Journal of Hydrologic Engineering

This paper explored various configurations of the ensemble Kalman filter, the GR4J hydrological model, and the Global Environmental Multiscale (GEM) atmospheric model in order to maximize the skill of ensemble hydrological forecasts for the Lake Champlain–Richelieu River watershed. In open-loop mode, the hydrological model represented very well the observed streamflow (Nash–Sutcliffe value above 90%). It sufficed to assimilate hydrological data to obtain a reliable and skillful analysis of streamflow; assimilation of snow water equivalent (SWE) information did not bring additional benefits. In forecast mode, the opposite was true: hydrological assimilation alone did not improve forecast performance, but assimilating SWE data improved reliability and skill of forecasts with lead times of 15 days to 1 month. The impact of SWE assimilation also depended on the quality of the precipitation analysis. It therefore is recommended to use SWE assimilation for monthly forecasting, especially if the precipitation data used to drive the hydrological model are biased.

Coastal cities of southern peninsular India are characterized by highly seasonal rainfall during a few weeks of a year, a long dry-weather period, flat topography, and shallow groundwater levels. This study investigated the challenges and opportunities prevailing in implementation of low-impact development techniques (LID) as hydrologic restoration measures in catchments of the coastal city of Chennai. Rainfall patterns, which were evaluated with precipitation concentration index (PCI), showed that rainfall in the city is irregularly distributed, with only 3.5–4 months of rainfall occurrence in a year. Catchment-scale numerical modeling of green roof and rainwater harvesting (RWH) structures demonstrated that RWHs are an efficient method of stormwater management in the study area. Vegetation-based LIDs, however, could not be adopted due to their irrigation water demands, which would add to the drinking water demand in the region. Further challenges in the implementation of LIDs because of extreme weather conditions and the shallow ground water table, and potential solutions, were discussed. We concluded that LIDs retrofitted with hydrologic interventions such as managed aquifer recharge and green roofs can provide economic benefits to the low- to middle-income population in the study area.

The hydraulic structures constructed for the benefit of society can cause perturbations in streamflows. Such disruptions to natural conditions may affect river ecosystems. The spatial scale of the impacts is further magnified in the case of interbasin water transfer (IBWT) projects, which can cause changes in the ecohydrological regime of donor as well as recipient watersheds. Assessment of the changes in the hydrological regime due to artificial structures requires a comparison of existing and counterfactual scenarios. In this paper, a methodological framework is proposed and applied to the Umiam Watershed to generate natural streamflow using postimpact data when preimpact data are not available. The Soil and Water Assessment Tool (SWAT) model is applied for simulating streamflow in the presence of a reservoir and water transfer out of the watershed. The Indicators of Hydrologic Alteration (IHA) method was used for the analysis of changes in streamflow. The results reveal a reduction in the monthly median flow rate by at least 21% in all months during the five-decade period. Large floods and small floods are found to be reduced in the presence of the reservoir, whereas it also causes more frequent low flows, which last longer. The extreme annual minimum flow conditions (1-, 3-, 7-, 30-, and 90-day minima) show low alteration, while the corresponding yearly maximum flow conditions show medium alteration. The frequency and duration of high and low pulses are greatly affected by the reservoir. The rising rate, falling rate, and number of reversals show a significantly decreasing trend. The results indicate a high overall degree of alteration in streamflow.

Calibrated hydrological models forced with the climate data from various climate models have been widely employed for future streamflow projection. But a major cause of concern in such an analysis has been the suite of uncertainties inherent in the modeling chain that begins from the climate models and ends with the hydrological models. The uncertainties contributed by the hydrological models have generally been given a lesser focus. In the present research, the contribution of the hydrological model parameter uncertainty has been investigated. The multiobjective evolutionary algorithm (MOEA) is employed for calibrating the hydrological model, the Soil and Water Assessment Tool (SWAT), developed for the Magpie River, located in Northern Ontario. The calibrated model was then forced with the data from an ensemble of six regional climate models for projecting the scenario streamflow and evaluating associated uncertainties. A significant variation in seasonal water availability is projected for the two scenario periods studied. The contribution of the hydrological model parameter uncertainty in the streamflow projection is found to be significant, lying in the range of 16%–83%, depending on the month.

This study investigated the potential of methods from information science to detect hydrological alterations caused by human activity. In particular, the influence of the construction of a cascade of dams and reservoirs on the daily streamflow of the São Francisco River in Brazil is investigated by using the sample entropy (SampEn) method and its generalization, the multiscale entropy (MSE). A long daily-streamflow time series at locations upstream and downstream of a cascade of dams, recorded during the period 1929–2015, encompassing the Sobradinho dam (1979) and the Xingó dam (1994), were analyzed. It was found that reservoir operations changed the temporal variability of both the original and deseasonalized streamflow series by decreasing the degree of regularity, as indicated by higher SampEn values. In the MSE analysis, this was held for the small time scales, while larger scales reservoir operations induced a more regular streamflow regime (lower entropy values). The time variation of the streamflow regularity was also analyzed using the time-dependent sample entropy, which confirmed the preceding finding. In both the MSE and time-dependent SampEn analyses, the streamflow recorded at the São Francisco station, which is located upstream of dams and reservoirs, did not exhibit any change in entropy values due to reservoir operation, while the deseasonalized series showed a similar (although less pronounced) behavior as that for the downstream stations, indicating that, in addition to the reservoir operations, some other natural factors could have coinduced, such as a shift toward the lower regularity of the streamflow regime. These results provide the evidence that methods from information science can be useful in assessing hydrological alterations caused by human activities.