Streamflow Analysis Research Articles

Assessment the Potential Impacts of Urbanization: Case of Jimma City (Research Note)

Currently the effect of urban discharges on water quantity and quality issues and additional recreational amenities perceived in the urban landscape have gained growing public interest for the provision of sustainable urban development. This is due to the fact that urbanization is converging to challenge city infrastructure due to their adverse impacts on precipitation extremes and the environment of urban areas at large. This study was aimed at identification of the treats of urban expansion and prediction of the environmental responses to urbanization of Jimma City. This is an important input for the decision of environmentalists, hydrologists, storm and waste water management for the better plan and sustainable development of the city. The study analysis of stream flow indicates, urbanization was found to be one of the responsible factors for changing the surface of the land disturbing the hydrological process of Jimma City by altering the magnitude of surface runoff, aquifer recharge and river flows. The expansion of Jimma city have intensified, surface water discharges from developed areas and uncontrolled waste release which have affected the social, environmental and economic state of the area. Increased flood peaks, water volume and pollutant loads, reduced ground water recharge were found to be the major sources water quantity and quality degradation. Degraded water quantity and quality in turn resulted in water crisis, ecological risk, reduced quality of life and reduced level of ecosystem service.

SYHDA – System of Hydrological Data Acquisition and Analysis

ABSTRACT Acquisition and analysis of hydrological series are essential activities for hydrological studies in watersheds. However, they require time and are usually complex and susceptible to human errors. In order to minimize these problems, computational tools are often used for hydrological analysis, although there are few of them in Brazil. This technical note aims to provide a structured document with information on the motivation, development, conception, main functionalities, and applications of the System of Hydrological Data Acquisition and Analysis (SYHDA). SYHDA is a software intended for acquisition and analysis of hydrological data (rainfall and streamflow) and was fully idealized to enable the user to deal with the country’s leading hydrology databases. It has several modules that include analysis by descriptive statistics and graphical tools, seasonality analysis of streamflows, non-parametric tests, and at-site and regional probabilistic modeling. SYHDA has been used in numerous scientific studies, which give grounds to affirm that it demonstrates a great potential to be used in both everyday and complex activities demanded by the scientific and technical community of hydrology and related areas.

Development of a Maximum Entropy-Archimedean Copula-Based Bayesian Network Method for Streamflow Frequency Analysis—A Case Study of the Kaidu River Basin, China

Frequency analysis of streamflow is critical for water-resources system planning, water conservancy projects and the mitigation of hydrological extremes events. In this study, a maximum entropy-Archimedean copula-based Bayesian network (MECBN) method has been proposed for frequency analysis of monthly streamflow in the Kaidu River Basin, which integrates the maximum entropy-Archimedean copula (MEAC) and Bayesian network methods into a general framework. MECBN is effective for representing the uncertainties that exist in model representation, preserving the distributional characteristics of streamflow records and addressing the correlation structure between streamflow pairs. Application to the Kaidu River Basin shows a good performance of MECBN in describing the historical data of this basin in China. The results indicate that the interactions between two adjacent monthly streamflow pairs are non-linear. There is upper tail dependence between monthly streamflow pairs. The dependence coefficients including Spearman’s rho, Kendall’s tau, and the upper tail dependence coefficient are in inverse proportion of monthly streamflow values in the Kaidu River Basin, due to the fact that other factors (i.e., rainfall, snow melting, evapotranspiration rate and requirement of water use) provide more contributions to the streamflow in the flooding season. These findings can be used for providing vital information in the prevention and control of hydrological extremes and to further water resources planning in Kaidu River Basin.

Evaluating Future Flood Scenarios Using CMIP5 Climate Projections

Frequent flooding events in recent years have been linked with the changing climate. Comprehending flooding events and their risks is the first step in flood defense and can help to mitigate flood risk. Floodplain mapping is the first step towards flood risk analysis and management. Additionally, understanding the changing pattern of flooding events would help us to develop flood mitigation strategies for the future. This study analyzes the change in streamflow under different future carbon emission scenarios and evaluates the spatial extent of floodplain for future streamflow. The study will help facility managers, design engineers, and stakeholders to mitigate future flood risks. Variable Infiltration Capacity (VIC) forcing-generated Coupled Model Intercomparison Project phase 5 (CMIP5) streamflow data were utilized for the future streamflow analysis. The study was done on the Carson River near Carson City, an agricultural area in the desert of Nevada. Kolmogorov–Smirnov and Pearson Chi-square tests were utilized to obtain the best statistical distribution that represents the routed streamflow of the Carson River near Carson City. Altogether, 97 projections from 31 models with four emission scenarios were used to predict the future flood flow over 100 years using a best fit distribution. A delta change factor was used to predict future flows, and the flow routing was done with the Hydrologic Engineering Center’s River Analysis System (HEC-RAS) model to obtain a flood inundation map. A majority of the climate projections indicated an increase in the flood level 100 years into the future. The developed floodplain map for the future streamflow indicated a larger inundation area compared with the current Federal Emergency Management Agency’s flood inundation map, highlighting the importance of climate data in floodplain management studies.

Multifractality and cross-correlation analysis of streamflow and sediment fluctuation at the apex of the Pearl River Delta

The fluctuation and distribution of hydrological signals are highly related to the fluvial and geophysical regime at estuarine regions. Based on the long daily streamflow and sediment data of Makou (MK) and Sanshui (SS) stations at the apex of the Pearl River Delta, the scaling behavior of the streamflow and sediment is explored by multifractal detrended fluctuation analysis (MF-DFA). The results indicated that there was significant multifractal structure present in the fluctuations of streamflow and sediment. Meanwhile, the multifractal degree and complexity of sediment were much stronger than streamflow. Although the scaling exponents of streamflow were larger than sediment at both MK and SS, no evident differences have been found on the scaling properties of streamflow and sediment for the ratios MK/SS. Moreover, the cross-correlation between streamflow and sediment is further detected by Multifractal Detrended Cross-Correlation Analysis (MF-DXA). The multifractal response between streamflow and sediment at small timescale is characterized by long-range correlations whereas it exhibits random behavior at large timescale. The interaction of the broadness of probability density function and the long-range correlations should be responsible for the multifractal properties of hydrological time series as the multifractal degree of surrogate and shuffled data was significantly undermined.

Projection of future streamflow of the Hunza River Basin, Karakoram Range (Pakistan) using HBV hydrological model

Hydrologiska Byrans Vattenbalansavdeling (HBV) Light model was used to evaluate the performance of the model in response to climate change in the snowy and glaciated catchment area of Hunza River Basin. The study aimed to understand the temporal variation of streamflow of Hunza River and its contribution to Indus River System (IRS). HBV model performed fairly well both during calibration (R2=0.87, Reff=0.85, PBIAS=−0.36) and validation (R2=0.86, Reff=0.83, PBIAS=−13.58) periods on daily time scale in the Hunza River Basin. Model performed better on monthly time scale with slightly underestimated low flows period during both calibration (R2=0.94, Reff=0.88, PBIAS=0.47) and validation (R2=0.92, Reff=0.85, PBIAS=15.83) periods. Simulated streamflow analysis from 1995–2010 unveiled that the average percentage contribution of snow, rain and glacier melt to the streamflow of Hunza River is about 16.5%, 19.4% and 64% respectively. In addition, the HBV-Light model performance was also evaluated for prediction of future streamflow in the Hunza River using future projected data of three General Circulation Model (GCMs) i.e. BCC-CSM1.1, CanESM2, and MIROCESM under RCP2.6, 4.5 and 8.5 and predictions were made over three time periods, 2010–2039, 2040–2069 and 2070–2099, using 1980–2010 as the control period. Overall projected climate results reveal that temperature and precipitation are the most sensitive parameters to the streamflow of Hunza River. MIROC-ESM predicted the highest increase in the future streamflow of the Hunza River due to increase in temperature and precipitation under RCP4.5 and 8.5 scenarios from 2010–2099 while predicted slight increase in the streamflow under RCP2.6 during the start and end of the 21th century. However, BCCCSM1.1 predicted decrease in the streamflow under RCP8.5 due to decrease in temperature and precipitation from 2010–2099. However, CanESM2 predicted 22%-88% increase in the streamflow under RCP4.5 from 2010–2099. The results of this study could be useful for decision making and effective future strategic plans for water management and their sustainability in the region.

Trend and Change-Point Analysis of Streamflow and Sediment Discharge of the Gongshui River in China during the Last 60 Years

The Gongshui River basin exhibits one of the most serious soil erosion areas in southern China, and has always been the key control area of national soil and water conservation programs. This study used daily precipitation, streamflow, and sediment concentration data collected from 1957 to 2015 from the main hydrological stations of the Gongshui River to investigate streamflow and sediment discharge variations and their responses to precipitation and human activities. The Mann-Kendall and Pettitt’s test were used for trend and change-point detection. The double mass curve (DMC) method was employed to quantify the effects of precipitation change and human activities on hydrological regime shifts. The results showed insignificant trends of both annual precipitation and streamflow for all stations, while the sediment discharge of most stations exhibited significant decreasing trends. Change-point analyses revealed that all hydrologic stations except Mazhou had transition years. The estimation via DMC indicated that after the change point years, there was a rapid reduction in sediment discharge at Hanlinqiao, Fengkeng, Julongtan, Xiashan, and Chawu stations, but not at Mazhou, Ruijin, and Yangxinjian stations. Human activity provided a significantly greater contribution to sediment discharge than precipitation. The evidence clearly indicates that the degree and extension of conservation or destruction measures and the construction of large- and medium-sized reservoirs were the major factors significantly decreasing or increasing annual sediment discharge of the Gongshui River. This work could serve as the basis for decision making regarding river basin water resources management to estimate the effects of anthropogenic impacts on water and sediment discharge variations during the last few decades, thereby guiding adaptation and protection of the water resources of the Gongshui River flowing into the Poyang Lake.

Variation Analysis of Streamflows from 1956 to 2016 Along the Yellow River, China

With the change of climate and the impacts of human activities, the water resources crisis of the Yellow River is becoming increasingly serious. How and why did the streamflows of the Yellow River basin change? Based on observed annual runoff data (1956–2016) of 10 main hydrological stations along the Yellow River, the linear regression method, the Spearman rank correlation method and the Mann-Kendall test method are used to analyze runoff trend. The orderly clustering method, the sliding t test method and the Lee-Heghinian Method are used to identify the abrupt change point. Finally, the wavelet analysis method is used to identify runoff time series period. The results show that: (1) With the exception of the streamflow of Tangnaihai, the streamflows of all examined stations have significantly declining trends. The decrease of the streamflow from the upper to the middle to the lower reaches is becoming more and more obvious; (2) The runoff of the Yellow River has changed greatly. The abrupt change point at Tangnaihai occurred in 1989. The abrupt change points of the other stations took place in 1985; (3) The runoff along the Yellow River presents multi-time scale changes. The streamflows appear to have strongest periods of 25–40 years with a 40-year scale, which indicate the alternate oscillations of the high and the low water periods. The periods of <6 and 7–24 years are not stable and are complicated. The first main period of runoff in the Yellow River is 30 years; (4) The streamflow upstream of Tangnaihai station is mainly affected by the climate. The streamflows downstream of Tangnaihai station are influenced by human activities, especially water extraction and diversion and the operations of the large reservoirs. These research results have important practical guiding significance for hydrological forecasting, evaluation and management of water resources, construction of water conservancy projects and sustainable utilization of water resources in the region.

Temporal streamflow analysis: Coupling nonlinear dynamics with complex networks

This study presents a new approach for complex networks-based analysis of temporal streamflow dynamics. The novelty comes in the form of using nonlinear dynamic concepts to construct the temporal streamflow network. The approach involves three steps. First, the single-variable streamflow time series is represented in a multi-dimensional phase space using delay embedding, i.e. phase space reconstruction. Next, this reconstructed phase space is treated as a network, with the reconstructed vectors (instead of the streamflow values themselves) serving as the nodes and the connections between them serving as the links. Finally, the strength of each node in the network is determined using a distance metric. The approach is employed independently to monthly streamflow time series observed over a period of 53 years (January 1950–December 2002) from each of 639 stations in the contiguous United States. For each time series, different delay time values for phase space reconstruction are considered and the optimum embedding dimension is determined using the false nearest neighbor (FNN) method. The results indicate the usefulness of the phase space reconstruction-based network construction for examining the temporal connections in streamflow. The distribution of the strengths of nodes for any streamflow network is used to identify the type of the underlying network. The average node strength of each of the 639 streamflow networks are also interpreted: (1) to identify similarities and differences between the stations; (2) to explain the role of catchment and flow properties (drainage area, elevation, and flow mean) on network strength; and (3) to assess the influence of time (i.e. month of the year) on network strength.

Trend analysis of hydro-climatic variables in the north of Iran

Trend analysis of climate variables such as streamflow, precipitation, and temperature provides useful information for understanding the hydrological changes associated with climate change. In this study, a nonparametric Mann-Kendall test was employed to evaluate annual, seasonal, and monthly trends of precipitation and streamflow for the Neka basin in the north of Iran over a 44-year period (1972 to 2015). In addition, the Inverse Distance Weight (IDW) method was used for annual seasonal, monthly, and daily precipitation trends in order to investigate the spatial correlation between precipitation and streamflow trends in the study area. Results showed a downward trend in annual and winter precipitation (Z < −1.96) and an upward trend in annual maximum daily precipitation. Annual and monthly mean flows for most of the months in the Neka basin decreased by 14% significantly, but the annual maximum daily flow increased by 118%. Results for the trend analysis of streamflow and climatic variables showed that there are statistically significant relationships between precipitation and streamflow (p value < 0.05). Correlation coefficients for Kendall, Spearman’s rank and linear regression are 0.43, 0.61, and 0.67, respectively. The spatial presentation of the detected precipitation and streamflow trends showed a downward trend for the mean annual precipitation observed in the upstream part of the study area which is consistent with the streamflow trend. Also, there is a good correlation between monthly and seasonal precipitation and streamflow for all sub-basins (Sefidchah, Gelvard, Abelu). In general, from a hydro-climatic point of view, the results showed that the study area is moving towards a situation with more severe drought events.

Wavelet-based variability on streamflow at 40-year timescale in the Black Sea region of Turkey

Under the effects of human activities and climate change, severe changes of stream discharge are observed in large river basins in the world. Accordingly, assessing the temporal variability in streamflow is crucial for better water resources planning and management. Thus, the aim of the present study was to perform monthly streamflow analyses using the wavelet transform and descriptive statistics. Temporal variability of streamflow data of nine stations (Yakabasi, Derecikviran, Durucasu, Sutluce, Kale, Gomeleonu, Simsirli, Tozkoy, and Topluca) for period of 1964–2007 to study the influence of climatic oscillations over the Black Sea Region of Turkey was analyzed. Although all studied time series presented annual periodicity, Kale, Gomeleonu, Simsirli, Tozkoy, and Topluca stations presented a semi-annual signal as well. However, some discontinuities in the annual periodicity were found in the Durucasu, Sutluce, and Kale time series between 1964 and 2007. Finally, the scale-average wavelet power time series for each station studied were used to perform a cluster analysis, and it was observed that Topluca station presented a particular spectrum or could form an isolate cluster together with Simsirli and Tozkoy stations, mainly due to the intermittent oscillations on the annual frequency observed after 1990.

Impact of climate change on water resources in Jordan: a case study of Azraq basin

Azraq basin is one of the most important groundwater basins in Jordan. Trend analysis using RClimDex for six rainfall stations and two metrological stations was performed to detect and predict climate change impacts on the Azraq basin until the year 2030. Three absolute homogeneity tests were used to detect any variation in the data time series. The results showed that monthly max value of daily mean temp, tropical night, monthly maximum value of daily maximum temp, monthly maximum value of daily minimum temp and cool days were found to be statistically significant climate change indices. The trend of the max temperature during July is significant, while insignificant trend for the minimum temperature in the same month was noticed. The frequency of days in which the maximum temperature exceeded 38 °C increased and there was increase in the minimum temperature count of values that are exceeding 20 °C in the last 46 years. Regarding the rainfall, there is no change in total annual precipitation over the study area during the studied period. The results of simulating climate change impact into the evaporation showed expected increase by 4.74 and 5.32% for Al Butum and El Janab wadis, respectively, during the period of 2013–2030. Streamflow analysis showed slight decrease by 1.51 and 1.02% for both wadis, respectively.

Testing the Hydrological Coherence of High‐Resolution Gridded Precipitation and Temperature Data Sets

AbstractAssessing the accuracy of gridded climate data sets is highly relevant to climate change impact studies, since evaluation, bias correction, and statistical downscaling of climate models commonly use these products as reference. Among all impact studies those addressing hydrological fluxes are the most affected by errors and biases plaguing these data. This paper introduces a framework, coined Hydrological Coherence Test (HyCoT), for assessing the hydrological coherence of gridded data sets with hydrological observations. HyCoT provides a framework for excluding meteorological forcing data sets not complying with observations, as function of the particular goal at hand. The proposed methodology allows falsifying the hypothesis that a given data set is coherent with hydrological observations on the basis of the performance of hydrological modeling measured by a metric selected by the modeler. HyCoT is demonstrated in the Adige catchment (southeastern Alps, Italy) for streamflow analysis, using a distributed hydrological model. The comparison covers the period 1989–2008 and includes five gridded daily meteorological data sets: E‐OBS, MSWEP, MESAN, APGD, and ADIGE. The analysis highlights that APGD and ADIGE, the data sets with highest effective resolution, display similar spatiotemporal precipitation patterns and produce the largest hydrological efficiency indices. Lower performances are observed for E‐OBS, MESAN, and MSWEP, especially in small catchments. HyCoT reveals deficiencies in the representation of spatiotemporal patterns of gridded climate data sets, which cannot be corrected by simply rescaling the meteorological forcing fields, as often done in bias correction of climate model outputs. We recommend this framework to assess the hydrological coherence of gridded data sets to be used in large‐scale hydroclimatic studies.

Trend analysis of monthly streamflows using Şen's innovative trend method

Trend analysis of monthly mean streamflows is essential for better water resources management and planning. In this study, Mann Kendall (MK), Sen's method and Sen's innovative trend method (ITM) were employed in order to examine the possible trends of monthly streamflows obtained from nine stations from three basins (Yakabasi and Derecikviran in Western Black Sea Basin; Durucasu, Sutluce, Kale and Gomeleonu in Yesilirmak Basin; Simsirli, Tozkoy and Topluca in Eastern Black Sea Basin) located in Black Sea Region of Turkey. Based on the MK, streamflow data of Tozkoy Station which is located in western part of the Eastern Black Sea Region showed a significantly increasing trend while a significantly decreasing trend was found for the Yakabasi, Derecikviran, Durucasu and Sutluce stations which are situated in western part of the Black Sea Region. According to the Sen's trend method, a significantly decreasing trend was seen in Durucasu, Sutluce, Yakabasi and Derecikviran stations while Tozkoy station showed significantly increasing trend. According to the ITM, low-medium values of Tozkoy Station indicated slightly increasing trend while low and medium streamflow values of Yakabasi, Derecikviran, Durucasu and Sutluce stations showed a decreasing trend. High streamflow values of Derecikviran and Sutluce stations showed a decreasing trend while corresponding values of Yakabasi, Simsirli and Tozkoy stations indicated an increasing trend. It was showed that trends of low, medium, and high data can be easily identified by ITM which has some advantages (having no assumption such as serial relationship, non-normality, and, test number) over the Sen's method and Mann-Kendall test.

A review on the applications of wavelet transform for streamflow and suspended sediment analysis

A review on the applications of wavelet transform for streamflow and suspended sediment analysis

Spectrum of climate change and streamflow alteration at a watershed scale

Worldwide, evidences of water cycle alteration and fresh water resources depletion are frequently reported with various magnitudes. This alteration in the hydrologic cycle is often regarded as a signal of the actual climate change. However, the debate on climate change seems to have preferentially focused on global-scale patterns such that the rich knowledge gathered in the domain is virtually less integrated to decision making at the watershed level. Indeed, the watershed apprehension of climate change is probably an imperative for sustainable water resources planning. The scope of the present study aligns with that imperative as it aims at conciliating patterns of climate change with observations of hydrologic alterations at the watershed level. Specifically, the paper describes the interplay between land-cover changes and the terrestrial water cycle disturbances under climate change at the global level. Thereafter, it reports a watershed-level analysis of streamflow, land-cover, PET and precipitation alteration. Specially, the case study focused on the Brazos River basin, located in the USA and shared by the states of Texas and New Mexico. From both regional and watershed prospects, signals of hydrologic alteration during the time period 1955–2014 are highlighted and then implications of climate change are discussed. The results show an overall longitudinal gradient of precipitation changes and a latitudinal gradient of PET changes across the Brazos watershed. However, these gradients of changes seem to be driven by regional climate components which extend beyond the physical boundary of the Brazos watershed. Mann–Kendall’s analysis of discharge time series (annual average, minimum and maximum) at 10 different stations exhibits meaningful contrasts from upstream to downstream. An assessment of land-cover changes shows critical patterns of landscape change across the watershed. The analyses depicted signals of urbanization sprawl and land-cover degradation. Specially, the significant statistical relationships observed between the time series of maximum green vegetation fraction (MGVF) and streamflow also indicate that the origin of the observed hydrologic alteration is anthropogenic. Ultimately, the results are discussed within the scope of climate change.

Threshold level approach for streamflow drought analysis in the Central Andes of Argentina: a climatological assessment

ABSTRACTA streamflow drought climatology was developed over the Central Andes of Argentina, a semi-arid region highly vulnerable to climatic variations, based on the analysis of daily historical streamflow records. A threshold level approach was applied on a daily basis for three different severity levels in order to depict the main characteristics of droughts – number of drought events, mean duration and mean severity – over the period 1957–2014. Based on three annual indices that summarize the frequency of drought events, their duration and severity, we identified the main regional dry periods and the main modes of variability through an empirical decomposition. These modes are linked to La Niña conditions on inter-annual time scales and the Pacific Decadal Oscillation for the decadal variations, showing the influence of the tropical Pacific Ocean in the development of streamflow drought conditions and its relevance for potential predictability of hydroclimatic variations over the region.

Large precipitation event variability among headwater SNOTEL sites and impacts on streamflow in the Upper Colorado River Basin

ABSTRACTThis exploratory study defines and characterizes large precipitation events (LPEs) at a sample of snow telemetry (SNOTEL) sites located in headwater subbasins of the Upper Colorado River Basin (UCRB) and assesses the relationships of interannual LPE variability on basin streamflow. LPE thresholds are defined as the 80th percentile of daily precipitation increments observed at each SNOTEL site from 1981 to 2014. On average, LPEs accounted for more than half (55.5%) of annual precipitation. Total precipitation, total LPE precipitation, LPE count, and LPE magnitude are assessed annually at each SNOTEL site. Statistical analysis shows that these LPE metrics, observed at the headwater SNOTEL sites, are strongly correlated with total annual streamflow downstream, as measured at river gages on major tributaries in the UCRB and at Lake Powell. Further analysis of streamflow during the early twenty-first century drought suggests that drought conditions have coincided with lower precipitation observed at the SNOTEL sites, due in part to fewer and drier LPEs in recent years. Investigation of upper air patterns during LPEs reveals that such events most commonly coincide with zonal, onshore flow among the northern subbasins and amplified troughs towards the south of the UCRB, patterns which have been less common during the drought.

Hydrologic Alterations Predicted by Seasonally-Consistent Subset Ensembles of General Circulation Models

Future climate forcing data at the temporal and spatial scales needed to drive hydrologic models are not readily available. Simple methods to derive these data from historical data or General Circulation Model (GCM) results may not adequately capture future hydrological variability. This study assessed streamflow response to daily future climate forcing data produced by a new method using subsets of multi-model GCM ensembles for the mid-21st century period in northeast Kansas. Daily timeseries of precipitation and temperature were developed for six future climate scenarios: stationary, uniform 10% changes in precipitation; shifts based on a 15-GCM ensemble-mean; and shifts based on three seasonally-consistent subsets of GCMs representing Spring–Summer combinations that were wetter or drier than the historical period. The analysis of daily streamflow and hydrologic index statistics were conducted. Stationary 10% precipitation shifts generally bounded the monthly mean streamflow projections of the other scenarios, and the 15-GCM ensemble-mean captured non-stationary effects of annual and seasonal hydrological response, but did not identify important intra-annual shifts in drought and flood characteristics. The seasonally-consistent subset ensembles produced a range of distinct monthly streamflow trends, particularly for extreme low-flow and high-flow events. Meaningful water management and planning for the future will require hydrological impact simulations that reflect the range of possible future climates. Use of GCM ensemble-mean climate forcing data without consideration of the range of seasonal patterns among models was demonstrated to remove important seasonal hydrologic patterns that were retained in the subset ensemble-mean approach.

Trend analysis of streamflow with different time scales: a case study of the upper Senegal River

This study investigates long-term trends of three different time scales including monthly, seasonally and annually at the upper Senegal River basin. Daily streamflows for the period 1961–2014 at Bafing Makana station were used and analyzed to conduct this research. The serial structural of the different time series (monthly, seasonal, and annual) were investigated in order to detect the presence of autocorrelation. Mann–Kendall test was applied to no autocorrelated series and the Modified Mann–Kendall test for the autocorrelated. Theil and Sen’s slope estimator test was used for finding the magnitude of change and Pettitt test was applied for detecting the most probable change year. Results exhibited a decreasing trend of the annual streamflow yet at the 5% significance level, streamflow series did not have any statistically significant trend for the whole period; however, integrating the different change years, decreasing trend is significant before the first breaking point (1976) and increasing trend is significant from first breaking point to the second change point (1993). For the monthly series, all months exhibit a non-significant decreasing trend except for the month of June. The seasonal series show a decreasing trend which a significant at MAMJ season. Change years were varying accordantly to the scale.