Value of river discharge data for global-scale hydrological modeling

his paper investigates the value of observed river discharge data for global-scale hydrological modeling of a number of flow characteristics that are required for assessing water resources, flood risk and habitat alteration of aqueous ecosystems. An improved version of WGHM (WaterGAP Global Hydrology Model) was tuned in a way that simulated and observed long-term average river discharges at each station become equal, using either the 724-station dataset (V1) against which former model versions were tuned or a new dataset (V2) of 1235 stations and often longer time series. WGHM is tuned by adjusting one model parameter (γ) that affects runoff generation from land areas, and, where necessary, by applying one or two correction factors, which correct the total runoff in a sub-basin (areal correction factor) or the discharge at the station (station correction factor). The study results are as follows. (1) Comparing V2 to V1, the global land area covered by tuning basins increases by 5%, while the area where the model can be tuned by only adjusting γ increases by 8% (546 vs. 384 stations). However, the area where a station correction factor (and not only an areal correction factor) has to be applied more than doubles (389 vs. 93 basins), which is a strong drawback as use of a station correction factor makes discharge discontinuous at the gauge and inconsistent with runoff in the basin. (2) The value of additional discharge information for representing the spatial distribution of long-term average discharge (and thus renewable water resources) with WGHM is high, particularly for river basins outside of the V1 tuning area and for basins where the average sub-basin area has decreased by at least 50% in V2 as compared to V1. For these basins, simulated long-term average discharge would differ from the observed one by a factor of, on average, 1.8 and 1.3, respectively, if the additional discharge information were not used for tuning. The value tends to be higher in semi-arid and snow-dominated regions where hydrological models are less reliable than in humid areas. The deviation of the other simulated flow characteristics (e.g. low flow, inter-annual variability and seasonality) from the observed values also decreases significantly, but this is mainly due to the better representation of average discharge but not of variability. (3) The optimal sub-basin size for tuning depends on the modeling purpose. On the one hand, small basins between 9000 and 20 000 km2 show a much stronger improvement in model performance due to tuning than the larger basins, which is related to the lower model performance (with and without tuning), with basins over 60 000 km2 performing best. On the other hand, tuning of small basins decreases model consistency, as almost half of them require a station correction factor

Arctic–CHAMP: A program to study Arctic hydrology and its role in global change

The Arctic constitutes a unique and important environment that is central to the dynamics and evolution of the Earth system. The Arctic water cycle, which controls countless physical, chemical, and biotic processes, is also unique and important. These processes, in turn, regulate the climate, habitat, and natural resources that are of great importance to both native and industrial societies. Comprehensive understanding of water cycling across the Arctic and its linkage to global biogeophysical dynamics is a scientific as well as strategic policy imperative

Impacts du changement climatique sur l'hydrologie et la gestion des ressources en eau du bassin de la Meuse (synthèse bibliographique)

Impacts of climate change on hydrological regimes and water resources management in the Meuse catchment. A review. This review examines the consequences of climate change on the hydrology of the Meuse catchment and on various water-related socio-economic sectors. It sums up the different modeling approaches in hydrological modeling, placing emphasis on current modeling assumptions and the restrictions inherent within them. It is useful to consider land use evolution and adapted management within the context of climate change, particularly with reference to agriculture. More specifically, a broader usage of physically-based hydrological models would be useful in order to represent climate change scenarios and possible adaptation tracks at the catchment scale. These physically-based hydrological models are able to represent a wide range of phenomena occurring in the water-soil-plant continuum. They thus allow a refinement of global hydrological solutions at the catchment scale, especially during low flow periods. Moreover, such models pave the way for the analysis of scenarios aimed at creating adaptation in the use and management of soils

Ensemble evaluation of hydrological model hypotheses

It is demonstrated for the first time how model parameter, structural and data uncertainties can be accounted for explicitly and simultaneously within the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. As an example application, 72 variants of a single soil moisture accounting store are tested as simplified hypotheses of runoff generation at six experimental grassland field-scale lysimeters through model rejection and a novel diagnostic scheme. The fields, designed as replicates, exhibit different hydrological behaviors which yield different model performances. For fields with low initial discharge levels at the beginning of events, the conceptual stores considered reach their limit of applicability. Conversely, one of the fields yielding more discharge than the others, but having larger data gaps, allows for greater flexibility in the choice of model structures. As a model learning exercise, the study points to a “leaking” of the fields not evident from previous field experiments. It is discussed how understanding observational uncertainties and incorporating these into model diagnostics can help appreciate the scale of model structural error

Analyzing runoff processes through conceptual hydrological modeling in the Upper Blue Nile Basin, Ethiopia

Understanding runoff processes in a basin is of paramount importance for the effective planning and management of water resources, in particular in data-scarce regions such as the Upper Blue Nile. Hydrological models representing the underlying hydrological processes can predict river discharges from ungauged catchments and allow for an understanding of the rainfall-runoff processes in those catchments. In this paper, such a conceptual process-based hydrological model is developed and applied to the upper Gumara and Gilgel Abay catchments (both located within the Upper Blue Nile Basin, the Lake Tana sub-basin) to study the runoff mechanisms and rainfall-runoff processes in the basin. Topography is considered as a proxy for the variability of most of the catchment characteristics. We divided the catchments into different runoff production areas using topographic criteria. Impermeable surfaces (rock outcrops and hard soil pans, common in the Upper Blue Nile Basin) were considered separately in the conceptual model. Based on model results, it can be inferred that about 65% of the runoff appears in the form of interflow in the Gumara study catchment, and baseflow constitutes the larger proportion of runoff (44-48%) in the Gilgel Abay catchment. Direct runoff represents a smaller fraction of the runoff in both catchments (18-19% for the Gumara, and 20% for the Gilgel Abay) and most of this direct runoff is generated through infiltration excess runoff mechanism from the impermeable rocks or hard soil pans. The study reveals that the hillslopes are recharge areas (sources of interflow and deep percolation) and direct runoff as saturated excess flow prevails from the flat slope areas. Overall, the model study suggests that identifying the catchments into different runoff production areas based on topography and including the impermeable rocky areas separately in the modeling process mimics the rainfall-runoff process in the Upper Blue Nile Basin well and yields a useful result for operational management of water resources in this data-scarce region

Assessment of different modelling studies on the spatial hydrological processes in an arid alpine catchment

To assess the model description of spatial hydrological processes in the arid alpine catchment, SWAT and MIKE SHE were jointly applied in Yarkant River basin located in northwest China. Not only the simulated daily discharges at the outlet station but also spatiotemporal distributions of runoff, snowmelt and evapotranspiration were analyzed contrastively regarding modules' structure and algorithm. The simulation results suggested both models have their own strengths for particular hydrological processes. For the stream runoff simulation, the significant contributions of lateral interflow flow were only reflected in SWAT with a proportion of 41.4 %, while MIKE SHE simulated a more realistic distribution of base flow from groundwater with a proportion of 21.3 %. In snowmelt calculation, SWAT takes account of more available factors and got better correlations between snowmelt and runoff in temporal distribution, however, MIKE SHE presented clearer spatial distribution of snowpack because of fully distributed structure. In the aspect of water balance, less water was evaporated because of limitation of soil evaporation and less spatially distributed approach in SWAT, on another hand, the spatial distribution of actual evapotranspiration (ETa) in MIKE SHE clearly expressed influence of land use. Whether SWAT or MIKE SHE, without multiple calibrations, the model's limitation might bring in some biased opinions of hydrological processes in a catchment scale. The complementary study of combined results from multiple models could have a better understanding of overall hydrological processes in arid and scarce gauges alpine region

Improving predictive power of physically based rainfall-induced shallow landslide models: a probabilistic approach

Distributed models to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides are based on deterministic laws. These models extend spatially the static stability models adopted in geotechnical engineering, and adopt an infinite-slope geometry to balance the resisting and the driving forces acting on the sliding mass. An infiltration model is used to determine how rainfall changes pore-water conditions, modulating the local stability/instability conditions. A problem with the operation of the existing models lays in the difficulty in obtaining accurate values for the several variables that describe the material properties of the slopes. The problem is particularly severe when the models are applied over large areas, for which sufficient information on the geotechnical and hydrological conditions of the slopes is not generally available. To help solve the problem, we propose a probabilistic Monte Carlo approach to the distributed modeling of rainfall-induced shallow landslides. For the purpose, we have modified the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis (TRIGRS) code. The new code (TRIGRS-P) adopts a probabilistic approach to compute, on a cell-by-cell basis, transient pore-pressure changes and related changes in the factor of safety due to rainfall infiltration. Infiltration is modeled using analytical solutions of partial differential equations describing one-dimensional vertical flow in isotropic, homogeneous materials. Both saturated and unsaturated soil conditions can be considered. TRIGRS-P copes with the natural variability inherent to the mechanical and hydrological properties of the slope materials by allowing values of the TRIGRS model input parameters to be sampled randomly from a given probability distribution. [..]Comment: 25 pages, 14 figures, 9 tables. Revised version; accepted for publication in Geoscientific Model Development on 13 February 201

A physically-based parsimonious hydrological model for flash floods in Mediterranean catchments

A spatially distributed hydrological model, dedicated to flood simulation, is developed on the basis of physical process representation (infiltration, overland flow, channel routing). Estimation of model parameters requires data concerning topography, soil properties, vegetation and land use. Four parameters are calibrated for the entire catchment using one flood event. Model sensitivity to individual parameters is assessed using Monte-Carlo simulations. Results of this sensitivity analysis with a criterion based on the Nash efficiency coefficient and the error of peak time and runoff are used to calibrate the model. This procedure is tested on the Gardon d'Anduze catchment, located in the Mediterranean zone of southern France. A first validation is conducted using three flood events with different hydrometeorological characteristics. This sensitivity analysis along with validation tests illustrates the predictive capability of the model and points out the possible improvements on the model's structure and parameterization for flash flood forecasting, especially in ungauged basins. Concerning the model structure, results show that water transfer through the subsurface zone also contributes to the hydrograph response to an extreme event, especially during the recession period. Maps of soil saturation emphasize the impact of rainfall and soil properties variability on these dynamics. Adding a subsurface flow component in the simulation also greatly impacts the spatial distribution of soil saturation and shows the importance of the drainage network. Measures of such distributed variables would help discriminating between different possible model structures