Uncertainty assessment of hydrological impacts of climatic change in small mediterranean catchments

The assessment of uncertainty associated with the hydrological impacts of climate change is of fundamental importance for sustainable water resources management. However, both hydrological and climate models are prone to uncertainties that interact and propagate in a complex chain. Quantifying and characterizing these uncertainties is a challenge particularly in Mediterranean catchments identified as “a hot spot” for climate change and variability. Results from a conjunctive use of a hydrological model underpinned with multi-climate models indicate that uncertainty arising from hydrological model parameter is important and should be routinely considered in climate change impact studies. The decomposition of modelling uncertainty reveals that climate models uncertainty prevails over hydrological parameter uncertainty during the wet period, whereas during the dry period the latter uncertainty source becomes more important. Despite these uncertainties climate change projection for 2050s is likely to induce severe changes in flow regime and general shortage of the available water resources in Mediterranean catchments. Other potentially important uncertainty sources were neglected in this work and, thus, the estimated uncertainty ranges are likely smaller than the overall uncertainty associated with climate impacts on catchment hydrology. This highlights the needs for complete assessment of all uncertainty sources in the future while investigating the hydrological impacts of climate change projections in Mediterranean catchments.(AGRO - Sciences agronomiques et ingénierie biologique) -- UCL, 201

Introducing uncertainty in the impact assessments of climate change on local scale hydrology

The recently released AR5 report of IPCC confirms that freshwater-related risks of climate change increase significantly with increasing greenhouse gas (GHG) concentrations and that climate change is projected to reduce renewable surface water and groundwater resources significantly in many areas overall the world. This will intensify competition for water among agriculture, ecosystems, settlements, industry, and energy production, affecting regional water, energy, and food security and increase water insecurity. This calls for paradigm shifts in the water management policy and adaptation of water management at different levels (physical technical, social, institutional). However, many barriers for adaptation exists. One of these barriers is related to a poor understanding of possible impacts of climate change at the local hydrological scale, and a poorly characterized uncertainty associated with such impact studies. To improve this, we show how uncertainty can be propagated for assessing hydrological impacts of climate change at the local scale. We illustrate the approach for two catchments of the Mediterranean region - which is considered as a hotspot for climate change – and demonstrate how uncertainty can be decomposed in uncertainty coming from the hydrological model and uncertainty coming from the climate model

Climate Induced Changes on the Hydrology of Mediterranean Basins. Results from the CLIMB project

Le Bassin méditerranéen est un "hotspot" des changements globaux. Ces changements se concrétisent par une croissance démographique concentrée sur la zone littorale, par un vieillissement de la population rurale, par un changement climatique accru et accentué par une modification majeure du contexte institutionnel et politique lié aux "Printemps arabes

Climatic change impact and associated uncertainty on catchment hydrology: a case study on the Chiba catchment in Tunisia

Projected changes in climate and their possible impacts on river flow are of concern for sustainable management of the water resources in Tunisia. Most of the climate model (CM) projections available so far suggest a decrease in precipitation and increase in temperature over the country in the future (next 25 to 50 years). These changes are expected to alter the catchment flow regime with exacerbated threats on the available water resources, yet limited and scarce. Surprisingly, there are few studies that quantify the impacts of climatic change on the catchment hydrology in Tunisia. One possible reason could be related to the inherent uncertainty in CM projection. Therefore, we here present a modelling approach that combines an ensemble of 4 CM projection to force the Soil and Water Assessment Tool (SWAT) physically based hydrological model for assessing changes and uncertainty in the hydrology of the Chiba catchment (North-East Tunisia) related to climatic change. Results indicate that the catchment is likely to experience drier conditions in the horizon 2050s facing a reduction in monthly flow magnitude, soil moisture conditions and water availability which is likely to be more pronounced in the dry season than in the rainy season

Is the governance of the Thau coastal lagoon ready to face climate change impacts ?

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Uncertainty propagation in hydrological modeling

Uncertainty in hydrological model prediction stems from different sources such as parameter uncertainty, errors of input data, model structure uncertainty, lack of knowledge about the physical characteristics of the watershed and uncertainty in discharge data used to calibrate the model. Portioning and quantifying all these uncertainty sources that affect models and predictions is a difficult and challenging task due to the possible correlation of model parameters, to the propagation and correlation of the errors, to the model complexity, etc. Parameter uncertainty is usually considered as the main source of the model prediction uncertainty while discharge data uncertainty is rarely taken into account when calibrating the model. In this work a new calibration technique of the SWAT model is developed to account explicitly for the uncertainty in discharge data caused by uncertainty in the rating curve. For a given discharge value, a probability distribution function of true discharge was estimated from the constructed uncertain rating curves. This method was applied in three automatic calibration techniques SUFI2, GLUE and ParaSol to calibrate the SWAT model in two Mediterranean watersheds (Vène and Pallas). The uncertainty prediction confidence interval (95PPU) of each of the applied techniques was more successful at bracketing the measured data when uncertainty in the rating curve is accounted for. Discharge uncertainty contributed to total model uncertainty by 8 to 27 % (with an average value of 13 %) for the Vène watershed and by 3 to 20% (with an average value of 9 %) which shows that uncertainty in discharge measurement is not a negligible uncertainty source and has to be considered in hydrological modeling for more accurate model prediction that can be used in decision making for developing sustainable water resource management strategies

Impact of land use land cover changes on flow uncertainty in Siliana watershed of northwestern Tunisia

It is widely admitted that changes in land use land cover (LULC) influence the hydrology of the catchment. However, how these changes affect hydrological model prediction uncertainty is still a raising question. In this paper we addressed this question by investigating the impacts of the rapid change in LULC in the Siliana catchment in Tunisia on monthly flow and magnitude of flow extremes using the SWAT hydrological model while quantifying the contribution of LULC to the model parameter and prediction uncertainty. At a first step, the SWAT model parameter and prediction uncertainty were estimated using the GLUE method and acceptable parameter sets were identified. Subsequently, the SWAT model was fed with historical LULC as derived from Landsat 5 and 8 satellite images for the years 1990, 2000, 2013 and 2019, and run with the acceptable parameter sets. The results show that the increase in olive plantations (+380 %), urban area (+200 %), and irrigated lands (+309 %) from 1990 to 2019, has LULC decreased monthly flow, high flows magnitude but did not impact low flows in particular over the previous two decades. The findings also suggest that model prediction uncertainty can mask LULC effects, suggesting that model results can be misleading without explicit consideration of uncertainty when assessing the hydrological impacts of changes in LULC

Comparison of different calibration and uncertainty analysis techniques of the SWAT model for discharge prediction of Mediterranean lagoon watershed in Southern France

Physically based watershed models are increasingly being used to support decisions about alternative management strategies in the areas of land use change, climate change, water allocation, and pollution control. Therefore, the ability of these hydrological models to reproduce the physical process of the watershed must be carefully evaluated, as well as the uncertainty in modeling predictions. We evaluate in this study the capability of the SWAT (Soil and Water Assessment Tools, Arnold et al., 2000) model in reproducing the hydrology of two small Mediterranean watersheds through sensitivity, calibration and uncertainty analysis. The objective is to compare different calibration techniques for assessing model performance and modeling uncertainty

Parameter and rating curve uncertainty propagation analysis of the SWAT model for two small Mediterranean catchments

The SWAT model was tested to simulate the streamflow of two small Mediterranean catchments (the Vène and the Pallas) in southern France. Model calibration and prediction uncertainty were assessed simultaneously by using three different techniques (SUFI-2, GLUE and ParaSol). Initially, a sensitivity analysis was conducted using the LH-OAT method. Subsequent sensitive parameter calibration and SWAT prediction uncertainty were analysed by considering, firstly, deterministic discharge data (assuming no uncertainty in discharge data) and secondly, uncertainty in discharge data through the development of a methodology that accounts explicitly for error in the rating curve (the stage−discharge relationship). To efficiently compare the different uncertainty methods and the effect of the uncertainty of the rating curve on model prediction uncertainty, common criteria were set for the likelihood function, the threshold value and the number of simulations. The results show that model prediction uncertainty is not only case-study specific, but also depends on the selected uncertainty analysis technique. It was also found that the 95% model prediction uncertainty interval is wider and more successful at encompassing the observations when uncertainty in the discharge data is considered explicitly. The latter source of uncertainty adds additional uncertainty to the total model prediction uncertainty