Reconciling the global terrestrial water budget using satellite remote sensing

Sahoo, Alok Kumar; Pan, Ming; Troy, Tara J.; Vinukollu, R. K.; Sheffield, Justin; Wood, Eric F.

doi:10.1016/j.rse.2011.03.009

Cited by 161 publications

(188 citation statements)

References 68 publications

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“…As in PM-MOD, snow sublimation and open-water evaporation are not considered independently of other processes. The model has been employed in a number of studies to estimate terrestrial evaporation on regional and global scales in recent years (see, e.g., Sahoo et al, 2011;Vinukollu et al, 2011a, b).…”

Section: Pt-jplmentioning

confidence: 99%

“…3.3). Given that river run-off and precipitation are more easily and extensively measured than evaporation, estimates of P -Q based on ground measurements of these two fluxes provide a convenient means to evaluate evaporation over large domains and long periods Miralles et al, 2011a;Vinukollu et al, 2011b;Sahoo et al, 2011). Here, we use globally distributed multiannual river discharge data for basins larger than 2500 km 2 .…”

Section: Catchment Water Balance Datamentioning

confidence: 99%

“…2.3.2, these analyses consist of a comparison of modelled evaporation estimates from PM-MOD, GLEAM, and PT-JPL (forced by the reference input data set over [2005][2006][2007] with estimates of P -Q. Such a comparison implies the validity of a series of assumptions (see discussion below), but overall, P -Q estimates remain a valid, recursive means to evaluate long-term evaporation patterns Miralles et al, 2011a;Vinukollu et al, 2011b;Sahoo et al, 2011). Here, different criteria have been applied to ensure…”

Section: Evaluation Of Evaporation Based On the Water Balance Closurementioning

confidence: 99%

See 2 more Smart Citations

The WACMOS-ET project – Part 2: Evaluation of global terrestrial evaporation data sets

Miralles

Jiménez²,

Jung

et al. 2016

Hydrol. Earth Syst. Sci.

272

209

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Abstract. The WAter Cycle Multi-mission Observation Strategy -EvapoTranspiration (WACMOS-ET) project aims to advance the development of land evaporation estimates on global and regional scales. Its main objective is the derivation, validation, and intercomparison of a group of existing evaporation retrieval algorithms driven by a common forcing data set. Three commonly used process-based evaporation methodologies are evaluated: the PenmanMonteith algorithm behind the official Moderate Resolution Imaging Spectroradiometer (MODIS) evaporation product (PM-MOD), the Global Land Evaporation Amsterdam Model (GLEAM), and the Priestley-Taylor Jet Propulsion Laboratory model (PT-JPL). The resulting global spatiotemporal variability of evaporation, the closure of regional water budgets, and the discrete estimation of land evaporation components or sources (i.e. transpiration, interception loss, and direct soil evaporation) are investigated using river discharge data, independent global evaporation data sets and results from previous studies. In a companion article (Part 1), Michel et al. (2016) inspect the performance of these three models at local scales using measurements from eddy-covariance towers and include in the assessment the Surface Energy Balance System (SEBS) model. In agreement with Part 1, our results indicate that the Priestley and Taylor products (PT-JPL and GLEAM) perform best overall for most ecosystems and climate regimes. While all three evaporation products adequately represent the expected average geographical patterns and seasonality, there is a tendency in PM-MOD to underestimate the flux in the tropics and subtropics. Overall, results from GLEAM and PT-JPL appear more realistic when compared to surface water balances from 837 globally distributed catchments and to separate evaporation estimates from ERAInterim and the model tree ensemble (MTE). Nonetheless, all products show large dissimilarities during conditions of water stress and drought and deficiencies in the way evaporation is partitioned into its different components. This observed inter-product variability, even when common forcing is used, suggests that caution is necessary in applying a single data set for large-scale studies in isolation. A general finding that different models perform better under different conditions highlights the potential for considering biome-or climatespecific composites of models. Nevertheless, the generation of a multi-product ensemble, with weighting based on validation analyses and uncertainty assessments, is proposed as the Published by Copernicus Publications on behalf of the European Geosciences Union. D. G. Miralles et al.: The WACMOS-ET project -Part 2best way forward in our long-term goal to develop a robust observational benchmark data set of continental evaporation.

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Section: Pt-jplmentioning

confidence: 99%

Section: Catchment Water Balance Datamentioning

confidence: 99%

Section: Evaluation Of Evaporation Based On the Water Balance Closurementioning

confidence: 99%

See 1 more Smart Citation

The WACMOS-ET project – Part 2: Evaluation of global terrestrial evaporation data sets

Miralles

Jiménez²,

Jung

et al. 2016

Hydrol. Earth Syst. Sci.

272

209

View full text Add to dashboard Cite

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“…But so far there seems to be no way of measuring the spatial field of runoff as it occurs. Therefore, previous studies used the streamflow measurements in place of runoff (Sahoo et al, 2011;Sheffield et al, 2009). However, as streamflow can be measured at river gauges and will be measured at large scales by space-borne altimetry sensors through Manning's equation (Alsdorf and Lettenmaier, 2003), for example, the planned Surface Water and Ocean Topography (SWOT) mission , it is not fully equivalent to runoff.…”

Section: Introductionmentioning

confidence: 99%

Inverse streamflow routing

Pan

Wood

2013

Hydrol. Earth Syst. Sci.

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Abstract. The process whereby the spatially distributed runoff (generated through saturation/infiltration excesses, subsurface flow, etc.) travels over the hillslope and river network and becomes streamflow is generally referred to as "routing". In short, routing is a runoff-to-streamflow process, and the streamflow in rivers is the response to runoff integrated in both time and space. Here we develop a methodology to invert the routing process, i.e., to derive the spatially distributed runoff from streamflow (e.g., measured at gauge stations) by inverting an arbitrary linear routing model using fixed interval smoothing. We refer to this streamflowto-runoff process as "inverse routing". Inversion experiments are performed using both synthetically generated and real streamflow measurements over the Ohio River basin. Results show that inverse routing can effectively reproduce the spatial field of runoff and its temporal dynamics from sufficiently dense gauge measurements, and the inversion performance can also be strongly affected by low gauge density and poor data quality.The runoff field is the only component in the terrestrial water budget that cannot be directly measured, and all previous studies used streamflow measurements in its place. Consequently, such studies are limited to scales where the spatial and temporal difference between the two can be ignored. Inverse routing provides a more sophisticated tool than traditional methods to bridge this gap and infer finescale (in both time and space) details of runoff from aggregated measurements. Improved handling of this final gap in terrestrial water budget analysis may potentially help us to use space-borne altimetry-based surface water measurements for cross-validating, cross-correcting, and assimilation with other space-borne water cycle observations.

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“…While other observational sources for the terrestrial water budget have become more readily available from satellite remote sensing, the lack of comprehensive river discharge observations has resulted in a key flux (runoff) in 10 climate models and large-scale land surface models being poorly constrained by observations over much of the global land surface (Sahoo et al, 2011). Furthermore, the amount of water stored at the land surface and its space-time variability are poorly known.…”

mentioning

confidence: 99%

Spatiotemporal Assimilation/Interpolation of Discharge Records through Inverse Streamflow Routing

Fisher¹,

Pan²,

Wood³

2018

Preprint

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Abstract.Poorly monitored river flows in many regions of the world have been hindering our ability to accurately estimate global water usage as well as the budgets and variability of the global water cycle. In-situ gauging sites, as well as a number of satellite-based systems, make observations of river discharge throughout the globe; however, these observations are often sparse due to, e.g., the sampling frequencies of sensors or a lack of reporting. Recently, efforts have been made to develop methods to integrate these discrete observations to gain a better understanding of the underlying processes. This paper 10 presents an application of a fixed interval Kalman smoother based model, called Inverse Streamflow Routing (ISR), to generate spatially and temporally continuous river discharge fields from discrete observations. The method propagates the observed information across all reachable parts of the river network (up/downstream from gauging point) and all reachable times (before/after observation time) using a two-sweep procedure that first propagates information backward in time to the furthest upstream locations (inverse routing) and then propagates it forward in time to the furthest downstream locations (forward 15 routing). The key advantages of this approach are that it (1) maintains all the physical consistencies embodied by a diffusive wave routing model (flow confluence relationships on the river network and the resulting mass balance, wave velocity and diffusivity), (2) updates the lateral influx (runoff) at pixel level (furthest upstream) to guarantee exhaustive propagation of observed information, (3) works both with a first guess of initial river discharge conditions from a routing model (assimilation) and without a first guess (pure interpolation of observations). Two sets of experiments are carried out under idealized 20 conditions as well as real-world conditions provided by U.S. Geological Survey observations. Results show that the method can effectively reproduce the spatial and temporal dynamics of river discharge in each of the experiments presented. The performance is driven by the density of the gauge network as well as the quality of the data being assimilated. We find that when assimilating the actual USGS observations, the performance decreases relative to our idealized scenario; however, we are still able to produce an improved discharge product at each validation site. With further testing as well as global application, 25 ISR may prove to be a useful method for extending our current network of global river discharge observations.

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Reconciling the global terrestrial water budget using satellite remote sensing

Cited by 161 publications

References 68 publications

The WACMOS-ET project – Part 2: Evaluation of global terrestrial evaporation data sets

The WACMOS-ET project – Part 2: Evaluation of global terrestrial evaporation data sets

Inverse streamflow routing

Spatiotemporal Assimilation/Interpolation of Discharge Records through Inverse Streamflow Routing

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