scholarly journals Historical trends in precipitation and stream discharge at the Skjern River catchment, Denmark

2014 ◽  
Vol 18 (2) ◽  
pp. 595-610 ◽  
Author(s):  
I. B. Karlsson ◽  
T. O. Sonnenborg ◽  
K. H. Jensen ◽  
J. C. Refsgaard
Keyword(s):  
Climate Change ◽  
Hydrological Model ◽  
Drought Indices ◽  
Homogeneity Test ◽  
Threshold Method ◽  
Data Set ◽  
River Catchment ◽  
Stream Discharge ◽  
Predict Climate Change ◽  
Standard Normal Homogeneity Test

Abstract. A 133 yr data set from the 1055 km2 Skjern River catchment in western Denmark has been analysed with respect to precipitation, temperature, evapotranspiration and discharge. The precipitation series have been tested and corrected using the standard normal homogeneity test and subsequently corrected for undercatch. The degree of change in the climatic variables is examined using the non-parametric Mann–Kendall test. During the last 133 yr the area has experienced a significant change in precipitation of 26% and a temperature change of 1.4°C, leading to increases in river discharge of 52% and groundwater recharge of 86%. A lumped conceptual hydrological model, NAM, was calibrated on the period 1951–1980 and showed generally an excellent match between simulated and observed discharge. The capability of the hydrological model to predict climate change impact was investigated by looking at performances outside the calibration period. The results showed a reduced model fit, especially for recent time periods (after the 1980s), and not all hydrological changes could be explained. This might indicate that hydrological models cannot be expected to predict climate change impacts on discharge as accurately in the future, compared to the performance under present conditions, where they can be calibrated. The (simulated) stream discharge was subsequently analysed using high flow and drought indices based on the threshold method. The extreme signal was found to depend highly on the period chosen as reference to normal. The analysis indicated that no significant amplitude increase of the hydrograph for both wet and dry extremes could be found superimposed on the overall discharge increase.

scholarly journals Evaluating the influence of long term historical climate change on catchment hydrology – using drought and flood indices

2013 ◽  
Vol 10 (2) ◽  
pp. 2373-2428 ◽  
Author(s):  
I. B. Karlsson ◽  
T. O. Sonnenborg ◽  
K. H. Jensen ◽  
J. C. Refsgaard
Keyword(s):  
Climate Change ◽  
Hydrological Model ◽  
Climate Change Impacts ◽  
Kendall Test ◽  
Drought Indices ◽  
Threshold Method ◽  
Data Set ◽  
Stream Discharge ◽  
Predict Climate Change

Abstract. This study uses a 133 yr data set from the 1055 km2 Skjern River catchment in a western Danish catchment to evaluate: long-term past climate changes in the area; the capability of a conceptual hydrological model NAM to simulate climate change impacts on river discharge; and the occurrences of droughts and floods in a changing climate. The degree of change in the climatic variables is examined using the non-parametric Mann-Kendall test. During the last 133 yr the area has experienced a significant change in precipitation of 46% and a temperature change of 1.3 °C leading to (simulated) increases in discharge of 103% and groundwater recharge of 172%. Only a small part of the past climatic changes was found to be correlated to the climatic drivers: NAO, SCA and AMO. The NAM model was calibrated on the period 1961–1970 and showed generally an excellent match between simulated and observed discharge. The capability of the hydrological model to predict climate change impact was investigated by looking at performances outside the calibration period. The results showed a reduced model fit, especially for the modern time periods (after the 1970s), and not all hydrological changes could be explained. This might indicate that hydrological models cannot be expected to predict climate change impacts on discharge as accurately in the future, as they perform under present conditions, where they can be calibrated. The (simulated) stream discharge was subsequently analyzed using flood and drought indices based on the threshold method. The extreme signal was found to depend highly on the period chosen as reference to normal. The analysis, however, indicated enhanced amplitude of the hydrograph towards the drier extremes superimposed on the overall discharge increase leading to more relative drought periods.

RAT (Robustness Assessment Test): a straightforward evaluation of hydrological model robustness to a changing climate

2021 ◽  
Author(s):  
Vazken Andréassian ◽  
Léonard Santos ◽  
Torben Sonnenborg ◽  
Alban de Lavenne ◽  
Göran Lindström ◽  
...  
Keyword(s):  
Climate Change ◽  
Hydrological Model ◽  
Hydrological Models ◽  
Climate Variables ◽  
Data Set ◽  
Hydrological Characteristics ◽  
Changing Climate ◽  
Split Sample ◽  
Sample Test ◽  
Model Robustness

<p>Hydrological models are increasingly used under evolving climatic conditions. They should thus be evaluated regarding their temporal transferability (application in different time periods) and extrapolation capacity (application beyond the range of known past conditions). In theory, parameters of hydrological models are independent of climate. In practice, however, many published studies based on the Split-Sample Test (Klemeš, 1986), have shown that model performances decrease systematically when it is used out of its calibration period. The RAT test proposed here aims at evaluating model robustness to a changing climate by assessing potential undesirable dependencies of hydrological model performances to climate variables. The test compares, over a long data period, the annual value of several climate variables (temperature, precipitation and aridity index) and the bias of the model over each year. If a significant relation exists between the climatic variable and the bias, the model is not considered to be robust to climate change on the catchment. The test has been compared to the Generalized Split-Sample Test (Coron et al., 2012) and showed similar results.</p><p>Here, we report on a large scale application of the test for three hydrological models with different level of complexity (GR6J, HYPE, MIKE-SHE) on a data set of 352 catchments in Denmark, France and Sweden. The results show that the test behaves differently given the evaluated variable (be temperature, precipitation or aridity) and the hydrological characteristics of each catchment. They also show that, although of different level of complexity, the robustness of the three models is similar on the overall data set. However, they are not robust on the same catchments and, then, are not sensitive to the same hydrological characteristics. This example highlights the applicability of the RAT test regardless of the model set-up and calibration procedure and its ability to provide a first evaluation of the model robustness to climate change.</p><p> </p><p><strong>References</strong></p><p>Coron, L., V. Andréassian, C. Perrin, J. Lerat, J. Vaze, M. Bourqui, and F. Hendrickx, 2012. Crash testing hydrological models in contrasted climate conditions: An experiment on 216 Australian catchments, Water Resour. Res., 48, W05552, doi:10.1029/2011WR011721</p><p>Klemeš, V., 1986. Operational testing of hydrological simulation models, Hydrol. Sci. J., 31, 13–24, doi:10.1080/02626668609491024</p><p> </p>

CLIMATE CHANGE IMPACTS ON ULZA DAM LIFESPAN

2020 ◽  
Author(s):  
Klodian Zaimi ◽  
Fatos Hoxhaj ◽  
Sergio Fattorelli ◽  
rancesca Ramazzina
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Sediment Transport ◽  
Climate Change Impact ◽  
Hydrological Model ◽  
Hydrological Process ◽  
River Catchment ◽  
Land Use Scenarios ◽  
Change Impact ◽  
The Mean

Ulza Dam is one of the oldest hydropower infrastructures in Albania. The water capacity of the reservoir has been reduced because of the accumulation of the sediments coming from Mat River. The bathymetric measurements and river sediment transport are used for quantifying the water storage change up to nowadays. Analyzing the future climate change impact in the sediment transport from the river is very important for understanding the Ulza Dam lifespan. In order to analyze the sediment regime in the future, the climate change projection from the EURO-CORDEX has been downscaled for Mat River catchment and used as input for the HEC-HMS hydrological model considering also the erosion and sediment module. The hydrological model was also calibrated with the MUSLE parameters, and it reproduces the average value of the total sediment transport. The analysis of climate change impact on erosion and sediment transported at the reservoirs was done considering the mean annual load for the different 30-year simulated periods related to values from the historical period 1981-2010. Considering the impacts of climate change, the mean annual sediment siltation could increase for RCP4.5 and RCP8.5 scenarios. Over this hypothesis, the remaining lifespan can be reduced drastically in both scenarios. Different land-use scenarios were analyzed in order to evaluate the impact of erosion and, because the current land use scenario doesn’t produce any impact on the hydrological process, but only effects at a small scale, two hypothetical scenarios were defined at large scale and applied for Mat River catchment. Extensive management of land use and reforestation produce a positive effect on the hydrological process and reducing the erosion rate. The change of land use significantly counteracts the negative effects of climate change by 15% and a 24% reduction in the case of these land-use scenarios.

Integrating Climate and Socio-Economic Scenarios in a Hydrological Model for the Santa River Basin, Peru

2020 ◽  
Author(s):  
Claudia Teutsch ◽  
Faizan Anwar ◽  
Jochen Seidel ◽  
András Bárdossy ◽  
Christian Huggel ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Water Balance ◽  
Water Use ◽  
Water Availability ◽  
Hydrological Model ◽  
Irrigated Agriculture ◽  
Domestic Water ◽  
Study Region ◽  
River Catchment

<p>High mountain regions, like the Andes, face various risks due to climate change. In the Santa River catchment in Peru which includes the glaciated Cordillera Blanca, water availability is threatened by many climatic and non-climatic impacts. The water resources in the catchment heavily rely on seasonal precipitation and during the dry season glacier melt water plays an important role. However, both, precipitation patterns and glacier extent are affected by climate change impacts. Additionally, socio-economic changes put further pressure on water resources and hence on water availability.</p> <p>Within the AguaFuturo Project we established a conceptual integrated water balance model based on a semi-distributed HBV model for the data scarce Santa River catchment. The hydrological model processes are extended by feedback loops for agricultural and domestic water use. The model runs on daily time scale and includes two hydrological response units. One includes the irrigated agricultural areas which are predominately located in the valley of the catchment; the other includes non-irrigated areas and domestic water use.</p> <p>To assess future water balance challenges we downscaled and disaggregated monthly CORDEX scenarios for 2020-2050 using information from the new Peruvian precipitation dataset PISCO (Peruvian Interpolated data of the SENAMHI’s Climatological and hydrological Observations) for simulations of future changes in hydro-climatology. In the model, these climate scenarios are combined with possible socio-economic scenarios which are translated into time series for domestic and agricultural water demand. The socio-economic scenarios are developed by using the Cross-Impact-Balance-Analysis (CIB), a method used for analyzing impact networks. Using CIB, the interrelations between 15 social, economic and policy descriptors were analyzed and as a result a total of 29 possible consistent scenarios were determined. For further analysis and validation of these scenarios a participatory process was included, involving local experts and stakeholders of the study region.</p> <p>The climate and socio-economic scenarios are independent and can be combined randomly. The uncertainties of the climatic and socio-economic scenarios are quantified by Monte Carlo simulations.</p> <p>The output of the model runs is an ensemble of possible future discharges of the Santa River, which can be further analyzed statistically to assess the range of the possible discharges. This evaluation provides an estimate of the probability of water shortages, especially with regard to conflict potential with hydropower production and the large scale irrigated agriculture areas in the adjacent coastal desert which also rely on water from the Santa River.</p>

scholarly journals Evaluating the Quality of Spatial Data for the Analysis of Climate Variability in the Coastal Region of Nigeria

2021 ◽  
Vol 5 (1) ◽  
pp. 76-90
Author(s):  
A.I. Agbonaye ◽  
O.C. Izinyon
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Spatial Data ◽  
Coastal Region ◽  
Climatic Research Unit ◽  
Data Series ◽  
Homogeneity Test ◽  
Climatic Data ◽  
Omnibus Test ◽  
Standard Normal Homogeneity Test

The lack of truly reliable data for climate change analyses and prediction presents challenges in climate modeling. Needed data are required to be hydrologically/statistically reliable to be useful for hydrological, meteorological, climate change, and estimation studies. Thus, data quality and homogeneity screening are preliminary analyses. In this study, the homogeneity of the climatic data used for analyses of climate variability was conducted in the coastal region of Nigeria. Climatic Research Unit (CRU 0.5× 0.5) gridded monthly climatic data for sixty years (1956- 2016) for nine states of the coastal region of Nigeria obtained from internet sources were validated with the Nigerian Meteorological Agency (NiMet) data to assure adequacy for use. The data were tested for normality using the Shapiro-Wilk (S-W) test, D’Agostino-Pearson omnibus test, and skewness test. Four homogeneity test methods were applied to 257 locations in the nine states of the coastal region of Nigeria and they include Pettit’s, Standard Normal Homogeneity Test (SNHT), Buishand’s and Von Neumann Ratio (VNR) tests. The results of the validity analysis indicated that the CRU data are very reliable and thus justified their use for the further analysis carried out in the study. Also, the results obtained indicated that CRU climatic data series were normally distributed and parametric methods could be used in further analysis of the data. Rainfall data homogeneity was detected for Bayelsa, Delta, Edo, Lagos, Ogun, and Ondo states and inhomogeneity for Akwa Ibom, Cross Rivers, and Rivers States. Also, temperature data inhomogeneity was detected for all the states in the study area.

NEURO-FUZZY SYSTEMS APPROACH TO INFILL MISSING RAINFALL DATA FOR KLANG RIVER CATCHMENT, MALAYSIA

2016 ◽  
Vol 78 (6-12) ◽  
Author(s):  
Nadeem Nawaz ◽  
Sobri Harun ◽  
Rawshan Othman ◽  
Arien Heryansyah
Keyword(s):  
Fuzzy System ◽  
Fuzzy Systems ◽  
Rainfall Data ◽  
System Model ◽  
Coefficient Of Determination ◽  
Homogeneity Test ◽  
River Catchment ◽  
Statistical Measures ◽  
Neuro Fuzzy ◽  
Standard Normal Homogeneity Test

Rainfall data can be regarded as the most essential input for various applications in hydrological sciences. Continuous rainfall data with adequate length is the main requirement to solve complex hydrological problems. Mostly in developing countries hydrologists are still facing problems of missing rainfall data with inadequate length. Researchers have been applying a number of statistical and data driven approaches to overcome this insufficiency. This study is an application of neuro-fuzzy system to infill the missing rainfall data for Klang River catchment. Pettitt test, standard normal homogeneity test (SNHT) and Von Neumann Ratio (VNR) tests were performed to check the homogeneity of rainfall data. The neuro-fuzzy model performances were assessed both in calibration and validation stages based on statistical measures such as coefficient of determination (R2), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). To evaluate the performance of the neuro-fuzzy system model, it was compared with a traditional modeling technique known as autoregressive model with exogenous inputs (ARX). The neuro-fuzzy system model gave better performances in both stages for the best input combinations. The missing rainfall data was predicted using the input combination with best performances. The results of this study showed the effectiveness of the neuro-fuzzy systems and it is recommended as a prominent tool for filling the missing data. 

scholarly journals The impact of the climate change on discharge of Suir River Catchment (Ireland) under different climate scenarios

2006 ◽  
Vol 6 (3) ◽  
pp. 387-395 ◽  
Author(s):  
S. Wang ◽  
R. McGrath ◽  
T. Semmler ◽  
C. Sweeney ◽  
P. Nolan
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Hydrological Model ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
General Circulation Models ◽  
Climate Data ◽  
River Catchment ◽  
The Impact

Abstract. The impact of climate change on local discharge variability is investigated in the Suir River Catchment which is located in the south-east of Ireland. In this paper, the Rossby Centre Regional Atmospheric Model (RCA) is driven by different global climate data sets. For the past climate (1961–2000), the model is driven by ECMWF reanalysis (ERA-40) data as well as by the output of the general circulation models (GCM's) ECHAM4 and ECHAM5. For the future simulation (2021–2060), the model is driven by two GCM scenarios: ECHAM4_B2 and ECHAM5_A2. To investigate the influence of changed future climate on local discharge, the precipitation of the model output is used as input for the HBV hydrological model. The calibration and validation results of our ERA-40 driven present day simulation shows that the HBV model can reproduce the discharge fairly well, except the extreme discharge is systematically underestimated by about 15–20%. Altogether the application of a high resolution regional climate model in connection with a conceptual hydrological model is capable of capturing the local variability of river discharge for present-day climate using boundary values assimilated with observations such as ERA-40 data. However, using GCM data to drive RCA and HBV suggests, that there is still large uncertainty connected with the GCM formulation: For present day climate the validation of the ECHAM4 and ECHAM5 driven simulations indicates stronger discharge compared to the observations due to overprediction of precipitation, especially for the ECHAM5 driven simulation in the summer season. Whereas according to the ECHAM4_B2 scenario the discharge generally increases – most pronounced in the wet winter time, there are only slight increases in winter and considerable decreases in summer according to the ECHAM5_A2 scenario. This also leads to a different behaviour in the evolution of return levels of extreme discharge events: Strong increases according to the ECHAM4_B2 scenario and slight decreases according to the ECHAM5_A2 scenario.

scholarly journals Comparing Meteorological Data Sets in the Evaluation of Climate Change Impact on Hydrological Indicators: A Case Study on a Mexican Basin

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2110
Author(s):  
Juan Alberto Velázquez-Zapata
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Change Impact ◽  
Hydrological Model ◽  
Meteorological Data ◽  
Data Sets ◽  
Data Set ◽  
Climate Simulations ◽  
Change Impact ◽  
Data Source

This study evaluates the choice of the meteorological data set in the simulation of the streamflow of a Mexican basin, in the bias correction of climate simulations, and in the climate change impact on hydrological indicators. The selected meteorological data sets come from stations, two interpolated data sets and one reanalysis data set. The climate simulations were taken from the five-member ensemble from the second generation Canadian Earth System Model (CanESM2) under two representative concentration pathways (RCPs), for a reference period (1981–2000) and two future periods (2041–2060 and 2081–2100). The selected lumped hydrological model is GR4J, which is a daily lumped four-parameter rainfall-runoff model. Firstly, the results show that GR4J can be calibrated and validated with the meteorological data sets to simulate daily streamflow; however, the hydrological model leads to different hydrological responses for the basin. Secondly, the bias correction procedure obtains a similar relative climate change signal for the variables, but the magnitude of the signal strongly varies with the source of meteorological data. Finally, the climate change impact on hydrological indicators also varies depending on the meteorological data source, thus, for the overall mean flow, this uncertainty is greater than the uncertainty related to the natural variability. On the other hand, mixed results were found for high flows. All in all, the selection of meteorological data source should be taken into account in the evaluation of climate change impact on water resources.

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