Journal of Hydrologic Engineering

The potential impact of climate change on the hydrologic regime is a crucial question for water resources management. This study explores regional trends in monthly maximum flows and their possible linkages to trends in selected climatic variables in a hydroclimatologically homogeneous region. Trends are identified using the Mann-Kendall nonparametric test, with a modification for autocorrelated data. The regional significance of trends identified at the local scale is evaluated by means of a regional bootstrap algorithm. A trend significance index that accounts for both local and regional significance levels is proposed as a convenient tool for quantification and visual comparison of different trend results. The index is also used for identifying potential linkages between trends in hydroclimatic records. The plausibility of identified linkages is explored by means of cross-correlation analysis applied on residuals that are obtained from the original records after subtracting all serially dependent components. An uncertainty in regional trend analysis resulting from different observation periods is presented and quantified by calculating trend significance indices for several scenarios of different locations and lengths of a common observation period shifted on a timescale. The results show significant changes in the intraannual flood regime in the case study area of southern British Columbia. A regionally, strongly significant increase in the spring air temperature shifts the timing of the snowmelt process, resulting in a significant increase in early spring maximum flows and a significant decrease in late spring maximum flows. An autumn decrease in flows is related to increasing air temperature in the preceding summer months, which tends to dry out catchments more intensively, and is also related to precipitation activity in the previous months. The regional trend results are highly sensitive to the location and length of a given regional observation period on a timescale. Possible sources of the uncertainty in a low frequency climatic variability such as the Pacific Decadal Oscillation are discussed.

By applying harmonic analysis to El Niño–Southern Oscillation (ENSO) composites of the 6-month Standardized Precipitation Index (SPI) and rainfall anomalies for the 1900–1996 period, and based on the 90% confidence limits established from bootstrap resampling, it was found that ENSO responses in East African rainfall are region and season dependent, and the influence of El Niño is stronger and opposite that of La Niña. Among five regions of unique ENSO responses identified, northeastern (R4) and southern Tanzania (R5) seem to have the most consistent (in terms of vector coherence, percentage of variance extracted by the first harmonic, and SPI magnitude) ENSO responses. R5 experiences positive (negative) response under La Niña (El Niño) influence during January and June of the post-ENSO year. Southern Uganda and much of the Lake Victoria basin show some significant positive ENSO response for November, December, and January. The temporal and regional patterns of ENSO response periods were also analyzed using the index time series and boxplots on the 6-month SPI. Boxplots confirm a shift in the distribution of 6-month SPI between ENSO and non-ENSO affected seasons.

This study compares the generalized rainfall intensity-duration-frequency relationships proposed by Bell in 1969 with results obtained from data registered in different climatic regions of Argentina. The results show that the relationships are applicable in different climatic zones (from subtropical to semiarid). This conclusion is considered important because in Argentina, as in other developing countries, data are generally sparse, expensive, and difficult to obtain.

Previous work by various authors has shown that gamma-Laguerre distributions are appropriate for hydrologic applications because they offer the flexibility necessary to fit both the bulk and tails of empirical distributions, as well as a handy estimation formalism. The present work solves problems that still remain in gamma-Laguerre parameter estimation formalism: evaluating the highest degree of Laguerre polynomial and avoiding decreasing intervals in fitted probability distribution functions. From a pool of over 200 maximal rainfall and maximal discharge time series from all over the world that have been analyzed, a couple of examples, located in Mexico City and Niamey, respectively, are presented to illustrate the functionality of the formalism.

A simple snowdrift model was developed, incorporated into a distributed winter-time hydrological model, and tested against snow measurements from a hillside in eastern Washington State. Snow movement can be an important factor in the distribution of spring soil moisture and runoff. Although current hydrological models often attempt to account for heterogeneities in precipitation distribution, they do not account for snowdrift. Snow melts and accumulates during the same times that it is redistributed. Therefore, evaluation required a snowmelt/accumulation model to be coupled with the snowdrift model. The snowmelt/accumulation model used the standard energy balance approach and performed well, i.e., standard errors of snow water equivalent ≈1 cm. The snowdrift model’s simulated snow distribution generally agreed with observed snow distribution across a hill. Most notable were the model’s ability to correctly place a snowdrift on the lee side of the hill and its ability to predict snow removal from nondrift areas. The effects of snow redistribution and the model’s ability to reproduce these were obvious when overlaid on model results that ignored snowdrift.

Distributed hydrologic models typically incorporate topographic data through the use of raster-based digital elevation models. The resampling of high-resolution grid data required to effectively use distributed models, however, can result in the distortion of terrain and hydrographic properties. In this study, we present a geographic information system approach for deriving multiple resolution meshes that conserve physiographic features while significantly reducing the number of computational nodes in a distributed hydrologic model. We utilize triangulated irregular networks (TINs) which serve to integrate information on the surface topography, hydrographic features and land surface characteristics into an adaptive representation of a basin. We discuss three approaches for constructing TIN models for hydrologic applications: (1) Traditional, (2) hydrographic and (3) hydrological similarity TINs. We focus on the generation of triangulated terrain models using the concept of hydrological similarity provided through a topographic or wetness index. This new method embeds an estimate of the steady-state hydrologic response directly into the basin terrain model. Through a series of case studies, we demonstrate the advantages of the multiple resolution approaches over a range of terrain characteristics, basin scales and elevation data products. Finally, we discuss the implications of TIN terrain representation for watershed simulation with the TIN-based Real-Time Integrated Basin Simulator model.

This study evaluates the studies by Kim, Yoo, and Yoo and Ha on the sampling of soil moisture to show if their studies are applicable to field experiments. The objective of this study was accomplished by a simulation of sampling experiments over Washita ’92 soil moisture data field to estimate the sampling errors, and by comparing them with those analytically derived. As a result of the study we found that the ensemble means of sampling errors estimated by repeated simulations of the sampling experiment agree well with those analytically derived. Also, sampling errors from evenly spaced and from randomly located sensor networks do not have any obvious difference. These findings indicate that the formulations by Kim, Yoo, and Yoo and Ha for the sampling errors are reliable enough to be used for evaluating the sampling networks as well as for planning purposes. Also, the model for soil moisture dynamics, even though it is a simple diffusion model with only two parameters, may have no serious problems and can be used for sampling related studies. However, the variance of the mean square sampling errors from the evenly spaced sensor networks was found to be much smaller than those from the randomly located sensor networks. This indicates the advantage of using evenly spaced sensor networks even though the expected mean square sampling error value is the same. Similar results can also be found for the soil porosity field.

A digital filtering algorithm for continuous base flow separation is compared to physically based simulations of base flow. It is shown that the digital filter gives comparable results to model simulations in terms of the multiyear base flow index when a filter coefficient is used that replicates the watershed-specific time delay of model simulations. This way, the application of the heuristic digital filter for practical continuous base flow separation can be justified when auxiliary hydrometeorological data (such as precipitation and air temperature) typically required for physically based base flow separation techniques are not available or not representative of the watershed. The filter coefficient can then be optimized upon an empirical estimate of the watershed-specific time delay, requiring only the drainage area of the watershed.

Tracer experiments are widely used tools in field studies on solute transport in streams. In addition, numerous injections are carried out each year as part of the so-called salt dilution technique of stream gauging, producing a large body of data (in principle) available for analysis, and most of these latter experiments are instantaneous slug releases. Interpretation of the observed breakthrough curves is often done with the aid of either the transient storage (TS) or the advection-dispersion (AD) model, the latter being a subset or simplification of the former. The work reported here aimed at the development of a criterion to determine when the use of the TS model is required to explain a given breakthrough curve and in what circumstances the AD model can be expected to produce comparable results. The transient storage (TS) or dead zone model was solved for 216 parameter combinations, believed to cover a large portion of the situations possibly encountered in practice. The advection-dispersion (AD) model was then calibrated to reproduce the TS breakthrough curves as closely as possible. The outcome was judged to determine whether a particular breakthrough curve was unique to the TS model or could have been produced by the AD model as well. Criteria in terms of Damköhler index, DaI, and skewness coefficient, $G_t\text{,}$ have been derived, and an application to a real world case is given. Use of an artificial neural network to improve the “diagnostics” is demonstrated.

Traditionally used methods for developing a synthetic unit hydrograph (SUH) are well known for their limitations. In last few decades, use of probability distribution functions in developing SUHs has received much attention. In this study, the potentials of a three-parameter beta distribution are explored. Using a analogy between the three-parameter beta-distribution shape and the SUH shape, approaches are developed to evaluate the unknown parameters. Based on nondimensional analysis and optimization, a simple accurate relation is introduced to estimate the three parameters of the beta distribution that is useful for unit hydrograph derivation. The relation yields results closer to those obtained by an available trial and error procedure. The unit hydrographs from the proposed method fit observed hydrographs better than those from the widely used two-parameter gamma distribution. The potential of the approach is demonstrated using data from different catchments lying within and outside India. The methodology is found to work consistently better in most cases.

The design of a storm water detention basin requires both hydrologic and hydraulic information. The basic hydrologic data include the inflow hydrograph and the allowable release. The hydraulic information of a basin requires prior knowledge of the basin geometry and outlet structures. With a known storage-outflow curve, the performance of the basin can be examined using a reservoir routing procedure. During the planning stage, a series of feasible basin sites is typically investigated for comparison and selection. During a feasibility study, the engineer faces a challenge as to how to derive the required storage-outflow curve when little hydraulic information is known. This paper presents a hydrology-based approach by which the storage-outflow curve can be approximated from the inflow hydrograph to the basin and the maximum allowable release from the basin. This hydrologic procedure significantly simplifies the storm water detention modeling technique and is a useful tool for regional drainage planning and alternative studies. In addition, this paper rearranges the continuity principle to derive two new reservoir routing functions. Both functions provide a direct solution using all variables at the same time step without iteration. The selection of routing functions is a matter of mathematical convenience.