rainfall-runoff» system and its long-term fluctuations in the Siverskyi Donets River Basin (Ukraine)

2021 ◽  
Author(s):  
Hanna Bolbot ◽  
Vasyl Grebin
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
River Basin ◽  
Air Temperature ◽  
River Runoff ◽  
Annual Runoff ◽  
Annual Precipitation ◽  
Spring Flood ◽  
Current Period

<p>The current patterns estimation of the water regime under climate change is one of the most urgent tasks in Ukraine and the world. Such changes are determined by fluctuations in the main climatic characteristics - precipitation and air temperature, which are defined the value of evaporation. These parameters influence on the annual runoff distribution and long-term runoff fluctuations. In particular, the annual precipitation redistribution is reflected in the corresponding changes in the river runoff.<br>The assessment of the current state and nature of changes in precipitation and river runoff of the Siverskyi Donets River Basin was made by comparing the current period (1991-2018) with the period of the climatological normal (1961-1990).<br>In general, for this area, it was defined the close relationship between the amount of precipitation and the annual runoff. Against the background of insignificant (about 1%) increase of annual precipitation in recent decades, it was revealed their redistribution by seasons and separate months. There is a decrease in precipitation in the cold period (November-February). This causes (along with other factors) a decrease in the amount of snow and, accordingly, the spring flood runoff. There are frequent cases of unexpressed spring floods of the Siverskyi Donets River Basin. The runoff during March-April (the period of spring flood within the Ukrainian part of the basin) decreased by almost a third.<br>The increase of precipitation during May-June causes a corresponding (insignificant) increase in runoff in these months. The shift of the maximum monthly amount of precipitation from May (for the period 1961-1990) to June (in the current period) is observed.<br>There is a certain threat to water supply in the region due to the shift in the minimum monthly amount of precipitation in the warm period from October to August. Compared with October, there is a higher air temperature and, accordingly, higher evaporation in August, which reduces the runoff. Such a situation is solved by rational water resources management of the basin. The possibility of replenishing water resources in the basin through the transfer runoff from the Dnieper (Dnieper-Siverskyi Donets channel) and the annual runoff redistribution in the reservoir system causes some increase in the river runoff of summer months in recent decades. This is also contributed by the activities of the river basin management structures, which control the maintenance water users' of minimum ecological flow downstream the water intakes and hydraulic structures in the rivers of the basin.<br>Therefore, in the period of current climate change, the annual runoff distribution of the Siverskyi Donets River Basin has undergone significant changes, which is related to the annual precipitation redistribution and anthropogenic load on the basin.</p>

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