Article

Uncertainties in Climate Change Projections and Regional Downscaling in the Tropical Andes: Implications for Water Resources Management

Hydrology and Earth System Sciences (Impact Factor: 3.54). 03/2010; 14(7). DOI: 10.5194/hessd-7-1821-2010
Source: OAI

ABSTRACT

Climate change is expected to have a large impact on water resources worldwide. A major problem in assessing the potential impact of a changing climate on these resources is the difference in spatial scale between available climate change projections and water resources management. Regional climate models (RCMs) are often used for the spatial disaggregation of the outputs of global circulation models. However, RCMs are time-intensive to run and typically only a small number of model runs is available for a certain region of interest. This paper investigates the value of the improved representation of local climate processes by a regional climate model for water resources management in the tropical Andes of Ecuador. This region has a complex hydrology and its water resources are under pressure. Compared to the IPCC AR4 model ensemble, the regional climate model PRECIS does indeed capture local gradients better than global models, but locally the model is prone to large discrepancies between observed and modelled precipitation. It is concluded that a further increase in resolution is necessary to represent local gradients properly. Furthermore, to assess the uncertainty in downscaling, an ensemble of regional climate models should be implemented. Finally, translating the climate variables to streamflow using a hydrological model constitutes a smaller but not negligible source of uncertainty.

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    • "Droughts are especially important in regions where economic activities are highly dependent on water resources[4], such as in mountain regions which traditionally provide water resources and services to local communities and lowland residents[5]. For example, the Andean basins, which have been identified as excellent providers of water for multiple uses[6,7], could be affected by droughts and climate change, putting the water supply at risk and augmenting the vulnerability of the basin's water resources systems and eco-services891011. The increasing tendency of water shortage is a concern of water managers[11], wrestling with questions such as which drought indicator[12]and threshold of the indicators should be used to qualify the drought status. "
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    ABSTRACT: The scarcity of water resources in mountain areas can distort normal water application patterns with among other effects, a negative impact on water supply and river ecosystems. Knowing the probability of droughts might help to optimize a priori the planning and management of the water resources in general and of the Andean watersheds in particular. This study compares Markov chain- (MC) and Bayesian network- (BN) based models in drought forecasting using a recently developed drought index with respect to their capability to characterize different drought severity states. The copula functions were used to solve the BNs and the ranked probability skill score (RPSS) to evaluate the performance of the models. Monthly rainfall and streamflow data of the Chulco River basin, located in Southern Ecuador, were used to assess the performance of both approaches. Global evaluation results revealed that the MC-based models predict better wet and dry periods, and BN-based models generate slightly more accurately forecasts of the most severe droughts. However, evaluation of monthly results reveals that, for each month of the hydrological year, either the MC- or BN-based model provides better forecasts. The presented approach could be of assistance to water managers to ensure that timely decision-making on drought response is undertaken.
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    • "Aún cuando estos modelos regionales mejoran la representación de los fenómenos locales con respecto a los modelos de circulación general, no ofrecen una adecuada estimación de fenómenos locales, en especial la precipitación y sus gradientes. En busca de soluciones a estos problemas, se ha postulado la necesidad de incrementar la resolución e implementar ensambles de modelos regionales (Buytaert, et al. 2010). Otro inconveniente de los MCG es que hasta ahora no permiten describir la intensidad y frecuencia de forzantes como el ENOS o la PDO, por lo cual forzantes de variabilidad climática de mucha importancia para los Andes no están adecuadamente representados. "

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    • "In complex terrain regions, the change of temperature is related to altitude (Gardner et al., 2009; You et al., 2010). Moreover, lapse rate change may affect climate model simulation results in mountain regions (Buytaert et al., 2010), especially in dry seasons (Beniston, 2003). Linear regression models of temperature and elevation were utilized to determine temperature lapse rates (Rolland, 2003; Minder et al., 2010). "
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    ABSTRACT: Climate change in complex mountain regions has an impact on the change of water resources, especially in arid areas. Here, we use long-term meteorological and hydrological station observation data to analyze the time series of climate indices and runoff to study the variability of climate in the Kaidu River Basin. The analysis results are as follows: 1) the variability rate of low temperature indices are of greater magnitude than high temperature indices; 2) overall, for the river basin, frost days and ice days all exhibited decreasing trends, and growing season lengths increased considerably; 3) during the past 50 years, overall precipitation has increased in the river basin, but there are some differences in some seasons, and precipitation from June to August accounts for approximately 66% of the annual precipitation; and 4) temperature lapse rate and precipitation of the mountain region are major factors influencing the change of runoff for the Kaidu River Basin, temperature lapse rates are the main factor influencing the run off change in the spring and fall, and precipitation in the mountain region is the major factor influencing the runoff change in the summer. Generally, climate change in complex mountain regions will be expected to seriously affect water resources in arid regions.
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