Basin Flow Research Articles

Assessment of hydrological baseline condition and its alteration in Athabasca River Basin, Canada

Study regionAthabasca River Basin (ARB), Canada. Study focusThis study aimed to characterize the flow regime of the ARB, a basin with diverse hydroclimatic and geological characteristics. Forty-two different flow indicators from the Indicators of Hydrological Alteration (IHA) and Cold regions Hydrological Indicators of Change (CHIC) were employed. The natural range of these indicators was established for the baseline period (1961–1990), and subsequent alterations during the recent period (1991–2020) were systematically examined. Principal Component Analysis (PCA) was applied to identify pivotal indicators shaping the basin's flow regime. In addition, trends of key indicators were examined at eight distinct locations within the basin. New hydrological insights for the study regionThe findings indicate spatiotemporal variation between the basin's upper and lower parts. The upstream region exhibited an earlier peak flow (9 days), an earlier ice break-up (17 days), and a shorter ice cover duration (22 days) compared to the downstream region. Increased winter and spring flow have led to an augmentation of annual flow by 3.8 % in the upper region. In contrast, downstream flow experienced a decline throughout the year (11.38 %), which was found to be statistically significant at a rate of 3.24 m3/s/year. Alteration analysis revealed a shift toward the 'low category' (below their defined baseline range) for most indicators in the recent period, underscoring a transition towards a diminishing flow regime, with an overall alteration ranging at low to moderate levels (19–38 %). Late summer flow reduction (8–25 %) can have critical implications, given the rising water demand in the basin. The study identified eleven key indicators encapsulating the basin's flow regime variability range. It was found that ice cover, its break-up, and spring freshet significantly influence the flow regime of the basin. The findings from this study will assist decision-makers in making more informed decisions for the holistic management of water resources in the basin.

Implementing advanced techniques for urban mountain torrent surveillance and early warning using rainfall predictive analysis

Urban flood forecasting and early warning play a pivotal role in ensuring efficient flood mitigation and management. The unpredictability in precipitation's intensity, temporal patterns, and spatial distribution introduces considerable variability into the basin's flow dynamics. This, in turn, escalates the uncertainty surrounding hydrological predictions, complicating the task of flood forecasting and early warning. To address these challenges, this research introduces a method that refines rainfall forecasts using a Wavelet Neural Network (WNN). By establishing a benchmark for area rainfall, we've developed a comprehensive disaster prevention and early warning system that synergizes real-time precipitation data, area rainfall, and flood peak predictions. Specifically tailored for urban terrains prone to mountain torrents, the WNN-based monitoring and pre-alarm model offers a sound and practical forecasting tool. Its relevance is accentuated by its potential to spearhead urban flood control initiatives. Our findings validate the model's adaptability and efficacy, particularly within urban mountainous watersheds, heralding a fresh paradigm in mountain flood disaster forecasting and early warnings.

Reconstructing Early Hydrologic Change in the California Delta and its Watersheds

AbstractRegulatory goals for the California Delta attempt to restore natural ecosystems through various water management efforts. Defining management criteria for restoration is challenging, given that the earliest data describing the hydrology of the region follow many decades of change associated with agricultural development, channel modification, and flood control. This study explores the hydrology of the 1850–1920 period by synthesizing new reconstructed precipitation, basin inflows, land use change, and levee construction time series, in a semidistributed hydrologic model. The model demonstrated that it is impossible to simultaneously reproduce estimated historical flood extents, frequencies, and durations given contemporary topography. Bounding cases were constructed to span potential water budget partitioning and suggest that the state of this region by the 1920s was hydrologically similar to that of the natural regime (i.e., flow experienced was depressed due to drought, but within the bounds of variability of the natural Delta system), partly due to the flow augmentation provided by flood control infrastructure and enhanced channel conveyance. The model suggests that levee construction, rather than land use change, had the greatest impact on Delta hydrology. This and other reconstructions, however, suggest that decreases in annual Delta outflows accelerated after 1920. Future efforts to reconstruct Delta hydrology should focus on improving information about the historical topography and channel geometry of the Central Valley river network, with a view to refining understanding of the natural and historical flood regime.

Satellite observations and modeling to understand the Lower Mekong River Basin streamflow variability

In this work, we have used the Soil & Water Assessment Tool (SWAT) to examine streamflow variability of the Lower Mekong River Basin (LMRB) associated with changes in the Upper Mekong River Basin (UMRB) inflows. Two hypothetical experiments were formulated and evaluated for the LMRB, where we conducted runoff simulations with multiple inflow changes that include upstream runoff yield increase and decrease scenarios. Streamflow variability of the LMRB was quantified by two streamflow metrics that explain flow variability and predictability, and high flow disturbance. The model experiments were performed for the Lower Mekong River Basin with identical climate, soil, and other watershed characteristics data. Remote sensing precipitation (Tropical Rainfall Measurement Mission, TRMM, and Global Precipitation Measurement mission, GPM), meteorological data as well as spatial data that include a digital elevation model, newly developed soil information (Harmonized World Soil Database, HWSD), and land use and land cover were processed as input to the LMRB model simulations. Observed daily streamflow data along the Lower Mekong River from Chiang Sean, Thailand to Kratie, Cambodia were used for calibration and validation. Our work results suggest that the Lower Mekong River streamflow is highly variable and has a low predictability (Colwell index of about 32%). We found that releasing more water from upstream Mekong during rainfall months by 30% would result in a reduction in the Lower Mekong streamflow predictability by about 21%. This reduction in predictability is mainly attributed to a decrease in the Contingency index. Our work shows that the ability to predict floods/droughts at the Lower Mekong River would be reduced if there is any anticipated change (i.e., increase/decrease) from UMRB releases. Our results also show that releasing more flows from the upstream Mekong would also affect flood duration and the frequency of flood occurrences downstream. The results of this work thus help to quantify the sensitivity of streamflow variability at the Lower Mekong River Basin to upstream anthropogenic changes.

Mediating stream baseflow response to climate change: The role of basin storage

AbstractInter‐basin differences in streamflow response to changes in regional hydroclimatology may reflect variations in storage characteristics that control the retention and release of water inputs. These aspects of storage could mediate a basin's sensitivity to climate change. The hypothesis that temporal trends in stream baseflow exhibit a more muted reaction to changes in precipitation and evapotranspiration for basins with greater storage was tested on the Oak Ridges Moraine (ORM) in Southern Ontario, Canada. Long‐term (>25 years) baseflow trends for 16 basins were compared to corresponding trends in precipitation amount and type and in potential evapotranspiration as well as shorter trends in groundwater levels for monitoring wells on the ORM. Inter‐basin differences in storage properties were characterized using physiographic, hydrogeologic, land use/land cover, and streamflow metrics. The latter included the slope of the basin's flow duration curve and basin dynamic storage. Most basins showed temporal increases in baseflow, consistent with limited evidence of increases and decreases in regional precipitation and snowfall: precipitation ratio, respectively, and recent increases in groundwater recharge along the crest of the ORM. Baseflow trend magnitude was uncorrelated to basin physiographic, hydrogeologic, land use/land cover, or flow duration curve characteristics. However, it was positively related to a basin's dynamic storage, particularly for basins with limited coverage of open water and wetlands. The dynamic storage approach assumes that a basin behaves as a first‐order dynamical system, and extensive open water and wetland areas in a basin may invalidate this assumption. Previous work suggested that smaller dynamic storage was linked to greater damping of temporal variations in water inputs and reduced interannual variability in streamflow regime. Storage and release of water inputs to a basin may assist in mediating baseflow response to temporal changes in regional hydroclimatology and may partly account for inter‐basin differences in that response. Such storage characteristics should be considered when forecasting the impacts of climate change on regional streamflow.

Multi-Objective Optimization for Analysis of Changing Trade-Offs in the Nepalese Water–Energy–Food Nexus with Hydropower Development

While the water–energy–food nexus approach is becoming increasingly important for more efficient resource utilization and economic development, limited quantitative tools are available to incorporate the approach in decision-making. We propose a spatially explicit framework that couples two well-established water and power system models to develop a decision support tool combining multiple nexus objectives in a linear objective function. To demonstrate our framework, we compare eight Nepalese power development scenarios based on five nexus objectives: minimization of power deficit, maintenance of water availability for irrigation to support food self-sufficiency, reduction in flood risk, maintenance of environmental flows, and maximization of power export. The deterministic multi-objective optimization model is spatially resolved to enable realistic representation of the nexus linkages and accounts for power transmission constraints using an optimal power flow approach. Basin inflows, hydropower plant specifications, reservoir characteristics, reservoir rules, irrigation water demand, environmental flow requirements, power demand, and transmission line properties are provided as model inputs. The trade-offs and synergies among these objectives were visualized for each scenario under multiple environmental flow and power demand requirements. Spatially disaggregated model outputs allowed for the comparison of scenarios not only based on fulfillment of nexus objectives but also scenario compatibility with existing infrastructure, supporting the identification of projects that enhance overall system efficiency. Though the model is applied to the Nepalese nexus from a power development perspective here, it can be extended and adapted for other problems.

Stormwater detention basin for improving road-runoff quality

Both wet and dry detention basins are commonly used for the treatment of road runoff. The basin investigated in this study was located on the eastern side of the southern expressway in Adelaide, Australia. Event mean pollutant concentrations (EMCs) and total pollutant loads were determined for the basin inflows and outflows. The water quality parameters tested included pH, conductivity, total suspended solids, total dissolved solids (TDS), total Kjeldahl nitrogen, total phosphorous, total hydrocarbons, cadmium, chromium, copper, lead, zinc and nickel. Six critical events were sampled in this manner during the course of the investigation. Total pollutant loads passing through as basin inflow were determined over the six monitored events. Comparison of basin inflow and outflow quality demonstrated that the average load reductions varied from as little as 18% for TDS up to 77% for total phosphorous and lead. While copper concentrations at the basin inflow were detected in four out of the six events, no detectable concentrations were found in the outflows. The average reductions for lead and zinc were more than 50% on more than 80% of occasions.

Predominant Bacteria Isolated from MoribundFusconaia ebenaEbonyshells Experiencing Die-Offs in Pickwick Reservoir, Tennessee River, Alabama

Mussel die-offs have been noted in recent years in Pickwick Reservoir, Tennessee River, Alabama. The primary affected species was Fusconaia ebena, but also affected to lesser degrees were Ellipsaria lineolata, Quadrula pustulosa, and Quadrula quadrula. These events were characterized by large numbers of empty shells—fresh-dead and live individuals that were presumed to be diseased because of weak and slow valve closure responses to external stimuli. Anecdotal evidence suggested the possible involvement of an etiological agent, such as a bacterial pathogen. The die-offs have occurred in Pickwick Reservoir (river miles 236–256) in sequential years during the past approximately 10 y. These timeframes have coincided with reduced basin inflows and warmer water temperatures. The majority of the moribund and freshly dead F. ebena were females possibly predisposed to infection and disease from ongoing reproductive activity. Affected and healthy-cohort mussels were collected to characterize the bacterial flora prior to, during, and after a July 2006 die-off, and during a subsequent die-off in September 2008. The numbers of total bacteria from both the 2006 and 2008 die-offs were significantly greater from the diseased specimens. For example, from the September 2008 die-off, the mean count from diseased F. ebena soft tissues was 9.75 × 106 cfu/g, which was more than 100 times greater (P = 0.025) than the mean from healthy cohorts (6.74 × 104 cfu/g). The predominant bacteria from affected F. ebena from July 2006 were Hafnia alvei and Aeromonas sobria, whereas from September 2008 the predominant bacteria were Enterobacter spp., Aeromonas schubertii, Aeromonas veronii bv. veronii, and Aeromonas veronii bv. sobria.

Synthetic Generation of Inflows in a Dam System of a Region Characterized by Extraordinary Winter Events

In this paper synthetic monthly series of net basin inflows in four dams were generated; there are correlations and crossed correlations in historic series; Svanidze’s modified method was applied, adding a different way in the random selection of years including the fact that the net basin inflows distribution was influenced by winter events. Statistics media, standard deviation, skew, autocorrelation and crossed correlation were successfully reproduced.

Impacts of climate change on lower Murray irrigation*

This article evaluates irrigated agriculture sector response and resultant economic impacts of climate change for a part of the Murray Darling Basin in Australia. A water balance model is used to predict reduced basin inflows for mild, moderate and severe climate change scenarios involving 1, 2 and 4°C warming, and predict 13, 38 and 63% reduced inflows. Impact on irrigated agricultural production and profitability are estimated with a mathematical programming model using a two‐stage approach that simultaneously estimates short and long‐run adjustments. The model accounts for a range of adaptive responses including: deficit irrigation, temporarily following of some areas, permanently reducing the irrigated area and changing the mix of crops. The results suggest that relatively low cost adaptation strategies are available for a moderate reduction in water availability and thus costs of such a reduction are likely to be relatively small. In more severe climate change scenarios greater costs are estimated. Adaptations predicted include a reduction in total area irrigated and investments in efficient irrigation. A shift away from perennial to annual crops is also predicted as the latter can be managed more profitably when water allocations in some years are very low.

The importance of the catchment area–length relationship in governing non-steady state hydrology, optimal junction angles and drainage network pattern

Analytical and numerical models of landscape evolution in general either assume steady state hydrology or use empirically based functions in the form of a drainage area power law to model runoff. A method to compute non-steady state runoff on the basis of the area–length relationship of river basins is proposed, for application in landscape evolution models. This shape-sensitive runoff function is derived analytically for environments with short storm duration (storm duration < concentration time) and it is supported numerically for environments with small storms (storm cell size < basin size). The effect of these area–length dependent relationships on drainage network development is analysed. The methodology is optimization through stream power minimization both on the level of individual junctions and on the level of the entire network. It is demonstrated that the way the area–length dependent runoff function influences the stream power of the network yields a systematic downstream increase of the network's optimal junction angles. An example for this prediction is given by a DEM-derived network from the Colorado High Plains. The inverse dependence of the runoff rate on the basin's flow path length implies that minimum total stream power is achieved through maximizing the flow path length of the system. This effect is responsible for the lateral instability of junction positions when runoff conditions shift from steady towards non-steady state. We offer this phenomenon as an explanation for the lateral instability and pronounced planation activity of semi-arid channels, especially on gently sloping piedmont surfaces. Finally throughout the paper much attention is paid to the runoff character in terms of advectivity vs. diffusivity, defined as the ratio between instream flow and lateral inflow. It is shown how optimal network pattern also relates to the advectivity/diffusivity of the runoff conditions.

Climatic variability of soil water in the American Midwest: Part 1. Hydrologic modeling

A conceptual hydrologic rainfall-runoff model that is an adaptation of the operational US National Weather Service hydrologic model is used to simulate the hydrologic processes in large basins of the US upper Mississippi region. In particular, the conceptual rainfall-runoff model is used to produce daily streamflow from daily rainfall, temperature and potential evapotranspiration input over three neighboring headwater basins that span 2° longitude by 2° latitude. When used for simulation of historical flows, the model provides a means of inference of the 40 year time series of unrecorded mesoscale soil water and actual evapo-transpiration for climate studies. In this paper we discuss issues associated with parameter estimation, the reliability and stability of parameter estimates, and the interpretation of soil water estimates. It is concluded that the conceptual hydrologic model may be used to estimate the variability of aggregate soil water over large areas of the Midwestern US provided that: (a) all significant basin inflows and outflows are accounted for; (b) model verification yields good agreement between observed and simulated flows on a daily basis. Parameter sensitivity studies showed that estimating the soil's capacity to hold water is most important for flood event prediction and flow simulation, and, for such parameters, underestimation is more critical than overestimation. Also, uncertainty associated with the parametrization of evapo-transpiration may introduce local errors in the time series of soil water estimates produced by the model. In a companion paper we present a spatio-temporal analysis of the estimated time series of soil water.