SWOT Mission Capabilities for the Prediction of Flow-Duration Curves: A Global Scale Assessment

2020 ◽  
Author(s):  
Alessio Domeneghetti ◽  
Alessio Pugliese ◽  
Attilio Castellarin ◽  
Armando Brath
Keyword(s):  
Hydrological Regime ◽  
Surface Characteristics ◽  
Flow Regimes ◽  
Time Frame ◽  
Global Scale ◽  
Random Errors ◽  
Satellite Mission ◽  
Flow Duration ◽  
Original Dataset ◽  
Flow Duration Curves

<p>The Surface Water and Ocean Topography (SWOT) satellite mission will provide high-resolution estimates of riverine water surface characteristics, such as river surface width, elevation and slope. Those parameters will enable a global estimation of river discharges flowing into rivers wider than 100 m, with a temporal resolution varying from 3 to 10 days, in dependence of latitude. Although errors on streamflow estimates are expected to be highly dependent on flow regimes and geomorphic conditions, the mission potential on providing insights on the hydrological regime of inland rivers is still not fully investigated. To this end, in this study we propose a comparison of remotely sensed and empirical period-of-record flow-duration curves (FDCs) on worldwide basis. We used the Global Runoff Data Centre (GRDC) dataset, the world largest and freely available source of streamflow data. We filtered the original dataset by selecting only those sites that matched 2 criteria: river width larger than 100 m and streamflow time series longer than 10 years of continuous daily discharges. Such dataset query resulted in 1200 gauged river cross-sections readily available to be used for our purposes. To simulate SWOT observations, each record has been reduced following 4 different sampling scenarios, i.e. 3, 5, 7, and 10 days interval for a 3-year moving time-frame (i.e., SWOT mission lifetime). We then corrupted gauged data with random errors sampled from a gaussian distribution having zero mean and 30% standard deviation. For each site, we obtained a set of SWOT simulated FDCs to compare with their empirical counterparts. We found that tropical and temperate climates deliver good estimates throughout flow regimes, whereas, mostly arid climates may have higher uncertainties, especially for high- and low-flows.</p>

scholarly journals Future shifts in extreme flow regimes in Alpine regions

2019 ◽  
Vol 23 (11) ◽  
pp. 4471-4489 ◽  
Author(s):  
Manuela I. Brunner ◽  
Daniel Farinotti ◽  
Harry Zekollari ◽  
Matthias Huss ◽  
Massimiliano Zappa
Keyword(s):  
Time Series ◽  
Frequency Analysis ◽  
Flow Regimes ◽  
High Flow ◽  
Discharge Time ◽  
Climate Conditions ◽  
Flow Duration ◽  
High Flows ◽  
Flow Duration Curves ◽  
Extreme Flow

Abstract. Extreme low and high flows can have negative economic, social, and ecological effects and are expected to become more severe in many regions due to climate change. Besides low and high flows, the whole flow regime, i.e., annual hydrograph comprised of monthly mean flows, is subject to changes. Knowledge on future changes in flow regimes is important since regimes contain information on both extremes and conditions prior to the dry and wet seasons. Changes in individual low- and high-flow characteristics as well as flow regimes under mean conditions have been thoroughly studied. In contrast, little is known about changes in extreme flow regimes. We here propose two methods for the estimation of extreme flow regimes and apply them to simulated discharge time series for future climate conditions in Switzerland. The first method relies on frequency analysis performed on annual flow duration curves. The second approach performs frequency analysis of the discharge sums of a large set of stochastically generated annual hydrographs. Both approaches were found to produce similar 100-year regime estimates when applied to a data set of 19 hydrological regions in Switzerland. Our results show that changes in both extreme low- and high-flow regimes for rainfall-dominated regions are distinct from those in melt-dominated regions. In rainfall-dominated regions, the minimum discharge of low-flow regimes decreases by up to 50 %, whilst the reduction is 25 % for high-flow regimes. In contrast, the maximum discharge of low- and high-flow regimes increases by up to 50 %. In melt-dominated regions, the changes point in the other direction than those in rainfall-dominated regions. The minimum and maximum discharges of extreme regimes increase by up to 100 % and decrease by less than 50 %, respectively. Our findings provide guidance in water resource planning and management and the extreme regime estimates are a valuable basis for climate impact studies. Highlights Estimation of 100-year low- and high-flow regimes using annual flow duration curves and stochastically simulated discharge time series Both mean and extreme regimes will change under future climate conditions. The minimum discharge of extreme regimes will decrease in rainfall-dominated regions but increase in melt-dominated regions. The maximum discharge of extreme regimes will increase and decrease in rainfall-dominated and melt-dominated regions, respectively.

scholarly journals Flow Duration Curves from Surface Reflectance in the Near Infrared Band

2021 ◽  
Vol 11 (8) ◽  
pp. 3458
Author(s):  
Angelica Tarpanelli ◽  
Alessio Domeneghetti
Keyword(s):  
Mississippi River ◽  
Near Infrared ◽  
Hydrological Regime ◽  
Physical Parameters ◽  
Surface Reflectance ◽  
Infrared Band ◽  
Earth Observations ◽  
Flow Duration ◽  
Specific Discharge ◽  
Flow Duration Curves

Flow duration curve (FDC) is a cumulative frequency curve that shows the percent of time a specific discharge has been equaled or exceeded during a particular period of time at a given river location, providing a comprehensive description of the hydrological regime of a catchment. Thus, relying on historical streamflow records, FDCs are typically constrained to gauged and updated ground stations. Earth Observations can support our monitoring capability and be considered as a valuable and additional source for the observation of the Earth’s physical parameters. Here, we investigated the potential of the surface reflectance in the Near Infrared (NIR) band of the MODIS 500 m and eight-day product, in providing reliable FDCs along the Mississippi River. Results highlight the capability of NIR bands to estimate the FDCs, enabling a realistic reconstruction of the flow regimes at different locations. Apart from a few exceptions, the relative Root Mean Square Error, rRMSE, of the discharge value in validation period ranges from 27–58% with higher error experienced for extremely high flows (low duration), mainly due to the limit of the sensor to penetrate the clouds during the flood events. Due to the spatial resolution of the satellite product higher errors are found at the stations where the river is narrow. In general, good performances are obtained for medium flows, encouraging the use of the satellite for the water resources management at ungauged river sites.

STOCHASTIC FLOW DURATION CURVES FOR EVALUATION OF FLOW REGIMES IN RIVERS

2003 ◽  
Vol 39 (1) ◽  
pp. 47-58 ◽  
Author(s):  
Hironobu Sugiyama ◽  
Varawoot Vudhivanich ◽  
Andrew C. Whitaker ◽  
Kosit Lorsirirat
Keyword(s):  
Flow Regimes ◽  
Stochastic Flow ◽  
Flow Duration ◽  
Flow Duration Curves

Testing the potential of Near Infrared band for the estimation of flow duration curves

2021 ◽  
Author(s):  
Angelica Tarpanelli ◽  
Alessio Domeneghetti
Keyword(s):  
Satellite Data ◽  
River Discharge ◽  
Near Infrared ◽  
Hydrological Regime ◽  
High Temporal Resolution ◽  
Physical Parameters ◽  
Time Duration ◽  
Flow Duration ◽  
Flow Duration Curves ◽  
Discharge Estimation

<p>The flow duration curves (FDCs) represent the relationship between river discharges observed at a given cross-section and the percent of time (duration) they are exceeded, or equaled, over an historical reference period. The FDC provides a comprehensive description of the hydrological regime of a catchment and its knowledge is fundamental for many water-related applications (e.g., water management and supply, human and irrigation purposes, etc.). However, relying on historical streamflow records, FDCs are constrained to gauged stations and, thus, typically available for a small portion of the world’s rivers. In this context, satellite data can support our monitoring capability and being considered as a valuable and additional source for the observation of the Earth’s physical parameters.</p><p>Recent studies demonstrated the efficiency of the surface reflectance in the Near Infrared (NIR) for the river discharge estimation. The high temporal resolution (almost daily), the high-medium spatial resolution (10 - 300 m) and the global coverage observing in a continuous way the range of 90-90 latitude encourage to extend the use of the NIR bands also for hydrology-related purposes. Here we tested the potential of MODIS 500 m 8-day product in providing discharge estimation for the construction of FDCs at 13 sites along the Mississippi River. In particular, this work considers records of river discharge from January 2003 to December 2019, calibrating and validating the FDCs for a period of 13 and 4 years, respectively. The aim is to test the ability to estimate the hydrological regime of a river at a given location using satellite data.</p><p>Results highlight the potential of the NIR bands to provide a realistic reconstruction of the flow regimes at different locations. Higher errors are obtained at the FDC tails, where extremely high or low flows have a low likelihood of being observed, mainly due to the limit of the sensor to see below the clouds during the flood events or to capture small water body. Better performances are obtained for the medium flows, encouraging the use of the satellite for the water resources management at ungauged river sites.</p>

Predicting annual and long-term flow-duration curves in ungauged basins

2007 ◽  
Vol 30 (4) ◽  
pp. 937-953 ◽  
Author(s):  
Attilio Castellarin ◽  
Giorgio Camorani ◽  
Armando Brath
Keyword(s):  
Ungauged Basins ◽  
Flow Duration ◽  
Flow Duration Curves

scholarly journals Exploring the physical controls of regional patterns of flow duration curves – Part 4: A synthesis of empirical analysis, process modeling and catchment classification

2012 ◽  
Vol 16 (11) ◽  
pp. 4483-4498 ◽  
Author(s):  
M. Yaeger ◽  
E. Coopersmith ◽  
S. Ye ◽  
L. Cheng ◽  
A. Viglione ◽  
...  
Keyword(s):  
Low Flow ◽  
Middle Portion ◽  
Qualitative Synthesis ◽  
Statistical Parameters ◽  
Regional Patterns ◽  
Flow Duration ◽  
Analysis Process ◽  
Wide Range ◽  
Physical Controls ◽  
Flow Duration Curves

Abstract. The paper reports on a four-pronged study of the physical controls on regional patterns of the flow duration curve (FDC). This involved a comparative analysis of long-term continuous data from nearly 200 catchments around the US, encompassing a wide range of climates, geology, and ecology. The analysis was done from three different perspectives – statistical analysis, process-based modeling, and data-based classification – followed by a synthesis, which is the focus of this paper. Streamflow data were separated into fast and slow flow responses, and associated signatures, and both total flow and its components were analyzed to generate patterns. Regional patterns emerged in all aspects of the study. The mixed gamma distribution described well the shape of the FDC; regression analysis indicated that certain climate and catchment properties were first-order controls on the shape of the FDC. In order to understand the spatial patterns revealed by the statistical study, and guided by the hypothesis that the middle portion of the FDC is a function of the regime curve (RC, mean within-year variation of flow), we set out to classify these catchments, both empirically and through process-based modeling, in terms of their regime behavior. The classification analysis showed that climate seasonality and aridity, either directly (empirical classes) or through phenology (vegetation processes), were the dominant controls on the RC. Quantitative synthesis of these results determined that these classes were indeed related to the FDC through its slope and related statistical parameters. Qualitative synthesis revealed much diversity in the shapes of the FDCs even within each climate-based homogeneous class, especially in the low-flow tails, suggesting that catchment properties may have become the dominant controls. Thus, while the middle portion of the FDC contains the average response of the catchment, and is mainly controlled by climate, the tails of the FDC, notably the low-flow tails, are mainly controlled by catchment properties such as geology and soils. The regime behavior explains only part of the FDC; to gain a deeper understanding of the physical controls on the FDC, these extremes must be analyzed as well. Thus, to completely separate the climate controls from the catchment controls, the roles of catchment properties such as soils, geology, topography etc. must be explored in detail.

Annual flow duration curves assessment in ephemeral small basins

2014 ◽  
Vol 519 ◽  
pp. 258-270 ◽  
Author(s):  
D. Pumo ◽  
F. Viola ◽  
G. La Loggia ◽  
L.V. Noto
Keyword(s):  
Flow Duration ◽  
Flow Duration Curves

scholarly journals Exploring the physical controls of regional patterns of flow duration curves – Part 1: Insights from statistical analyses

2012 ◽  
Vol 16 (11) ◽  
pp. 4435-4446 ◽  
Author(s):  
L. Cheng ◽  
M. Yaeger ◽  
A. Viglione ◽  
E. Coopersmith ◽  
S. Ye ◽  
...  
Keyword(s):  
Gamma Distribution ◽  
Classical Method ◽  
Regional Patterns ◽  
Flow Duration ◽  
Total Runoff ◽  
Time Symmetry ◽  
Physical Controls ◽  
Flow Duration Curves ◽  
Predictions In Ungauged Basins ◽  
Fast Flow

Abstract. The flow duration curve (FDC) is a classical method used to graphically represent the relationship between the frequency and magnitude of streamflow. In this sense it represents a compact signature of temporal runoff variability that can also be used to diagnose catchment rainfall-runoff responses, including similarity and differences between catchments. This paper is aimed at extracting regional patterns of the FDCs from observed daily flow data and elucidating the physical controls underlying these patterns, as a way to aid towards their regionalization and predictions in ungauged basins. The FDCs of total runoff (TFDC) using multi-decadal streamflow records for 197 catchments across the continental United States are separated into the FDCs of two runoff components, i.e., fast flow (FFDC) and slow flow (SFDC). In order to compactly display these regional patterns, the 3-parameter mixed gamma distribution is employed to characterize the shapes of the normalized FDCs (i.e., TFDC, FFDC and SFDC) over the entire data record. This is repeated to also characterize the between-year variability of "annual" FDCs for 8 representative catchments chosen across a climate gradient. Results show that the mixed gamma distribution can adequately capture the shapes of the FDCs and their variation between catchments and also between years. Comparison between the between-catchment and between-year variability of the FDCs revealed significant space-time symmetry. Possible relationships between the parameters of the fitted mixed gamma distribution and catchment climatic and physiographic characteristics are explored in order to decipher and point to the underlying physical controls. The baseflow index (a surrogate for the collective impact of geology, soils, topography and vegetation, as well as climate) is found to be the dominant control on the shapes of the normalized TFDC and SFDC, whereas the product of maximum daily precipitation and the fraction of non-rainy days was found to control the shape of the FFDC. These relationships, arising from the separation of total runoff into its two components, provide a potential physical basis for regionalization of FDCs, as well as providing a conceptual framework for developing deeper process-based understanding of the FDCs.

Alternative for the regionalization of flow duration curves

2019 ◽  
Vol 7 (3) ◽  
pp. 198-206 ◽  
Author(s):  
Raimunda da Silva e Silva ◽  
Claudio José Cavalcante Blanco ◽  
Francisco Carlos Lira Pessoa
Keyword(s):  
Flow Duration ◽  
Flow Duration Curves
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