Climate change impacts on extreme precipitation of water supply area in Istanbul: use of ensemble climate modelling and geo-statistical downscaling

ABSTRACT

Numerous statistical downscaling models have been applied to impact studies, but none clearly recommended the most appropriate one for a particular application. This study uses the geographically weighted regression (GWR) method, based on local implications from physical geographical variables, to downscale climate change impacts to a small-scale catchment. The ensembles of daily precipitation time series from 15 different regional climate models (RCMs) driven by five different general circulation models (GCMs), obtained through the European Union (EU)-ENSEMBLES project for reference (1960–1990) and future (2071–2100) scenarios are generated for the Omerli catchment, in the east of Istanbul city, Turkey, under scenario A1B climate change projections. Special focus is given to changes in extreme precipitation, since such information is needed to assess the changes in the frequency and intensity of flooding for future climate. The mean daily precipitation from all RCMs is under-represented in the summer, autumn and early winter, but it is overestimated in late winter and spring. The results point to an increase in extreme precipitation in winter, spring and summer, and a decrease in autumn in the future, compared to the current period. The GWR method provides significant modifications (up to 35%) to these changes and agrees on the direction of change from RCMs. The GWR method improves the representation of mean and extreme precipitation compared to RCM outputs and this is more significant, particularly for extreme cases of each season. The return period of extreme events decreases in the future, resulting in higher precipitation depths for a given return period from most of the RCMs. This feature is more significant with downscaling. According to the analysis presented, a new adaption for regulating excessive water under climate change in the Omerli basin may be recommended.     

Generalized extreme value shape parameter and its nature for extreme precipitation using long time series and the Bayesian approach

Assessing the probability of extreme precipitation events is consequential in civil planning. This requires an understanding of how return values change with return periods, which is essentially described by the generalized extreme value (GEV) shape parameter. Some works in the field suggest a constant shape parameter, while our analysis indicates a non-universal value. We re-analysed an older precipitation dataset (169 stations) extended by Norwegian data (71 stations). We showed that while each set seems to have a constant shape parameter, it differs between the two datasets, indicating regional differences. For a more comprehensive analysis of spatial effects, we examined a global dataset (1495 stations). We provided shape parameter maps for two models and found clear evidence that the shape parameter depends on elevation, while the effect of latitude remains uncertain. Our results confirm an explanation in terms of dominating precipitation systems based on a proxy derived from the Köppen-Geiger climate classification.

EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR not assigned     

Identifying the relationships between trophic states and their driving factors in the Shihmen Reservoir,Taiwan

Eutrophication has become a crucial issue for water resource management in recent years. In addition, reservoir trophic states are varied with environmental and water quality variables. The objectives of this study were to apply the DFA model to examine which water quality variables significantly affect variations of trophic state index (TSI) factors (i.e. total phosphorus (TP), chlorophyll-a (Chl-a), and Secchi disk transparency (SD)) and use classification and regression tree (CART) to determine the trophic states of the Shinmen Reservoir based on the levels of TSI factors during spring 2001–winter 2009. Results showed that the optimal DFA model contained one common trend (the underlying processes influencing trophic states, which can be rainfall intensity or runoff volume) and 7 explanatory variables. Turbidity (TB), pH, and dissolved oxygen (DO) influence concentrations of TP, while ammonium nitrogen (NH₃-N), organic nitrogen (O-N), and nitrate nitrogen (NO₃-N) control variations of Chl-a, and TB is related to SD. The CART model can specify trophic states only using two dominant driving factors, i.e. TP and Chl-a. The results of the CART illustrated that eutrophication could be occurred in the Shihmen Reservoir if TP is greater than 31.65 μg/L or if Chl-a is greater than 5.95 μg/L while TP concentration is less than 31.65 μg/L. Runoff nonpoint source pollution resulted from heavy storms may be the important factor affecting reservoir trophic states. Establishing vegetative filter strips along the riparian zone may able to effectively reduce this pollution in a reservoir. The integrated DFA and CART serves as good-fit relationships among trophic states, TSI factors, and water quality variables and provide control strategies for managing water quality in the Shihmen Reservoir.     

Assessment of hydropower potential using spatial technology and SWAT modelling in the Mat River,southern Mizoram,India

Abstract

In this study, a hydrological model and spatial technologies have been employed to assess water availability in the Mat River basin, southern Mizoram, India. Furthermore, the results obtained from the SWAT (Soil and Water Assessment Tool) model, satellite data and GIS tools were utilized to identify the hydropower potential in the basin. Thirty three sites with hydropower potential were identified within 147 km² of the Mat River basin. A total of 3039, 1127 and 805 kW can be harnessed with 50, 75 and 90% dependability, respectively. The study revealed that the hydropower potential of a river basin can be correctly assessed by employing a digital elevation model, stream network data and a hydrological model, such as the SWAT model, within a GIS framework.

Editor D. Koutsoyiannis     

Comparison analysis of the summer monsoon precipitation between northern and southern slopes of Tanggula Mountains,Qinghai–Xizang (Tibetan) Plateau: a case study in summer 1998

Based on the precipitation data obtained through GEWEX Asian Monsoon Experiment–Tibet fieldwork from May to September 1998, this study investigated the features of the summer monsoon precipitation on the northern and southern slopes of the huge Tanggula Mountains in the Qinghai–Xizang (Tibetan) Plateau. The results show that the precipitation on the southern slope is about 50% higher than on the northern slope, whereas the frequency and diurnal pattern of the precipitation are very similar. The mean precipitation intensity on the southern slope is larger than on the northern slope. In most cases, the daily precipitation showed similar variation on both slopes, demonstrating that the precipitation processes might be similar. In the summer monsoon period, the local convective precipitation contributed to the total precipitation on both slopes and such a contribution on the southern slope is larger. Copyright © 2006 John Wiley & Sons, Ltd.