scholarly journals A water availability and low-flow analysis of the Tagliamento River discharge in Italy under changing climate conditions

2012 ◽  
Vol 16 (3) ◽  
pp. 1033-1045 ◽  
Author(s):  
L. N. Gunawardhana ◽  
S. Kazama
Keyword(s):  
River Discharge ◽  
General Circulation ◽  
Flow Analysis ◽  
Low Flow ◽  
Climate Conditions ◽  
Changing Climate ◽  
Time Period ◽  
Lower Elevation ◽  
Pearson Type ◽  
Tagliamento River

Abstract. This study estimated the effects of projected variations in precipitation and temperature on snowfall-snowmelt processes and subsequent river discharge variations in the Tagliamento River in Italy. A lumped-parameter, non-linear, rainfall-runoff model with 10 general circulation model (GCM) scenarios was used. Spatial and temporal changes in snow cover were assessed using 15 high-quality Landsat images. The 7Q10 low-flow probability distribution approximated by the Log-Pearson type III distribution function was used to examine river discharge variations with respect to climate extremes in the future. On average, the results obtained for 10 scenarios indicate a consistent warming rate for all time periods, which may increase the maximum and minimum temperatures by 2.3 °C (0.6–3.7 °C) and 2.7 °C (1.0–4.0 °C), respectively, by the end of the 21st century compared to the present climate. Consequently, the exponential rate of frost day decrease for 1 °C winter warming in lower-elevation areas is approximately three-fold (262%) higher than that in higher-elevation areas, revealing that snowfall in lower-elevation areas will be more vulnerable under a changing climate. In spite of the relatively minor changes in annual precipitation (−17.4 ~ 1.7% compared to the average of the baseline (1991–2010) period), snowfall will likely decrease by 48–67% during the 2080–2099 time period. The mean river discharges are projected to decrease in all seasons, except winter. The low-flow analysis indicated that while the magnitude of the minimum river discharge will increase (e.g. a 25% increase in the 7Q10 estimations for the winter season in the 2080–2099 time period), the number of annual average low-flow events will also increase (e.g. 16 and 15 more days during the spring and summer seasons, respectively, in the 2080–2099 time period compared to the average during the baseline period), leading to a future with a highly variable river discharge. Moreover, a consistent shift in river discharge timing would eventually cause snowmelt-generated river discharge to occur approximately 12 days earlier during the 2080–2099 time period compared to the baseline climate. These results are expected to raise the concern of policy makers, leading to the development of new water management strategies in the Tagliamento River basin to cope with changing climate conditions.

scholarly journals A water availability and low-flow analysis of the Tagliamento River discharge in Italy under changing climate conditions

2012 ◽  
Vol 9 (1) ◽  
pp. 139-173 ◽  
Author(s):  
L. N. Gunawardhana ◽  
S. Kazama
Keyword(s):  
River Discharge ◽  
Flow Analysis ◽  
Low Flow ◽  
Present Climate ◽  
Climate Conditions ◽  
Changing Climate ◽  
Time Period ◽  
Lower Elevation ◽  
Tagliamento River ◽  
Time Periods

Abstract. This study estimated the effects of projected variations in precipitation and temperature on snowfall-snowmelt processes and subsequent river discharge variations in the Tagliamento River in Italy. A lumped-parameter, non-linear, rainfall-runoff model with 10 general circulation model (GCM) scenarios was used to capture river response variations attributed to climate-driven changes in 3 future time periods in comparison to the present climate. Spatial and temporal changes in snow cover were assessed using 15 high-quality Landsat images collected during the 2001–2003 time period, which were further used to define different elevation bands to incorporate the elevation effects on snowfall-snowmelt processes. The 7Q10 low-flow probability distribution approximated by the Log-Pearson type III distribution function was used to examine river discharge variations with respect to climate extremes in the future. On average, the results obtained for 10 scenarios indicate a consistent warming rate for all time periods, which may increase the maximum and minimum temperatures by 2.3 °C (0.6–3.7 °C) and 2.7 °C (1.0–4.0 °C), respectively, by the end of the 21st century compared to the present climate. Consequently, the exponential rate of frost day decrease for 1 °C winter warming in lower-elevation areas is approximately three-fold (262%) higher than that in higher-elevation areas, revealing that snowfall in lower-elevation areas will be more vulnerable under a changing climate. In spite of the relatively minor changes in annual precipitation (−17.4 ~ 1.7% compared to the average of the baseline (1991–2010) period), snowfall will likely decrease by 48–67% during the 2080–2099 time period. The accumulated effects of a decrease in winter precipitation and an increase in evapotranspiration demand on winter river discharge will likely be compensated for by early snowmelt runoff due to increases in winter temperatures. Nevertheless, the river discharge in other seasons will decrease significantly, with a 59% decrease in the predicted river discharge in October over 100 yr. The low-flow analysis indicated that while the magnitude of the minimum river discharge will increase (e.g. a 25% increase in the 7Q10 estimations for the winter season in the 2080–2099 time period), the number of annual average low-flow events will also increase (e.g. 16 and 15 more days during the spring and summer seasons, respectively, in the 2080–2099 time period compared to the average during the baseline period), leading to a future with a highly variable river discharge. Moreover, a consistent shift in river discharge timing would eventually cause snowmelt-generated river discharge to occur approximately 12 days earlier during the 2080–2099 time period compared to the baseline climate. These results are expected to raise the concern of policy makers, leading to the development of new water management strategies in the Tagliamento River basin to cope with changing climate conditions.

scholarly journals Frequency Analysis of Low Flows

1985 ◽  
Vol 16 (2) ◽  
pp. 105-128 ◽  
Author(s):  
G. V. Loganathan ◽  
C. Y. Kuo ◽  
T. C. McCormick
Keyword(s):  
Lower Bounds ◽  
Frequency Analysis ◽  
Probability Distributions ◽  
Flow Analysis ◽  
Extreme Value ◽  
Low Flow ◽  
Type Iii ◽  
Low Flows ◽  
Pearson Type

The transformations (i) SMEMAX (ii) Modified SMEMAX (iii) Power and Probability Distributions (iv) Weibull (α,β,γ) or Extreme value type III (v) Weibull (α,β,0) (vi) Log Pearson Type III (vii) Log Boughton are considered for the low flow analysis. Also, different parameter estimating procedures are considered. Both the Weibull and log Pearson can have positive lower bounds and thus their use in fitting low flow probabilities may not be physically justifiable. A new derivation generalizing the SMEMAX transformation is proposed. A new estimator for the log Boughton distribution is presented. It is found that the Boughton distribution with Cunnane's plotting position provides a good fit to low flows for Virginia streams.

scholarly journals Comparison of Distribution Methods of Low Flow Analysis for Bandar Segamat, Johor

2015 ◽  
Vol 773-774 ◽  
pp. 1266-1270
Author(s):  
Yuliarahmadila Erfen ◽  
Mohd Shalahuddin Adnan ◽  
Noorfathiah Che Ali ◽  
Nurul Farehah Amat ◽  
Zawani Mohd Zahudi
Keyword(s):  
Stream Flow ◽  
Transition Period ◽  
Monsoon Season ◽  
Flow Analysis ◽  
Gumbel Distribution ◽  
Low Flow ◽  
Flow Data ◽  
Type Iii ◽  
Pearson Type ◽  
Pearson Type Iii Distribution

During the monsoon season, certain areas in Malaysia are experiencing a flood. While during the transition period Malaysia is experiencing a drought. This phenomenon could lead to severe disaster and precaution monitoring is needed to avoid this occurrences. Low flow during the dry season could lead to several negative effects on the river ecosystem. Thus, this study was conducted to determine the low flow frequency and intensity for the Segamat city. The duration for 2 years to 100 years based on the previous 20 years of stream flow data were used to calculated. Stream flow data were obtained from the Department of Irrigation and Drainage (DID). Two prominent distribution analyses methods known as Gumbel Distribution and Log pearson Type III Distribution were applied. The distribution results were validated using Root Mean Square Error (RMSE) and California method and Weibull method are selected. Based on the analyses results, it clearly shows that the distibution of low flow are between 1 m3/s to 10 m3/s. The flow are significantly correlate with the rainfall intensity. RMSE was selected based on the lowest value of 0.721 for the Gumble Distribution and 1.831 for Log Pearson Type III Distribution. Chi-square test shows a good agreement for Gumble Distribution (7.615<12.59) and Log Pearson Type III(5.201<11.07) using 5% significant level. The confident level form both tests are valid (p>0.05), thus, this results could be used for further analyses to alleviate the low flow in the study area.

scholarly journals Potential shift from a carbon sink to a source in Amazonian peatlands under a changing climate

2018 ◽  
Vol 115 (49) ◽  
pp. 12407-12412 ◽  
Author(s):  
Sirui Wang ◽  
Qianlai Zhuang ◽  
Outi Lähteenoja ◽  
Frederick C. Draper ◽  
Hinsby Cadillo-Quiroz
Keyword(s):  
21St Century ◽  
Carbon Sink ◽  
Accumulation Rate ◽  
Foreland Basin ◽  
Carbon Accumulation ◽  
Climate Conditions ◽  
Changing Climate ◽  
Soil Carbon Density ◽  
Increasing Precipitation ◽  
Aerobic And Anaerobic

Amazonian peatlands store a large amount of soil organic carbon (SOC), and its fate under a future changing climate is unknown. Here, we use a process-based peatland biogeochemistry model to quantify the carbon accumulation for peatland and nonpeatland ecosystems in the Pastaza-Marañon foreland basin (PMFB) in the Peruvian Amazon from 12,000 y before present to AD 2100. Model simulations indicate that warming accelerates peat SOC loss, while increasing precipitation accelerates peat SOC accumulation at millennial time scales. The uncertain parameters and spatial variation of climate are significant sources of uncertainty to modeled peat carbon accumulation. Under warmer and presumably wetter conditions over the 21st century, SOC accumulation rate in the PMFB slows down to 7.9 (4.3–12.2) g⋅C⋅m−2⋅y−1 from the current rate of 16.1 (9.1–23.7) g⋅C⋅m−2⋅y−1, and the region may turn into a carbon source to the atmosphere at −53.3 (−66.8 to −41.2) g⋅C⋅m−2⋅y−1 (negative indicates source), depending on the level of warming. Peatland ecosystems show a higher vulnerability than nonpeatland ecosystems, as indicated by the ratio of their soil carbon density changes (ranging from 3.9 to 5.8). This is primarily due to larger peatlands carbon stocks and more dramatic responses of their aerobic and anaerobic decompositions in comparison with nonpeatland ecosystems under future climate conditions. Peatland and nonpeatland soils in the PMFB may lose up to 0.4 (0.32–0.52) Pg⋅C by AD 2100 with the largest loss from palm swamp. The carbon-dense Amazonian peatland may switch from a current carbon sink into a source in the 21st century.

scholarly journals Do Downscaled General Circulation Models Reliably Simulate Historical Climatic Conditions?

2018 ◽  
Vol 22 (10) ◽  
pp. 1-22 ◽  
Author(s):  
Andrew R. Bock ◽  
Lauren E. Hay ◽  
Gregory J. McCabe ◽  
Steven L. Markstrom ◽  
R. Dwight Atkinson
Keyword(s):  
General Circulation ◽  
Statistical Tests ◽  
Circulation Model ◽  
General Circulation Models ◽  
Climatic Conditions ◽  
Low Flow ◽  
Balance Model ◽  
Monthly Precipitation ◽  
Significance Level ◽  
Ks Test

Abstract The accuracy of statistically downscaled (SD) general circulation model (GCM) simulations of monthly surface climate for historical conditions (1950–2005) was assessed for the conterminous United States (CONUS). The SD monthly precipitation (PPT) and temperature (TAVE) from 95 GCMs from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) were used as inputs to a monthly water balance model (MWBM). Distributions of MWBM input (PPT and TAVE) and output [runoff (RUN)] variables derived from gridded station data (GSD) and historical SD climate were compared using the Kolmogorov–Smirnov (KS) test For all three variables considered, the KS test results showed that variables simulated using CMIP5 generally are more reliable than those derived from CMIP3, likely due to improvements in PPT simulations. At most locations across the CONUS, the largest differences between GSD and SD PPT and RUN occurred in the lowest part of the distributions (i.e., low-flow RUN and low-magnitude PPT). Results indicate that for the majority of the CONUS, there are downscaled GCMs that can reliably simulate historical climatic conditions. But, in some geographic locations, none of the SD GCMs replicated historical conditions for two of the three variables (PPT and RUN) based on the KS test, with a significance level of 0.05. In these locations, improved GCM simulations of PPT are needed to more reliably estimate components of the hydrologic cycle. Simple metrics and statistical tests, such as those described here, can provide an initial set of criteria to help simplify GCM selection.

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