scholarly journals Application of SWAT Using Snow Data and Detecting Climate Change Impacts in the Mountainous Eastern Regions of Turkey

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1982
Author(s):  
Ismail Bilal Peker ◽  
Ali Arda Sorman
Keyword(s):  
Climate Change ◽  
Hydrological Modeling ◽  
Snow Water Equivalent ◽  
Climate Change Impacts ◽  
Model Parameters ◽  
Slight Reduction ◽  
Covered Area ◽  
Snow Water ◽  
Headwater Basins ◽  
Impacts Of Climate Change

In recent years, the potential impacts of climate change on water resources and the hydrologic cycle have gained importance especially for snow-dominated mountainous basins. Within this scope, the Euphrates–Tigris Basin, a snow-fed transboundary river with several large dams, was selected to investigate the effects of changing climate on seasonal snow and runoff. In this study, two headwater basins of the Euphrates River, ranging in elevation between 1500–3500 m, were assigned and SWAT was employed as a hydrological modeling tool. Model calibration and validation were conducted in a stepwise manner for snow and runoff consecutively. For the snow routine, model parameters were adjusted using MODIS daily snow-covered area, achieving hit rates of more than 95% between MODIS and SWAT. Other model parameters were calibrated successively and later validated according to daily runoff, reaching a Nash–Sutcliffe efficiency of 0.64–0.82 in both basins. After the modeling stage, the focus was drawn to the impacts of climate change under two different climate scenarios (RCP4.5 and RCP8.5) in two 30-year projection periods (2041–2070 and 2071–2099). From the results, it is estimated that on average snow water equivalent decreases in the order of 30–39% and snow-covered days shorten by 37–43 days for the two basins until 2099. In terms of runoff, a slight reduction of at most 5% on average volume is projected but more notably, runoff center-time is expected to shift 1–2 weeks earlier by the end of the century.

scholarly journals Projected cryospheric and hydrological impacts of 21st century climate change in the Ötztal Alps (Austria) simulated using a physically based approach

2018 ◽  
Vol 22 (2) ◽  
pp. 1593-1614 ◽  
Author(s):  
Florian Hanzer ◽  
Kristian Förster ◽  
Johanna Nemec ◽  
Ulrich Strasser
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Snow Water Equivalent ◽  
Climate Change Impacts ◽  
Future Climate Change ◽  
Climate Projections ◽  
Early 21St Century ◽  
Physically Based ◽  
Snow Water ◽  
High Elevations

Abstract. A physically based hydroclimatological model (AMUNDSEN) is used to assess future climate change impacts on the cryosphere and hydrology of the Ötztal Alps (Austria) until 2100. The model is run in 100 m spatial and 3 h temporal resolution using in total 31 downscaled, bias-corrected, and temporally disaggregated EURO-CORDEX climate projections for the representative concentration pathways (RCPs) 2.6, 4.5, and 8.5 scenarios as forcing data, making this – to date – the most detailed study for this region in terms of process representation and range of considered climate projections. Changes in snow coverage, glacierization, and hydrological regimes are discussed both for a larger area encompassing the Ötztal Alps (1850 km2, 862–3770 m a.s.l.) as well as for seven catchments in the area with varying size (11–165 km2) and glacierization (24–77 %). Results show generally declining snow amounts with moderate decreases (0–20 % depending on the emission scenario) of mean annual snow water equivalent in high elevations (> 2500 m a.s.l.) until the end of the century. The largest decreases, amounting to up to 25–80 %, are projected to occur in elevations below 1500 m a.s.l. Glaciers in the region will continue to retreat strongly, leaving only 4–20 % of the initial (as of 2006) ice volume left by 2100. Total and summer (JJA) runoff will change little during the early 21st century (2011–2040) with simulated decreases (compared to 1997–2006) of up to 11 % (total) and 13 % (summer) depending on catchment and scenario, whereas runoff volumes decrease by up to 39 % (total) and 47 % (summer) towards the end of the century (2071–2100), accompanied by a shift in peak flows from July towards June.

scholarly journals Projected cryospheric and hydrological impacts of 21st century climate change in the Ötztal Alps (Austria) simulated using a physically based approach

2017 ◽  
Author(s):  
Florian Hanzer ◽  
Kristian Förster ◽  
Johanna Nemec ◽  
Ulrich Strasser
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Snow Water Equivalent ◽  
Climate Change Impacts ◽  
Future Climate Change ◽  
Climate Projections ◽  
Early 21St Century ◽  
Physically Based ◽  
Snow Water ◽  
High Elevations

Abstract. A physically based hydroclimatological model (AMUNDSEN) is used to assess future climate change impacts on the cryosphere and hydrology of the Ötztal Alps (Austria) until 2100. The model is run in 100 m spatial and 3 h temporal resolution using in total 31 downscaled, bias-corrected, and temporally disaggregated EURO-CORDEX climate projections for the RCP2.6, RCP4.5, and RCP8.5 scenarios as forcing data. Changes in snow coverage, glacierization, and hydrological regimes are discussed both for a larger area encompassing the Ötztal Alps (1850 km2, 862–3770 m a.s.l.) as well as for seven catchments in the area with varying size (11–16 km2) and glacierization (24–77 %). Results show generally declining snow amounts with moderate decreases (0–20 % depending on the emission scenario) of mean annual snow water equivalent in high elevations (> 2500 m a.s.l.) until the end of the century, however decreases of 25–80 % in elevations below 1500 m a.s.l. Glaciers in the region will continue to retreat strongly, leaving only 4–20 % of the initial (as of 2006) ice volume left by 2100. Total and summer (JJA) runoff will change little during the early 21st century (2011–2040) with simulated decreases (compared to 1997–2006) of up to 11 % (total) and 13 % (summer) depending on catchment and scenario, whereas runoff volumes decrease by up to 39 % (total) and 47 % (summer) towards the end of the century (2071–2100), accompanied by a shift in peak flows from July towards June.

scholarly journals Climate change impacts on maritime mountain snowpack in the Oregon Cascades

2012 ◽  
Vol 9 (11) ◽  
pp. 13037-13081 ◽  
Author(s):  
E. Sproles ◽  
A. Nolin ◽  
K. Rittger ◽  
T. Painter
Keyword(s):  
Climate Change ◽  
Snow Water Equivalent ◽  
Regional Scale ◽  
Climate Change Impacts ◽  
Snow Accumulation ◽  
Distributed Model ◽  
Modeling Framework ◽  
Highly Sensitive ◽  
Snow Cover Extent ◽  
Snow Water

Abstract. Globally maritime snow comprises 10% of seasonal snow and is considered highly sensitive to changes in temperature. This study investigates the effect of climate change on maritime mountain snowpack in the McKenzie River Basin (MRB) in the Cascades Mountains of Oregon, USA. Melt water from the MRB's snowpack provides critical water supply for agriculture, ecosystems, and municipalities throughout the region especially in summer when water demand is high. Because maritime snow commonly falls at temperatures close to 0 °C, accumulation of snow versus rainfall is highly sensitive to temperature increases. Analyses of current climate and projected climate change impacts show rising temperatures in the region. To better understand the sensitivity of snow accumulation to increased temperatures, we modeled the spatial distribution of snow water equivalent (SWE) in the MRB for the period of 1989–2009 with the SnowModel spatially distributed model. Simulations were evaluated using point-based measurements of SWE, precipitation, and temperature that showed Nash-Sutcliffe Efficiency coefficients of 0.83, 0.97, and 0.80, respectively. Spatial accuracy was shown to be 82% using snow cover extent from the Landsat Thematic Mapper. The validated model was used to evaluate the sensitivity of snowpack to projected temperature increases and variability in precipitation, and how changes were expressed in the spatial and temporal distribution of SWE. Results show that a 2 °C increase in temperature would shift peak snowpack 12 days earlier and decrease basin-wide volumetric snow water storage by 56%. Snowpack between the elevations of 1000 and 1800 m is the most sensitive to increases in temperature. Upper elevations were also affected, but to a lesser degree. Temperature increases are the primary driver of diminished snowpack accumulation, however variability in precipitation produce discernible changes in the timing and volumetric storage of snowpack. This regional scale study serves as a case study, providing a modeling framework to better understand the impacts of climate change in similar maritime regions of the world.

scholarly journals Climate change impacts on maritime mountain snowpack in the Oregon Cascades

2013 ◽  
Vol 17 (7) ◽  
pp. 2581-2597 ◽  
Author(s):  
E. A. Sproles ◽  
A. W. Nolin ◽  
K. Rittger ◽  
T. H. Painter
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Snow Water Equivalent ◽  
Climate Change Impacts ◽  
Snow Cover Extent ◽  
Spatially Distributed ◽  
Primary Driver ◽  
Snow Water ◽  
Distributed Process ◽  
Oregon Cascades

Abstract. This study investigates the effect of projected temperature increases on maritime mountain snowpack in the McKenzie River Basin (MRB; 3041 km2) in the Cascades Mountains of Oregon, USA. We simulated the spatial distribution of snow water equivalent (SWE) in the MRB for the period of 1989–2009 with SnowModel, a spatially-distributed, process-based model (Liston and Elder, 2006b). Simulations were evaluated using point-based measurements of SWE, precipitation, and temperature that showed Nash-Sutcliffe Efficiency coefficients of 0.83, 0.97, and 0.80, respectively. Spatial accuracy was shown to be 82% using snow cover extent from the Landsat Thematic Mapper. The validated model then evaluated the inter- and intra-year sensitivity of basin wide snowpack to projected temperature increases (2 °C) and variability in precipitation (±10%). Results show that a 2 °C increase in temperature would shift the average date of peak snowpack 12 days earlier and decrease basin-wide volumetric snow water storage by 56%. Snowpack between the elevations of 1000 and 2000 m is the most sensitive to increases in temperature. Upper elevations were also affected, but to a lesser degree. Temperature increases are the primary driver of diminished snowpack accumulation, however variability in precipitation produce discernible changes in the timing and volumetric storage of snowpack. The results of this study are regionally relevant as melt water from the MRB's snowpack provides critical water supply for agriculture, ecosystems, and municipalities throughout the region especially in summer when water demand is high. While this research focused on one watershed, it serves as a case study examining the effects of climate change on maritime snow, which comprises 10% of the Earth's seasonal snow cover.

scholarly journals Assessing biophysical and socio-economic impacts of climate change on regional avian biodiversity

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Simon Kapitza ◽  
Pham Van Ha ◽  
Tom Kompas ◽  
Nick Golding ◽  
Natasha C. R. Cadenhead ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Change Impacts ◽  
Integrated Modelling ◽  
Land Use Patterns ◽  
Economic Changes ◽  
Use Patterns ◽  
Modelling Framework ◽  
Avian Biodiversity ◽  
Biodiversity Change ◽  
Impacts Of Climate Change

AbstractClimate change threatens biodiversity directly by influencing biophysical variables that drive species’ geographic distributions and indirectly through socio-economic changes that influence land use patterns, driven by global consumption, production and climate. To date, no detailed analyses have been produced that assess the relative importance of, or interaction between, these direct and indirect climate change impacts on biodiversity at large scales. Here, we apply a new integrated modelling framework to quantify the relative influence of biophysical and socio-economically mediated impacts on avian species in Vietnam and Australia and we find that socio-economically mediated impacts on suitable ranges are largely outweighed by biophysical impacts. However, by translating economic futures and shocks into spatially explicit predictions of biodiversity change, we now have the power to analyse in a consistent way outcomes for nature and people of any change to policy, regulation, trading conditions or consumption trend at any scale from sub-national to global.

scholarly journals Assessment of MERRA-2 and ERA5 to Model the Snow Water Equivalent in the High Atlas (1981–2019)

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 890
Author(s):  
Mohamed Wassim Baba ◽  
Abdelghani Boudhar ◽  
Simon Gascoin ◽  
Lahoucine Hanich ◽  
Ahmed Marchane ◽  
...  
Keyword(s):  
River Discharge ◽  
Snow Water Equivalent ◽  
High Elevation ◽  
Water Runoff ◽  
High Atlas ◽  
Seasonal Snow ◽  
Snow Covered Area ◽  
Covered Area ◽  
Snow Water

Melt water runoff from seasonal snow in the High Atlas range is an essential water resource in Morocco. However, there are only few meteorological stations in the high elevation areas and therefore it is challenging to estimate the distribution of snow water equivalent (SWE) based only on in situ measurements. In this work we assessed the performance of ERA5 and MERRA-2 climate reanalysis to compute the spatial distribution of SWE in the High Atlas. We forced a distributed snowpack evolution model (SnowModel) with downscaled ERA5 and MERRA-2 data at 200 m spatial resolution. The model was run over the period 1981 to 2019 (37 water years). Model outputs were assessed using observations of river discharge, snow height and MODIS snow-covered area. The results show a good performance for both MERRA-2 and ERA5 in terms of reproducing the snowpack state for the majority of water years, with a lower bias using ERA5 forcing.

scholarly journals Nimbus-7 SMMR Derived Global Snow Cover Parameters

1987 ◽  
Vol 9 ◽  
pp. 39-44 ◽  
Author(s):  
A.T.C. Chang ◽  
J.L. Foster ◽  
D.K. Hall
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Snow Water Equivalent ◽  
Theoretical Calculations ◽  
Winter Season ◽  
Western China ◽  
High Plains ◽  
Snow Covered Area ◽  
Covered Area ◽  
Snow Water

Snow covers about 40 million km2of the land area of the Northern Hemisphere during the winter season. The accumulation and depletion of snow is dynamically coupled with global hydrological and climatological processes. Snow covered area and snow water equivalent are two essential measurements. Snow cover maps are produced routinely by the National Environmental Satellite Data and Information Service of the National Oceanic and Atmospheric Administration (NOAA/NESDIS) and by the US Air Force Global Weather Center (USAFGWC). The snow covered area reported by these two groups sometimes differs by several million km2, Preliminary analysis is performed to evaluate the accuracy of these products.Microwave radiation penetrating through clouds and snowpacks could provide depth and water equivalent information about snow fields. Based on theoretical calculations, snow covered area and snow water equivalent retrieval algorithms have been developed. Snow cover maps for the Northern Hemisphere have been derived from Nimbus-7 SMMR data for a period of six years (1978–1984). Intercomparisons of SMMR, NOAA/NESDIS and USAFGWC snow maps have been conducted to evaluate and assess the accuracy of SMMR derived snow maps. The total snow covered area derived from SMMR is usually about 10% less than the other two products. This is because passive microwave sensors cannot detect shallow, dry snow which is less than 5 cm in depth. The major geographic regions in which the differences among these three products are the greatest are in central Asia and western China. Future study is required to determine the absolute accuracy of each product.Preliminary snow water equivalent maps have also been produced. Comparisons are made between retrieved snow water equivalent over large area and available snow depth measurements. The results of the comparisons are good for uniform snow covered areas, such as the Canadian high plains and the Russian steppes. Heavily forested and mountainous areas tend to mask out the microwave snow signatures and thus comparisons with measured water equivalent are poorer in those areas.

scholarly journals Nimbus-7 SMMR Derived Global Snow Cover Parameters

1987 ◽  
Vol 9 ◽  
pp. 39-44 ◽  
Author(s):  
A.T.C. Chang ◽  
J.L. Foster ◽  
D.K. Hall
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Snow Water Equivalent ◽  
Theoretical Calculations ◽  
Winter Season ◽  
Western China ◽  
High Plains ◽  
Snow Covered Area ◽  
Covered Area ◽  
Snow Water

Snow covers about 40 million km2 of the land area of the Northern Hemisphere during the winter season. The accumulation and depletion of snow is dynamically coupled with global hydrological and climatological processes. Snow covered area and snow water equivalent are two essential measurements. Snow cover maps are produced routinely by the National Environmental Satellite Data and Information Service of the National Oceanic and Atmospheric Administration (NOAA/NESDIS) and by the US Air Force Global Weather Center (USAFGWC). The snow covered area reported by these two groups sometimes differs by several million km2, Preliminary analysis is performed to evaluate the accuracy of these products.Microwave radiation penetrating through clouds and snowpacks could provide depth and water equivalent information about snow fields. Based on theoretical calculations, snow covered area and snow water equivalent retrieval algorithms have been developed. Snow cover maps for the Northern Hemisphere have been derived from Nimbus-7 SMMR data for a period of six years (1978–1984). Intercomparisons of SMMR, NOAA/NESDIS and USAFGWC snow maps have been conducted to evaluate and assess the accuracy of SMMR derived snow maps. The total snow covered area derived from SMMR is usually about 10% less than the other two products. This is because passive microwave sensors cannot detect shallow, dry snow which is less than 5 cm in depth. The major geographic regions in which the differences among these three products are the greatest are in central Asia and western China. Future study is required to determine the absolute accuracy of each product.Preliminary snow water equivalent maps have also been produced. Comparisons are made between retrieved snow water equivalent over large area and available snow depth measurements. The results of the comparisons are good for uniform snow covered areas, such as the Canadian high plains and the Russian steppes. Heavily forested and mountainous areas tend to mask out the microwave snow signatures and thus comparisons with measured water equivalent are poorer in those areas.

scholarly journals Climate change impacts model parameter sensitivity – What does this mean for calibration?

2020 ◽  
Author(s):  
Lieke Anna Melsen ◽  
Björn Guse
Keyword(s):  
Climate Change ◽  
Climate Change Impacts ◽  
The United States ◽  
Parameter Sensitivity ◽  
Model Parameters ◽  
Hydrological Models ◽  
The Future ◽  
Influence Parameter ◽  
Sensitivity Changes ◽  
Sensitive Parameters

Abstract. Hydrological models are useful tools to explore the hydrological impact of climate change. Many of these models require calibration. A frequently employed strategy is to calibrate the five parameters that were found to be most relevant as identified in a sensitivity analysis. However, parameter sensitivity varies over climate, and therefore climate change could influence parameter sensitivity. In this study we explore the change in parameter sensitivity within a plausible climate change rate, and investigate if changes in sensitivity propagate into the calibration strategy. We employed three frequently used hydrological models (SAC, VIC, and HBV), and explored parameter sensitivity changes across 605 catchments in the United States by comparing a GCM-forced historical and future period. Consistent among all models is that the sensitivity of snow parameters decreases in the future. Which parameters increase in sensitivity is less consistent among the models. In 43 % to 49 % of the catchments, dependent on the model, at least one parameter changes in the future in the top-5 most sensitive parameters. The maximum number of changes in the parameter top-5 is two, in 2–4 % of the investigated catchments. The value of the parameters that enter the top-5 cannot easily be identified based on historical data, because the model is not yet sensitive to these parameters. This requires an adapted calibration strategy for long-term projections, for which we provide several suggestions. The disagreement among the models on processes becoming relevant in future projections also calls for a strict evaluation of the adequacy of the model structure and the model parameters implemented therein.

scholarly journals Possible adaptation measures of agriculture sector in the Nile Delta to climate change impacts

2009 ◽  
Vol 3 (1) ◽  
pp. 123-126 ◽  
Author(s):  
S. M. Attaher ◽  
M. A. Medany ◽  
A. F. Abou-Hadid
Keyword(s):  
Climate Change ◽  
Nile Delta ◽  
Climate Change Impacts ◽  
Yield Reduction ◽  
Agricultural System ◽  
Delta Region ◽  
Adaptation Measures ◽  
Agriculture Sector ◽  
The World ◽  
Impacts Of Climate Change

Abstract. The overall agricultural system in the Nile Delta region is considered as one of the highest intensive and complicated agriculture systems in the world. According to the recent studies, the Nile Delta region is one of the highly vulnerable regions in the world to climate change. Sea level rise, soil and water degradation, undiversified crop-pattern, yield reduction, pests and disease severity, and irrigation and drainage management were the main key factors that increased vulnerability of the agriculture sector in that region. The main objective of this study is to conduct a community-based multi-criteria adaptation assessment in the Nile Delta using a preset questionnaire. A list of possible adaptation measures for agriculture sector was evaluated. The results indicated that the Nile Delta growers have strong perceptions to act positively to reduce the impacts of climate change. They reflected the need to improve the their adaptive capacity based on clear scientific message with adequate governmental support to coop with the negative impacts of climate change.

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