Journal of Hydrologic Engineering

The Muskingum model is one of the most widely used methods adopted for river flood routing. Apart from the conventional linear form, there are three possible nonlinear forms associated with the weighted flow and the storage volume, which are required to be incorporated in the Muskingum model. Comparative evaluation of these nonlinear forms has been carried out in this study. This study is based on the application of Microsoft Excel Solver, which has been used to estimate the optimal values of the model parameters in the nonlinear Muskingum models. The calibrated models have been verified by using two very common benchmark data sets of nonlinear Muskingum channel flood routing from the literature. The comparison between the models calibrated for all the three general nonlinear forms by using two distinct objective functions, namely, sum of squares of deviation (SSQ) and mean absolute relative error (MARE), in nonlinear optimization has been presented. Sensitivity analysis for different initial values for the model parameters has also been carried out for the optimization. From this study, it is found that the first form of nonlinear Muskingum model provided better results. Existing literature shows more focus on the use of this form of nonlinear Muskingum model and less consideration for the other two nonlinear forms. This may have been due to higher degree of nonlinearity involved in the other two nonlinear forms, which increases the complexity of obtaining optimal solutions and also requires more computational time. This paper presents a broad comparison of all three nonlinear forms of Muskingum models with respect to the efficiencies of the models to generate desired optimal solutions.

Predictions in ungauged basins (PUBs) are an increasingly important question in the water resource and quality management fields, especially for small watersheds where the phenomenon of data scarcity is prevalent. The transfer of hydrological parameters on the basis of regionalization is a common approach for solving PUB problems, and plenty of research has been undertaken on how to transfer calibrated parameters from gauged to ungauged watersheds. However, hydrological parameters estimation is substantially influenced by calibration objectives, which may affect model performance on the recipient watershed as well. In this paper the influence of calibration objectives on the transfer of parameter sets from one watershed to another is discussed. The HSPF hydrological model and the PEST automatic calibration model with four calibration objectives (squared error of daily flow, squared error of monthly flow, squared error of exceedance flow time, and sum of these squared errors) were applied. One gauged watershed of the Lake Dianchi Basin with daily flow data from 1999 to 2010 was calibrated by the combined HSPF-PEST model to obtain the transferrable parameters. Then the entire parameter sets were transferred to another neighborhood watershed, and model performance was tested by conventional goodness-of-fit statistics. Results show that (1) parameters transferred from all four calibration objectives perform well on the target watershed; (2) selection of calibration objective has a significant impact on model performance for both donor and recipient watersheds; and (3) the differences among objectives are similar in the two watersheds, suggesting that the objectives’ features are transferrable. Therefore, the selection of calibration objective should be considered as a significant factor when transferring parameters to ungauged watersheds.

This study investigates the performance of the covariance matrix adaptation-evolution strategy (CMA-ES), a stochastic optimization method, in solving groundwater inverse problems. The objectives of the study are to evaluate the computational efficiency of the parallel CMA-ES and to investigate the use of the empirically estimated covariance matrix in quantifying model prediction uncertainty due to parameter estimation uncertainty. First, the parallel scaling with increasing number of processors up to a certain limit is discussed for synthetic and real-world groundwater inverse problems. Second, through the use of the empirically estimated covariance matrix of parameters from the CMA-ES, the study adopts the Monte Carlo simulation technique to quantify model prediction uncertainty. The study shows that the parallel CMA-ES is an efficient and powerful method for solving the groundwater inverse problem for computationally demanding groundwater flow models and for deriving covariances of estimated parameters for uncertainty analysis.

Hydrologic impacts of land disturbance and management can be confounded by rainfall variability. As a consequence, attempts to gauge and quantify these effects through streamflow monitoring are typically subject to uncertainties. This paper addresses the quantification and delineation of different sources of how uncertainty is manifested in a long-term hydrologic monitoring study and through two concepts: (1) detectability, i.e., the chance of observing anticipated changes in streamflow following a known change in land cover; and (2) interpretational uncertainty, i.e., the chance of improperly attributing an observed effect to the wrong cause. The paper offers probabilistic interpretation of each concept and illustrates, through a set of hypothetical monitoring experiments, the dependence of these entities on factors such as monitoring duration and the choice of indicators. Central to the experiments is a resampling scheme which randomly redistributes historical rainfall events and thereby generates an ensemble of weather scenarios. The rainfall events are coupled with a hydrologic model to generate of preurbanization and simulated posturbanization runoff events. In each hypothetical monitoring experiment, two indicators, i.e., runoff ratio and scaled peak discharge rates, are computed and compared for designated subsets of the preurbanization and posturbanization rainfall-runoff time series and the outcomes of the experiments are then synthesized to derive the probabilities. The results suggest that (1) the duration of observation very likely enhances detectability but does not necessarily reduce interpretational uncertainties, and (2) extending the duration of baseline monitoring alone yields only a minor decrease in uncertainty.

This paper presents a physics-based two-dimensional (2D) numerical model to simulate overland flows typically generated by rainfall of a storm event or multiple events in natural terrain with complex topography, landform, soil characteristics, and land use. The model is based on the 2D fully nonlinear shallow-water equations (SWEs) in which tempospatial variations of rainfall intensity and infiltration are taken into account as source and sink terms, respectively. The Green-Ampt equation is used to simulate infiltration. Due to strong nonlinearity of the coupled dynamic processes in overland flow and stormwater runoff, special efforts were made to solve this coupled-flow system under the conditions of unsteady rainfall intensity and natural terrain. To attain the modeling capabilities for multiple flow regimes including subcritical, supercritical, and the transitions, a second-order central-upwind shock-capturing scheme, which is well balanced and depth-positivity preserving, is used to solve the governing equations. The model is capable of simulating the Hortonian overland flows resulting from the complex rainfall storm events recorded by multiple rain gauges. Model verification was achieved by comparing numerical results with corresponding analytical solutions. The model was validated by reproducing the field-scale rainfall-runoff experiments conducted in Niger, West Africa, in 1994. It was further applied to simulate historical storm events in the Goodwin Creek watershed in Mississippi. Verification and validation indicate that the developed numerical model is capable of simulating hydraulic and hydrological processes in rainfall-generated overland flows over a watershed with natural terrain by considering land use and soil characteristics.

The Yellow River is an important source of sediment flux to oceans in the world, and approximately 90% of the sediment originates from the middle Yellow River, an area with known high rates of soil erosion and sediment delivery. Trends and interannual variations in sediment discharge have considerable implications for reservoir operation and river management of the lower Yellow River. The annual sediment discharge of four main stream stations and ten tributary stations was used to show the spatiotemporal variation in sediment yield and to quantify the relative contribution of precipitation change and human activities, especially the influence of vegetation restoration with implementation of the Grain for Green Project (GGP) in 1999. The Mann-Kendall and Pettitt tests were used to detect the abrupt change in sediment discharge since the 1950s. The annual sediment yield of the middle Yellow River has shown a significant downward trend, decreasing by an order of magnitude in the last decade (2000–2010) compared with the 1950s. Annual sediment yield was reduced by 95.5% from $\mathrm{3,887.0}\mathrm{t}·{\mathrm{km}}^{-2}·{\mathrm{year}}^{-1}$ in the 1950s to $174.7\mathrm{t}·{\mathrm{km}}^{-2}·{\mathrm{year}}^{-1}$ in the 2000s. The eastern part of the middle Yellow River basin showed the most significant decrease, with sediment yield decreasing up to 90% in the 2000s compared with the 1950s. Annual precipitation decreased by 7.3% in the periods 1980–2010 and 1959–1979. Human activities and precipitation explain 83.6 and 16.4% of the total reduction in sediment yield, respectively, using the double mass curve method. Annual sediment discharge decreased by $597\times {10}^6\mathrm{t}·{\mathrm{year}}^{-1}$—from $660\times {10}^6$ in 1980–1999 to $63\times {10}^6$ in 2000–2010. Sediment deposition along the Longmen-Huayuankou section amounted to $120\times {10}^6\mathrm{t}·{\mathrm{year}}^{-1}$ during 1980–1999 and $229\times {10}^6\mathrm{t}·{\mathrm{year}}^{-1}$ during 2000–2010 based on mass balance. The additional $109\times {10}^6\mathrm{t}·{\mathrm{year}}^{-1}$ of sediment was trapped following completion of the Xiaolangdi Reservoir in the Longmen-Huayuankou section. This explains 18.3% of the sediment reduction in the 2000s. Soil conservation practices have further reduced sediment discharge by $253\times {10}^6\mathrm{t}·{\mathrm{year}}^{-1}$, which explains about 42.4% of the decrease ($597\times {10}^6$) during 2000–2010. A reduction of approximately $235\times {10}^6\mathrm{t}·{\mathrm{year}}^{-1}$ occurred because of vegetation restoration driven by the Grain for Green Project, which accounted for 39.4% of the total reduction ($597\times {10}^6\mathrm{t}·{\mathrm{year}}^{-1}$) in the last decade compared to 1980–1999.

The Wind River Range is a continuous mountain range, approximately 160 km in length, in west-central Wyoming. The presence of glaciers results in meltwater contributions to streamflow during the late summer (July, August, and September: JAS) when snowmelt is decreasing; temperatures are high; precipitation is low; evaporation rates are high; and municipal, industrial, and irrigation water are at peak demands. Thus, the quantification of glacier meltwater (e.g., volume and mass) contributions to late summer/early fall streamflow is important, given that this resource is dwindling owing to glacier recession. The current research expands upon previous research efforts and identifies two glaciated watersheds, one on the east slope (Bull Lake Creek) and one on the west slope (Green River) of the Wind River Range, in which unimpaired streamflow is available from 1966 to 2006. Glaciers were delineated within each watershed and area estimates (with error) were obtained for the years 1966, 1989, and 2006. Glacier volume (mass) loss (with error) was estimated by using empirically based volume–area scaling relationships. For 1966 to 2006, glacier mass contributions to JAS streamflow on the east slope were approximately 8%, whereas those on the west slope were approximately 2%. The volume–area scaling glacier mass estimates compared favorably with measured (stereo pair remote sensed data) estimates of glacier mass change for three glaciers (Teton, Middle Teton, and Teepe) in the nearby Teton Range and one glacier (Dinwoody) in the Wind River Range.

In this paper, climate change impact on flood frequency has been investigated in Bagmati River Basin of Nepal using bias-corrected global climate model (GCM) precipitation output. The research reported in this paper employed a high-resolution (approximately 20-km) daily GCM precipitation and temperature output of Meteorological Research Institute (MRI), Japan. Comparison of observation and GCM data pointed out that the MRI-GCM precipitation consists of significant biases in frequency and intensity values. Quantile-quantile mapping method of GCM bias correction was applied for minimizing the biases in precipitation frequencies and intensities. Concept of homogeneous precipitation regions was introduced to link the uneven observation data stations and GCM grid cells. Analyses of return period curves, shape, and scale factors at different observation stations enabled delineation of three homogeneous precipitation regions. Accordingly, regional quantile-quantile bias-correction technique was developed for minimizing biases in MRI-GCM precipitation output. A distributed rainfall-runoff model enabled generation of streamflow series using bias-corrected GCM output for 1979–2003 and 2075–2099 periods, as current and future scenarios, respectively. Finally, comparative flood frequency analyses were carried out for the simulated annual daily maximum streamflow series of current and future climates. The analyses revealed that the climate change will result more extreme precipitation events in monsoon months and less precipitation in other months. The analyses also revealed that flood events will be significantly increased in future. The range of change in 2–100 year return period floods was from 24–40%.

Recharge rates evaluated from pilot projects of surface managed aquifer recharge are extrapolated to develop design criteria for full-scale projects. Field experiments at surface-managed artificial aquifer recharge facilities in the Walla Walla River basin, Oregon, United States, were used to estimate recharges rates in relation to groundwater mounding and to the expansion in surface area of infiltration basins. Analysis of the results shows that in the case scenarios where the water table mounding does not reach the infiltration basin floor (thereby maintaining an unsaturated zone between the water table and the infiltration basin), the recharge rates from pilot tests scale linearly with the basin’s surface area expansion. However, in the case where the groundwater mound reaches the bottom of the basin floor (thereby providing a full hydraulic connection between the infiltration basins and the aquifer), recharge rates should be extrapolated using the perimeter of the infiltration basin. The explanation for this effect is offered by evaluating the distribution of the water velocities at the infiltration basin floor as the length difference between aquifer thickness and the radius of the infiltration basins increases. These findings enable pilot project results to be used as design criteria for full scale projects.

Drought is one of the most common natural hazards with adverse effects on agriculture and the water resources. This study aims to spatially analyze the drought hazard in the Upper Tiber River basin and find a representative indicator on the basis of meteorological data that are widely available. To this end, the significance of using solely precipitation versus including evapotranspiration (ET) in drought characterization is thoroughly investigated. Three relevant indicators are considered: (1) a new index Standardized Effective Precipitation EvapoTranspiration Index (SPETI) incorporating, besides ET, the losses due to runoff; (2) the commonly used Standardized Precipitation Index (SPI); and (3) the Reconnaissance Drought Index (RDI). A comparison is undertaken at various timescales (9, 12, and 24 months) using precipitation and temperature data from two stations for the period 1953–2011, for which complete rainfall and temperature time series are available. This analysis demonstrates (1) the very similar evolution and behavior of the three indexes and (2) the reliability of the SPI for drought monitoring and characterization in the case of the Upper Tiber River basin, also using observed hydrological effects. Based on these findings, a longer data set of available precipitation data (45 stations, 96-year-long time series from 1916 to 2011) is used to calculate the ${\mathrm{SPI}}_{12}$ and to derive four new subindicators reflecting the intensity, magnitude, duration, and frequency of drought events. These subindicators, once classified, are blended into a Drought Hazard Index (DHI), thus providing a more holistic characterization of the drought hazard on a scale of 1 to 4. A spatial analysis is finally performed across the resulting DHI values in order to investigate the spatial variability of a drought hazard and identify drought-prone areas. It is found that the most vulnerable areas are located in the southern and eastern part of the Upper Tiber River basin, and the north-central part is less affected by drought conditions.

In recent decades, the Tarim River basin in northwestern China has seen intense confrontation between economic development and environmental protection. How to balance sustainable socioeconomic development and harmony between humans and water has been a critical issue facing local governments for many years. This study proposes a quantitative method of harmony theory that contains three basic criteria, heath, development, and coordination, to address the harmony problem regarding the human–water relationship in the basin. Indicators were used to quantify levels of health, development, and coordination in the basin. An optimal scheme is proposed, based on the three aggregate indicators. The evaluation results indicate the following: (1) health conditions in the middle and lower reaches of the river basin are not optimal. Development conditions in the lower reach are slightly better, and coordination conditions there are the poorest; and (2) the Aksu and Kaidu-Kongqi rivers have a relatively harmonious state, but remaining districts have relative disharmony. Scenario simulation results show that human system development and water system health are equally important for a harmonious relationship. When the human and water systems achieve coordinated development, the degree of harmony increased from 0.4230 to 0.6618. Regulation results are of scientific and practical value in basin-scale water resource management in arid regions.

The reliability of the low-impact development (LID) module of the widely used Storm Water Management Model (SWMM) for modeling the runoff reduction performance of permeable pavement systems was evaluated through example applications with rainfall data from Atlanta. The method of calculating infiltration through the pavement layers of permeable pavement systems of the LID module was found to be inadequate when the depths of the pavement layer are less than 120 mm and the computational time steps are longer than 30 min. An alternative method of representing permeable pavement systems as equivalent regular subcatchments is proposed. Using this method, the hydrologic operation of permeable pavement systems can be modeled by SWMM or other hydrologic models.

The measurement and computation of discharge measurement in tidal streams using a fast and minimally intrusive method is developed. The discharge of tidal streams is highly unsteady because of influences from ocean tides and upstream river flow. Measurement of the discharge at a stream with such complex currents is limited by the efficiency and cost of conventional measurement instruments and methods. Thus, it is necessary to introduce new measurement approaches and instruments for measuring the discharge of tidal streams. This study installs high-precision Argonaut-SW under a sounding weight to be hung from a vertical line using a single-drum winch. The Argonaut-SW is modified to be a mobile device to measure the velocity distribution and water depth from the surface. This study also uses the observed data to establish an efficient discharge measurement method suitable for tidal streams, which utilizes the relationship between mean and maximum velocities for rapidly estimating discharge in the future. This method is applied on the tidal reach of the Keelung River. The results show that the discharge measurement method established by this study can not only greatly improve the accuracy of discharge measurement but also significantly reduce the time, labor, and cost required for measuring discharge in tidal streams.

Applications of artificial neural networks (ANNs) in forecasting flow rates at multiple sections in a river system are presented. Model formulations are based on learning characteristics of the actual and fractional storage variations in river reaches during unsteady flow. Multilayer perceptrons (MLP), MLPs with memory, time delay neural networks (TDNNs), and multiple gamma memory neural networks in three model forms are used to forecast flow rates in Tar River Basin, United States. Model performances are evaluated in terms of statistical criteria, RMS error, and coefficient of efficiency. Maximum RMS error resulted for the models are less than 6.50% of the respective observed mean value. A coefficient of efficiency value of more than 0.95 for the models indicates satisfactory performances. Results presented in this paper depict flow variations corresponding to implicitly specified storage variations and demonstrate applicability of the ANNs in real time flow forecasting for multiple sections in a basin obeying continuity principle.

Sensitivity analysis is a technique for quantitatively analyzing the variation in a dependent variable caused by each independent variable. In this study, a global sensitivity analysis method is proposed that is suitable and effective for multivariable and nonlinear systems. Specifically, sensitivity is defined before nonlinear multipolynomial expansion is conducted according to the Taylor midvalue theorem to intuitively determine nonlinear relationships between the rate of change in the dependent variable and each independent variable. A back-propagation network is also used to determine these relationships. The detailed computational steps and methods for evaluating the results are provided. The proposed method was tested using computer simulation and with an actual hydrological engineering problem. Computer simulations aided the design of experimental plans directed at linear and nonlinear polynomials. The experimental results showed that sensitivity analysis of dependent variables and each independent variable depends on two main characteristics: (1) the relation mapped between dependent variables and each independent variable, and (2) the value of each independent variable. The randomness of the sample, the structure of the back-propagation network, and the parameters did not significantly affect the final sensitivity calculation results. Analysis of the hydrological engineering problem showed that, given antecedent runoff and precipitation, the main factor that affected runoff in the Nenjiang River basin during flood season was antecedent precipitation whereas antecedent runoff was the main factor in the nonflood season. These results were reasonable and consistent with hydrological laws. Based on theoretical experiments and an actual engineering example, this preliminary study demonstrated the feasibility and effectiveness of this method of global sensitivity analysis in addressing complex problems.