Modelling the influence of hydrogeological parameters on low flow in hilly and mountainous regions of Serbia / Modélisation de l'influence de paramètres hydrogéologiques sur les basses eaux dans des régions de collines et de montagnes de Serbie

Abstract

During dry weather periods of the year with long rainless intervals, streams slacken to what is generally termed “low flow”. This work presents an analysis of the influence of hydrogeology on low flows, using multiple linear regression, in natural medium and small streams in hilly and mountainous regions of Serbia. The study cases encompass 61 gauged catchments south of the rivers Sava and Danube. Characteristic relevant minimum mean 30-day flows of 80- or 95-percentile exceedence (Q _80%, Q _95%) are taken as dependent variables. Independent variables are the observable hydrogeological quantities: catchment area upstream of a gauging station; surface area of a hydrogeological soil category in a catchment; number of perennial springs of minimum flow higher than or equal to 1 L/s in a gauged catchment; number of perennial springs, each of minimum flow higher than or equal to 1 L/s, in a given hydrogeological soil category of the catchment; cumulative perennial spring flow of minimum single flow higher than or equal to 1 L/s in a catchment; and cumulative perennial spring flow of minimum single flow higher than or equal to 1 L/s in a hydrogeological soil category of a catchment. Through multiple linear regression between the characteristic relevant low flow and the hydrogeological elements, 16 models are developed and analysed, each based on a different combination of hydrogeological elements and characteristic low flow. The regional relationships developed for the minimum mean 30-day flows of 80- and 95-percentile exceedences are evaluated. The statistical tests of the representation quality of each multiple regression relationship show that the models justify the use of hydrogeological elements.     

Seasonality indices for regionalizing low flows

In this study we examine three seasonality indices for their potential in regionalizing low flows. The indices are seasonality histograms (SHs) that represent the monthly distribution of low flows, a cyclic seasonality index (SI) that represents the average timing of low flows within a year, and the seasonality ratio (SR), which is the ratio of summer and winter low flows. The rationale of examining these indices is the recognition that summer and winter low flows are subject to important differences in the underlying hydrological processes. We analyse specific low flow discharges q₉₅, i.e. the specific discharge that is exceeded on 95% of all days at a particular site. Data from 325 subcatchments in Austria, ranging in catchment area from 7 to 963 km², are used in the analysis. In a first step, three seasonality indices are compared. Their spatial patterns can be interpreted well on hydrological grounds. In a second step, the indices are used to classify the catchments into two, three, and eight regions based on different combinations of the indices. In a third step, the value of the seasonality indices for low flow regionalization is examined by comparing the cross‐validation performance of multiple regressions between low flows and catchment characteristics. The regressions make use of the three seasonality‐based classifications. The results indicate that grouping the study area into two regions and three regions and separate regressions in each region gives the best performance. A global regression model yields the lowest performance and a global regression model that uses different calibration coefficients in each of the eight regions only performs slightly better. This suggests that separate regression models in each of the regions are to be preferred over a global model in order to represent differences in the way catchment characteristics are related to low flows. Copyright © 2006 John Wiley & Sons, Ltd.     

Physically‐based modelling of double‐peak discharge responses at Slapton Wood catchment

Heavy winter rainfall produces double‐peak hydrographs at the Slapton Wood catchment, Devon, UK. The first peak is saturation‐excess overland flow in the hillslope hollows and the second (i.e. the delayed peak) is subsurface stormflow. The physically‐based spatially‐distributed model SHETRAN is used to try to improve the understanding of the processes that cause the double peaks. A three‐stage (multi‐scale) approach to calibration is used: (1) water balance validation for vertical one‐dimensional flow at arable, grassland and woodland plots; (2) two‐dimensional flow for cross‐sections cutting across the stream valley; and (3) three‐dimensional flow in the full catchment. The main data are for rainfall, stream discharge, evaporation, soil water potential and phreatic surface level. At each scale there was successful comparison with measured responses, using as far as possible parameter values from measurements. There was some calibration but all calibrated values at one scale were used at a larger scale. A large proportion of the subsurface runoff enters the stream from three dry valleys (hillslope hollows), and previous studies have suggested convergence of the water in the three large hollows as being the major mechanism for the production of the delayed peaks. The SHETRAN modelling suggests that the hillslopes that drain directly into the stream are also involved in producing the delayed discharges. The model shows how in the summer most of the catchment is hydraulically disconnected from the stream. In the autumn the catchment eventually ‘wets up’ and shallow subsurface flows are produced, with water deflected laterally along the soil‐bedrock interface producing the delayed peak in the stream hydrograph. Copyright © 2007 John Wiley & Sons, Ltd.     

Quantifying hydrological budgets and pathways in a small upland catchment using a combined modelling and tracer approach

Hydrological budgets and flow pathways have been quantified for a small upland catchment (1.76 km²) in the northeast of Scotland. Water balance calculations for four subcatchments identified spatial variability within the catchment, with an estimated runoff enhancement of up to 25% for the upper western area, compared with the rest of the catchment. Data from spatial hydrochemical sampling, over a range of flow conditions, were used to identify the principal hillslope runoff mechanisms within the catchment. A hydrochemical mixing analysis revealed that runoff emerging from springs in various locations of the hillslope accounted for a significant proportion of flow in the streams, even during storm events. A hydrological model of the catchment was calibrated using the calculated stream flows for four locations, together with results from the mixing analysis for different time points. The calibrated model was used to predict the temporal variability in contributions to stream flow from the hillslope springs and soil water flows. The overall split ranged from 57%:43% spring water:soil water in the upper eastern subcatchment, to 76%:24% in the upper western subcatchment. Copyright © 2006 John Wiley & Sons, Ltd.     

Regional flood frequency analysis using Bayesian generalized least squares: a comparison between quantile and parameter regression techniques

Regression‐based regional flood frequency analysis (RFFA) methods are widely adopted in hydrology. This paper compares two regression‐based RFFA methods using a Bayesian generalized least squares (GLS) modelling framework; the two are quantile regression technique (QRT) and parameter regression technique (PRT). In this study, the QRT focuses on the development of prediction equations for a flood quantile in the range of 2 to 100 years average recurrence intervals (ARI), while the PRT develops prediction equations for the first three moments of the log Pearson Type 3 (LP3) distribution, which are the mean, standard deviation and skew of the logarithms of the annual maximum flows; these regional parameters are then used to fit the LP3 distribution to estimate the desired flood quantiles at a given site. It has been shown that using a method similar to stepwise regression and by employing a number of statistics such as the model error variance, average variance of prediction, Bayesian information criterion and Akaike information criterion, the best set of explanatory variables in the GLS regression can be identified. In this study, a range of statistics and diagnostic plots have been adopted to evaluate the regression models. The method has been applied to 53 catchments in Tasmania, Australia. It has been found that catchment area and design rainfall intensity are the most important explanatory variables in predicting flood quantiles using the QRT. For the PRT, a total of four explanatory variables were adopted for predicting the mean, standard deviation and skew. The developed regression models satisfy the underlying model assumptions quite well; of importance, no outlier sites are detected in the plots of the regression diagnostics of the adopted regression equations. Based on ‘one‐at‐a‐time cross validation’ and a number of evaluation statistics, it has been found that for Tasmania the QRT provides more accurate flood quantile estimates for the higher ARIs while the PRT provides relatively better estimates for the smaller ARIs. The RFFA techniques presented here can easily be adapted to other Australian states and countries to derive more accurate regional flood predictions. Copyright © 2011 John Wiley & Sons, Ltd.     

Effect of climate changes and water‐related human activities on annual stream flows of the Shiyang river basin in arid north‐west China

The change of annual stream flow in the Shiyang river basin, a typical arid‐inland basin in north‐west China, was investigated using hydrological, meteorological and water‐related human activities' data of the past 50 years. The long‐term trends of the hydrological time series were examined by non‐parametric techniques, including the Pettitt and Mann–Kendall tests. Double cumulative curves and multi‐regression methods were used to separate and quantify the effects of climate changes and human activities on the stream flows. The results show that the study area has been experiencing a significant upward warming trend since 1986 and precipitation shows a decreasing trend in the mountainous region but an increasing trend in the plains region. All stream flows in the upper reach and lower reaches of the Shiyang river exhibit decreasing tendencies. Since 1970, human activities, such as irrigation, have had a significant effect on the upstream flow, and account for 60% of total flow decreases in the 1970s. However, climate changes are the main reason for the observed flow decreases in the 1980s and 1990s, with contributions to total flow decrease of 68% and 63%, respectively. Before 1975, flow decreases in the upper reaches were the main factor causing reduced flows in the lower reaches of the Shiyang river. After 1975, the effect of human activities became more pronounced, with contributions of 63%, 68% and 56% to total flow decreases in the lower reaches of the Shiyang river in the periods 1975 to 1980, 1980s and 1990s, respectively. As a result, climate change is responsible for a large proportion of the flow decreases in the upstream section of the catchment during the 1980s and 1990s, while human activities have caused flow decreases downstream during the same period. Copyright © 2007 John Wiley & Sons, Ltd.     

Assessment of the adequacy of the regional relationships between catchment attributes and catchment response dynamics,calibrated by a multi‐objective approach

This study aimed to evaluate the effectiveness of the regionalization method on the basis of a combination of a parsimonious model structure and a multi‐objective calibration technique. For this study, 12 gauged catchments in the Republic of Korea were used. The parsimonious model structure, requiring minimal input data, was used to avoid adverse effects arising from model complexity, over‐parameterization and data requirements. The IHACRES rainfall‐runoff model was applied to represent the dynamic response characteristics of catchments in Korea. A multi‐objective approach was adopted to reduce the predictive uncertainty arising from the calibration of a rainfall‐runoff model, by increasing the amount of information retrieved from the available data. The regional relationships (or models) between the model parameters and the catchment attributes were established via a multiple regression approach, incorporating correlation analysis and stepwise regression on linear and logarithmic scales. The impacts of the parameters, calibrated by the multi‐objective approach, on the adequacy of regional relationships were assessed by comparison with impacts obtained by the single‐objective approach. The regional relationships were well defined, despite limited available data. The drainage area, the effective soil depth, the mean catchment slope and the catchment gradient appeared to be the main factors for describing the hydrologic response characteristics in the areas studied. The overall model performance of the regional models based on the multi‐objective approach was good, producing reasonable results for high and low flows and for the overall water balance, simultaneously. The regional models based on the single‐objective approach yielded accurate predictions in high flows but showed limited predictive capability for low flows and the overall water balance. This was due to the optimal model parameter estimates when using a single‐objective measure. The parameters calibrated by the single‐objective approach decreased the predictability of the regional models. Copyright © 2013 John Wiley & Sons, Ltd.     

Cokriging for enhanced spatial interpolation of rainfall in two Australian catchments

Rainfall data in continuous space provide an essential input for most hydrological and water resources planning studies. Spatial distribution of rainfall is usually estimated using ground‐based point rainfall data from sparsely positioned rain‐gauge stations in a rain‐gauge network. Kriging has become a widely used interpolation method to estimate the spatial distribution of climate variables including rainfall. The objective of this study is to evaluate three geostatistical (ordinary kriging [OK], ordinary cokriging [OCK], kriging with an external drift [KED]), and two deterministic (inverse distance weighting, radial basis function) interpolation methods for enhanced spatial interpolation of monthly rainfall in the Middle Yarra River catchment and the Ovens River catchment in Victoria, Australia. Historical rainfall records from existing rain‐gauge stations of the catchments during 1980–2012 period are used for the analysis. A digital elevation model of each catchment is used as the supplementary information in addition to rainfall for the OCK and kriging with an external drift methods. The prediction performance of the adopted interpolation methods is assessed through cross‐validation. Results indicate that the geostatistical methods outperform the deterministic methods for spatial interpolation of rainfall. Results also indicate that among the geostatistical methods, the OCK method is found to be the best interpolator for estimating spatial rainfall distribution in both the catchments with the lowest prediction error between the observed and estimated monthly rainfall. Thus, this study demonstrates that the use of elevation as an auxiliary variable in addition to rainfall data in the geostatistical framework can significantly enhance the estimation of rainfall over a catchment.     

Channel precipitation dynamics in a forested Pennsylvania headwater catchment (USA)

Seasonal and event variations in stream channel area and the contributions of channel precipitation to stream flow were studied on a 106‐ha forested headwater catchment in central Pennsylvania. Variations in stream velocity, flowing stream surface width and widths of near‐stream saturated areas were periodically monitored at 61 channel transects over a two‐year period. The area of flowing stream surface and near‐stream saturated zones combined, ranged from 0·07% of basin area during summer low flows to 0·60% of total basin area during peak storm flows. Near‐stream saturated zones generally represented about half of the total channel area available to intercept throughfall and generate channel precipitation. Contributions of routed channel precipitation from the flowing stream surface and near‐stream zones, calculated using the Penn State Runoff Model (PSRM, v. 95), represented from 1·1 to 6·4% of total stream flow and 2·5–29% of total storm flow (stream flow–antecedent baseflow) during the six events. Areas of near‐stream saturated zones contributed 35–52% of the computed channel precipitation during the six events. Channel precipitation contributed a higher percentage of stream flow for events with low antecedent baseflow when storm flow generated by subsurface sources was relatively low. Expansion of channel area and consequent increases in volumes of channel precipitation with flow increases during events was non‐linear, with greater rates of change occurring at lower than at higher discharge rates. Copyright © 1999 John Wiley & Sons, Ltd.     

Regional flood frequency analysis using residual kriging in physiographical space

In this article, an approach using residual kriging (RK) in physiographical space is proposed for regional flood frequency analysis. The physiographical space is constructed using physiographical/climatic characteristics of gauging basins by means of canonical correlation analysis (CCA). This approach is a modified version of the original method, based on ordinary kriging (OK). It is intended to handle effectively any possible spatial trends within the hydrological variables over the physiographical space. In this approach, the trend is first quantified and removed from the hydrological variable by a quadratic spatial regression. OK is therefore applied to the regression residual values. The final estimated value of a specific quantile at an ungauged station is the sum of the spatial regression estimate and the kriged residual. To evaluate the performance of the proposed method, a cross‐validation procedure is applied. Results of the proposed method indicate that RK in CCA physiographical space leads to more efficient estimates of regional flood quantiles when compared to the original approach and to a straightforward regression‐based estimator. Copyright © 2010 John Wiley & Sons, Ltd.     

Interpolations of groundwater table elevation in dissected uplands

The variable elevation of the groundwater table in the St. Louis area was estimated using multiple linear regression (MLR), ordinary kriging, and cokriging as part of a regional program seeking to assess liquefaction potential. Surface water features were used to determine the minimum water table for MLR and supplement the principal variables for ordinary kriging and cokriging. By evaluating the known depth to the water and the minimum water table elevation, the MLR analysis approximates the groundwater elevation for a contiguous hydrologic system. Ordinary kriging and cokriging estimate values in unsampled areas by calculating the spatial relationships between the unsampled and sampled locations. In this study, ordinary kriging did not incorporate topographic variations as an independent variable, while cokriging included topography as a supporting covariable. Cross validation suggests that cokriging provides a more reliable estimate at known data points with less uncertainty than the other methods. Profiles extending through the dissected uplands terrain suggest that: (1) the groundwater table generated by MLR mimics the ground surface and elicits a exaggerated interpolation of groundwater elevation; (2) the groundwater table estimated by ordinary kriging tends to ignore local topography and exhibits oversmoothing of the actual undulations in the water table; and (3) cokriging appears to give the realistic water surface, which rises and falls in proportion to the overlying topography. The authors concluded that cokriging provided the most realistic estimate of the groundwater surface, which is the key variable in assessing soil liquefaction potential in unconsolidated sediments.     

Modelling stream flow for use in ecological studies in a large,arid zone river,central Australia

Australian arid zone ephemeral rivers are typically unregulated and maintain a high level of biodiversity and ecological health. Understanding the ecosystem functions of these rivers requires an understanding of their hydrology. These rivers are typified by highly variable hydrological regimes and a paucity, often a complete absence, of hydrological data to describe these flow regimes. A daily time‐step, grid‐based, conceptual rainfall–runoff model was developed for the previously uninstrumented Neales River in the arid zone of northern South Australia. Hourly, logged stage data provided a record of stream‐flow events in the river system. In conjunction with opportunistic gaugings of stream‐flow events, these data were used in the calibration of the model. The poorly constrained spatial variability of rainfall distribution and catchment characteristics (e.g. storage depths) limited the accuracy of the model in replicating the absolute magnitudes and volumes of stream‐flow events. In particular, small but ecologically important flow events were poorly modelled. Model performance was improved by the application of catchment‐wide processes replicating quick runoff from high intensity rainfall and improving the area inundated versus discharge relationship in the channel sections of the model. Representing areas of high and low soil moisture storage depths in the hillslope areas of the catchment also improved the model performance. The need for some explicit representation of the spatial variability of catchment characteristics (e.g. channel/floodplain, low storage hillslope and high storage hillslope) to effectively model the range of stream‐flow events makes the development of relatively complex rainfall–runoff models necessary for multisite ecological studies in large, ungauged arid zone catchments. Grid‐based conceptual models provide a good balance between providing the capacity to easily define land types with differing rainfall–runoff responses, flexibility in defining data output points and a parsimonious water‐balance–routing model. Copyright © 2004 John Wiley & Sons, Ltd.     

The dynamics of natural pipe hydrological behaviour in blanket peat

Natural soil pipes are found in peatlands, but little is known about their hydrological role. This paper presents the most complete set of pipe discharge data to date from a deep blanket peatland in Northern England. In a 17.4‐ha catchment, we identified 24 perennially flowing and 60 ephemerally flowing pipe outlets. Eight pipe outlets along with the catchment outlet were continuously gauged over an 18‐month period. The pipes in the catchment were estimated to produce around 13.7% of annual streamflow, with individual pipes often producing large peak flows (maximum peak of 3.8 l s^?1). Almost all pipes, whether ephemerally or perennially flowing, shallow or deep (outlets > 1 m below the peat surface), showed increased discharge within a mean of 3 h after rainfall commencement and were dominated by stormflow, indicating good connectivity between the peatland surface and the pipes. However, almost all pipes had a longer period between the hydrograph peak and the return to base flow compared with the stream (mean of 23.9 h for pipes, 19.7 h for stream). As a result, the proportion of streamflow produced by the pipes at any given time increased at low flows and formed the most important component of stream discharge for the lowest 10% of flows. Thus, a small number of perennially flowing pipes became more important to the stream system under low‐flow conditions and probably received water via matrix flow during periods between storms. Given the importance of pipes to streamflow in blanket peatlands, further research is required into their wider role in influencing stream water chemistry, water temperature and fluvial carbon fluxes, as well as their role in altering local hydrochemical cycling within the peat mass itself. Enhanced piping within peatlands caused by environmental change may lead to changes in the streamflow regime with larger low flows and more prolonged drainage of the peat. Copyright © 2012 John Wiley & Sons, Ltd.     

Predicting wetted width in any river at any discharge

Coefficients describing at‐a‐station power‐law relationships between discharge and width were calculated by applying multilevel models to field data collected during routine hydrological monitoring at 326 gauging stations across New Zealand. These hydraulic geometry coefficients were then estimated for each of these stations using standard stepwise multiple‐linear regression models. Analysis was carried out to quantify how the relationship between width and discharge changed in relation to several available explanatory variables. All coefficients describing the at‐a‐station hydraulic geometry were found to have statistically significant relationships with catchment area. Statistically significant relationships between each of the coefficients were also found with the addition of catchment climate as an explanatory variable. Further statistically significant relationships were found when station elevation and channel slope, as well as hydrological source of flow and landcover of the upstream catchment were added to the explanatory variables. The level of confidence that can be associated with estimates of width at ungauged sites, and sites with limited data availability, was then assessed by comparing model predictions with independent paired data on observed width and discharge from 197 sites. When compared against these independent data, model predictions of width were improved with the addition of predictor variables of the hydraulic geometry coefficients. The greatest improvements were made when climate was added to catchment area as predictor variables. Minor improvements were made when all available information was used to predict width at these independent sites. Although the analysis was purely empirical, results describing relationships between hydraulic geometry coefficients and catchment characteristics corresponded well with knowledge of the processes controlling at‐a‐station hydraulic geometry of river width. Copyright © 2010 John Wiley & Sons, Ltd.     

Spatial prediction of river channel topography by kriging

Topographic information is fundamental to geomorphic inquiry, and spatial prediction of bed elevation from irregular survey data is an important component of many reach‐scale studies. Kriging is a geostatistical technique for obtaining these predictions along with measures of their reliability, and this paper outlines a specialized framework intended for application to river channels. Our modular approach includes an algorithm for transforming the coordinates of data and prediction locations to a channel‐centered coordinate system, several different methods of representing the trend component of topographic variation and search strategies that incorporate geomorphic information to determine which survey data are used to make a prediction at a specific location. For example, a relationship between curvature and the lateral position of maximum depth can be used to include cross‐sectional asymmetry in a two‐dimensional trend surface model, and topographic breaklines can be used to restrict which data are retained in a local neighborhood around each prediction location. Using survey data from a restored gravel‐bed river, we demonstrate how transformation to the channel‐centered coordinate system facilitates interpretation of the variogram, a statistical model of reach‐scale spatial structure used in kriging, and how the choice of a trend model affects the variogram of the residuals from that trend. Similarly, we show how decomposing kriging predictions into their trend and residual components can yield useful information on channel morphology. Cross‐validation analyses involving different data configurations and kriging variants indicate that kriging is quite robust and that survey density is the primary control on the accuracy of bed elevation predictions. The root mean‐square error of these predictions is directly proportional to the spacing between surveyed cross‐sections, even in a reconfigured channel with a relatively simple morphology; sophisticated methods of spatial prediction are no substitute for field data. Copyright © 2007 John Wiley & Sons, Ltd.     

Modelling and assessment of hydrological changes in a developing urban catchment

Urbanization strongly changes natural catchment by increasing impervious coverage and by creating a need for efficient drainage systems. Such land cover changes lead to more rapid hydrological response to storms and change distribution of peak and low flows. This study aims to explore and assess how gradual hydrological changes occur during urban development from rural area to a medium‐density residential catchment. The Stormwater Management Model (SWMM) is utilized to simulate a series of scenarios in a same developing urban catchment. Sub‐hourly hydro‐meteorological data in warm season is used to calibrate and validate the model in the fully developed catchment in 2006. The validated model is then applied to other cases in development stage and runoff management scenarios. Based on the simulations and observations, three key problems are solved: (1) how catchment hydrology changes with land cover change, (2) how urban development changes pre‐development flows, and (3) how stormwater management techniques affect catchment hydrology. The results show that the low‐frequency flow rates had remarkably increased from 2004 to 2006 along with the increase of impervious areas. Urbanization in the residential catchment expands the runoff contributing area, accelerates hydrological response, raises peak flows in an order of magnitude of over 10, and more than doubles the total runoff volume. The effects of several LID controls on runoff hydrograph were simulated, and the techniques were able to reduce flows towards the pre‐development levels. However, the partly restored flow regime was still clearly changed in comparison to the pre‐development flow conditions. Copyright © 2014 John Wiley & Sons, Ltd.     

Field determination of the spatial variation of resistance to flow along a steep Alpine stream

Accurate field data have been collected along the Febbraro River (central Italian Alps) during quasi‐steady, low‐flow conditions to investigate the spatial variations of hydraulic and geomorphologic quantities potentially affecting resistance to flow. Detailed uncertainty analysis and weighted least‐squares fitting of simple power function relationships to field‐derived data are carried out to identify possible interdependencies between observed variables. Mean flow velocity is found to depend on water‐surface slope, bed material particle size, and upstream drainage area, whereas its dependence on hydraulic depth appears less susceptible to quantification. Upstream drainage area is found to explain the variations of hydraulic depth, water‐surface slope, Gauckler–Strickler conductance coefficient, and (although less significantly) flow discharge. Specifically, a highly significant positive dependence of the Gauckler–Strickler conductance coefficient on the upstream drainage area is found to exist, although anomalies in the variations of hydraulic depth and flow discharge are observed along the stream. The combined use of uncertainty analysis, hydraulic equations, and geomorphological relationships allows a possible characterization of resistance to flow along a steep Alpine stream and, perhaps more importantly, provides useful guidelines for future investigative efforts. Copyright © 2006 John Wiley & Sons, Ltd.     

Generation of runoff series at ungauged locations using empirical orthogonal functions in combination with kriging

The method of Empirical Orthogonal Functions (EOF method) is combined with an objective interpolation technique, kriging, to generate runoff series at ungauged locations. In a case study the results are compared to series interpolated by a combination of EOF analysis and regression using catchment characteristics as independent variables. The results are also compared to linear weighting of an existing runoff series, a commonly used method for spatial interpolation. The influence of altitude on the runoff is studied comparing kriging based on 2 and 3 coordinates. The study showed that the capacity of EOF analysis combined with kriging is as good as the traditionally used linear weighting. The results, when altitude is included in the kriging, are improved.     

Predicting landscape sensitivity to present and future floods in the Pacific Northwest,USA

Floods are the most frequent natural disaster, causing more loss of life and property than any other in the USA. Floods also strongly influence the structure and function of watersheds, stream channels, and aquatic ecosystems. The Pacific Northwest is particularly vulnerable to climatically driven changes in flood frequency and magnitude, because snowpacks that strongly influence flood generation are near the freezing point and thus sensitive to small changes in temperature. To improve predictions of future flooding potential and inform strategies to adapt to these changes, we mapped the sensitivity of landscapes to changes in peak flows due to climate warming across Oregon and Washington. We first developed principal component‐based models for predicting peak flows across a range of recurrence intervals (2‐, 10‐, 25‐, 50‐, and 100‐years) based on historical instantaneous peak flow data from 1000 gauged watersheds in Oregon and Washington. Key predictors of peak flows included drainage area and principal component scores for climate, land cover, soil, and topographic metrics. We then used these regression models to predict future peak flows by perturbing the climate variables based on future climate projections (2020s, 2040s, and 2080s) for the A1B emission scenario. For each recurrence interval, peak flow sensitivities were computed as the ratio of future to current peak flow magnitudes. Our analysis suggests that temperature‐induced changes in snowpack dynamics will result in large (>30–40%) increases in peak flow magnitude in some areas, principally the Cascades, Olympics, and Blue Mountains and parts of the western edge of the Rocky Mountains. Flood generation processes in lower elevation areas are less likely to be affected, but some of these areas may be impacted by floodwaters from upstream. These results can assist land, water, and infrastructure managers in identifying watersheds and resources that are particularly vulnerable to increased peak flows and developing plans to increase their resilience. Copyright © 2015 John Wiley & Sons, Ltd.     

Effects of commercial timber harvesting on streamflow regimes in the Plynlimon catchments,mid‐Wales

This paper presents the first large‐scale British study of the impacts of commercial forest cutting on stream‐flow regimes. The 70% forested headwaters of the River Severn are part of the intensively instrumented long‐term Plynlimon catchment study into the impact of land use on stream flow. The forest area, comprising predominantly Sitka spruce (Picea sitchensis), was planted mainly in the 1930s and 1940s. Harvesting commenced in the mid‐1980s and over the study period about half the forest has been felled. Changes in annual water yield and extreme flows were studied in four nested catchments ranging in area from about 1 to 10 km² and compared with an adjacent benchmark grassland catchment. As expected from earlier process studies the cutting of the forest increased total annual flows. Less expected was the clear evidence that the felling augmented low flows. This informs a long‐standing debate whether upland forestry increases or reduces baseflows. A particularly notable result was the lack of impact of the harvesting on storm peak flows. This may result from the application of forest management guidelines designed to reduce soil damage and erosion during the harvesting, and indicates that the forest itself has a limited impact on flooding. These findings are timely because British forest expansion peaked in the 30 years following the Second World War, and large areas of these woodlands are now approaching economic maturity and will be harvested in the next two decades. Copyright © 2004 John Wiley & Sons, Ltd.