Nationwide hydrological statistics for Sweden with high resolution using the hydrological model S-HYPE

2013 ◽  
Vol 45 (3) ◽  
pp. 349-356 ◽  
Author(s):  
Marie Bergstrand ◽  
Sara-Sofia Asp ◽  
Göran Lindström
Keyword(s):  
Hydrological Model ◽  
Gumbel Distribution ◽  
Cost Effective ◽  
High Flow ◽  
Low Flow ◽  
Small Scale ◽  
Mean Flow ◽  
Low Flows ◽  
Kolmogorov Smirnov ◽  
Regulation Strategies

A first version of nationally covering hydrological statistics for Sweden based on the S-HYPE hydrological model for the period 1961–2010 is described. A key feature of the proposed method is that observed data are used as input wherever such data are available, and the model is used for interpolation in between stations. Short observation records are automatically extended by the use of the model. High flow statistics typically differed by about ±10% from observations. The corresponding number for low flow was about ±30%. High flow peaks were usually simulated slightly too low whereas low flows were too high. In a relative sense low flows were more uncertain than high flows. The mean flow was relatively certain. The annual maximum values were fitted to a Gumbel distribution, by the method of moments, for each subbasin. Flood statistics were then calculated up to a return period of 50 years. According to a Kolmogorov–Smirnov test, less than 1% of the fitted distributions were rejected. Most rejections occurred in regulated systems, due to difficulties in simulating regulation strategies, but also due to uncertainties in the precipitation input in the mountainous region. Results at small scale are very uncertain. The proposed method is a cost-effective way of calculating hydrological statistics with high spatial resolution.

scholarly journals The Cumulative Effects of Forest Disturbance and Climate Variability on Streamflow in the Deadman River Watershed

Forests ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 196 ◽  
Author(s):  
Krysta Giles-Hansen ◽  
Qiang Li ◽  
Xiaohua Wei
Keyword(s):  
Climate Variability ◽  
Forest Cover ◽  
Forest Disturbance ◽  
Climatic Variability ◽  
High Flow ◽  
The Body ◽  
Cumulative Effects ◽  
Low Flow ◽  
Mean Flow ◽  
River Watershed

Climatic variability and cumulative forest cover change are the two dominant factors affecting hydrological variability in forested watersheds. Separating the relative effects of each factor on streamflow is gaining increasing attention. This study adds to the body of literature by quantifying the relative contributions of those two drivers to the changes in annual mean flow, low flow, and high flow in a large forested snow dominated watershed, the Deadman River watershed (878 km2) in the Southern Interior of British Columbia, Canada. Over the study period of 1962 to 2012, the cumulative effects of forest disturbance significantly affected the annual mean streamflow. The effects became statistically significant in 1989 at the cumulative forest disturbance level of 12.4% of the watershed area. The modified double mass curve and sensitivity-based methods consistently revealed that forest disturbance and climate variability both increased annual mean streamflow during the disturbance period (1989–2012), with an average increment of 14 mm and 6 mm, respectively. The paired-year approach was used to further investigate the relative contributions to low and high flows. Our analysis showed that low and high flow increased significantly by 19% and 58%, respectively over the disturbance period (p < 0.05). We conclude that forest disturbance and climate variability have significantly increased annual mean flow, low flow and high flow over the last 50 years in a cumulative and additive manner in the Deadman River watershed.

scholarly journals Contrasting Differences in Responses of Streamflow Regimes between Reforestation and Fruit Tree Planting in a Subtropical Watershed of China

Forests ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 212 ◽  
Author(s):  
Zhipeng Xu ◽  
Wenfei Liu ◽  
Xiaohua Wei ◽  
Houbao Fan ◽  
Yizao Ge ◽  
...  
Keyword(s):  
Flow Regime ◽  
Fruit Tree ◽  
High Flow ◽  
Tree Planting ◽  
Low Flow ◽  
Jiangxi Province ◽  
Negative Effects ◽  
Flow Duration ◽  
Low Flows ◽  
High Flows

Fruit tree planting is a common practice for alleviating poverty and restoring degraded environment in developing countries. Yet, its environmental effects are rarely assessed. The Jiujushui watershed (261.4 km2), located in the subtropical Jiangxi Province of China, was selected to assess responses of several flow regime components on both reforestation and fruit tree planting. Three periods of forest changes, including a reference (1961 to 1985), reforestation (1986 to 2000) and fruit tree planting (2001 to 2016) were identified for assessment. Results suggest that the reforestation significantly decreased the average magnitude of high flow by 8.78%, and shortened high flow duration by 2.2 days compared with the reference. In contrast, fruit tree planting significantly increased the average magnitude of high flow by 27.43%. For low flows, reforestation significantly increased the average magnitude by 46.38%, and shortened low flow duration by 8.8 days, while the fruit tree planting had no significant impact on any flow regime components of low flows. We conclude that reforestation had positive impacts on high and low flows, while to our surprise, fruit tree planting had negative effects on high flows, suggesting that large areas of fruit tree planting may potentially become an important driver for some negative hydrological effects in our study area.

scholarly journals Long-term and Two-period Analysis of Hydrologic Conditions of the South Edisto River

2017 ◽  
pp. 13-20
Author(s):  
Rebecca W. Berzinis
Keyword(s):  
South Carolina ◽  
Low Flow ◽  
Mean Flow ◽  
South Fork ◽  
The South ◽  
Period Analysis ◽  
Daily Streamflow ◽  
Low Flows ◽  
Significant Difference

The U.S. Geological Survey (USGS) long-term daily streamflow record at station 02173000 in Bamberg County, South Carolina on the South Fork Edisto River (Latitude 33°23’35”, Longitude 81°08’00” NAD27) spans from 1932 to 2015 and was used for this study. The Nature Conservancy’s Indicators of Hydrologic Alteration (IHA) software was used to analyze the entire record of hydrologic data as ecologically relevant parameters and to categorize the flows. A two-period analysis was conducted to evaluate whether a significant difference could be observed in historic flow data from 1932–1985 (period one) compared to 1986–2015 (period two). An extreme low flow was defined as an initial low flow below 10% of daily flows for the period. Over the entire 76-year period of record, 51 years had at least one occurrence of extreme low flows. A median of 4 days per year had occurrences of extreme flows in period one in contrast to a median of 60 days per year during period two. Annual precipitation totals were not correlated with the number of days per year with extreme low flows. The two-period analysis showed significant differences between period one and period two for monthly mean flow for February, April, May, and August, as well as for 1-day and 30-day minima and maxima values. The analysis calculated the 7Q10 (the lowest stream flow for seven consecutive days that would be expected to occur once in ten years) at 4.4 cubic meters per second (cms), which was -10.9% different from the most recently published estimate. Results presented in this study have shown that spring and summer flows in the South Fork Edisto are statistically significantly lower in period two compared to period one.

scholarly journals Topography significantly influencing low flows in snow-dominated watersheds

2017 ◽  
Author(s):  
Qiang Li ◽  
Xiaohua Wei ◽  
Xin Yang ◽  
Krysta Giles-Hansen ◽  
Mingfang Zhang ◽  
...  
Keyword(s):  
Regression Models ◽  
Low Flow ◽  
Mean Flow ◽  
Slope Length ◽  
Low Flows ◽  
Slope Length Factor ◽  
High Flows ◽  
Flow Variables ◽  
Characterization Index

Abstract. Watershed topography plays an important role in determining the spatial heterogeneity of ecological, geomorphological, and hydrological processes. Few studies have quantified the role of topography on various flow variables. In this study, 28 watersheds with snow-dominated hydrological regimes were selected with daily flow records from 1989 to 1996. The watersheds are located in the Southern Interior of British Columbia, Canada and range in size from 2.6 to 1,780 km2. For each watershed, 22 topographic indices (TIs) were derived, including those commonly used in hydrology and other environmental fields. Flow variables include annual mean flow (Qmean), Q10%, Q25%, Q50%, Q75%, Q90%, and annual minimum flow (Qmin), where Qx% is defined as flows that at the percentage (x) occurred in any given year. Factor analysis (FA) was first adopted to exclude some redundant or repetitive TIs. Then, stepwise regression models were employed to quantify the relative contributions of TIs to each flow variable in each year. Our results show that topography plays a more important role in low flows than high flows. However, the effects of TIs on flow variables are not consistent. Our analysis also determines five significant TIs including perimeter, surface area, openness, terrain characterization index, and slope length factor, which can be used to compare watersheds when low flow assessments are conducted, especially in snow-dominated regions.

scholarly journals Hierarchy of climate and hydrological uncertainties in transient low flow projections

2015 ◽  
Vol 12 (12) ◽  
pp. 12649-12701 ◽  
Author(s):  
J.-P. Vidal ◽  
B. Hingray ◽  
C. Magand ◽  
E. Sauquet ◽  
A. Ducharne
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Internal Variability ◽  
General Circulation Models ◽  
Low Flow ◽  
Small Scale ◽  
Total Uncertainty ◽  
Low Flows ◽  
The Difference ◽  
Flow Variables

Abstract. This paper proposes a methodology for estimating the transient probability distribution of yearly hydrological variables conditional to an ensemble of projections built from multiple general circulation models (GCMs), multiple statistical downscaling methods (SDMs) and multiple hydrological models (HMs). The methodology is based on the quasi-ergodic analysis of variance (QE-ANOVA) framework that allows quantifying the contributions of the different sources of total uncertainty, by critically taking account of large-scale internal variability stemming from the transient evolution of multiple GCM runs, and of small-scale internal variability derived from multiple realizations of stochastic SDMs. The QE-ANOVA framework was initially developed for long-term climate averages and is here extended jointly to (1) yearly anomalies and (2) low flow variables. It is applied to better understand possible transient futures of both winter and summer low flows for two snow-influenced catchments in the southern French Alps. The analysis takes advantage of a very large dataset of transient hydrological projections that combines in a comprehensive way 11 runs from 4 different GCMs, 3 SDMs with 10 stochastic realizations each, as well as 6 diverse HMs. The change signal is a decrease in yearly low flows of around −20 % in 2065, except for the most elevated catchment in winter where low flows barely decrease. This signal is largely masked by both large- and small-scale internal variability, even in 2065. The time of emergence of the change signal on 30 year low-flow averages is however around 2035, i.e. for time slices starting in 2020. The most striking result is that a large part of the total uncertainty – and a higher one than that due to the GCMs – stems from the difference in HM responses. An analysis of the origin of this substantial divergence in HM responses for both catchments and in both seasons suggests that both evapotranspiration and snowpack components of HMs should be carefully checked for their robustness in a changed climate in order to provide reliable outputs for informing water resource adaptation strategies.

scholarly journals Mekong River flow and hydrological extremes under climate change

2016 ◽  
Vol 20 (7) ◽  
pp. 3027-3041 ◽  
Author(s):  
Long Phi Hoang ◽  
Hannu Lauri ◽  
Matti Kummu ◽  
Jorma Koponen ◽  
Michelle T. H. van Vliet ◽  
...  
Keyword(s):  
Climate Change ◽  
River Flow ◽  
High Flow ◽  
Mekong River ◽  
Low Flow ◽  
Future Climate Change ◽  
Climate Projections ◽  
Low Flows ◽  
Hydrological Extremes ◽  
Hydrological Impact

Abstract. Climate change poses critical threats to water-related safety and sustainability in the Mekong River basin. Hydrological impact signals from earlier Coupled Model Intercomparison Project phase 3 (CMIP3)-based assessments, however, are highly uncertain and largely ignore hydrological extremes. This paper provides one of the first hydrological impact assessments using the CMIP5 climate projections. Furthermore, we model and analyse changes in river flow regimes and hydrological extremes (i.e. high-flow and low-flow conditions). In general, the Mekong's hydrological cycle intensifies under future climate change. The scenario's ensemble mean shows increases in both seasonal and annual river discharges (annual change between +5 and +16 %, depending on location). Despite the overall increasing trend, the individual scenarios show differences in the magnitude of discharge changes and, to a lesser extent, contrasting directional changes. The scenario's ensemble, however, shows reduced uncertainties in climate projection and hydrological impacts compared to earlier CMIP3-based assessments. We further found that extremely high-flow events increase in both magnitude and frequency. Extremely low flows, on the other hand, are projected to occur less often under climate change. Higher low flows can help reducing dry season water shortage and controlling salinization in the downstream Mekong Delta. However, higher and more frequent peak discharges will exacerbate flood risks in the basin. Climate-change-induced hydrological changes will have important implications for safety, economic development, and ecosystem dynamics and thus require special attention in climate change adaptation and water management.

scholarly journals Hydrological Foundation as a Basis for a Holistic Environmental Flow Assessment of Tropical Highland Rivers in Ethiopia

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 547 ◽  
Author(s):  
Wubneh B. Abebe ◽  
Seifu A. Tilahun ◽  
Michael M. Moges ◽  
Ayalew Wondie ◽  
Minychl G. Derseh ◽  
...  
Keyword(s):  
Flow Regime ◽  
Current Flow ◽  
Environmental Flow ◽  
High Flow ◽  
Low Flow ◽  
Trend Test ◽  
Floodplain Wetlands ◽  
Low Flows ◽  
Flow Components ◽  
Large Floods

The sustainable development of water resources includes retaining some amount of the natural flow regime in water bodies to protect and maintain aquatic ecosystem health and the human livelihoods and wellbeing dependent upon them. Although assessment of environmental flows is now occurring globally, limited studies have been carried out in the Ethiopian highlands, especially studies to understand flow-ecological response relationships. This paper establishes a hydrological foundation of Gumara River from an ecological perspective. The data analysis followed three steps: first, determination of the current flow regime—flow indices and ecologically relevant flow regime; second, naturalization of the current flow regime—looking at how flow regime is changing; and, finally, an initial exploration of flow linkages with ecological processes. Flow data of Gumara River from 1973 to 2018 are used for the analysis. Monthly low flow occurred from December to June; the lowest being in March, with a median flow of 4.0 m3 s−1. Monthly high flow occurred from July to November; the highest being in August, with a median flow of 236 m3 s−1. 1-Day low flows decreased from 1.55 m3 s−1 in 1973 to 0.16 m3 s−1 in 2018, and 90-Day (seasonal) low flow decreased from 4.9 m3 s−1 in 1973 to 2.04 m3 s−1 in 2018. The Mann–Kendall trend test indicated that the decrease in low flow was significant for both durations at α = 0.05. A similar trend is indicated for both durations of high flow. The decrease in both low flows and high flows is attributed to the expansion of pump irrigation by 29 km2 and expansion of plantations, which resulted in an increase of NDVI from 0.25 in 2000 to 0.29 in 2019. In addition, an analysis of environmental flow components revealed that only four “large floods” appeared in the last 46 years; no “large flood” occurred after 1988. Lacking “large floods” which inundate floodplain wetlands has resulted in early disconnection of floodplain wetlands from the river and the lake; which has impacts on breeding and nursery habitat shrinkage for migratory fish species in Lake Tana. On the other hand, the extreme decrease in “low flow” components has impacts on predators, reducing their mobility and ability to access prey concentrated in smaller pools. These results serve as the hydrological foundation for continued studies in the Gumara catchment, with the eventual goal of quantifying environmental flow requirements.

scholarly journals Comparison of hydrological model structures based on recession and low flow simulations

2011 ◽  
Vol 8 (4) ◽  
pp. 6833-6866 ◽  
Author(s):  
M. Staudinger ◽  
K. Stahl ◽  
J. Seibert ◽  
M. P. Clark ◽  
L. M. Tallaksen
Keyword(s):  
Hydrological Model ◽  
Lower Layer ◽  
Model Performance ◽  
Low Flow ◽  
Model Structure ◽  
Hydrological Models ◽  
Flow Simulations ◽  
Low Flows ◽  
The Impact ◽  
Model Structures

Abstract. Low flows are often poorly reproduced by commonly used hydrological models, which are traditionally designed to meet peak flow situations. Hence, there is a need to improve hydrological models for low flow prediction. This study assessed the impact of model structure on low flow simulations and recession behaviour using the Framework for Understanding Structural Errors (FUSE). FUSE identifies the set of subjective decisions made when building a hydrological model, and provides multiple options for each modeling decision. Altogether 79 models were created and applied to simulate stream flows in the snow dominated headwater catchment Narsjø in Norway (119 km2). All models were calibrated using an automatic optimisation method. The results showed that simulations of summer low flows were poorer than simulations of winter low flows, reflecting the importance of different hydrological processes. The model structure influencing winter low flow simulations is the lower layer architecture, whereas various model structures were identified to influence model performance during summer.

scholarly journals Hierarchy of climate and hydrological uncertainties in transient low-flow projections

2016 ◽  
Vol 20 (9) ◽  
pp. 3651-3672 ◽  
Author(s):  
Jean-Philippe Vidal ◽  
Benoît Hingray ◽  
Claire Magand ◽  
Eric Sauquet ◽  
Agnès Ducharne
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Large Data ◽  
Internal Variability ◽  
General Circulation Models ◽  
Low Flow ◽  
Small Scale ◽  
Data Set ◽  
Total Uncertainty ◽  
Low Flows

Abstract. This paper proposes a methodology for estimating the transient probability distribution of yearly hydrological variables conditional to an ensemble of projections built from multiple general circulation models (GCMs), multiple statistical downscaling methods (SDMs), and multiple hydrological models (HMs). The methodology is based on the quasi-ergodic analysis of variance (QE-ANOVA) framework that allows quantifying the contributions of the different sources of total uncertainty, by critically taking account of large-scale internal variability stemming from the transient evolution of multiple GCM runs, and of small-scale internal variability derived from multiple realizations of stochastic SDMs. This framework thus allows deriving a hierarchy of climate and hydrological uncertainties, which depends on the time horizon considered. It was initially developed for long-term climate averages and is here extended jointly to (1) yearly anomalies and (2) low-flow variables. It is applied to better understand possible transient futures of both winter and summer low flows for two snow-influenced catchments in the southern French Alps. The analysis takes advantage of a very large data set of transient hydrological projections that combines in a comprehensive way 11 runs from four different GCMs, three SDMs with 10 stochastic realizations each, as well as six diverse HMs. The change signal is a decrease in yearly low flows of around −20  % in 2065, except for the more elevated catchment in winter where low flows barely decrease. This signal is largely masked by both large- and small-scale internal variability, even in 2065. The time of emergence of the change signal is however detected for low-flow averages over 30-year time slices starting as early as 2020. The most striking result is that a large part of the total uncertainty – and a higher one than that due to the GCMs – stems from the difference in HM responses. An analysis of the origin of this substantial divergence in HM responses for both catchments and in both seasons suggests that both evapotranspiration and snowpack components of HMs should be carefully checked for their robustness in a changed climate in order to provide reliable outputs for informing water resource adaptation strategies.

scholarly journals Climate change and its impacts on river discharge in two climate regions in China

2015 ◽  
Vol 12 (7) ◽  
pp. 7099-7126
Author(s):  
H. Xu ◽  
Y. Luo
Keyword(s):  
Climate Change ◽  
River Discharge ◽  
Climate Change Impacts ◽  
High Flow ◽  
Assessment Tools ◽  
Low Flow ◽  
Climate Projections ◽  
Seasonal Temperature ◽  
Mean Flow ◽  
Pronounced Increase

Abstract. Understanding the heterogeneity of climate change and its impacts on annual and seasonal discharge, and the difference between mean flow and extreme flow in different climate regions is of utmost importance to successful water management. To quantify the spatial and temporal heterogeneity of climate change impacts on hydrological processes, this study simulated river discharge in the River Huangfuchuan in semi-arid northern China and the River Xiangxi in humid southern China. We assessed the uncertainty in projected discharge for three time periods (2020s, 2050s and 2080s) using seven equally weighted GCMs for the SRES A1B scenario. Climate projections that were applied to semi-distributed hydrological models Soil Water Assessment Tools (SWAT) in both catchments showed trends toward warmer and wetter conditions, particularly for the River Huangfuchuan. Results based on seven GCMs' projections indicated −1.1 to 8.6 and 0.3 to 7.0 °C changes in seasonal temperature and −29 to 139 and −32 to 85 % changes in seasonal precipitation in River Huangfuchuan and River Xiangxi, respectively. The largest increases in temperature and precipitation in both catchments were projected in the spring and winter seasons. The main projected hydrologic impact was a more pronounced increase in annual discharge in the River Huangfuchuan than in the River Xiangxi. Most of the GCMs projected increased discharge in all seasons, especially in spring, although the magnitude of these increases varied between GCMs. Peak flows was projected to appear earlier than usual in River Huangfuchuan and later than usual in River Xiangxi. While the GCMs were fairly consistent in projecting increased extreme flows in both catchments, the increases were of varying magnitude compared to mean flows. For River Huangfuchuan in the 2080s, median flow changed from −2 to 304 %, compared to a −1 to 145 % change in high flow (Q05 exceedence threshold). For River Xiangxi, low flow (Q95 exceedence threshold) changed from −1 to 77 % and high flow changed from −1 to 62 %, while mean flow changed from −4 to 23 %. The uncertainty analysis provided an improved understanding of future hydrologic behavior in the watershed. Furthermore, this study indicated that the uncertainty constrained by GCMs was critical and should always be considered in analysis of climate change impacts and adaptation.

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