Baseflow Index Research Articles

Projected impacts of climate change on stream salmonids with implications for resilience‐based management

AbstractThe sustainability of freshwater fisheries is increasingly affected by climate warming, habitat alteration, invasive species and other drivers of global change. The State of Michigan, USA, contains ecologically, socioeconomically valuable coldwater stream salmonid fisheries that are highly susceptible to these ecological alterations. Thus, there is a need for future management approaches that promote resilient stream ecosystems that absorb change amidst disturbances. Fisheries professionals in Michigan are responding to this need by designing a comprehensive management plan for stream brook charr (Salvelinus fontinalis), brown trout (Salmo trutta) and rainbow trout (Oncorhynchus mykiss) populations. To assist in developing such a plan, we used stream‐specific regression models to forecast thermal habitat suitability in streams throughout Michigan from 2006 to 2056 under different predicted climate change scenarios. As baseflow index (i.e., relative groundwater input) increased, stream thermal sensitivity (i.e., relative susceptibility to temperature change) decreased. Thus, the magnitude of temperature warming and frequency of thermal habitat degradation were lowest in streams with the highest baseflow indices. Thermal habitats were most suitable in rainbow trout streams as this species has a wider temperature range for growth (12.0–22.5 °C) compared to brook charr (11.0–20.5 °C) and brown trout (12.0–20.0 °C). Our study promotes resilience‐based salmonid management by providing a methodology for stream temperature and thermal habitat suitability prediction. Fisheries professionals can use this approach to protect coldwater habitats and drivers of stream cooling and ultimately conserve resilient salmonid populations amidst global change.

Regionalisation of hydrological responses under land-use change and variable data quality

ABSTRACTEstimating river flows at ungauged sites is generally recognised as an important area of research. In countries or regions with rapid land development and sparse hydrological gauging networks, three particular challenges may arise—data scarcity, data quality, and hydrological non-stationarity. Using data from 44 gauged sub-catchments of the upper Ping catchment in northern Thailand from the period 1995–2006, three relevant flow response indices (runoff coefficient, base flow index and seasonal elasticity of flow) were regionalised by regression against available catchment properties. The runoff coefficient was the most successfully regionalised, followed by base flow index and lastly the seasonal elasticity. The non-stationarity (represented by the differences between two 6-year sub-periods) was significant both in the flow response indices and in land use indices; however relationships between the two sets of indices were weak. The regression equations derived from regionalisation were not helpful in predicting the non-stationarity in the flow indices except somewhat for the runoff coefficient. A partly subjective data quality scoring system was devised, and showed the clear influence of rainfall and flow data quality on regionalisation uncertainty. Recommendations towards improving data support for hydrological regionalisation in Thailand include more relevant soils databases, improved records of abstractions and investment in the gauge network. Widening of the regionalisation beyond the upper Ping and renewed efforts at using remotely sensed rainfall data are other possible ways forward.EDITOR Z.W. Kundzewicz ASSOCIATE EDITOR T. Wagener

Event-based prediction of stream turbidity using a combined cluster analysis and classification tree approach

Summary Stream turbidity typically increases during streamflow events; however, similar event hydrographs can produce markedly different event turbidity behaviors because many factors influence turbidity in addition to streamflow, including antecedent moisture conditions, season, and supply of turbidity-causing materials. Modeling of sub-hourly turbidity as a function of streamflow shows that event model parameters vary on an event-by-event basis. Here we examine the extent to which stream turbidity can be predicted through the prediction of event model parameters. Using three mid-sized streams from the Mid-Atlantic region of the U.S., we show the model parameter set for each event can be predicted based on the event characteristics (e.g., hydrologic, meteorologic and antecedent moisture conditions) using a combined cluster analysis and classification tree approach. The results suggest that the ratio of beginning event discharge to peak event discharge (an estimate of the event baseflow index), as well as catchment antecedent moisture, are important factors in the prediction of event turbidity. Indicators of antecedent moisture, particularly those derived from antecedent discharge, account for the majority of the splitting nodes in the classification trees for all three streams. For this study, prediction of turbidity during streamflow events is based upon observed data (e.g., measured streamflow, precipitation and air temperature). However, the results also suggest that the methods presented here can, in future work, be used in conjunction with forecasts of streamflow, precipitation and air temperature to forecast stream turbidity.

Entropy-based neural networks model for flow duration curves at ungauged sites

An apportionment entropy disorder index (AEDI), capturing both temporal and spatial variability of precipitation, was introduced as a new input parameter to an artificial neural networks (ANN) model to more accurately predict flow duration curves (FDCs) at ungauged sites. The ANN model was trained on the randomly selected 2/3 of the dataset of 147 gauged streams in Ontario, and validated on the remaining 1/3. Both location and scale parameters that define the lognormal distribution for the FDCs were highly sensitive to the driving climatic factors, such as, mean annual precipitation, mean annual snowfall, and AEDI. Of the long list of watershed characteristics, the location parameter was most sensitive to drainage area, shape factor and percent area covered by natural vegetation that enhanced evapotranspiration. However, scale parameter was sensitive to drainage area, watershed slope and the baseflow index. Incorporation of the AEDI in the ANN model improved prediction performance of the location and scale parameters by 7% and 21%, respectively. A case study application of the new model for the design of micro-hydropower generators in ungauged rural headwater streams was presented.

Use of baseflow indices to delineate baseflow dominated and rapid response flow dominated watersheds.

Use of baseflow indices to delineate baseflow dominated and rapid response flow dominated watersheds.

Global Maps of Streamflow Characteristics Based on Observations from Several Thousand Catchments*

AbstractStreamflow Q estimation in ungauged catchments is one of the greatest challenges facing hydrologists. Observed Q from 3000 to 4000 small-to-medium-sized catchments (10–10 000 km2) around the globe were used to train neural network ensembles to estimate Q characteristics based on climate and physiographic characteristics of the catchments. In total, 17 Q characteristics were selected, including mean annual Q, baseflow index, and a number of flow percentiles. Testing coefficients of determination for the estimation of the Q characteristics ranged from 0.55 for the baseflow recession constant to 0.93 for the Q timing. Overall, climate indices dominated among the predictors. Predictors related to soils and geology were relatively unimportant, perhaps because of their data quality. The trained neural network ensembles were subsequently applied spatially over the entire ice-free land surface, resulting in global maps of the Q characteristics (at 0.125° resolution). These maps possess several unique features: they represent observation-driven estimates, they are based on an unprecedentedly large set of catchments, and they have associated uncertainty estimates. The maps can be used for various hydrological applications, including the diagnosis of macroscale hydrological models. To demonstrate this, the produced maps were compared to equivalent maps derived from the simulated daily Q of four macroscale hydrological models, highlighting various opportunities for improvement in model Q behavior. The produced dataset is available online (http://water.jrc.ec.europa.eu/GSCD).

Time series analysis of the long-term hydrologic impacts of afforestation in the Águeda watershed of north-central Portugal

Abstract. The north-central region of Portugal has undergone significant land cover change since the early 1900s, with large-scale replacement of natural vegetation types with plantation forests. This transition consisted of an initial conversion primarily to Pinus pinaster, followed by a secondary transition to Eucalyptus globulus. This land cover change is likely to have altered the hydrologic functioning of this region; however, these potential impacts are not fully understood. To contribute to a better understanding of the potential hydrologic impacts of this land cover change, this study examines the temporal trends in 75 years of data from the Águeda watershed (part of the Vouga Basin) over the period of 1936–2010. A number of hydrometeorological variables were analyzed using a combined Thiel–Sen/Mann–Kendall trend-testing approach, to assess the magnitude and significance of patterns in the observed data. These trend tests indicated that there have been no significant reductions in streamflow over either the entire test period, or during sub-record periods, despite the large-scale afforestation which has occurred. This lack of change in streamflow is attributed to the specific characteristics of the watershed and land cover change. By contrast, a number of significant trends were found for baseflow index, with positive trends in the early data record (primarily during Pinus pinaster afforestation), followed by negative trends later in the data record (primarily during Eucalyptus globulus afforestation). These trends are attributed to land use and vegetation impacts on streamflow generating processes, both due to species differences and to alterations in soil properties (i.e., infiltration capacity, soil water repellency). These results highlight the importance of considering both vegetation types/dynamics and watershed characteristic when assessing hydrologic impacts, in particular with respect to soil properties.

Impacts of Climate Change on Mean Annual Water Balance for Watersheds in Michigan, USA

Evaluation of water balance at the watershed scale is a fundamental step for estimating streamflow in watersheds. Mean annual water balance of 17 watersheds across Michigan were evaluated by comparing observed streamflow with simulated streamflow estimated using Fu’s Equation, which is based on the Budyko Hypothesis. The Budyko Hypothesis describes mean annual water balance as a function of available water and energy. Impact of long-term climatic controls (e.g., precipitation, potential evapotranspiration (ETP)) on mean annual water balance was also investigated with Fu’s Equation. Results indicated that observed streamflow ranged from 237 to 529 mm per year, with an average of 363 mm per year in the study watersheds during 1967–2011. On average, 40% of long-term precipitation in the study watersheds was converted into surface runoff. The performance of Fu’s Equation in estimating mean annual streamflow resulted in Root Mean Square Error (RMSE) value of 64.1 mm/year. Mean annual streamflow was sensitive to changes in mean annual precipitation, and less sensitive to changes in mean annual ETp in the watersheds. With the increase of baseflow index (BFI), mean annual streamflow was less sensitive to climate change. Overall, different contributions of baseflow to streamflow modified the impact of climate controls on mean annual water balance in the baseflow-dominated watersheds.

Flow Regime Classification and Hydrological Characterization: A Case Study of Ethiopian Rivers

The spatiotemporal variability of a stream flow due to the complex interaction of catchment attributes and rainfall induce complexity in hydrology. Researchers have been trying to address this complexity with a number of approaches; river flow regime is one of them. The flow regime can be quantified by means of hydrological indices characterizing five components: magnitude, frequency, duration, timing, and rate of change of flow. Similarly, this study aimed to understand the flow variability of Ethiopian Rivers using the observed daily flow data from 208 gauging stations in the country. With this process, the Hierarchical Ward Clustering method was implemented to group the streams into three flow regimes (1) ephemeral, (2) intermittent, and (3) perennial. Principal component analysis (PCA) is also applied as the second multivariate analysis tool to identify dominant hydrological indices that cause the variability in the streams. The mean flow per unit catchment area (QmAR) and Base flow index (BFI) show an incremental trend with ephemeral, intermittent and perennial streams. Whereas the number of mean zero flow days ratio (ZFI) and coefficient of variation (CV) show a decreasing trend with ephemeral to perennial flow regimes. Finally, the streams in the three flow regimes were characterized with the mean and standard deviation of the hydrological variables and the shape, slope, and scale of the flow duration curve. Results of this study are the basis for further understanding of the ecohydrological processes of the river basins in Ethiopia.

Model-based assessment of groundwater recharge in Slovenia

The implementation process of the EU water legislation (EU WFD, EU GWD) has put pressure on environmental managers to create, analyse and disseminate hydrological data in recent years. In this context, distributed hydrological model results at the macro scale (>10,000 km2) have gained importance for the Environment Agency of the Republic of Slovenia, too. Within a joint project the distributed water balance model GROWA, developed for Germany, has been adapted to Slovenia by re-calibrating the routine for determining the average annual groundwater recharge rate. This routine consists mainly of a base flow index approach (BFI). This BFI is based on 41 different site conditions in Slovenia, whereas lithology dominates the recharge process. This paper outlines the general GROWA approach, the required input data, and the calibration process. Validated model results for the period 1971–2000, especially total runoff and base flow, are presented and discussed. These results have been used already for practical water management issues in Slovenia on European, national and regional level. It is shown that Slovenian groundwater resources exhibit high regional and seasonal variability. Tendencies of more frequent and more pronounced droughts have been detected. As demonstrated by the results GROWA is a valuable tool for the spatially distributed assessment of groundwater recharge in Slovenia.

Groundwater balance estimation in karst by using simple conceptual rainfall–runoff model

The objective of this work is the study of Opacac karst spring which geographically lies in Dalmatia (Croatia). Numerous studies have been carried out in karst aiming the investigation of groundwater regime. The karst spring hydrograph can reflect the groundwater regime and consequently the analysis is based on them. A simple conceptual rainfall–runoff model is used for the estimation of groundwater balance components including the influences of time-invariant catchment boundaries (Jukic and Denic-Jukic 2009). The proposed parameter estimation procedure merges the soil-moisture balance and the groundwater balance approaches to obtain the complete groundwater budget. The effective rainfall is calculated by using mathematical model based on soil-moisture balance equations, i.e. Palmer’s fluid mass balance method. The parameters of model of effective rainfall are determined by using simple conceptual rainfall–runoff model consisting of two linear reservoirs representing the fast and slow flow component of the recession. The weight coefficient between the fast and slow component is determined by using base flow index analysis of hydrograph. Recession coefficient of the slow flow component and the weight coefficient are determined from hydrograph analysis. Available data from nearby meteorological station includes daily average discharge, the amount of precipitation, the average temperature and the humidity from 1995 to 2010. The average catchment area is also estimated with the average yearly runoff deficit using Turc’s method and compared with the values obtained from the application of the rainfall–runoff model. Nash–Sutcliffe model efficiency, root mean square error and Pearson’s correlation coefficient for simulated hydrograph are applied to assess the predictive power of model. Calculated groundwater balance shows that the Opacac spring aquifer contains a significant storage capacity. The application of series of linear reservoirs is a classical and common technique, but the proposed simple approach enables the estimation of the components of groundwater balance in karst areas.

Investigation of the potential surface–groundwater relationship using automated base-flow separation techniques and recession curve analysis in Al Zerba region of Aleppo, Syria

The management of water resources requires an adequate understanding of the relationship between the various components of the hydrological cycle. The accelerated urbanization and agricultural development impose the concern about the sustainability of water resources, particularly in arid and semi-arid regions. In such environments, water scarcity and drought often lead to intensive groundwater abstraction which can adversely affect the hydrological system. Severe over-exploitation of groundwater has been observed on the Aleppo basin of the Al Qweek River. The Al Qweek valley constitutes the central part of the study area (southwestern parts of the Aleppo basin). The region is characterized by a semi-arid climate with an average annual precipitation of 325 mm. The intensive exploitation of the upper aquifer in the catchment is responsible for a continuous decline of the piezometric levels with an average of 1.8 m/year. The objective of this study was to investigate the relationship between the upper aquifer and the Al Qweek River within the catchment boundary using streamflow and hydrograph separation techniques by means of daily discharge data for both the Al Qweek and Al Qwaak rivers. HydroOffice was used for the base-flow separation, flow duration curves (FDC), and recession curve displacement analysis. Furthermore, groundwater recharge was estimated by means of RECESS and RORA. This is the first study using the hydrograph separation method in this region to our knowledge. The results indicate a proportional relationship between the surface and groundwater with an average discharge fluctuation that ranged from 0.30 to 0.20 m for the Al Qweek and Al Qwaak rivers, respectively. The results also revealed a dominant base flow in the catchment that ranged from 86.3 to 88.2 % of the total flow with a computed base-flow index that varied from 0.85 to 0.90 in all gauge stations, indicating a stable flow regime in the region. Furthermore, the high base flow is resulting in high permeability conditions of the upper aquifer and low direct surface runoff. The visual interpretation of the FDC suggests sustained base flow from groundwater storage. The low-flow index indicates an average contribution of groundwater storage of 45 to 58 %. The result of recession curve analysis shows a recession constant from 0.8 to 0.9 indicating a dominant interflow and low overland runoff. Furthermore, the results also show that estimation of groundwater recharge using RORA is inappropriate for the region of interest.

Analysis of baseflow index based hydrological model in Upper Wei River basin on the Loess Plateau in China

Abstract. The baseflow is the drainage from the groundwater and soil water to the streamflow. As one important source of the streamflow, the baseflow could be the main source of the streamflow in the dry season. The Wei River, located in the semi-arid region of the Loess Plateau which is overlain by deep and loose soil, is the largest tributary of the Yellow River. According to former research, most of the streamflow in the dry season in the headwater of the Yellow River is baseflow. For the whole Yellow River basin, the baseflow is an important component of the streamflow, and accounts for about 44% of the annual runoff. Physically-based distributed hydrological models can simulate the runoff components separately, and are important tools to analyse the runoff components. Given the importance of the baseflow in the dry season for drought relief to support the ecological water requirement and irrigation, especially in the Wei River, the baseflow is analysed in this study. To investigate the baseflow in the Upper Wei River basin, a semi-distributed hydrological model based on a Representative Elementary Watershed approach (THREW) is employed to investigate the runoff generation process. To compare the results, an automatic baseflow separation method proposed by Arnold is used to separate the baseflow from the daily streamflow at Beidao hydrological station in Upper Wei River basin from 2001 to 2004. Based on the hydrological modelling and the Arnold separation method, the average annual baseflow index, i.e. the ratio of baseflow to the total runoff, is estimated as in the range of 0.30–0.36. The average intra-annual monthly baseflow index represents the seasonality of the baseflow due to the seasonality of the precipitation and evapotranspiration, and is also analysed.

Baseflow characteristics in alpine rivers — a multi-catchment analysis in Northwest China

As a component of streamflow, baseflow is critical for regulating seasonal distribution of river flows and stabilizing water supplies. Water resources in the arid area of Northwest China are mainly from multiple catchments in the alpine that could be influenced by varieties of climatic, land cover, soil and geological factors. While numerous studies have been done on streamflow, systematic analysis of baseflow in the alpine river systems is scare. Based on historical daily streamflow data and the automated digital filter method of baseflow separation, this study investigated characteristics of hydrographs of overland flow, streamflow and baseflow of river systems fed by rainfall, snowmelt, glacier melt or mixtures of these. This study also calculated the recession constants and baseflow indices of 65 river systems. While the recession constant was 0.0034–0.0728 with a mean of 0.018, the baseflow index was 0.27–0.79 with a mean of 0.57. Further, Spearman’s correlation analysis showed that the baseflow index was significantly correlated with catchment climatic factors (e.g., precipitation and temperature), topographic factors (e.g., elevation and slope) and aquifer properties represented by the recession constant. Multiple regression analysis indicated that the factors explained 65% of the variability of baseflow index in the study area.

한강수계의 하천에 대한 직접유출과 기저유출의 기여도 정량화

River characteristics in South Korea has been affected by seasonal climatic variability due to climate change and by remarkable land cover change due to rapid economic growth. In this regard, the roles of river management is getting more important to eco-system and human community in watersheds of South Korea. Understanding river characteristics including direct runoff and baseflow, the first step of river management, can give a significant contribution to sustainable river environment. Therefore, the objective of this study is to quantify the contributions of the direct runoff and baseflow to river streamflow. For this, we used the BFLOW and WHAT programs to conduct baseflow separation for 71 streamflow gauge stations in Han River system, South Korea. The results showed that baseflow index for 71 stations ranges from 0.42 to 0.78. Also, gauge stations which have baseflow index more than 0.5 occupied 76% of a total stations. However, baseflow index can be overestimated due to human impacts such as discharge from dams, reservoirs, and lakes. This study will be used as fundamental information to understand river characteristics in river management at the national level.

At which time step do we need to monitor the stream hydro-chemistry properties for low flow characterization?

The low flow regime features are frequently described in terms of global indices and, among these, the most relevant are the baseflow index and the flow duration curve. Low flow indices have to be computed from observed streamflow data, but monitoring campaigns are time and cost consuming activities. The aim of the present study is then to identify the impact of the monitoring time step resolution, with particular reference to the low flow regime. To the scope, the hydro-chemographical dataset recorded, during a two year monitoring campaign, at the T. Ciciriello experimental catchment, a 3km2 watershed located in the Cilento, European and Global Geopark (Southern Italy), have been analyzed. Water depth (D), discharge (Q), electrical conductivity (EC) and rainfall time series are available. Assuming the daily time scale as the baseline, a fictitious monitoring experiment has been performed, sampling the observed daily time series at different multiple-day time steps. Main global statistic are computed for the different fictitious series and compared to the daily series. The baseflow patterns, filtered with the use of a mass balance method, appear statistically similar and the differences in terms of low flow indices fall within a 10% range.

The use of CMIP5 data to simulate climate change impacts on flow regime within the Lake Champlain Basin

Abstract Study region Lake Champlain Basin, northwestern New England, USA. Study focus Our study uses regional hydrologic analyses and modeling to examine alternative possibilities that might emerge in the Lake Champlain Basin streamflow regime for various climate scenarios. Climate data as well as spatial data were processed to calibrate the Regional Hydro-Ecological Simulation System (RHESSys) model runoff simulations. The 21st century runoff simulations were obtained by driving the RHESSys model with climate data from the Coupled Model Intercomparison Project phase 5 (CMIP5) for representative concentration pathways RCP 4.5 and 8.5. New hydrological insights for the region Our analyses suggest that most of CMIP5 ensembles fail to capture both the trends and variability observed in historical precipitation when run in hindcast. This raises concerns of using such products in driving hydrologic models for the purpose of obtaining reliable runoff projections that can aid researchers in regional planning. A subset of five climate models among the CMIP5 ensembles have shown statistically significant trends in precipitation, but the magnitude of these trends is not adequately representative of those seen in observed annual precipitation. Adjusted precipitation forecasts project a streamflow regime described by an increase of about 30% in seven-day maximum flow, a four days increase in flooded days, a three orders of magnitude increase in base flow index, and a 60% increase in runoff predictability (Colwell index).

A hydrograph separation method based on information from rainfall and runoff records

Summary Hydrograph separation is considered as the first step to catchment-scale water balance analysis. A wide variety of hydrograph separation methods exists ranging from empirical to analytical and physical. This study discusses a physically-based approach that combines baseflow separation and event identification with minimal data requirement. The input datasets are basin-average rainfall and discharge time series. Outputs are baseflow time series, the timing of the runoff events, differentiated as single- or multi-peak, and the associated rainfall event time series. To assess the method’s feasibility, hydrograph properties are evaluated for both long-term (annual and monthly) and event-scale time series. Results show that the long-term derived baseflow indices are positive (negative) correlated with basin area (runoff coefficient). The event scale analysis shows that the timing-related parameters (i.e. durations of rainfall and flow events and time lag between rainfall to flow events) increase with basin area in terms of magnitude and variability. Similar dependence on basin scale is shown for the water balance-related parameters determined from this analysis, namely event rainfall and baseflow volumes and baseflow index. Water balance parameters are shown to be characterized with less degree of variability for single-peak events relative to multi-peak events.

Spatiotemporal patterns of baseflow metrics for basins draining the Oak Ridges Moraine, southern Ontario, Canada

The Oak Ridges Moraine (ORM) is a key hydrogeologic feature in southern Ontario, supplying potable water along with important aquatic ecosystem services. Stream baseflow is a useful indicator of groundwater discharge to streams on the ORM and gives insight into the regional hydrogeologic system. This study examines how climatic and basin attributes explain spatiotemporal patterns in baseflow metrics for streams draining the ORM. Baseflow was separated from streamflow using an automated digital filter, and water-year baseflow and baseflow as a fraction of precipitation and total streamflow (baseflow index, BFI) were determined. Much of the variability in baseflow metrics was explained by such characteristics as water-year precipitation, mean basin slope, spatial extent of outcrops of permeable sands and gravels, and forest and urban cover. Identified thresholds for basins with above- or below-average baseflow and BFI could serve as a screening tool in resource management decisions on the ORM. Precipitation has increased for many basins in the latter part of the twentieth and early part of the twenty-first century, often accompanied by greater baseflow. The rate of baseflow increase was related to the spatial extent of sand and gravel outcrops, implying a nonuniform response of baseflow to rising precipitation for basins across the ORM. Although baseflow from these basins may continue to increase under the wetter climate predicted for southern Ontario in the twenty-first century, such forecasts must consider the role of land-use change (e.g. forest expansion, urban development) in altering the partitioning of precipitation between direct runoff and baseflow contributions to streamflow.La moraine Oak Ridges (ORM) est une caractéristique hydrogéologique importante dans le sud de l’Ontario fournissant en eau potable et délivrant de nombreux services pour l’écosystème aquatique. Le débit de base des cours d’eau est un indicateur important de l’écoulement des eaux souterraines dans l’ORM et donne un aperçu du système hydrogéologique régional. Cette étude examine l’influence des caractéristiques climatiques et les propriétés du bassin versant sur les variations spatio-temporelles des débits de base des cours d’eau drainants l’ORM. Le débit de base a été séparé du débit d’eau à l’aide d’un filtre numérique automatisé alors que le débit de base eau annuel, le débit de base sous forme de précipitation et le débit total (débit de base indice, BFI) ont été déterminés expérimentalement. Une grande partie de la variabilité des mesures de débit de base s’expliquait par les précipitations annuelles, la pente moyenne du bassin, l’étendue spatiale des affleurements de couches perméables de sable et gravier, et du couvert forestier et urbain. Les seuils identifiés pour les bassins avec débit de base supérieur ou inférieur au débit de base moyen et BFI pourraient servir d’outil de dépistage dans les décisions de gestion des ressources pour l’ORM. Au cours des dernières décennies, les précipitations ont augmenté dans de nombreux bassins versants et elles ont souvent été accompagnées par de grands débits de base. Les taux d’augmentation du débit de base étaient associés à l’étendue spatiale des affleurements de sable et de gravier, impliquant une réponse non uniforme du débit de base vers la hausse des précipitations pour les bassins à travers l’ORM. Bien que le débit de base de ces bassins pourrait continuer à augmenter avec un climat plus humide comme prédit pour le sud de l’Ontario au vingt-et-unième siècle, les prévisions de débit de base devraient considérer le rôle du changement d’affectation des terres telle que l’expansion des forêts et le développement urbain, et modifier le cloisonnement des précipitations entre ruissellement direct et contribution du débit de base au débit d’eau.

Seasonal Variability of Flow and Nitrate Flux in Gilgel Gibe River, South West, Ethiopia

Nitrate is a limiting nutrient for plant growth and vital for crop production to increase agricultural productivity. However, its excessive presence in aquatic environment poses risk turning in to major aquatic ecosystem perturbation. Dissolved nitrate from lands to waterways is mainly exported via runoff and leaching. The transport of nitrate in a river is a function of the streamflow rate and its concentration, which render to the seasonal variation. Therefore, the aim of this study was to assess the seasonal variation of flow and nitrate flux. Streamflow data of the Gilgel Gibe River for the period of two years (2013-2014) were used. The baseflow is separated using Web-based Hydrograph Analysis Tool (WHAT). Dissolved nitrate concentrations measured on daily basis were also used. The effects of storm events on flow and nitrate transport were examined during dry and wet seasons. The river had shown high discharge rate from the mid June to late October. The baseflow index (BFI) was found 0.76 indicating that the streamflow is mainly controlled by groundwater discharge. Similarly, during the dry seasons, total nitrate input was considerably less than in wetter seasons. Nitrate concentrations, however, were unusually high in the first summer storm runoff after the dry season. The average annual nitrate loads varied from 13761.2 ton to 156.45 ton during the wet and dry seasons respectively. The regression curve for the nitrate load against streamflow (r2=0.88) has shown significant relationship (p-value=0.000). In the time interval studied, over 95% of the nitrate was transported from the watershed during the wet seasons of greater rainfall, which disclosed that seasonality and river flow are primary forcing functions when considering nitrate loadings in this watershed