No abstract

Abstract:Tropical montane cloud forests (TMCF) typically experience conditions of frequent to persistent fog. On the basis of the altitudinal limits between which TMCF generally occur (800-3500 m.a.s.l. depending on mountain size and distance to coast) their current areal extent is estimated at ¾215 000 km 2 or 6Ð6% of all montane tropical forests. Alternatively, on the basis of remotely sensed frequencies of cloud occurrence, fog-affected forest may occupy as much as 2Ð21 Mkm 2 . Four hydrologically distinct montane forest types may be distinguished, viz. lower montane rain forest below the cloud belt (LMRF), tall lower montane cloud forest (LMCF), upper montane cloud forest (UMCF) of intermediate stature and a group that combines stunted sub-alpine cloud forest (SACF) and 'elfin' cloud forest (ECF). Average throughfall to precipitation ratios increase from 0Ð72 š 0Ð07 in LMRF (n D 15) to 0Ð81 š 0Ð11 in LMCF (n D 23), to 1Ð0 š 0Ð27 (n D 18) and 1Ð04 š 0Ð25 (n D 8) in UMCF and SACF-ECF, respectively. Average stemflow fractions increase from LMRF to UMCF and ECF, whereas leaf area index (LAI) and annual evapotranspiration (ET) decrease along the same sequence. Although the data sets for UMCF (n D 3) and ECF (n D 2) are very limited, the ET from UMCF (783 š 112 mm) and ECF (547 š 25 mm) is distinctly lower than that from LMCF (1188 š 239 mm, n D 9) and LMRF (1280 š 72 mm; n D 7). Field-measured annual 'cloud-water' interception (CWI) totals determined with the wet-canopy water budget method (WCWB) vary widely between locations and range between 22 and 1990 mm (n D 15). Field measured values also tend to be much larger than modelled amounts of fog interception, particularly at exposed sites. This is thought to reflect a combination of potential model limitations, a mismatch between the scale at which the model was applied (1 ð 1 km) and the scale of the measurements (small plots), as well as the inclusion of near-horizontal wind-driven precipitation in the WCWB-based estimate of CWI. Regional maps of modelled amounts of fog interception across the tropics are presented, showing major spatial variability. Modelled contributions by CWI make up less than 5% of total precipitation in wet areas to more than 75% in low-rainfall areas. Catchment water yields typically increase from LMRF to UMCF and SACF-ECF reflecting concurrent increases in incident precipitation and decreases in evaporative losses. The conversion of LMCF (or LMRF) to pasture likely results in substantial increases in water yield. Changes in water yield after UMCF conversion are probably modest due to trade-offs between concurrent changes in ET and CWI. General circulation model (GCM)-projected rates of climatic drying under SRES greenhouse gas scenarios to the year 2050 are considered to have a profound effect on TMCF hydrological functioning and ecology, although different GCMs produce different and sometimes opposing results. Whilst there have been substantial increases in our understanding of the hydrological processes operating in TMCF, additional re...

No abstract

Current state-of-the-art models typically applied at continental to global scales (hereafter called macroscale) tend to use a priori parameters, resulting in suboptimal streamflow (Q) simulation. For the first time, a scheme for regionalization of model parameters at the global scale was developed. We used data from a diverse set of 1787 small-to-medium sized catchments (10-10;000 km 2 ) and the simple conceptual HBV model to set up and test the scheme. Each catchment was calibrated against observed daily Q, after which 674 catchments with high calibration and validation scores, and thus presumably good-quality observed Q and forcing data, were selected to serve as donor catchments. The calibrated parameter sets for the donors were subsequently transferred to 0.58 grid cells with similar climatic and physiographic characteristics, resulting in parameter maps for HBV with global coverage. For each grid cell, we used the 10 most similar donor catchments, rather than the single most similar donor, and averaged the resulting simulated Q, which enhanced model performance. The 1113 catchments not used as donors were used to independently evaluate the scheme. The regionalized parameters outperformed spatially uniform (i.e., averaged calibrated) parameters for 79% of the evaluation catchments. Substantial improvements were evident for all major K€ oppen-Geiger climate types and even for evaluation catchments > 5000 km distant from the donors. The median improvement was about half of the performance increase achieved through calibration. HBV with regionalized parameters outperformed nine state-of-the-art macroscale models, suggesting these might also benefit from the new regionalization scheme. The produced HBV parameter maps including ancillary data are available via www.gloh2o.org.

[1] Numerous previous studies have constructed models to estimate base flow characteristics from climatic and physiographic characteristics of catchments and applied these to ungauged regions. However, these studies generally used streamflow observations from a relatively small number of catchments (<200) located in small, homogeneous study areas, which may have led to less reliable models with limited applicability elsewhere. Here, we use streamflow observations from a highly heterogeneous set of 3394 catchments (<10,000 km 2 ) worldwide to construct reliable, widely applicable models based on 18 climatic and physiographic characteristics to estimate two important base flow characteristics: (1) the base flow index (BFI), defined as the ratio of long-term mean base flow to total streamflow; and (2) the base flow recession constant (k), defined as the rate of base flow decay. Regression analysis results revealed that BFI and k were related to several climatic and physiographic characteristics, notably mean annual potential evaporation, mean snow water equivalent depth, and abundance of surface water bodies. Ensembles of artificial neural networks (ANNs; obtained by subsampling the original set of catchments) were trained to estimate the base flow characteristics from climatic and physiographic data. The catchment-scale estimation of the base flow characteristics demonstrated encouraging performance with R 2 values of 0.82 for BFI and 0.72 for k. The connection weights of the trained ANNs indicated that climatic characteristics were more important for estimating k than BFI. Global maps of estimated BFI and k were obtained using global climatic and physiographic data as input to the derived models. The resulting global maps are available for free download at http://www.hydrology-amsterdam.nl.