The calibration of hydrological models without streamflow observations is problematic, and the simultaneous, combined use of remotely sensed products for this purpose has not been exhaustively tested thus far. Our hypothesis is that the combined use of products can (1) reduce the parameter search space and (2) improve the representation of internal model dynamics and hydrological signatures. Five different conceptual hydrological models were applied to 27 catchments across Europe. A parameter selection process, similar to a likelihood weighting procedure, was applied for 1,023 possible combinations of 10 different data sources, ranging from using 1 to all 10 of these products. Distances between the two empirical distributions of model performance metrics with and without using a specific product were determined to assess the added value of a specific product. In a similar way, the performance of the models to reproduce 27 hydrological signatures was evaluated relative to the unconstrained model. Significant reductions in the parameter space were obtained when combinations included Advanced Microwave Scanning Radiometer ‐ Earth Observing System and Advanced Scatterometer soil moisture, Gravity Recovery and Climate Experiment total water storage anomalies, and, in snow‐dominated catchments, the Moderate Resolution Imaging Spectroradiometer snow cover products. The evaporation products of Land Surface Analysis ‐ Satellite Application Facility and MOD16 were less effective for deriving meaningful, well‐constrained posterior parameter distributions. The hydrological signature analysis indicated that most models profited from constraining with an increasing number of data sources. Concluding, constraining models with multiple data sources simultaneously was shown to be valuable for at least four of the five hydrological models to determine model parameters in absence of streamflow.

Abstract. The core component of many hydrological systems, the moisture storage capacity available to vegetation, is impossible to observe directly at the catchment scale and is typically treated as a calibration parameter or obtained from a priori available soil characteristics combined with estimates of rooting depth. Often this parameter is considered to remain constant in time. Using long-term data (30–40 years) from three experimental catchments that underwent significant land cover change, we tested the hypotheses that: (1) the root-zone storage capacity significantly changes after deforestation, (2) changes in the root-zone storage capacity can to a large extent explain post-treatment changes to the hydrological regimes and that (3) a time-dynamic formulation of the root-zone storage can improve the performance of a hydrological model.A recently introduced method to estimate catchment-scale root-zone storage capacities based on climate data (i.e. observed rainfall and an estimate of transpiration) was used to reproduce the temporal evolution of root-zone storage capacity under change. Briefly, the maximum deficit that arises from the difference between cumulative daily precipitation and transpiration can be considered as a proxy for root-zone storage capacity. This value was compared to the value obtained from four different conceptual hydrological models that were calibrated for consecutive 2-year windows.It was found that water-balance-derived root-zone storage capacities were similar to the values obtained from calibration of the hydrological models. A sharp decline in root-zone storage capacity was observed after deforestation, followed by a gradual recovery, for two of the three catchments. Trend analysis suggested hydrological recovery periods between 5 and 13 years after deforestation. In a proof-of-concept analysis, one of the hydrological models was adapted to allow dynamically changing root-zone storage capacities, following the observed changes due to deforestation. Although the overall performance of the modified model did not considerably change, in 51 % of all the evaluated hydrological signatures, considering all three catchments, improvements were observed when adding a time-variant representation of the root-zone storage to the model.In summary, it is shown that root-zone moisture storage capacities can be highly affected by deforestation and climatic influences and that a simple method exclusively based on climate data can not only provide robust, catchment-scale estimates of this critical parameter, but also reflect its time-dynamic behaviour after deforestation.

No abstract

Abstract:Long-term river flow data and one year of isotopic tracer data in a nested 749 km 2 catchment were analysed conjunctively to evaluate the relationships between hydrometric statistics, transit times, and catchment characteristics. The catchment comprised two distinct geomorphic provinces; upland headwaters draining glaciated landscapes underlain by crystalline geology and lowland headwaters draining a major regional sandstone aquifer. In the uplands, flow regimes were 'flashy' with high runoff coefficients for storm hydrographs, steep recession curves and strong nonlinearity in event responses. In the lowlands, runoff coefficients were low, recessions less steep, and event responses more linear. Flow data from the catchment outfall showing damping of these extremes, but was most strongly influenced by the upland headwaters where precipitation was highest. The damping of variability in stable water isotopes between precipitation inputs and streamflow outputs reflected this; with upland tributaries least damped and lowland tributaries most damped. Attempts to quantify the mean transit times of the sampling points met with mixed success; partly reflecting the short run (1 year) of data, but mainly as a result of the marked damping in lowland sites. As a consequence, MTT estimates can only be said to be in the order of a few years in upland sites, but are probably decadal or greater in lowland tributaries. Again, the catchment outfall averages these extremes, but is more similar to the upland headwaters. Despite the difficulties in quantifying MTTs, it is clear that they, like the hydrological response, primarily reflect the dominant control of catchment soil cover, which in turn is determined by geology and glacial history.

No abstract