Global hydrology 2015: State, trends, and directions

Self Cite

231

160

Abstract. The diversity in hydrologic models has historically led to great controversy on the "correct" approach to processbased hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. In this paper, we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, provide examples of modeling advances that address these challenges, and define outstanding research needs. We illustrate how modeling advances have been made by groups using models of different type and complexity, and we argue for the need to more effectively use our diversity of modeling approaches in order to advance our collective quest for physically realistic hydrologic models.

Section: Parameter Estimation Solutionsmentioning

confidence: 99%

The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism

Clark

Bierkens

Samaniego

et al. 2017

Self Cite

231

160

“…The above-mentioned challenges that we face in estimating key physical parameters in LSMs/HMs have been intensively discussed in many studies Bierkens et al, 2014;Bierkens, 2015;Clark et al, 2016Clark et al, , 2017Mizukami et al, 2017;Peters-Lidard et al, 2017). To further visualize the problems and to understand the deficiencies of current parameterization techniques, we selected a representative sample of LSMs/HMs used for research and/or operational purposes, namely CABLE, CLM, JULES, LISFLOOD, Noah-MP, mHM, PCR-GLOBWB, WaterGAP2 (30 arcmin), Wa-terGAP3 (5 arcmin), CHTESSEL, and HBV.…”

Section: Parameterization Of Soil Porosity and Available Water Capacimentioning

confidence: 99%

“…Richard P. Feynman Land surface and hydrologic models (LSMs/HMs) are currently used at diverse spatial resolutions ranging from 1 to 10 km in catchment-scale impact analysis and forecasting (Christensen and Lettenmaier, 2007;Addor et al, 2014) to over 50 km in global-scale climate change simulations to estimate land surface boundary conditions of key state variables (Haddeland et al, 2011;Bierkens, 2015;Wanders and Wada, 2015). The fundamental conditions behind the applicability of the same LSM/HM model structure at different spatial scales requires that the model parameterizations are scale invariant and that the model estimates similar fluxes across a range of spatial resolutions.…”

Section: Introductionmentioning

confidence: 99%

Toward seamless hydrologic predictions across spatial scales

Samaniego

Kumar

Thober

et al. 2017

111

134

Abstract. Land surface and hydrologic models (LSMs/HMs) are used at diverse spatial resolutions ranging from catchment-scale (1-10 km) to global-scale (over 50 km) applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the chosen resolution, i.e., fulfills a fluxmatching condition across scales. An analysis of state-of-theart LSMs and HMs reveals that most do not have consistent hydrologic parameter fields. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB, and WaterGAP models demonstrate the pitfalls of deficient parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. Based on a review of existing parameter regionalization techniques, we postulate that the multiscale parameter regionalization (MPR) technique offers a practical and robust method that provides consistent (seamless) parameter and flux fields across scales. Herein, we develop a general model protocol to describe how MPR can be applied to a particular model and present an example application using the PCR-GLOBWB model. Finally, we discuss potential advantages and limitations of MPR in obtaining the seamless prediction of hydrological fluxes and states across spatial scales.

“…A number of GHMs (but not all) are able to incorporate human water use in their calculations (see Table 2 in Bierkens, 2015). Neglecting anthropogenic water consumption prevents meaningful water resources assessments, at least in regions with high water consumption relative to renewable resources (e.g., High Plains aquifer, Indus, Ganges-Brahmaputra).…”

Section: Introductionmentioning

confidence: 99%

“…Since the 1980s, global hydrological models (GHMs) have been developed to calculate the water balance on global and/or continental scales. Recent reviews of such models are presented by Bierkens (2015), Sood and Smakhtin (2015), and Trambauer et al (2013).…”

Section: Introductionmentioning

confidence: 99%

Variations of global and continental water balance components as impacted by climate forcing uncertainty and human water use

Schmied

Adam

Eisner

et al. 2016

174

106

Abstract. When assessing global water resources with hydrological models, it is essential to know about methodological uncertainties. The values of simulated water balance components may vary due to different spatial and temporal aggregations, reference periods, and applied climate forcings, as well as due to the consideration of human water use, or the lack thereof. We analyzed these variations over the period 1901–2010 by forcing the global hydrological model WaterGAP 2.2 (ISIMIP2a) with five state-of-the-art climate data sets, including a homogenized version of the concatenated WFD/WFDEI data set. Absolute values and temporal variations of global water balance components are strongly affected by the uncertainty in the climate forcing, and no temporal trends of the global water balance components are detected for the four homogeneous climate forcings considered (except for human water abstractions). The calibration of WaterGAP against observed long-term average river discharge Q significantly reduces the impact of climate forcing uncertainty on estimated Q and renewable water resources. For the homogeneous forcings, Q of the calibrated and non-calibrated regions of the globe varies by 1.6 and 18.5 %, respectively, for 1971–2000. On the continental scale, most differences for long-term average precipitation P and Q estimates occur in Africa and, due to snow undercatch of rain gauges, also in the data-rich continents Europe and North America. Variations of Q at the grid-cell scale are large, except in a few grid cells upstream and downstream of calibration stations, with an average variation of 37 and 74 % among the four homogeneous forcings in calibrated and non-calibrated regions, respectively. Considering only the forcings GSWP3 and WFDEI_hom, i.e., excluding the forcing without undercatch correction (PGFv2.1) and the one with a much lower shortwave downward radiation SWD than the others (WFD), Q variations are reduced to 16 and 31 % in calibrated and non-calibrated regions, respectively. These simulation results support the need for extended Q measurements and data sharing for better constraining global water balance assessments. Over the 20th century, the human footprint on natural water resources has become larger. For 11–18% of the global land area, the change of Q between 1941–1970 and 1971–2000 was driven more strongly by change of human water use including dam construction than by change in precipitation, while this was true for only 9–13 % of the land area from 1911–1940 to 1941–1970.