A hydrological approach to estimating daily glacier ablation

2016 ◽  
Vol 53 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Sylvain Jobard ◽  
Marc Dzikowski
Keyword(s):  
Electrical Conductivity ◽  
Air Temperature ◽  
Time Scale ◽  
Glacier Retreat ◽  
Component Testing ◽  
Water Users ◽  
Glacier Melt ◽  
Glacier Ablation ◽  
Discharge Measurements ◽  
Daily Time

Reduced meltwater discharge owing to glacier retreat can have severe impacts on downstream water users. To assess these impacts, it is essential to differentiate between water from glacier melt and other sources. We propose a method for doing this on a daily time scale by applying a mixing law to electrical conductivity and proglacial discharge measurements. Daily ablation is then estimated by applying a recession law to the glacier melt component. Testing this method on summer hydrology and meteorology measurements from the Baounet Glacier (France) taken over six consecutive years (2008–2013) allowed us to reconstruct daily ablation during the ablation period. Mean ablation rates ranged from 20 to 30 mm·day−1. Air temperature measurements showed that periods of low ablation during the summer were linked to cooler days and snowfall periods. Comparisons for three consecutive summers showed that the ablation rates obtained by summing calculated daily ablation were statistically similar to the rates recorded by ablation stakes.

scholarly journals Sub-daily runoff simulations with parameters inferred at the daily time scale

2015 ◽  
Vol 12 (8) ◽  
pp. 7437-7467 ◽  
Author(s):  
J. E. Reynolds ◽  
S. Halldin ◽  
C. Y. Xu ◽  
J. Seibert ◽  
A. Kauffeldt
Keyword(s):  
Time Series ◽  
Numerical Method ◽  
Time Scales ◽  
Time Scale ◽  
Input Data ◽  
Flood Forecasting ◽  
Euler Method ◽  
Time Stepping ◽  
Parameter Values ◽  
Daily Time

Abstract. Concentration times in small and medium-sized watersheds (~ 100–1000 km2) are commonly less than 24 h. Flood-forecasting models then require data at sub-daily time scales, but time-series of input and runoff data with sufficient lengths are often only available at the daily time scale, especially in developing countries. This has led to a search for time-scale relationships to infer parameter values at the time scales where they are needed from the time scales where they are available. In this study, time-scale dependencies in the HBV-light conceptual hydrological model were assessed within the generalized likelihood uncertainty estimation (GLUE) approach. It was hypothesised that the existence of such dependencies is a result of the numerical method or time-stepping scheme used in the models rather than a real time-scale-data dependence. Parameter values inferred showed a clear dependence on time scale when the explicit Euler method was used for modelling at the same time steps as the time scale of the input data (1–24 h). However, the dependence almost fully disappeared when the explicit Euler method was used for modelling in 1 h time steps internally irrespectively of the time scale of the input data. In other words, it was found that when an adequate time-stepping scheme was implemented, parameter sets inferred at one time scale (e.g., daily) could be used directly for runoff simulations at other time scales (e.g., 3 or 6 h) without any time scaling and this approach only resulted in a small (if any) model performance decrease, in terms of Nash–Sutcliffe and volume-error efficiencies. The overall results of this study indicated that as soon as sub-daily driving data can be secured, flood forecasting in watersheds with sub-daily concentration times is possible with model-parameter values inferred from long time series of daily data, as long as an appropriate numerical method is used.

scholarly journals Identifying robust bias adjustment methods for extreme precipitation in a pseudo-reality setting

2020 ◽  
Author(s):  
Torben Schmith ◽  
Peter Thejll ◽  
Peter Berg ◽  
Fredrik Boberg ◽  
Ole Bøssing Christensen ◽  
...  
Keyword(s):  
Time Scale ◽  
Extreme Value ◽  
Extreme Value Analysis ◽  
Climate Factor ◽  
Value Analysis ◽  
Model Simulations ◽  
Bias Adjustment ◽  
Return Levels ◽  
Hourly Data ◽  
Daily Time

Abstract. Severe precipitation events occur rarely and are often localized in space and of short duration; but they are important for societal managing of infrastructure. Therefore, there is a demand for estimating future changes in the statistics of these rare events. These are usually projected using Regional Climate Model (RCM) scenario simulations combined with extreme value analysis to obtain selected return levels of precipitation intensity. However, due to imperfections in the formulation of the physical parameterizations in the RCMs, the simulated present-day climate usually has biases relative to observations. Therefore, the RCM results are often bias-adjusted to match observations. This does, however, not guarantee that bias-adjusted projected results will match future reality better, since the bias may change in a changed climate. In the present work we evaluate different bias adjustment techniques in a changing climate. This is done in an inter-model cross-validation setup, in which each model simulation in turn plays the role of pseudo-reality, against which the remaining model simulations are bias adjusted and validated. The study uses hourly data from present-day and RCP8.5 late 21st century from 19 model simulations from the EURO-CORDEX ensemble at 0.11° resolution, from which fields of selected return levels are calculated for hourly and daily time scale. The bias adjustment techniques applied to the return levels are based on extreme value analysis and include analytical quantile-matching together with the simpler climate factor approach. Generally, return levels can be improved by bias adjustment, compared to obtaining them from raw scenarios. The performance of the different methods depends of the time scale considered. On hourly time scale, the climate factor approach performs better than the quantile-matching approaches. On daily time scale, the superior approach is to simply deduce future return levels from observations and the second best choice is using the quantile-mapping approaches. These results are found in all European sub-regions considered.

scholarly journals On Anomalous Ocean Heat Transport toward the Arctic and Associated Climate Predictability

2016 ◽  
Vol 29 (2) ◽  
pp. 689-704 ◽  
Author(s):  
Marius Årthun ◽  
Tor Eldevik
Keyword(s):  
Heat Transport ◽  
Air Temperature ◽  
Time Scale ◽  
Heat Content ◽  
Surface Air Temperature ◽  
Meridional Overturning Circulation ◽  
Ocean Heat Content ◽  
The Arctic ◽  
Ocean Heat Transport ◽  
Climate Predictability

Abstract A potential for climate predictability is rooted in anomalous ocean heat transport and its consequent influence on the atmosphere above. Here the propagation, drivers, and atmospheric impact of heat anomalies within the northernmost limb of the Atlantic meridional overturning circulation are assessed using a multicentury climate model simulation. Consistent with observation-based inferences, simulated heat anomalies propagate from the eastern subpolar North Atlantic into and through the Nordic seas. The dominant time scale of associated climate variability in the northern seas is 14 years, including that of observed sea surface temperature and modeled ocean heat content, air–sea heat flux, and surface air temperature. A heat budget analysis reveals that simulated ocean heat content anomalies are driven by poleward ocean heat transport, primarily related to variable volume transport. The ocean’s influence on the atmosphere, and hence regional climate, is manifested in the model by anomalous ocean heat convergence driving subsequent changes in surface heat fluxes and surface air temperature. The documented northward propagation of thermohaline anomalies in the northern seas and their consequent imprint on the regional atmosphere—including the existence of a common decadal time scale of variability—detail a key aspect of eventual climate predictability.

scholarly journals Effects of clouds on surface melting of Laohugou glacier No. 12, western Qilian Mountains, China

2018 ◽  
Vol 64 (243) ◽  
pp. 89-99 ◽  
Author(s):  
JIZU CHEN ◽  
XIANG QIN ◽  
SHICHANG KANG ◽  
WENTAO DU ◽  
WEIJUN SUN ◽  
...  
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Meteorological Data ◽  
Water Vapor Pressure ◽  
Longwave Radiation ◽  
Turbulent Heat Flux ◽  
Qilian Mountains ◽  
Shortwave Radiation ◽  
Turbulent Heat ◽  
Glacier Melt

ABSTRACTWe analyzed a 2-year time series of meteorological data (January 2011–December 2012) from three automatic weather stations on Laohugou glacier No. 12, western Qilian Mountains, China. Air temperature, humidity and incoming radiation were significantly correlated between the three sites, while wind speed and direction were not. In this work, we focus on the effects of clouds on other meteorological parameters and on glacier melt. On an average, ~18% of top-of-atmosphere shortwave radiation was attenuated by the clear-sky atmosphere, and clouds attenuated a further 12%. Most of the time the monthly average increases in net longwave radiation caused by clouds were larger than decreases in net shortwave radiation but there was a tendency to lose energy during the daytime when melting was most intense. Air temperature and wind speed related to turbulent heat flux were found to suppress glacier melt during cloudy periods, while increased water vapor pressure during cloudy days could enhance glacier melt by reducing energy loss by latent heat. From these results, we have increased the physical understanding of the significance of cloud effects on continental glaciers.

scholarly journals Development and Integration of Sub-Daily Flood Modelling Capability within the SWAT Model and a Comparison with XAJ Model

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1263 ◽  
Author(s):  
Dachen Li ◽  
Simin Qu ◽  
Peng Shi ◽  
Xueqiu Chen ◽  
Feng Xue ◽  
...  
Keyword(s):  
Time Scale ◽  
Flood Control ◽  
Assessment Tool ◽  
Spatial Scales ◽  
Swat Model ◽  
Flood Forecasting ◽  
Base Flow ◽  
Flood Simulation ◽  
Promising Tool ◽  
Daily Time

To date, floods have become one of the most severe natural disasters on Earth. Flood forecasting with hydrological models is an important non-engineering measure for flood control and disaster reduction. The Xin’anjiang (XAJ) model is the most widely used hydrological model in China for flood forecasting, while the Soil and Water Assessment Tool (SWAT) model is widely applied for daily and monthly simulation and has shown its potential for flood simulation. The objective of this paper is to evaluate the performance of the SWAT model in simulating floods at a sub-daily time-scale in a slightly larger basin and compare that with the XAJ model. Taking Qilijie Basin (southeast of China) as a study area, this paper developed the XAJ model and SWAT model at a sub-daily time-scale. The results showed that the XAJ model had a better performance than the sub-daily SWAT model regarding relative runoff error (RRE) but the SWAT model performed well according to relative peak discharge error (RPE) and error of occurrence time of peak flow (PTE). The SWAT model performed unsatisfactorily in simulating low flows due to the daily calculation of base flow but behaved quite well in simulating high flows. We also evaluated the effect of spatial scale on the SWAT model. The results showed that the SWAT model had a good applicability at different spatial scales. In conclusion, the sub-daily SWAT model is a promising tool for flood simulation though more improvements remain to be studied further.

scholarly journals Using Large-Aperture Scintillometer to Estimate Lake-Water Evaporation and Heat Fluxes in the Badain Jaran Desert, China

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2575
Author(s):  
Han ◽  
Wang ◽  
Wang
Keyword(s):  
Water Temperature ◽  
Shallow Water ◽  
Time Scale ◽  
Open Water ◽  
Heat Fluxes ◽  
Accurate Estimation ◽  
Badain Jaran Desert ◽  
Large Aperture ◽  
Different Depths ◽  
Daily Time

Accurate estimation of evaporation (E0) over open water bodies in arid regions (e.g., lakes in the desert) is of great importance for local water resource management. Due to the ability to accurately determine sensible (H) and latent (LE) heat fluxes over scales of hundreds to thousands of meters, scintillometers are more and more appreciated. In this study, a scintillometer was installed on both sides of the shore over the Sumu Barun Jaran Lake in the Badain Jaran Desert and was applied to estimate the sensible and latent heat fluxes and evaporation to be compared with the data of an evaporation pan and an aerodynamic model. Based on the field data, we further analyzed the seasonal differences in the flux evaluation using water temperature at different depths at half-hour and daily time scales, respectively. The results showed that in cold seasons, values of H were barely affected by the changes of shallow water temperature, whereas in hot seasons, the values were changed by 20%–30% at the half-hour time scale and 6.2%–18.3% at the daily time scale. In different seasons, shallow water temperature at different depths caused changes in the range of 0%–20% of LE (E0). This study contributes to a better understanding of uncertainties in measurements by large-aperture scintillometers in open-water environments.

scholarly journals Simplified stochastic soil-moisture models: a look at infiltration

2006 ◽  
Vol 10 (6) ◽  
pp. 861-871 ◽  
Author(s):  
J. R. Rigby ◽  
A. Porporato
Keyword(s):  
Soil Moisture ◽  
Time Scale ◽  
Rectangular Pulse ◽  
Short Time Scale ◽  
Soil Moisture Dynamics ◽  
Physically Based ◽  
Probabilistic Structure ◽  
Averaged Model ◽  
Moisture Dynamics ◽  
Daily Time

Abstract. A simplified, vertically-averaged model of soil moisture interpreted at the daily time scale and forced by a stochastic process of instantaneous rainfall events is compared with a vertically-averaged model which uses a non-overlapping rectangular pulse rainfall model and a more physically based description of infiltration. The models are compared with respect to the importance of short time-scale (intra-storm) variable infiltration in determining the probabilistic structure of soil-moisture dynamics at the daily time-scale. Differences in approach to infiltration modelling show only minor effects on the probabilistic structure of soil-moisture dynamics as simulated in the two models. The partitioning of losses during a single rainfall event are examined closely and the conditions under which surface-controlled runoff is significant, as a proportion of total losses, are delineated.

scholarly journals Evaluation of Three-Hourly TMPA Rainfall Products Using Telemetric Rain Gauge Observations at Lai Nullah Basin in Islamabad, Pakistan

2018 ◽  
Vol 10 (12) ◽  
pp. 2040 ◽  
Author(s):  
Asid Rehman ◽  
Farrukh Chishtie ◽  
Waqas Qazi ◽  
Sajid Ghuffar ◽  
Imran Fatima
Keyword(s):  
Time Scale ◽  
Rain Gauge ◽  
Mean Bias Error ◽  
Bias Error ◽  
Rainfall Analysis ◽  
Light Rain ◽  
Post Monsoon ◽  
Statistical Measures ◽  
Rain Rates ◽  
Daily Time

Flash floods which occur due to heavy rainfall in hilly and semi-hilly areas may prove deleterious when they hit urban centers. The prediction of such localized and heterogeneous phenomena is a challenge due to a scarcity of in-situ rainfall. A possible solution is the utilization of satellite-based precipitation products. The current study evaluates the efficacy of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) three-hourly products, i.e., 3B42 near-real-time (3B42RT) and 3B42 research version (3B42V7) at a sub-daily time scale. Various categorical indices have been used to assess the capability of products in the detection of rain/no-rain. Hourly rain rates are assessed by employing the most commonly used statistical measures, such as correlation coefficients (CC), mean bias error (MBE), mean absolute error (MAE), and root-mean-square error (RMSE). Further, a diurnal analysis is performed to authenticate TMPA’s performance in specific hours of the day. In general, the results show the good capability of both TMPA products in the detection of rain/no-rain events in all seasons except winter. Specifically, 3B42V7 performed better than 3B42RT. Moreover, both products detect a high number of rainy days falsely in light rain ranges. Regarding rainfall measurements, TMPA products exhibit an overall underestimation. Seasonally, 3B42V7 underestimates rainfall in monsoon and post-monsoon, and overestimates in winter and pre-monsoon. 3B42RT, on the other hand, underestimates rainfall in all seasons. A greater MBE and RMSE are found with both TMPA rain measurements in monsoon and post-monsoon seasons. Overall, a weak correlation and high MBE between the TMPA (3B42RT, 3B42V7) and reference gauge hourly rain rates are found at a three-hourly time scale (CC = 0.41, 0.38, MBE = −0.92, −0.70). The correlation is significant at decadal (CC = 0.79, 0.77) and monthly (CC = 0.91, 0,90) timescales. Furthermore, diurnal rainfall analysis indicates low credibility of 3B42RT to detect flash flooding. Within the parameters of this study, we conclude that the TMPA products are not the best choice at a three-hourly time scale in hilly/semi-hilly areas of Pakistan. However, both products can be used at daily, yet more reliably above daily, time scales, with 3B42V7 preferable due to its consistency.

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