Lower Return Periods Research Articles

Cross-Analysis of Land and Runoff Variations in Response to Urbanization on Basin, Watershed, and City Scales with/without Green Infrastructures

Evaluating land and runoff variations caused by urbanization is crucial to ensure the safety of people living in highly developed areas. Based on spatial scales, runoff analysis involves different methods associated with the interpretation of land cover and land use, the application of hydrological models, and the consideration of flood mitigation measures. Most studies have focused on analyzing the phenomenon on a certain scale by using a single data source and a specific model without discussing mutual influences. In this study, the runoff changes caused by urbanization are assessed and cross-analyzed on three sizes of study areas in the Zhuoshui River Basin in Taiwan, including basin (large), watershed (medium), and city (small) scales. The results demonstrate that, on the basin scale, land-cover changes interpreted from satellite images are very helpful for identifying the watersheds with urbanization hotspots that might have larger runoff outputs. However, on the watershed scale, the resolution of the land-cover data is too low, and land-cover data should be replaced by investigated land-use data for sophisticated hydrological modeling. The mixed usage of land-cover and land-use data is not recommended because large discrepancies occur when determining hydrological parameters for runoff simulation. According to present and future land-use scenarios, the influence of urbanization on runoff is simulated by HEC-1 and SWMM on watershed and city scales, respectively. The results of both models are in agreement and show that runoff peaks will obviously increase as a result of urbanization from 2008 to 2030. For low return periods, the increase in runoff as a result of urbanization is more significant and the city’s contribution to runoff is much larger than its area. Through statistical regression, the watershed runoff simulated by HEC-1 can be perfectly predicted by the city runoff simulated by SWMM in combination with other land/rainfall parameters. On the city scale, the installation of LID satisfactorily reduces the runoff peaks to pre-urbanization levels for low return periods, but the effects of LID are not as positive and are debatable for higher return periods. These findings can be used to realize the applicability and limitations of different approaches for analyzing and mitigating urbanization-induced runoff in the process of constructing a sponge city.

Shallow landslide initiation on terraced slopes: inferences from a physically based approach

ABSTRACTIn the last years, great efforts have been made to improve the assessment of the temporal and spatial occurrence of rainfall-induced shallow landslides. Therefore, in this paper we used a physically based stability model (TRIGRS) in order to reproduce the landslide event occurred in the Monterosso catchment (Cinque Terre, Eastern Liguria, Italy) on 25 October 2011. The input parameters of the numerical model have been evaluated taking into account the land-use setting and paying specific attention to the evaluation of the spatial variation of soil thickness on terraced areas. The resulting safety factor maps have been compared with the inventory map of the landslides triggered during the event. The simulation results, which have been obtained also considering four different spatial resolutions of the digital terrain model, emphasize the influence of land use in shallow landslide occurrence and indicate the importance of a realistic spatial variation of soil thickness to enhance the reliability of the model. Finally, different triggering scenarios have been defined using hourly rainfall values statistically derived from historical data. The results indicate the proneness of the area to shallow landsliding, given that rainfall events with a relatively low return period (e.g. 25 years) can trigger numerous slope failures.

Development of damage functions for flood risk assessment in the city of Colombo (Sri Lanka)

Abstract Depth vs. damage curves were developed for a flood risk assessment carried out in Colombo, Sri Lanka. The major elements of the damage assessment comprised building fabrics, building contents, distributed infrastructure and vehicles. Current approaches to damage function development were improved on by separating damage to building fabric and contents; using actual building footprints rather than assigning building functions to city zones; assessing infrastructure damage accurately; and incorporating damage to vehicles. Information sources included infrastructure agencies, bills of quantities for buildings, expert consultations, household surveys and insurance agencies. The building fabric was assigned three categories, namely semi-permanent, single storey and two storey. The building contents were classified into 7 types based on function as warehouse/storage, industrial, shops, offices, residential, educational and health. The proportion of contents asset values to that of the fabric ranged from 1.67 for warehouse/storage to 0.20for educational. Both ‘what-if’ analyses and historic data were used to generate the curves. Data were obtained as losses per unit area or unit length; or as point losses.For the 140 square km urban area, the generated flood damages ranged from USD 37 to 549 million for return periods from 5 to 100 years, with average inundation depths ranging from 0.48 m to 1.28 m (and outliers up to 5.8 m). The total non-residential to residential building damage increased with return period (and together accounted for 75-85% of damage). The residential contents to fabric damage ratio was generally around 1.5. The percentage damage to infrastructure was not very significant, although that to vehicles was, especially at lower return periods.

Earthquake-Induced Damage Detection in a Monumental Masonry Bell-Tower Using Long-Term Dynamic Monitoring Data

ABSTRACTThis work investigates the use of an advanced long-term vibration-based structural health monitoring tool to automatically detect earthquake-induced damages in heritage structures. Damage produced in a monumental bell-tower at increasing values of the Peak Ground Acceleration (PGA) of the seismic input is predicted by incremental nonlinear dynamic analysis, using a Finite Element model calibrated on the basis of experimentally identified natural modes. Then, predicted damage effects are artificially introduced in the monitoring data to check for their detectability. The results demonstrate that a very small damage, associated to a low intensity and low return period earthquake, is clearly detected by the monitoring system.

Quantifying the impact of community-scale flood mitigation

Federal, State, and local governments, non-governmental organizations, and independent local community organizations spend billions of dollars on watershed management activities. The goals of watershed management projects may span a wide spectrum including, but limited to flood reduction, soil erosion reduction, water quality improvement or protection, and/or increase source of wood fiber for fuel or construction material. Accomplishing these goals is commonly done through revegetation campaigns, construction of small-scale hydraulic works, contour terracing, and urban development planning, among others. An ongoing challenge for these agencies, along with local stakeholders is to understand the various individual and combined impacts of different mitigation measures.The methodology and models developed and applied herein provide important tools for examining the feasibility of construction and the likely impacts of gabion dams and vegetation coverage applications (e.g., hillside and channel revegetation campaigns) in steep mountainous areas upstream of populated areas. The purpose of this investigation is to quantify the impact of changes in the size and location of the gabion dams and of changes in vegetation coverage in the Ravine Millet watershed near Port-au-Price, Haiti. This environment frequently experiences strong convective precipitation events, often the result of hurricane passage over the region.Intensity-Duration-Frequency curves were developed with available data, which were then used to develop design storms associated with different return period frequencies. Hourly satellite-derived precipitation was used to identify the shape and duration of various return period storm events. This investigation then applies some commonly available hydrologic and hydraulic models and various concomitant tools used to construct those models, along with a Kinematic Routing Model to assess the impact of various mitigation strategies. Storm events with multiple peaks of similar magnitude interact with channel geometry and other hydraulic characteristics and may result in peak delay or reduce the time of arrival and may increase or decrease the magnitude of flood peaks. Results indicate that hillslope revegetation impacts to flood peak and the time or arrival of flood peaks at the watershed outlet are limited to relatively low return period storms. Results also indicate that channel vegetation can reduce the peak discharge and significantly delay the arrival of flood peaks. The combined impacts of gabion dams and channel vegetation are highly non-linear, and depend on the shape and duration of storm peaks.

Extreme weather exposure identification for road networks – a comparative assessment of statistical methods

Abstract. The assessment of road infrastructure exposure to extreme weather events is of major importance for scientists and practitioners alike. In this study, we compare the different extreme value approaches and fitting methods with respect to their value for assessing the exposure of transport networks to extreme precipitation and temperature impacts. Based on an Austrian data set from 25 meteorological stations representing diverse meteorological conditions, we assess the added value of partial duration series (PDS) over the standardly used annual maxima series (AMS) in order to give recommendations for performing extreme value statistics of meteorological hazards. Results show the merits of the robust L-moment estimation, which yielded better results than maximum likelihood estimation in 62 % of all cases. At the same time, results question the general assumption of the threshold excess approach (employing PDS) being superior to the block maxima approach (employing AMS) due to information gain. For low return periods (non-extreme events) the PDS approach tends to overestimate return levels as compared to the AMS approach, whereas an opposite behavior was found for high return levels (extreme events). In extreme cases, an inappropriate threshold was shown to lead to considerable biases that may outperform the possible gain of information from including additional extreme events by far. This effect was visible from neither the square-root criterion nor standardly used graphical diagnosis (mean residual life plot) but rather from a direct comparison of AMS and PDS in combined quantile plots. We therefore recommend performing AMS and PDS approaches simultaneously in order to select the best-suited approach. This will make the analyses more robust, not only in cases where threshold selection and dependency introduces biases to the PDS approach but also in cases where the AMS contains non-extreme events that may introduce similar biases. For assessing the performance of extreme events we recommend the use of conditional performance measures that focus on rare events only in addition to standardly used unconditional indicators. The findings of the study directly address road and traffic management but can be transferred to a range of other environmental variables including meteorological and hydrological quantities.

Hydrological impacts of land use–land cover change and detention basins on urban flood hazard: a case study of Poisar River basin, Mumbai, India

Flooding in urban area is a major natural hazard causing loss of life and damage to property and infrastructure. The major causes of urban floods include increase in precipitation due to climate change effect, drastic change in land use–land cover (LULC) and related hydrological impacts. In this study, the change in LULC between the years 1966 and 2009 is estimated from the toposheets and satellite images for the catchment of Poisar River in Mumbai, India. The delineated catchment area of the Poisar River is 20.19 km2. For the study area, there is an increase in built-up area from 16.64 to 44.08% and reduction in open space from 43.09 to 7.38% with reference to total catchment area between the years 1966 and 2009. For the flood assessment, an integrated approach of Hydrological Engineering Centre-Hydrological Modeling System (HEC-HMS), HEC-GeoHMS and HEC-River analysis system (HEC-RAS) with HEC-GeoRAS has been used. These models are integrated with geographic information system (GIS) and remote sensing data to develop a regional model for the estimation of flood plain extent and flood hazard analysis. The impact of LULC change and effects of detention ponds on surface runoff as well as flood plain extent for different return periods have been analyzed, and flood plain maps are developed. From the analysis, it is observed that there is an increase in peak discharge from 2.6 to 20.9% for LULC change between the years 1966 and 2009 for the return periods of 200, 100, 50, 25, 10 and 2 years. For the LULC of year 2009, there is a decrease in peak discharge from 10.7% for 2-year return period to 34.5% for 200-year return period due to provision of detention ponds. There is also an increase in flood plain extent from 14.22 to 42.5% for return periods of 10, 25, 50 and 100 years for LULC change between the year 1966 and year 2009. There is decrease in flood extent from 4.5% for 25-year return period to 7.7% for 100-year return period and decrease in total flood hazard area by 14.9% due to provisions of detention pond for LULC of year 2009. The results indicate that for low return period rainfall events, the hydrological impacts are higher due to geographic characteristics of the region. The provision of detention ponds reduces the peak discharge as well as the extent of the flooded area, flood depth and flood hazard considerably. The flood plain maps and flood hazard maps generated in this study can be used by the Municipal Corporation for flood disaster and mitigation planning. The integration of available software models with GIS and remote sensing proves to be very effective for flood disaster and mitigation management planning and measures.

基于Copula函数的嘉陵江流域干支流洪水遭遇分析

洪水遭遇是一个多变量水文事件，目前研究多限于对实测资料进行统计分析。基于二维copula函数分别建立嘉陵江干流北碚站与支流小河坝站、罗渡溪站、武胜站洪峰流量的联合分布。计算各站不同重现期的设计洪水，推求出对应的洪水遭遇概率。结果表明，嘉陵江流域低重现期洪水遭遇概率大于高重现期；同一重现期下，嘉陵江各支流与干流(北碚站)的洪水遭遇概率，渠江大于嘉陵江，涪江最低。此方法为计算洪水遭遇分析计算提供了一条新途径。 Flood coincidence probability is a multivariable hydrologic event. At present, the research is mostly limited to the statistical analysis of observed data. In this study, the annual maximum flood peak data of four hydrological stations in Jialing River and its tributaries, including the Beibei, Xiaoheba, Luoduxi and Wusheng station, are selected for case study. The bivariate copula functions are introduced and used to construct the joint distributions of flood peak. The design flood and flood coincidence probability are computed for different return periods. The result shows that the flood coincidence probability of high return periods is smaller than low return periods. The flood coincidence probability of Jialing River and its tributaries in the same return periods, Qujiang River is greater than Jialing River, and Fujiang River is among the smallest. This study will provide a new approach for Flood encounter analysis.

Reconstruction of a flash flood event through a multi-hazard approach: focus on the Rwenzori Mountains, Uganda

The increased use of complex and holistic modelling for multi-hazard analysis is in sharp contrast with a lacuna in hazard analysis in equatorial Africa. This study aims to increase understanding of multi-hazard events in poorly documented regions with low accessibility. We focus on the Nyamwamba catchment (107 km2) located in the Rwenzori Mountains (Uganda) where on May 1, 2013, a severe flash flood occurred. In this region, wildfires, earthquakes and landslides occur as well. Here we reconstruct the circumstances under which this flash flood event was triggered, characterize the different processes acting upon the catchment dynamics and estimate the damaging effects of the flash flood within the catchment. The combined occurrence of intense rainfall, a forest fire having burned 18 % of the catchment area and the occurrence of 29 landslides providing debris to the river system, induced a debris-rich and very destructive flash flood which caused several fatalities, the destruction of 70 buildings, several bridges, a hospital, a school, a tarmac road and several lifelines. Although the methodologies applied to estimate peak discharge, detect landslides and delineate wildfires are well established in their disciplines and sometimes limited in their precision, their combination is required to demonstrate the importance of the wildfire and landslides for the magnitude of this flood, unprecedented in decades but characterized by a low return period of the triggering rainfall event. This indicates that flash floods should not be considered as self-determined phenomena but as a result of several cascading and interacting hazard processes.

Vibration-based structural health monitoring of a historic bell-tower using output-only measurements and multivariate statistical analysis

This article presents the development and the results of 1 year of implementation of a simple vibration-based structural health monitoring system for preventive conservation and condition-based maintenance of an Italian monumental masonry bell-tower. The system is based on the data recorded by a small number of high-sensitivity accelerometers, on remote automated frequency tracking and on a multivariate statistical analysis criterion for damage detection, combining data regression, principal component analysis, and novelty analysis. The analysis of monitoring data highlights the main characteristics of the response of the tower to wind, swinging bells, and low-return period earthquakes. Despite the low levels of vibration in operational conditions, the system is seen able to track the time evolution of five natural frequencies of the structure and successfully use such information for detecting anomalous deviations from normal conditions. More in general, the presented results show a promise toward a more widespread use of low-cost vibration-based monitoring systems for cultural heritage preservation.

Analysis of Spatio-temporal Characteristics and Regional Frequency of Droughts in the Southern Peninsula of India

A detailed regional drought study is carried out in the southern peninsula of India to characterize the spatio-temporal nature of droughts and to predict the drought magnitudes for various probabilities in the homogeneous drought regions. The method of several random initializations of the cluster centres of the K-means algorithm is suggested for the identification of the initial regions in the context of drought regionalization, which is shown to perform better than the initialization from the Ward’s algorithm and the Ward’s algorithm itself. The peninsula is classified into seven spatially well-separated homogeneous drought regions. The robust L-moment framework is used for the regional frequency analysis of drought magnitudes computed using the standardized precipitation index. The Pearson type III is found to be appropriate for regional drought frequency analysis in six of the regions, while the robust Wakeby distribution is suggested for one region. Low magnitude droughts are frequent and dominant in the northern part of west coast, the north-eastern coast and its adjoining inland region, while high magnitude droughts are less in number and are experienced in semi-arid central part, southern part of western coast, south-eastern part and north-western inland region. The spatial maps of drought magnitudes indicate that at higher return periods (100 and 200 years) the south-eastern part of the peninsula is likely to encounter high magnitude droughts, while the central region is likely to experience the same at lower return periods (10 and 50 years). Hence these regions need to be given special importance in the drought mitigation planning activities.

Storms or cold fronts: what is really responsible for the extreme waves regime in the Colombian Caribbean coastal region?

Abstract. The aim of this study is to determine the contribution and importance of cold fronts and storms to extreme waves in different areas of the Colombian Caribbean in an attempt to determine the extent of the threat posed by the flood processes to which these coastal populations are exposed. Furthermore, the study wishes to establish the actions to which coastal engineering constructions should be subject. In the calculation of maritime constructions, the most important parameter is the height of the wave. For this reason, it is necessary to establish the design wave height to which a coastal engineering structure should be resistant. This wave height varies according to the return period considered. The significant height values for the areas focused on in the study were calculated in accordance with Gumbel's extreme value methodology. The methodology was evaluated using data from the reanalysis of the spectral National Oceanic and Atmospheric Administration (NOAA) WAVEWATCH III® (WW3) model for 15 points along the 1600 km of the Colombian Caribbean coastline (continental and insular) between the years 1979 and 2009. The results demonstrated that the extreme waves caused by tropical cyclones and those caused by cold fronts have different effects along the Colombian Caribbean coast. Storms and hurricanes are of greater importance in the Guajira Peninsula (Alta Guajira). In the central area (consisting of Baja Guajira, and the cities of Santa Marta, Barranquilla, and Cartagena), the strong impact of cold fronts on extreme waves is evident. However, in the southern region of the Colombian Caribbean coast (ranging from the Gulf of Morrosquillo to the Gulf of Urabá), the extreme values of wave heights are lower than in the previously mentioned regions, despite being dominated mainly by the passage of cold fronts. Extreme waves in the San Andrés and Providencia insular region present a different dynamic from that in the continental area due to their geographic location. The wave heights in the extreme regime are similar in magnitude to those found in Alta Guajira, but the extreme waves associated with the passage of cold fronts in this region have lower return periods than those associated with the hurricane season.

The impact of catchment management on emergency management of flash-flood

Flash floods cause damages and need emergency actions especially in urban areas. Flood forecasting and flood warning systems (FFFWSs) can be used for reducing flood damages and saving lives in areas vulnerable to flooding. However, researches are needed to evaluate the effect of urbanisation and the significance of implementing catchment-management plan (ICMP) on FFFWS. This paper describes a framework proposed to assess the impact of ICMP on expected lead time (ELT) of flash-flood warning and it was applied for an urbanised steep catchment in an arid region, north of metropolitan city, Tehran, Iran. The model is well calibrated and validated before and after ICMP by four observed floods. The results show that ICMP reduces mainly flood risk only in low-return periods (about 30%) than in high-return periods. Finally, this paper demonstrated the efficiency of ICMP in increasing emergency time for evacuation from possible inundated areas except in extreme floods events.

Regionalization of Rainfall Intensity-Duration-Frequency (IDF) Curves in Botswana

A regional analysis of design storms, defined as the expected rainfall intensity for given storm duration and return period, is conducted to determine storm Rainfall Intensity-Duration-Frequency (IDF) relationships. The ultimate purpose was to determine IDF curves for homogeneous regions identified in Botswana. Three homogeneous regions were identified based on topographic and rainfall characteristics which were constructed with the K-Means Clustering algorithm. Using the mean annual rainfall and the 24 hr annual maximum rainfall as an indicator of rainfall intensity for each homogeneous region, IDF curves and maps of rainfall intensities of 1 to 24 hr and above durations were produced. The Gamma and Lognormal probability distribution functions were able to provide estimates of rainfall depths for low and medium return periods (up to 100 years) in any location in each homogeneous region of Botswana.

Aplicación de la distribución de probabilidades no acotada del Sistema Johnson para estimación de crecientes

Floods designs constitute a key to estimate the sizing of new water works and to review the hydrological security of existing ones. The most reliable method for estimating their magnitudes associated with certain return periods is to fit a probabilistic model to available records of maximum annual flows. Since such model is at first unknown, several models need to be tested in order to select the most appropriate one according to an arbitrary statistical index, commonly the standard error of fit. Several probability distributions have shown versatility and consistency of results when processing floods records and therefore, its application has been established as a norm or precept. The Johnson System has three families of distributions, one of which is the Log–Normal model with three parameters of fit, which is also the border between the bounded distributions and those with no upper limit. These families of distributions have four adjustment parameters and converge to the standard normal distribution, so that their predictions are obtained with such a model. Having contrasted the three probability distributions established by precept in 31 historical records of hydrological events, the Johnson system is applied to such data. The results of the unbounded distribution of the Johnson system (SJU) are compared to the optimal results from the three distributions. It was found that the predictions of the SJU distribution are similar to those obtained with the other models in the low return periods (< 50 years) and in general are of the same order of magnitude in higher recurrence intervals (> 1000 years). Because of its theoretical support, the SJU model is recommended in flood estimation.

Evaluation of shallow landslide-triggering scenarios through a physically based approach: an example of application in the southern Messina area (northeastern Sicily, Italy)

Abstract. Rainfall-induced shallow landslides are a widespread phenomenon that frequently causes substantial damage to property, as well as numerous casualties. In recent~years a wide range of physically based models have been developed to analyze the triggering process of these events. Specifically, in this paper we propose an approach for the evaluation of different shallow landslide-triggering scenarios by means of the TRIGRS (transient rainfall infiltration and grid-based slope stability) numerical model. For the validation of the model, a back analysis of the landslide event that occurred in the study area (located SW of Messina, northeastern Sicily, Italy) on 1 October 2009 was performed, by using different methods and techniques for the definition of the input parameters. After evaluating the reliability of the model through comparison with the 2009 landslide inventory, different triggering scenarios were defined using rainfall values derived from the rainfall probability curves, reconstructed on the basis of daily and hourly historical rainfall data. The results emphasize how these phenomena are likely to occur in the area, given that even short-duration (1–3 h) rainfall events with a relatively low return period (e.g., 10–20~years) can trigger numerous slope failures. Furthermore, for the same rainfall amount, the daily simulations underestimate the instability conditions. The high susceptibility of this area to shallow landslides is testified by the high number of landslide/flood events that have occurred in the past and are summarized in this paper by means of archival research. Considering the main features of the proposed approach, the authors suggest that this methodology could be applied to different areas, even for the development of landslide early warning systems.

Sample size effect on the reliability and calibration of design wind load

The small sample size of the annual maximum wind speed at a wind speed recording site causes uncertainty in the estimated return period of wind speed. The influence of this uncertainty on the estimated return period values of annual maximum wind speed and structural reliability is quantified in this study. The results show that the effect of statistical uncertainty due to limited sample size on the estimated return period value of the wind speed and structural reliability is largely reduced if the sample size is increased from 10 to 20. The implication of the results is discussed in terms of two alternative options to specify the factored design wind load: (i) a low return period for selecting nominal wind speed combined with a large wind load factor and (ii) a high return period for selecting nominal wind speed combined with unity wind load factor. It was concluded that option (i) is preferred to cope with sample size effect if the design in a region with statistically homogeneous wind climate; for code making with spatially varying coefficient of variation of annual maximum wind speed, the analysis results support the use of option (ii) since it leads to improved consistency of reliability.

A deterministic approach for shallow landslide triggering scenarios in the southern Messina area (north-eastern Sicily, Italy)

The aim of this work is to define different triggering scenarios for shallow landslides through a physically-based approach. In particular, numerical simulations have been performed using TRIGRS model for the back-analysis of a reference landslide event, i.e. the disaster occurred in the Giampilieri area (located approximately SW of Messina in north-eastern Sicily, Italy) on October 1st, 2009. The simulation results, expressed in terms of safety factor (FS), describe a temporal evolution of the slope instability substantially consistent with the real event. With regard to the spatial distribution of the slope failures, the model is able to identify quite well the 2009 landslide phenomena, since 48.5% of the source areas and 79.8% of the stable areas are correctly classified. After the calibration of the physically-based model, different triggering scenarios have been reconstructed by varying the rainfall input, on the basis of the hourly rainfall probability curves obtained through a statistical analysis of historical rainfall data. The results indicate that even rainfalls with low return period and short duration (i.e. one hour) can produce a considerable instability level, in agree with the high number of landslide/flood events recorded in the study area since the last century.

Is the Ex-Ante Equity Risk Premium Always Positive? Evidence from a New Conditional Expectations Model

In this paper, we propose a new two-stage method, including Principal Component Analysis and Boosted Regression Tree, to model conditional expected returns. With this technique, we address two potential criticisms on how to capture the true identity of the investors’ information set, and how investors use the information in forming expected returns. Applying this risk premium proxy, we test whether risk premium is always positive. A number of asset pricing studies have focused on testing linear restrictions imposed by asset pricing models and largely ignore this important restriction. We find evidence that the positivity condition of the risk premium is violated for the US (CRSP index) in some states of the economy; these states are associated with periods of low corporate returns, low long term government bond returns, lagged negative risk premium, and downward sloping term structure.

Projected Changes in the Dynamics of Flood Hazard in the Grand River Basin, Canada

In this study future flooding frequencies have been estimated for the Grand River catchment located in south - western Ontario, Canada. Historical and future climatic projections made by fifteen Coupled Model Inter - comparison Project - 3 climate models are bias - corrected and downscaled before they are used to obtain mid - and end of 21 st century streamflow projections. By comparing the future projected and historically observed precipitation and temperature record s it is found that the mean and extreme temperature events will intensify in future across the catchment. The increase is more drastic in the case of extreme events than the mean events. The sign of change in future precipitation is uncertain. Further flow extremes are expected to increase in magnitude and frequency in future across the catchment. The confidence in the projection is more for low return period (<10 years) extreme events than higher return period (10 - 100 years) events. It can be expected that increases in temperature will play a dominant role in increasing the magnitude of low return period flooding events while precipitation seems to play an important role in shaping the high return period events.