Where does all the water go? Partitioning water transmission losses in a data-sparse, multi-channel and low-gradient dryland river system using modelling and remote sensing

Jarihani, Ben; Larsen, Joshua; Callow, Nik; McVicar, Tim R.; Johansen, Kasper

doi:10.1016/j.jhydrol.2015.08.030

Cited by 53 publications

(42 citation statements)

References 97 publications

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“…Minor (<5 mm) rainfall events are lower than total transmission losses (infiltration, evaporation and terminal water storage) of catchments and never reach catchment outlets [67]. This finding agrees with results of Roth [21] that showed relatively high infiltration rates at the beginning of events for this area using a rainfall simulator in small plots.…”

Section: Water Balance Assessmentsupporting

confidence: 90%

Characterisation of Hydrological Response to Rainfall at Multi Spatio-Temporal Scales in Savannas of Semi-Arid Australia

Jarihani

Sidle

Bartley

et al. 2017

Water

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Abstract:Rainfall is the main driver of hydrological processes in dryland environments and characterising the rainfall variability and processes of runoff generation are critical for understanding ecosystem function of catchments. Using remote sensing and in situ data sets, we assess the spatial and temporal variability of the rainfall, rainfall-runoff response, and effects on runoff coefficients of antecedent soil moisture and ground cover at different spatial scales. This analysis was undertaken in the Upper Burdekin catchment, northeast Australia, which is a major contributor of sediment and nutrients to the Great Barrier Reef. The high temporal and spatial variability of rainfall are found to exert significant controls on runoff generation processes. Rainfall amount and intensity are the primary runoff controls, and runoff coefficients for wet antecedent conditions were higher than for dry conditions. The majority of runoff occurred via surface runoff generation mechanisms, with subsurface runoff likely contributing little runoff due to the intense nature of rainfall events. MODIS monthly ground cover data showed better results in distinguishing effects of ground cover on runoff that Landsat-derived seasonal ground cover data. We conclude that in the range of moderate to large catchments (193-36,260 km 2 ) runoff generation processes are sensitive to both antecedent soil moisture and ground cover. A higher runoff-ground cover correlation in drier months with sparse ground cover highlighted the critical role of cover at the onset of the wet season (driest period) and how runoff generation is more sensitive to cover in drier months than in wetter months. The monthly water balance analysis indicates that runoff generation in wetter months (January and February) is partially influenced by saturation overland flow, most likely confined to saturated soils in riparian corridors, swales, and areas of shallow soil. By March and continuing through October, the soil "bucket" progressively empties by evapotranspiration, and Hortonian overland flow becomes the dominant, if not exclusive, flow generation process. The results of this study can be used to better understand the rainfall-runoff relationships in dryland environments and subsequent exposure of coral reef ecosystems in Australia and elsewhere to terrestrial runoff.

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Section: Water Balance Assessmentsupporting

confidence: 90%

Characterisation of Hydrological Response to Rainfall at Multi Spatio-Temporal Scales in Savannas of Semi-Arid Australia

Jarihani

Sidle

Bartley

et al. 2017

Water

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show abstract

“…Minor (< 5 mm) rainfall events are lower than total transmission losses (infiltration, evaporation and terminal water storage) of catchments and never reach catchment outlets [71]. This finding agrees with results of Roth [21] that showed relatively high infiltration rates at the beginning of events for this area using a rainfall simulator in small plots.…”

Section: Changes In Soil Moisture Conditionssupporting

confidence: 90%

Characterisation of Hydrological Response to Rainfall at Multi Spatio-Temporal Scales in Savannas of Semi-Arid Australia

Jarihani¹,

Sidle²,

Bartley³

et al. 2017

Preprint

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Abstract:Rainfall is the main driver of hydrological processes in dryland environments and characterising the rainfall variability and processes of runoff generation are critical for understanding ecosystem function of catchments. Using remote sensing and in situ data sets, we assess the spatial and temporal variability of the rainfall, rainfall-runoff response, and effects of antecedent soil moisture and ground cover at different spatial scales on runoff coefficients in the Upper Burdekin catchment, northeast Australia, which is a major contributor of sediment and nutrients to the Great Barrier Reef. The high temporal and spatial variability of rainfall exerts significant controls on runoff generation processes. Rainfall amount and intensity are the primary runoff controls, and runoff coefficients for wet antecedent conditions were higher than for dry conditions. The majority of runoff occurred via surface runoff generation mechanisms, with subsurface runoff likely contributing little runoff due to the intense nature of rainfall events. At annual to seasonal temporal scales and for relatively large catchments, we could not detect a significant effect of ground cover on runoff. We conclude that in the range of moderate to large catchments (193 -36,260 km 2 ) runoff generation processes are sensitive to both antecedent soil moisture and ground cover. A higher runoff-ground cover correlation in drier months with sparse ground cover highlighted the critical role of cover at the onset of the wet season and how runoff generation is more sensitive to cover in drier months than in wetter months. The monthly water balance analysis indicates that runoff generation in wetter months (January and February) is partially influenced by saturation overland flow, most likely confined to saturated soils in riparian corridors, swales, and areas of shallow soil. By March and continuing through October, the soil 'bucket' progressively empties by evapotranspiration, and Hortonian overland flow becomes the dominant, if not exclusive, flow generation process. The results of this study can be used to better understand the rainfall-runoff relationships in dryland environments and subsequent exposure of coral reef ecosystems in Australia and elsewhere to terrestrial runoff.

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“…In addition, runoff generation mechanisms are strongly nonlinear and depend too much on storage processes, which are parameterized with large uncertainty (Gudmundsson et al, 2012). For instance, there is little knowledge about the influence of transmission losses, their partitioning between its main components (e.g., infiltration/evaporation from channels or floodplains) (Jarihani et al, 2015) and the dominant mechanisms of losing/gaining water according to different periods of the wet season (Costa et al, 2013). Processes such as reinfiltration of surface runoff, 10 lateral redistribution of subsurface runoff and hydraulic-connected stream-aquifer interactions have been shown to be necessary for hydrological modeling in Northeast Brazil (Güntner and Bronstert, 2004;Costa et al, 2012Costa et al, , 2013), but are not explicitly accounted for in any structure of the assessed models.…”

Section: Cross-scale Comparison Of River Discharges From Continental mentioning

confidence: 99%

Toward continental hydrologic–hydrodynamic modeling in South America

Paiva¹,

Siqueira²,

Fleischmann³

et al. 2018

Preprint

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Abstract. Providing reliable estimates of streamflow and hydrological fluxes is a major challenge for water resources management over national and transnational basins in South America. Global hydrological models and land surface models are a possible solution to simulate the terrestrial water cycle at the continental scale, but issues on parameterization and limitations in representing lowland river systems put into question their utility for basin-scale analysis and to deliver daily 15 discharges to meet local needs. In an attempt to overcome such limitations, we extended a regional, fully coupled hydrologic-hydrodynamic model (MGB) to the continental domain of South America and assessed its performance using daily river discharges, water levels from independent sources (in situ, satellite altimetry), estimates of terrestrial water storage (TWS) and evapotranspiration (ET) from remote sensing and other available global datasets. In addition, river discharges were compared with outputs from global models acquired through the eartH2Observe project (HTESSEL/CaMa-20 Flood, LISFLOOD and WaterGAP3), providing the first cross-scale assessment (regional/continental  global models) that makes use of spatially consistent daily discharge data. A satisfactory representation of discharges and water levels was obtained (NSE > 0.6 in 55 % of the cases) and MGB was able to capture patterns of seasonality and magnitude of TWS and ET especially over the largest basins of South America. Continental-scale modeling significantly improved discharge estimates when compared with global models, which resulted in a large number of gauges with negative (or close to 0) NSE 25 values. Models were largely affected by positive bias mainly over East/Northeast Brazil and Argentina as well as over regions of Sao Francisco and Parnaiba basins, while major issues on flow timing were observed in regions affected by floodplain processes such as the Amazon, La Plata, Tocantins-Araguaia, Orinoco and Magdalena basins. We state that efforts in calibrating rainfall-runoff parameters within large basins are necessary to simulate daily river discharges appropriately in this continent, but implementing a hydrodynamic routing component is also important. We hope that our 30 study provides further insights about hydrological simulation in South America, helping to reduce the gap between global and regional hydrological modeling communities.Hydrol. Earth Syst. Sci. Discuss., https://doi

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Where does all the water go? Partitioning water transmission losses in a data-sparse, multi-channel and low-gradient dryland river system using modelling and remote sensing

Cited by 53 publications

References 97 publications

Characterisation of Hydrological Response to Rainfall at Multi Spatio-Temporal Scales in Savannas of Semi-Arid Australia

Characterisation of Hydrological Response to Rainfall at Multi Spatio-Temporal Scales in Savannas of Semi-Arid Australia

Characterisation of Hydrological Response to Rainfall at Multi Spatio-Temporal Scales in Savannas of Semi-Arid Australia

Toward continental hydrologic–hydrodynamic modeling in South America

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