Streamflow Discharge Research Articles

Stochastic modeling of variations in stream flow discharge induced by random spatiotemporal fluctuations in lateral inflow rate

Due to natural heterogeneity in runoff processes, the analysis of response of stream channels to the variation of lateral inflow is therefore viewed in terms of stochastic spatiotemporal processes. Based on the representation theorem, a closed-form expression is derived to describe the spectral response characteristic of stream subject to spatiotemporal fluctuations in lateral inflow. It provides a basis for evaluating the induced discharge variability in stream channels. It is found that the evolutionary power spectrum of the stream flow discharge process and therefore the variance is increased with the distance from the upstream boundary and the characteristic length scale of the lateral inflow process. Flow discharge prediction in the downstream region has a high degree of uncertainty by solving the deterministic partial differential equation.

복합형 유역모델 STREAM의 개발(II): 모델의 시험 적용

In this study, some of the model verification results of STREAM (Spatio-Temporal River-basin Ecohydrology Analysis Model), a newly-developed hybrid watershed model, are presented for the runoff processes of nonpoint source pollution. For verification study of STREAM, the model was applied to a test watershed and a sensitivity analysis was also carried out for selected parameters. STREAM was applied to the Mankyung River Watershed to review the applicability of the model in the course of model calibration and validation against the stream flow discharge, suspended sediment discharge and some water quality items (TOC, TN, TP) measured at the watershed outlet. The model setup, simulation and data I/O modules worked as designed and both of the calibration and validation results showed good agreement between the simulated and the measured data sets: NSE over 0.7 and <TEX>$R^2$</TEX> greater than 0.8. The simulation results also include the spatial distribution of runoff processes and watershed mass balance at the watershed scale. Additionally, the irrigation process of the model was examined in detail at reservoirs and paddy fields.

Influence of bedrock groundwater on streamflow characteristics in a volcanic catchment

AbstractGroundwater movements in volcanic mountains and their effects on streamflow discharge and representative elementary area (REA) have remained largely unclear. We surveyed the discharge and chemical composition of spring and stream water in two catchments: the Hontani river (NR) catchment (6.6 km2) and the Hosotani river (SR) catchment (4.0 km2) at the southern part of Daisen volcano, Japan. Daisen volcano is a young volcano (17 × 103 years) at an early stage of erosion. Our study indicated that deep groundwater that moved through thick lava and pyroclastic flows and that could not be explained by shallow movements controlled by surface topography contributed dominantly to streamflow at larger catchment areas. At the NR catchment, the deep groundwater contribution clearly increased at a catchment boundary defined by an area of 3.0 km2 and an elevation of 800 m. At the SR catchment, the contribution deep groundwater to the stream also increased suddenly at a boundary threshold of 2.0 and 700 m. Beyond these thresholds, the contributions of deep bedrock groundwater remained constant, indicating that the REA is between 2 and 3 km2 at the observed area. These results indicate that the hydrological conditions of base flow were controlled mainly by the deep bedrock groundwater that moved through thick lava and pyroclastic flows in the undissected volcanic body of the upper part of the catchment. Our study demonstrates that deep and long groundwater movements via a deep bedrock layer including thick deposits of volcanic materials at the two catchments on Daisen volcano strongly determined streamflow discharge instead of the mixing of small‐scale hydrological conditions. Copyright © 2015 John Wiley &amp; Sons, Ltd.

ANN-based interval forecasting of streamflow discharges using the LUBE method and MOFIPS

The estimation of prediction intervals (PIs) is a major issue limiting the use of Artificial Neural Networks (ANN) solutions for operational streamflow forecasting. Recently, a Lower Upper Bound Estimation (LUBE) method has been proposed that outperforms traditional techniques for ANN-based PI estimation. This method construct ANNs with two output neurons that directly approximate the lower and upper bounds of the PIs. The training is performed by minimizing a coverage width-based criterion (CWC), which is a compound, highly nonlinear and discontinuous function. In this work, we test the suitability of the LUBE approach in producing PIs at different confidence levels (CL) for the 6h ahead streamflow discharges of the Susquehanna and Nehalem Rivers, US. Due to the success of Particle Swarm Optimization (PSO) in LUBE applications, variants of this algorithm have been employed for CWC minimization. The results obtained are found to vary substantially depending on the chosen PSO paradigm. While the returned PIs are poor when single-objective swarm optimization is employed, substantial improvements are recorded when a multi-objective framework is considered for ANN development. In particular, the Multi-Objective Fully Informed Particle Swarm (MOFIPS) optimization algorithm is found to return valid PIs for both rivers and for the three CL considered of 90%, 95% and 99%. With average PI widths ranging from a minimum of 7% to a maximum of 15% of the range of the streamflow data in the test datasets, MOFIPS-based LUBE represents a viable option for straightforward design of more reliable interval-based streamflow forecasting models.

Correlation analysis of spatio-temporal images for estimating two-dimensional flow velocity field in a rotating flow condition

Summary Flow velocity estimation in actual rivers using image processing technique has been highlighted for hydrometric communities in the last decades, and this technique is called Large Scale Particle Image Velocimetry (LSPIV). Although LSPIV has been successfully tested in many flow conditions, it has addressed several limitations estimating mean flow field because of difficult flow conditions such as rotating, lack of light and seeds, and noisy flow conditions. Recently, an alternative technique named STIV to use spatio-temporal images based on successively recorded images has been introduced to overcome the limitations of LSPIV. The STIV was successfully applied to obtain one-dimensional flow component in the river for estimating streamflow discharge, where the main flow direction is known. Using the 5th order of central difference scheme, the STIV directly calculated the mean angle of slopes which appeared as strips in the spatio-temporal images and has been proved to be more reliable and efficient for the discharge estimation as compared with the conventional LSPIV. However, yet it has not been sufficiently qualified to derive two-dimensional flow field in the complex flow, such as rotating or locally unsteady flow conditions. We deemed that it was because the strips in the given spatio-temporal images from not properly oriented for main flow direction are not narrow enough or clearly visible, thus the direct estimating strip slope could give erroneous results. Thereby, the STIV has been mainly applied for obtaining one-dimensional flow component. In this regard, we proposed an alternative algorithm to estimate the mean slope angle for enhancing the capability of the STIV, which used correlation coefficient between odd and even image splits from the given spatio-temporal image. This method was named CASTI (Correlation Analysis of Spatio-Temporal Image). This paper described the step-by-step procedure of the CASTI and validated its capability for estimating two-dimensional flow field in the rotating flow. For this purpose, we generated artificial images for lid-driven cavity flow where true velocity field can be manipulated and validated with respect to the proposed CASTI algorithm. As a result, the CASTI was successfully performed to capture two-dimensional velocity vector in the given cavity flow.

Optimal Selection of Hydraulic Turbines for Small Hydro Electric Power Generation – A Case Study of Opeki River, South Western Nigeria

The overall net annual energy production from Small Hydro Power (SHP) scheme using stream flow or run-of-water is usually depend on the water height (head), stream flow (discharge) and turbine efficiency. However, experience has shown that the annual capacity of the plant which is a measure of what the machine can deliver throughout the year without interruption is usually in conflict with theoretical power rated output when analysed with different turbines and subjected to the same values of the above mentioned variables. This work provided a platform for optimum selection of SHP turbine for optimum power output that can be sustained throughout the year. Conventional power Equations, seven years of mean daily flow and a medium range of gross head of Opeki River, Ogun State, Nigeria were used to develop Flow Duration Curve (FDC) and annual energy production of a proposed SHP power plant. A net head of 37m and reserved flow of 2.97 m 3 /s was used. Seven hydraulic turbines were examined using their permissible efficiencies. Results from the analysis showed that turbines that gave maximum and minimum power outputs respectively did not imply maximum and minimum annual capacities. The study indicates the usefulness of this work as a guide for SHP scheme. http://dx.doi.org/10.4314/njt.v34i3.15

Direct and indirect effects of human population density and land use on physical features and invertebrates of Iowa (U.S.A.) streams

To improve understanding of human impacts on headwater stream condition, we quantified relationships between human, terrestrial landscape, and stream system variables in 29 central Iowa watersheds. Across study watersheds, between 0 and 100 % of total land area was characterized as “urban” (developed and barren land), whereas cultivated land constituted between 0 and 71 % of watershed area. Several variables were measured for each stream and associated watershed. Strengths of correlative relationships were used to select variables for path analysis, which we used to gain insight into factors affecting stream condition by evaluating direct and indirect effects of human system variables, terrestrial landscape variables, and physical stream variables on stream invertebrates. Results indicated that in predominantly urban watersheds, contaminant inputs to streams (measured by streamwater conductivity) negatively affected invertebrates, including EPT taxa (Ephemeroptera, Plecoptera, Trichoptera), and streamwater contaminant concentrations increased with impervious surface and human population density in the watershed. In rural watersheds, high streamwater nitrogen concentrations associated with cultivated land were related to declines in invertebrate taxon richness. Independent of land use, invertebrate abundance and taxonomic diversity were positively related to coarse substrate abundance on the streambed. Additionally, stream flow (discharge) increased with watershed area, which in turn increased invertebrate taxonomic diversity. Apparently, mechanisms responsible for human impacts on stream condition in central Iowa depend on dominant land use in the watershed. Additionally, stream ecosystems with high quality benthic habitat, and those located in large watersheds with greater flow, appear to be more resilient to land use effects.

Urbanização e Impactos no Ciclo Hidrológico na Bacia do Mineirinho

Este trabalho teve como objetivo comparar cenários de ocupação urbana e seus efeitos no ciclo hidrológico da Bacia do Mineirinho. Buscou-se avaliar os riscos de enchentes causados pelo aumento das áreas de impermeabilização que tem ocorrido com a implantação do novo Campus da USP, São Carlos, SP. Foram estabelecidos quatro cenários de ocupação urbana: cenário pré-urbanização (1972); cenário 2000, cenário 2025 com Plano Diretor (CPD); e cenário 2025 sem Plano Diretor (SPD). Para comparação dos diferentes cenários realizaram-se simulações hidrológicas com modelo hidrológico IPH II. Pode-se observar que no cenário 2025 SPD a vazão máxima aumentou 388,0% quando comparada ao cenário 1972 e 319,4% quando comparada ao cenário 2000. Entre os cenários 2025 CPD e 2025 SPD há diminuição de 22,3% na vazão máxima e aumento no tempo de pico é de 50 minutos. Mesmo com aplicação de diretrizes do PD os riscos de inundações continuam altos.

Variability of flow discharge in lateral inflow-dominated stream channels

Abstract. The influence of the temporal changes in lateral inflow rate on the discharge variability in stream channels is explored through the analysis of the diffusion wave equation (i.e. the linearized Saint-Venant equation). To account for variability and uncertainty, the lateral inflow rate is regarded as a temporal random function. On the basis of the spectral representation theory, analytical expressions for the covariance function and evolutionary power spectral density of the random discharge perturbation process are derived to quantify variability in stream flow discharge induced by the temporal changes in lateral inflow rate. The treatment of the discharge variance (square root of the variance) gives us a quantitative estimate of uncertainty in predictions from the deterministic model. It is found that the discharge variability of stream flow is very large in the downstream reach, indicating large uncertainty anticipated from the use of the deterministic model. A larger temporal correlation scale of inflow rate fluctuations, representing more temporal consistency of fluctuations in inflow rate around the mean, introduces a higher variability in stream flow discharge.

Stepwise sensitivity analysis from qualitative to quantitative: Application to the terrestrial hydrological modeling of a Conjunctive Surface‐Subsurface Process (CSSP) land surface model

AbstractAn uncertainty quantification framework was employed to examine the sensitivities of 24 model parameters from a newly developed Conjunctive Surface‐Subsurface Process (CSSP) land surface model (LSM). The sensitivity analysis (SA) was performed over 18 representative watersheds in the contiguous United States to examine the influence of model parameters in the simulation of terrestrial hydrological processes. Two normalized metrics, relative bias (RB) and Nash‐Sutcliffe efficiency (NSE), were adopted to assess the fit between simulated and observed streamflow discharge (SD) and evapotranspiration (ET) for a 14 year period. SA was conducted using a multiobjective two‐stage approach, in which the first stage was a qualitative SA using the Latin Hypercube‐based One‐At‐a‐Time (LH‐OAT) screening, and the second stage was a quantitative SA using the Multivariate Adaptive Regression Splines (MARS)‐based Sobol’ sensitivity indices. This approach combines the merits of qualitative and quantitative global SA methods, and is effective and efficient for understanding and simplifying large, complex system models. Ten of the 24 parameters were identified as important across different watersheds. The contribution of each parameter to the total response variance was then quantified by Sobol’ sensitivity indices. Generally, parameter interactions contribute the most to the response variance of the CSSP, and only 5 out of 24 parameters dominate model behavior. Four photosynthetic and respiratory parameters are shown to be influential to ET, whereas reference depth for saturated hydraulic conductivity is the most influential parameter for SD in most watersheds. Parameter sensitivity patterns mainly depend on hydroclimatic regime, as well as vegetation type and soil texture.

Objective hydrograph baseflow recession analysis

Summary A streamflow hydrograph recession curve expresses the theoretical relationship between aquifer structure and groundwater outflow to a stream channel. That theoretical relationship is often portrayed empirically using a recession plot defined as a plot of ln(− dQ / dt ) versus ln( Q ), where Q is streamflow discharge. Such hydrograph recession plots are commonly used to estimate recession parameters, aquifer properties and for evaluating alternative hydrologic hypotheses. We introduce a comprehensive and objective approach to analyze baseflow recessions with innovations including the use of quantile regression, efficient and objective numerical estimation of dQ / dt , inclusion of groundwater withdrawals, and incorporation of seasonal effects. We document that these innovations when all combined, lead to significant improvements, over previous studies, in our ability to discern the theoretical behavior of stream aquifer systems. A case study reveals that our methodology enables us to reject the simple linear reservoir hypothesis of stream aquifer interactions for watersheds in New Jersey and results in improved correlations between low flow statistics and aquifer properties for those same watersheds.

Temporal Changes in Streamflow and Attribution of Changes to Climate and Landuse in Wisconsin Watersheds

AbstractPrevious historic trends analyses on 21st Century hydrologic data in the United States generally focus on annual flow statistics and have continued to use USGS hydro‐climatic data network (HCDN) stations, although post‐1988 diversions and runoff regulations are not reflected in the HCDN. Using a more recent dataset, Geospatial Attributes of Gages for Evaluating Streamflow, version II (GAGES II), compiled by Falcone (2012), which includes more watersheds with reference conditions, a comprehensive analysis of changes in seasonal, and annual streamflow in Wisconsin watersheds is demonstrated. Given the pronounced influence of seasonal hydrology in Wisconsin watersheds, the objective of this study is to elucidate the nature of temporal (annual, seasonal, and monthly) changes in runoff. Considerable temporal and regional variability was found in annual and seasonal streamflow changes between the two historic periods 1951‐1980 and 1981‐2010 considered in the study. For example, the northern watersheds show relatively small changes in streamflow discharge ranging from −6.0 to 4.2%, while the southern watersheds show relatively large increases in streamflow discharge ranging from 13.1 to 18.2%. To apportion streamflow changes to climate and nonclimatic factors, a method based on potential evapotranspiration changes is demonstrated. Results show that nonclimatic factors account for more than 60% of changes in annual runoff in Wisconsin watersheds considered in the study.

Determination of runoff components using path analysis and isotopic measurements in a glacier-covered alpine catchment (upper Hailuogou Valley) in southwest China

Monitoring of stable water isotopes (δ18O and δ2H) at the watershed scales can improve our understanding of complex hydrology and hydroclimatology of the watershed, especially in remote regions. Previous studies that used tracers for hydrograph separation are largely based on end-member mixing approach (EMMA), but one drawback of this approach is that at least two independent tracers are required for multi-component separation. Here we introduce a new approach—path analysis, in combination with isotopic measurements to investigate the runoff generation in a glacier-covered alpine catchment (upper Hailuogou Valley) in southwest China. This newly developed method can not only provide a multi-component hydrograph separation with the aid of only one tracer but also determine the direct and indirect influence of sources on streamflow. Path analysis show that the majority of streamflow is dominated by ice/snow meltwater that represents about 63–78% of the total discharge, whereas precipitation and groundwater contribute approximately 19–39% and 2–4% of the streamflow discharge, respectively. These results are in good agreement with those derived from EMMA (using 18O and Cl− as tracers), corroborating that our proposed approach is successful in hydrograph separation of the catchment. This approach may provide new opportunities for the hydrograph separation of catchment with sparse data and be of interest to catchment hydrologists who seek to understand the behaviour of hydrologic systems. Copyright © 2015 John Wiley & Sons, Ltd.

Hydrological time series analysis and modelling using statistical tests and linear time series models (case study: West Azerbaijan province of Iran)

In this paper, the time series of hydrological processes analysed using ADF, KPSS, Mann-Kendall tests and linear time series models on monthly scale in the West Azerbaijan province of Iran. Significant decreasing trend in precipitation and stream flow discharge were observed. Also, non-stationarity in precipitation was observed in four studied basins. Decreasing stream flow discharge partially can be a result of trends in precipitation and evaporation. The population growth, land use changes and increase in water withdrawal are other reasons to blame. The results of linear time series modelling indicates that ARMA models for modelling stream flow only appears when precipitation or evaporation models have a MA component. On the other hand, when precipitation and evaporation models only have AR component, stream flow models are also follow autoregressive models and moving average components vanish. Moreover, in climatically homogenous basins, the same models were best-fitted for different hydrologic processes.

Coupling Land Use Change Modeling with Climate Projections to Estimate Seasonal Variability in Runoff from an Urbanizing Catchment Near Cincinnati, Ohio

This research examines the impact of climate and land use change on watershed hydrology. Seasonal variability in mean streamflow discharge, 100-year flood, and 7Q10 low-flow of the East Fork Little Miami River watershed, Ohio was analyzed using simulated land cover change and climate projections for 2030. Future urban growth in the Greater Cincinnati area, Ohio, by the year 2030 was projected using cellular automata. Projected land cover was incorporated into a calibrated BASINS-HSPF model. Downscaled climate projections of seven GCMs based on the assumptions of two IPCC greenhouse gas emissions scenarios were integrated through the BASINS Climate Assessment Tool (CAT). The discrete CAT output was used to specify a seed for a Monte Carlo simulation and derive probability density functions of anticipated seasonal hydrologic responses to account for uncertainty. Sensitivity analysis was conducted for a small catchment in the watershed using the Storm Water Management Model (SWMM) developed U.S. Environmental Protection Agency. The results indicated higher probability of exceeding the 100-year flood over the fall and winter months, and a likelihood of decreasing summer low flows.

The hydrological and the hydrogeological framework of the Lottenbachtal, Bochum, Germany

This study was performed to investigate the hydrological and the hydrogeological framework of the Lottenbachtal, Germany. Long-term climatic data were statistically analyzed, water and soil samples were collected and analyzed, stream flow discharge was measured and separated, the hydrological balance of this catchment was calculated and a hydrological and hydrogeological conceptual model was constructed. The study area is characterized mainly by the precipitation value ranged between 0.1 and 5 mm/day. The actual evapotranspiration constitutes 31.90 % of the total precipitation, the direct surface runoff constitutes 61.04 %, the soil storage constitutes 3 % and the groundwater recharge of the Lottenbachtal constitutes only 4 % of the total precipitation. The Lottenbachtal has largely affected the diversity of the land use, which includes forests, arable areas, abandoned coal mines and settlement areas. The soil of the forested area is represented by relatively high acidic conditions and relatively high sulfate concentrations, while the soil of the arable areas is represented by near-neutral conditions associated with relatively high concentrations of nutrients and other chemical elements (calcium, magnesium, sodium, potassium, chloride, sulfate, nitrate). The settlement areas are characterized by huge blocks of concrete and backfills, which are rich in calcium and magnesium carbonates. The effects of this diversity in the land use on groundwater and surface water quality resulting by leaching the chemical elements from the soil covers and the other materials. These effects are represented by the following complex water types of Ca–Na–Mg–Cl–SO4–HCO3, Ca–Mg–HCO3–SO4, Ca–Na–Mg–Cl–SO4, Ca–Na–Mg–Cl–SO4 and Ca–HCO3, which represent the diversity of the flow paths of the water as well as to mixing processes. The diversity of the land use also affected the physical hydrological-hydrogeological characteristics of the study area by increasing the direct surface runoff and decreasing the groundwater recharge. The impervious surfaces of the settlement areas and the low hydraulic conductivities of the soil covers are responsible for these conditions.

Effects of El-Niño and La-Niña Sea Surface Temperature Anomalies on Annual Precipitations and Streamflow Discharges in Southeastern United States

Clark II, C.; Nnaji, G.A., and Huang, W., 2014. Effects of El-Nino and La-Nina sea surface temperature anomalies on annual precipitations and streamflow discharges in southeastern United States.Statistical analysis shows that El Niño and La Niña are partially responsible for the amounts of annual precipitation and annual streamflow discharges in Gulf Atlantic hydrologic unit of Southeast United States. The study is based on 61-year records of precipitation and streamflow discharge stations spread across the region. The cross-correlation coefficients for both the sea surface temperature (SST) anomalies and precipitation, and SST anomalies and streamflow were calculated after the data series were prewhitened by an Autoregressive Integrated Moving Average (ARIMA) model (2,0,3). The cross-correlations between SST anomalies and both precipitations and streamflow discharges were positively significant. Using statistical relationship established relating SST anomalies with precipitation and streamflow in the area; comparison analyses of observed and filtered data series are performed at locations where there is significant influence of El Niño – Southern Oscillation (ENSO) on precipitations and streamflow discharges in the region. The degree of influence ENSO has on each hydrologic series hence can be predicted for different water sheds in the area. This can be of immense help for water management strategy and planning in the region.

Global drivers effect in multi-annual variability of runoff

Abstract Changes in runoff parameters are very important for Slovakia, where stream-flow discharges, being supplied by precipitation and groundwater runoff, are preferentially influenced by climatic conditions. Therefore, teleconnections between runoff parameters, climate parameters and global atmospheric drivers such as North Atlantic Oscillation, Southern Pacific Oscillation, Quasi-biennial oscillation and solar activity were studied in the Nitra River Basin, Slovakia. Research was mostly based on records of 80 years (1931-2010) for discharges and baseflow, and 34 years for groundwater heads. Methods of autocorrelation, spectral analysis, cross-correlation and coherence function were used. Results of auto- correllograms for discharges, groundwater heads and base flow values showed a very distinct 11-year and 21-year periodicity. Spectrogram analysis documented the 11-year, 7.8-year, 3.6-year and 2.4-year periods in the discharge, precipitation and air temperature time series. The same cycles except of 11-years were also identified in the long-term series of the North Atlantic Oscillation and Southern Pacific Oscillation indices. The cycle from approximately 2.3 to 2.4-years is most likely connected with Quasi-biennial oscillation. The close negative correlation between the North Atlantic Oscillation winter index and the hydrological surface and groundwater parameters can be used for their prediction within the same year and also for one year in advance.

Neural network river forecasting with multi-objective fully informed particle swarm optimization

In this work, we suggest that the poorer results obtained with particle swarm optimization (PSO) in some previous studies should be attributed to the cross-validation scheme commonly employed to improve generalization of PSO-trained neural network river forecasting (NNRF) models. Cross-validation entails splitting the training dataset into two, and accepting particle position updates only if fitness improvements are concurrently measured on both subsets. The NNRF calibration process thus becomes a multi-objective (MO) optimization problem which is still addressed as a single-objective one. In our opinion, PSO cross-validated training should be carried out under an MO optimization framework instead. Therefore, in this work, we introduce a novel MO variant of the swarm optimization algorithm to train NNRF models for the prediction of future streamflow discharges in the Shenandoah River watershed, Virginia (USA). The case study comprises over 9,000 observations of both streamflow and rainfall observations, spanning a period of almost 25 years. The newly introduced MO fully informed particle swarm (MOFIPS) optimization algorithm is found to provide better performing models with respect to those developed using the standard PSO, as well as advanced gradient-based optimization techniques. These findings encourage the use of an MO approach to NNRF cross-validated training with swarm optimization.

Impacts of Rainfall and Land Use on Sediment Regime in a Semi-Arid Region: Case Study of the Wuqi Catchment in the Upper Beiluo River Basin, China

The middle reaches of the Yellow River Basin transport the vast majority of sediment (>85% of the basin's total available sediment load), which has had profound effects on the characteristics of the middle and lower reaches of the Yellow River. With recent land use and land cover change, the Yellow River Basin has experienced significant sediment regime fluctuations. In this study, we analyzed the sediment regime from the Wuqi catchment which feeds into the upper reaches of the Beiluo River. Results show that a significant decreasing trend in annual suspended sediment discharge and suspended sediment concentration has existed from 1985 to 2008. The change-point year (the year that abrupt changes in sediment regime occurred in the catchment) was detected in 2001 (p < 0.05) for suspended sediment discharge and sediment concentration. There was a significant decreasing trend in streamflow discharge with the change-point year detected in 2002. Meanwhile, erosive rainfall and heavy rainfall exhibits an increasing but not significant trend. Coevally, land use has undergone considerable transformation. Compared to rainfall, land use, and land cover change and soil and water conservation have played a major role in influencing the sediment regime post-2000. In order to reduce soil erosion and sediment yield, more attention should be paid to changes in land use pattern and the impacts of soil and water conservation.