Low Flow Variability Research Articles

Lessons learned from the spatiotemporal analysis of long‐term and time‐variable young water fractions of large central European river basins

AbstractThe transit time of precipitation entering a catchment and leaving it as streamflow spatiotemporally varies according to the flow paths that precipitation takes. However, investigating influences of hydrometeorological variables and catchment characteristics on time‐variable transit times is challenging due to the complex water flow through heterogeneous landscapes. Recent studies investigated the fraction of streamflow younger than approximately 3 months (Fyw) using multi‐year data (long‐term Fyw) or one‐year calculation windows to investigate its time‐variability (time‐variable Fyw). Nonetheless, it is still unclear if the inter‐annual variability of one‐year Fyw is due to hydrological influences or its uncertainty, and no minimum time series length for the long‐term Fyw was defined yet. Here, we investigated the impact of catchment characteristics and hydrometeorological variables on the long‐term Fyw, the time‐variable Fyw, and the Fyw depending on discharge of nine river basins in Central Europe. All methods of estimating Fyw led to similar results, with Fyw depending on discharge deemed unreliable due to the monthly sampling interval of streamflow isotopes. Danube and Rhine had the lowest Fyw (0.06), medium Fyw (0.20) were found in eastern basins (e.g., Oder), and the western ones (e.g., Mosel) had the highest Fyw (0.33). Spatial analysis indicated a negative relationship between Fyw and altitude. Contradicting or lacking spatiotemporal relationships to other variables pointed to unknown influential factors controlling the runoff process. Using flow duration curves, it was found that basins with a low flow variability had low Fyw, indicating that the old water of their runoff stems from large subsurface storage. With increasing calculation window size, the within‐basin variability of time‐variable Fyw decreased. Long‐term Fyw depended on the method used to define ‘long‐term’ and the time series length and start and end date. We thus recommend future studies to calculate long‐term and time‐variable Fyw to facilitate comparability between different catchments, and to account for this source of uncertainty. Further, more studies are needed in diverse catchments to investigate the hydrometeorological impacts on Fyw and thus on runoff generation processes.

Catchment-scale hydrology limits the benefits of geomorphic complexity for instream vegetation communities

Improving instream habitat complexity is a common stream restoration approach despite often limited improvements to stream biota with catchment-scale stressors such as altered hydrology thought to be more important. Instream vegetation is a critical component of lowland stream ecosystems, providing multiple ecological benefits. Thus, we asked: How does instream vegetation respond to (1) geomorphic complexity; (2) different flow regime components; and (3) what is the relationship between geomorphic complexity and flow in driving instream vegetation?We surveyed instream vegetation and geomorphology along 23 lowland stream reaches. We investigated associations between six measures of geomorphic complexity, six flow metrics, and amphibious and aquatic vegetation richness, Shannon diversity and cover.Amphibious vegetation was negatively associated with simplified channels and increasing flood frequency. Increasing depth and width variation, and Julian day low flow variability, were positively associated with aquatic vegetation. Considering sites with complex (stable) or simplified (unstable) geomorphology separately, only vegetation at stable sites showed strong relationships to flow regime components, with variables related to flow flashiness negatively associated with both amphibious and aquatic vegetation, and Julian day low flow variability positively associated with aquatic vegetation.We identified channel complexity, variables related to flow flashiness and variation in low flow timing, as key geomorphic and flow drivers of instream vegetation, respectively. Importantly, our results suggest that instream vegetation benefits from improving geomorphic complexity are likely to be limited without also addressing altered flow regimes.

Analysis of Changes in Water Flow after Passing through the Planned Dam Reservoir Using a Mixture Distribution in the Face of Climate Change: A Case Study of the Nysa Kłodzka River, Poland

Climate change and extreme weather events have the potential to increase the occurrences of flooding and hydrological droughts. Dam reservoir operation can mitigate or aggravate this impact. This study aims to evaluate the influence of the planned Kamieniec Ząbkowicki dam reservoir on the flow patterns of the Nysa Kłodzka river in the context of changing hydrological conditions and climate change. In the study, a 40-year observational series of hydrological data was used to simulate changes in water flow through the river valley in a numerical model. This simulation was conducted both for the natural river valley and for the same river valley but with the added reservoir dam. Flow simulations revealed that dam operation increased downstream flow values, reducing variability in extreme high-flow events. Addition, the mixture log-normal distribution shows that the operation of the dam resulted in a reduction in the variability of both low flows and extreme high-flow events. Furthermore, the model illustrates that moderate-flow conditions remain relatively stable and similar before and after dam construction. The Mann–Kendall trend test, Sen slope trend test and Innovative Trend Analysis indicated that the dam had a significant impact on flow trends, reducing the negative trend. This hydrotechnical structure stabilizes and regulates flows, especially in response to climate-induced changes. These findings highlight the effectiveness of the dam in mitigating flood risk and supporting water resource management. It is essential to consider the role of the dam in adapting to changing hydrological conditions influenced by climate change. For practical application, efficient flow regulation by reservoir administration is crucial.

The persistence of snow on the ground affects the shape of streamflow hydrographs over space and time: a continental-scale analysis

Snow persistence (SP) is a widely available remotely-sensed measure of snowpack accumulation and ablation, reflecting the duration of snow presence on the ground in a given year. Available local-scale studies showed that SP is associated with the average magnitude of streamflow. However, despite the intuitive relationship between SP and catchment storage/release functioning, the spatial and temporal links between the persistence of snow on the ground and the shape and functionality of streamflow hydrographs were not studied empirically and were not generalized to diverse climatic settings. This study empirically explores the spatial and temporal links that SP has with measures of hydrograph shape and variability during low-flow and high-flow conditions across continent-wide gradients of aridity and seasonality. In arid in-phase and wet out-of-phase climates, higher SP is spatially associated with a damper (i.e., less flashy) streamflow hydrograph during low-flow and high-flow conditions. This is shown by a larger ratio of baseflow to average flow, a larger ratio of extreme low-flow to average flow, lower low-flow variability, and lower high-flow variability. While SP is spatially associated with a damped hydrograph in both arid/in-phase and wet/out-of-phase climates, this effect is stronger in the former region. For example, the size of the nonlinear impact of SP on reducing low-flow and high-flow variabilities is larger in arid in-phase climates (−7.64, −3.44, respectively) than in wet out-of-phase climates (−4.34, −2.02, respectively). Temporal analyses for “typical snow-rich” catchments show that years with relatively higher SP may lead to relatively flashier streamflow hydrographs, with lower baseflow indices, lower ratios of extreme low-flow to average flow, higher ratios of extreme high-flow to average flow and higher high-flow variability. Such results 1) demonstrate the utility of SP as a globally available descriptor of streamflow hydrograph shape and variability in a wide diversity of climatic conditions, 2) highlight that climate-driven snow loss may lead to substantial changes to hydrograph form and functionality, and 3) indicate that space-time symmetry may not be a valid assumption in hydrology.

Phenotypes of hemodynamic response to fluid challenge during anesthesia: a cluster analysis.

The fluid challenge (FC) response is usually evaluated as binary, which may be inadequate to describe the complex interactions between heart function and vascular tone response after fluid administration. We applied a clustering approach to assess the different phenotypes of cardiovascular responses to FC administration, considering the associations of all the baseline variables potentially influencing pressure and flow response to a FC. Secondarily, we evaluated the reliability of baseline hemodynamic variables in discriminating fluid responsiveness, which is considered the standard approach at the bedside. Five merged datasets from elective surgical patients receiving a FC dose ≥4 mL/kg, infused over 10 minutes. In a principal component approach, hierarchical clustering was used to define hemodynamic phenotypes of response to FC administration. Hierarchical cluster analysis with Ward linkage was carried out to define similar patient groups using the Gower distance for the mixed combination of continuous and categorical variables. No a priori criteria of fluid responsiveness were applied. The area (AUC) under the pre-FC variables' receiver operating characteristic curves (ROC) was also built to predict fluid responsiveness, defined as SVI ≥10% after FC. We analyzed 223 patients. The cluster analysis identified three hemodynamic clusters of patients: cluster 1 (98 patients, 44.0%) showed an average increase of mean arterial pressure (MAP) and Stroke Volume Index (SVI) of 17.3% (11.9-23.1) and 13.1% (0.5-23.4) at the end of FC, respectively. These patients showed baseline flow and pressure variables slightly below physiological ranges, with high pulse pressure variation (PPV). Cluster 2 (68 patients, 30.5%) showed no increase of MAP and SVI at the end of FC. These patients showed baseline flow and pressure variables within physiological ranges, with low hear rate (HR) and PPV. Cluster 3 (57 patients, 25.5%) showed no MAP increase and an SVI increase of 13.1 (2.1-19.6). These patients showed baseline pressure variables within physiological ranges, low flow variables associated to high HR and PPV. The pulse pressure variation (PPV) showed an AUC of 0.82 (0.03), with a grey zone ranging from 6% to 12%, including 86 (38.5%) patients. Clustering analysis identified three hemodynamic clusters with different response phenotypes to FC. This promising approach may enhance the ability to detect fluid responsiveness at the bedside, by considering the specific association of parameters and not the presence of a single one, such as the PPV. In fact, in our cohort the reliability of the PPV was limited, showing high sensibility and specificity only above 12% and below 6%, respectively, and a grey zone including 38.5% of patients.

Response of Low Flows of Polish Rivers to Climate Change in 1987–1989

The paper discusses changes in the low-flow regime of rivers in Poland, resulting from climate change that occurred between 1987 and 1989. The low-flow variability of rivers was measured with the use of the number of days with low flows (NDLF) below a threshold value, which was adopted as the 0.1 (10%) percentile (Q10) from the set of daily flows recorded in the multi-annual period 1951–2020 at 140 water gauges on 83 rivers. The analysis of the course of climate change over Poland showed that it was caused by macro-circulation conditions, controlled by changes in the intensity of thermohaline circulation in the North Atlantic (NA THC). Climate change consisted of a sharp increase in sunshine duration and air temperature, and a decrease in relative humidity after 1988. Along with the lack of changes in precipitation totals, characterized by a strong yearly variability, and an increase in field evaporation, it led to noticeable changes in the water balance. As a result, in 1989–2020, there was a significant increase in NDFL detected in about 2/3 of the area of Poland. With the change in the NA THC phase and the macro-circulation conditions, there was also a change in the spatial distribution of areas drained by rivers with increased NDFL. In 1951–1988, these included the eastern parts of Poland, while after the climate change (1989–2020), its western and south-western parts.

Assessment of variability among morphological and molecular characters in wild populations of mint [Mentha longifolia (L.) L.] germplasm

Mentha longifolia is an important medicinal and aromatic perennial herb that exhibits wide distribution range from sub-tropical to temperate regions. In the present study, agro-morphological traits and genetic differences in 19 different populations of M. longifolia were studied to evaluate the level and extent of its diversity. Analysis of variance (ANOVA) showed that the different phenotypic characters show considerable differences among various populations and was significant at p < 0.05. Molecular diversity analysis performed by using arbitrary amplified eleven ISSR primers generated a total of 121 amplicons that range within the size of 200–2500 base pairs (bp). Each primer on average generated 11 amplicons with percentage polymorphism being 100. The analysis of molecular variance (AMOVA) showed more (64%) among population genetic diversity and less (36%) within the populations. Greater genetic differentiation (Gst = 0.6852) among these populations occurs due to low gene flow (Nm = 0.2297) and greater habitat variability. Geographic and genetic distances were positively correlated according to Mantel’s test. In order to remove any kind of biases, we used R software to perform cluster and redundancy analysis to analyse the extent of relatedness among studied populations. In terms of morphological and molecular aspects, the populations were grouped into four and five clusters respectively based on hierarchical clustering method. The results demonstrated that M. longifolia displays a great degree of morphological and genetic variation and can be utilized in breeding, genetic improvement, and gene bank conservation programmes in future.

Impacts of El Niño–southern oscillation on global runoff: Characteristic signatures and potential mechanisms

AbstractRunoff signatures, including low flow, high flow, mean flow and flow variability, have important implications on the environment and society, predominantly through drought, flooding and water resources. Yet, the response of runoff signatures has not been previously investigated at the global scale, and the influencing mechanisms are largely unclear. Hence, this study makes a global assessment of runoff signature responses to the El Niño and La Niña phases using daily streamflow observations from 8217 gauging stations during 1960–2015. Based on the Granger causality test, we found that ~15% of the hydrological stations of multiple runoff signatures show a significant causal relationship with El Niño–southern oscillation (ENSO). The quantiles of all runoff signatures were larger during the El Niño phase than during the La Niña phase, implying that the entire flow distribution tends to shift upward during El Niño and downward during La Niña. In addition, El Niño has different effects on low and high flows: it tends to increase the low and mean flow signatures but reduces the high flow and flow variability signatures. In contrast, La Niña generally reduces all runoff signatures. We highlight that the impacts of ENSO on streamflow signatures are manifested by its effects on precipitation (P), potential evaporation (PET) and leaf area index (LAI) through ENSO‐induced atmospheric circulation changes. Overall, our study provides a comprehensive picture of runoff signature responses to ENSO, with valuable insights for water resources management and flood and drought disaster mitigation.

Influence of climate change on low flow conditions. Case study: Laborec River, eastern Slovakia

The paper deals with the long-term and seasonal variability of low flows using the example of a mountain river. The study covers the Laborec River in the eastern part of Slovakia, and the main aim of the research is to identify and establish long-term fluctuations of low flows on this river. The analysis aims to indicate trends of low flows and seasonal variability of outflows based on various measures and research methods as well as the links between them. Basic data on daily flow and precipitation series were collected from 1980 to 2019. Low flow periods were identified in relation to the fitting of the threshold level method to the 70th and 95th percentile on the flow duration curve as a constant, multi-annual cut-off (Q70%, Q95%). The longest lasting flows were those below q70%, which were determined in the shallow cut-offs that occurred for most of the year, i.e. from June to December and in January. The greatest culmination of flows below q95% was in August and September. The range of minimal unit outflow is the smallest in the summer-autumn period and results from long periods without precipitation and with increased evapotranspiration. The highest range of unit outflow was recorded from December to April. Knowledge of low river flows should be one of the important elements of advanced planning, which in the future may help to reduce conflicts between water users during the peak demand period.

Evaluating low flow patterns, drivers and trends in the Delaware River Basin

In the humid, temperate Delaware River Basin (DRB) where water availability is generally reliable, summer low flows can cause competition between various human and ecological water uses. As temperatures continue to rise, population increases and development expands, it is critical to understand historical low flow variability to anticipate and plan for future flows. Using a sample of 325 U.S. Geological Survey gages, we evaluated spatial patterns in several low flow metrics, the biophysical and climatic drivers of these metrics, and trends in low flows for two periods: 1950–2018 and 1980–2018. We calculated the annual 7-day low flow and date, low flow deficit as the departure below a long-term daily flow threshold and the number of discrete low flow periods below this threshold. We also aggregated several climate metrics to watershed scale and used existing watershed properties quantifying land cover, topography, soils, geology, and human activity. Random forest models were used to assess the hierarchy of variable importance in explaining mean-annual low flow variability for each low flow metric using all gages. We find muted regional patterns in mean-annual low flow and low flow variability, likely due to the myriad of anthropogenic, landscape, and flow modifications that obscure flow regimes from their natural characteristics. In contrast, individual years show markedly different spatial patterns in low flow magnitude and severity. Coincident with increases in precipitation, 7-day low flows have generally increased and low flow deficits decreased for both 1950–2018 and 1980–2018 periods. However, 7-day low flows have decreased in the Coastal Plain physiographic province where water use and impervious area have increased in recent decades, highlighting the effects of land and water management on low flows. With continued change expected in the DRB, additional research needs are highlighted to enable estimation of future low flows and to plan for periods of prolonged low flow.

Changing Low Flow and Streamflow Drought Seasonality in Central European Headwaters

In the context of the ongoing climate warming in Europe, the seasonality and magnitudes of low flows and streamflow droughts are expected to change in the future. Increasing temperature and evaporation rates, stagnating precipitation amounts and decreasing snow cover will probably further intensify the summer streamflow deficits. This study analyzed the long-term variability and seasonality of low flows and streamflow droughts in fifteen headwater catchments of three regions within Central Europe. To quantify the changes in the low flow regime of selected catchments during the 1968–2019 period, we applied the R package lfstat for computing the seasonality ratio (SR), the seasonality index (SI), mean annual minima, as well as for the detection of streamflow drought events along with deficit volumes. Trend analysis of summer minimum discharges was performed using the Mann–Kendall test. Our results showed a substantial increase in the proportion of summer low flows during the analyzed period, accompanied with an apparent shift in the average date of low flow occurrence towards the start of the year. The most pronounced seasonality shifts were found predominantly in catchments with the mean altitude 800–1000 m.a.s.l. in all study regions. In contrast, the regime of low flows in catchments with terrain above 1000 m.a.s.l. remained nearly stable throughout the 1968–2019 period. Moreover, the analysis of mean summer minimum discharges indicated a much-diversified pattern in behavior of long-term trends than it might have been expected. The findings of this study may help identify the potentially most vulnerable near-natural headwater catchments facing worsening summer water scarcity.

Both Forest Harvesting and Hydropower Dams Yielded Negative Impact on Low Flow Regimes in the Zagunao River Watershed, Southwest China

Forest harvesting and hydropower dams can significantly affect flow regimes (magnitude, timing, duration, frequency, and variability), resulting in changes in degraded aquatic ecosystems and unstable water supply. Despite numerous studies on the effects of forest harvesting on mean flows, the impact of forest harvesting on flow regimes has been less investigated. A great difficulty lies in separating the hydrological effect of forest harvesting from that of climate variability and other watershed disturbances such hydropower dams. In this study, the Upper Zagunao River watershed (2242 km2) was selected as an example to provide a quantitative assessment of the effects of forest harvesting and hydropower dams on low flow regimes. The key findings include: (1) Forest harvesting led to a significant reduction in the magnitude and return period of low flows, and a significant increment in the variability and duration of low flows; (2) the recovery of low flow regimes occurred 40 years after forest harvesting as forest recovery processed; and (3) hydropower dams caused significant impact on all components of low flow regimes, e.g., a reduction in the magnitude, return period, and timing of low flows, and an increment in the variability and duration of low flows. Our findings highlight the negative impact of both forest harvesting and hydropower dams on low flow regimes in the Upper Zagunao River watershed. A watershed management strategy for offsetting the negative effect of hydropower dams on low flow regimes by restoring hydrological functions of subalpine forests is highly recommended in subalpine watersheds of the Upper Yangtze River.

Evolution of streamflow patterns in Goulburn-Broken catchment during 1884–2018 and its implications for floodplain management

Abstract Development of water resources infrastructure largely decoupled floodplains and wetlands from rivers due to alteration of streamflow patterns. However, there is limited understanding of undesirable changes in streamflow patterns due to flow regulation. This study aimed to examine effects of flow regulation and rainfall variation on: 1) long-term flow, 2) upstream and downstream flow, and 3) seasonal flow patterns in the Goulburn-Broken catchment in Victoria, Australia, and discuss the implications for floodplains and wetlands. The non-parametric Mann-Kendall test and other statistical methods were used to analyse changes in long-term (1884–2018), upstream and downstream (1977–2018), and seasonal flow patterns of Goulburn River. Results showed that average annual discharge of Goulburn River decreased over 59% during the post-change period (1957–2018) as compared to pre-change (1884–1956) discharge mainly due to flow regulation and diversion (>86%). This reduced frequency of overbank flows from once every 1.6 years in the pre-change period to once every 5 years in the post-change period. This extended disconnection of floodplains from the Goulburn River has had detrimental effects on biota. Finally, generation of adequate overbank flows and maintaining natural variability of high and low flows with a riverine functional flow approach is recommended to rejuvenate floodplains and wetlands.

On the Effect of Nonlinear Recessions on Low Flow Variability: Diagnostic of an Analytical Model for Annual Flow Duration Curves

AbstractPredicting the proportion of the water year a given stream will remain at or above various flow thresholds is critically important for making sound water management decisions. Flow duration curves (FDCs) succinctly capture this information using all data available over some historical period, while annual flow duration curves (AFDCs) instead use data from each individual water year. Analyzing the population of AFDCs, and in particular the tails of this distribution, can allow water managers to better prepare for years with extreme streamflow conditions. However, long time series of observations are necessary to capture interannual streamflow variations and are problematic to obtain in rapidly changing and poorly gauged catchments. By incorporating a process‐based model to construct AFDCs based on daily rainfall statistics and flow recession characteristics, the proposed approach is a first step toward addressing this challenge. Results indicate that prediction performance varies substantially across flow quantiles and that the current model fails to properly capture the interannual variability of low flows. Numerical analyses attributed these errors to nonlinearity in storage‐discharge relation, rather than cross‐scale streamflow correlations and non‐Poissonian rainfall, explaining the origin of commonly observed heavy‐tailed behavior in low flow quantiles. We present a case study on hydroelectric power generation, showing that faithfully capturing both interannual streamflow variability and recession nonlinearity has important implications for installation profitability.

Effects of adiabatic index on the sonic surface and time variability of low angular momentum accretion flows

We study the role of adiabatic index in determining the critical points in the transonic low angular momentum accretion flow onto a black hole. We present the general relativistic 2D hydrodynamic simulations of axisymmetric, inviscid accretion flows in a fixed Kerr black hole gravitational field. A relativistic fluid where its bulk velocity is comparable to the speed of light, flowing in the accretion disk very close to the horizon can be described by an adiabatic index of 4/3 < {\gamma} < 5/3. The time dependent evolution of the shock position and respective effects on mass accretion rate and oscillation frequency with varying adiabatic index is discussed in the context of the observed microquasars.

Modeling Habitat Suitability for the Western Ridged Mussel (Gonidea angulata Lea) in Okanagan Lake, British Columbia, Canada

Once common throughout surface waters west of the Rocky Mountains, the western ridged mussel (Gonidea angulata Lea) has been extirpated throughout much of its range (Blevins et al. 2017). This species is currently listed as endangered in Canada (COSEWIC 2010), where its northernmost occurrences are thought to be in Okanagan Lake within the southern interior of British Columbia. Recovery plans are legally required for listed species; but for G. angulata, recovery planning is a challenge as little is known about its habitat requirements, particularly within lakes. To be able to recover G. angulata throughout its historic range, we must study lentic as well as lotic habitats. We developed habitat suitability models for G. angulata in Okanagan Lake using snorkel survey data, habitat data, and two complementary classification methods based on the RandomForest algorithm. Both classification methods ranked the top four predictor variables as effective fetch between 1 and 2.25 km, medium-high embeddedness of substrates (25 to > 75%), high proportion of sand in the substrate, and low slope (0–20%). In comparison, G. angulata habitat in river systems have been described as having low sediment accumulation, boulders that offer refuge, low flow variability, and bank stability. These findings suggest that the drivers for G. angulata distribution in lakes are similar to those in rivers, although predictor variables themselves may vary. This is important because simply using predictor variables from lotic systems would not correctly predict G. angulata occurrence in lakes, demonstrating the importance of this lake-specific investigation.

The role of cross-correlation between precipitation and temperature in basin-scale simulations of hydrologic variables

Uncertainty in climate forcings causes significant uncertainty in estimating streamflow and other land-surface fluxes in hydrologic model simulations. Earlier studies primarily analyzed the importance of reproducing cross-correlation between precipitation and temperature (P-T cross-correlation) using various downscaling and weather generator schemes, leaving out how such biased estimates of P-T cross-correlation impact streamflow simulation and other hydrologic variables. The current study investigates the impacts of biased P-T cross-correlation on hydrologic variables using a fully coupled hydrologic model (Penn-state Integrated Hydrologic Model, PIHM). For this purpose, a synthetic weather generator was developed to generate multiple realizations of daily climate forcings for a specified P-T cross-correlation. Then, we analyzed how reproducing/neglecting P-T cross-correlation in climate forcings affect the accuracy of a hydrologic simulation. A total of 50 synthetic data sets of daily climate forcings with different P-T cross-correlation were forced into to estimate streamflow, soil moisture, and groundwater level under humid (Haw River basin in NC, USA) and arid (Lower Verde River basin in AZ, USA) hydroclimate settings. Results show that climate forcings reproducing the P-T cross-correlation yield lesser root mean square errors in simulated hydrologic variables (primarily on the sub-surface variables) as compared to climate forcings that neglect the P-T cross-correlation. Impacts of P-T cross-correlation on hydrologic simulations were remarkable to low flow and sub-surface variables whereas less significant to flow variables that exhibit higher variability. We found that hydrologic variables with lower internal variability (for example: groundwater and soil-moisture depth) are susceptible to the bias in P-T cross-correlation. These findings have potential implications in using univariate linear downscaling techniques to bias-correct GCM forcings, since univariate linear bias-correction techniques reproduce the GCM estimated P-T cross-correlation without correcting the bias in P-T cross-correlation.

Spatio‐temporal variability in contributions to low flows in the high Alpine Poschiavino catchment

AbstractIn order to predict streamflow accurately during extended dry periods, we need to understand the spatial variability of low flows and the extent to which it is affected by the spatial organization and drainage of catchment subsurface storage areas. This is especially true in Alpine catchments with widely varying topography, lithology, sediment deposits, and soil properties. Field measurements in the Poschiavino catchment in southern Switzerland, during a winter recession period without recharge, provided a unique opportunity to demonstrate the connections between subsurface storage areas, low flows, and their variability. We measured discharge in four nested sub‐catchments during seven field campaigns in the winter of 2013–2014. We analysed stream water electrical conductivity (EC) and water chemistry to identify the areas contributing to low‐flow discharge and estimated their contributions. Sediment cover type and thickness were mapped using a recently developed tool for geomorphology‐based storage classification of mountainous terrain, to determine the physical properties of the subsurface storage areas contributing to low‐flow discharge. Recession analyses combined with water chemistry data allowed the detection of different drainage timescales and the estimation of storage potential of the unconsolidated (Quaternary) deposits. We found substantial spatial variation in storage depletion between the sub‐catchments, ranging from 54 mm to 200 mm for the four‐month monitoring period. Variability in low‐flow contributions from different catchments and different recession behavior could be related to the differences in the estimated storage potential. For some point sources, we could quantify the contributing area and thus quantify low flows at the hillslope scale. Overall, the low‐flow variability is mostly related to the fraction of precipitation that recharges subsurface storage areas and to the properties influencing their drainage. To capture these processes, we suggest low‐flow geomorphological mapping approaches that consider not only morphometric (shape of the landscape) and geologic (properties of the bedrock) controls but also the water storage potential of debris cover and weathered rock.

Recent trends in the low-flow variability in Romania

Recent trends in the low-flow variability in Romania

Entropy analysis for spatiotemporal variability of seasonal, low, and high streamflows

Climate variability and change lead to changes in spatiotemporal variability in streamflow, which complicate management of water resources. This problem is particularly critical for small island regions, such as the small island state of Tasmania in Australia. In Tasmania, water resources play an important role for hydro-electricity generation and agriculture, whose water demands are highly seasonal in nature. However, identification of possible changes in seasonal streamflow variability can be difficult due to the inherent uncertainties resulting from the seasonal variability of climate. Entropy theory can provide a suitable framework to analyze the spatiotemporal variability in streamflows. In this study, we propose to use Shannon entropy with Chao–Shen estimator to assess the space–time variability of seasonal as well as low and high streamflows (i.e., 25th and 75th percentiles of streamflows) in Tasmania. In conjunction with isoentropy maps that depict spatial variability of seasonal, low, and high flows, trend detection analyses are performed to evaluate the significance of temporal variability. The results indicate that there is a distinct pattern between summer–autumn and winter–spring streamflow entropies, with the entropies of streamflows observed in winter–spring found to be higher than those observed in summer–autumn. The results also suggest that the spatial variability of uncertainty in streamflow is closely associated with the spatial pattern of rainfall in Tasmania. Finally, statistically insignificant trends in entropies of seasonal, low, and high streamflows possibly imply consistency in cyclic patterns and underlying probability distributions of these streamflows.