In this paper we implement a degree day snowmelt and glacier melt model in the Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) model. The purpose is to develop a hydrological model that can be applied to large glaciated and snow-fed catchments yet is computationally efficient enough to include model uncertainty in streamflow predictions. The model is evaluated by simulating monthly discharge at six gauging stations in the Naryn River catchment (57 833 km2) in central Asia over the period 1951 to a variable end date between 1980 and 1995 depending on the availability of discharge observations. The spatial distribution of simulated snow cover is validated against MODIS weekly snow extent for the years 2001–2007. Discharge is calibrated by selecting parameter sets using Latin hypercube sampling and assessing the model performance using six evaluation metrics. The model shows good performance in simulating monthly discharge for the calibration period (NSE is 0.74<NSE<0.87) and validation period (0.7<NSE<0.9), where the range of NSE values represents the 5th–95th percentile prediction limits across the gauging stations. The exception is the Uch-Kurgan station, which exhibits a reduction in model performance during the validation period attributed to commissioning of the Toktogul reservoir in 1975 which impacted the observations. The model reproduces the spatial extent in seasonal snow cover well when evaluated against MODIS snow extent; 86 % of the snow extent is captured (mean 2001–2007) for the median ensemble member of the best 0.5 % calibration simulations. We establish the present-day contributions of glacier melt, snowmelt and rainfall to the total annual runoff and the timing of when these components dominate river flow. The model predicts well the observed increase in discharge during the spring (April–May) associated with the onset of snow melting and peak discharge during the summer (June, July and August) associated with glacier melting. Snow melting is the largest component of the annual runoff (89 %), followed by the rainfall (9 %) and the glacier melt component (2 %), where the values refer to the 50th percentile estimates at the catchment outlet gauging station Uch-Kurgan. In August, glacier melting can contribute up to 66 % of the total runoff at the highly glacierized Naryn headwater sub-catchment. The glaciated area predicted by the best 0.5 % calibration simulations overlaps the Landsat observations for the late 1990s and mid-2000s. Despite good predictions for discharge, the model produces a large range of estimates for the glaciated area (680–1196 km2) (5th–95th percentile limits) at the end of the simulation period. To constrain these estimates further, additional observations such as glacier mass balance, snow depth or snow extent should be used directly to constrain model simulations.

Observed streamflow of headwater catchments of the Tarim River (Central Asia) increased by about 30% over the period 1957–2004. This study aims at assessing to which extent these streamflow trends can be attributed to changes in air temperature or precipitation. The analysis includes a data‐based approach using multiple linear regression and a simulation‐based approach using a hydrological model. The hydrological model considers changes in both glacier area and surface elevation. It was calibrated using a multiobjective optimization algorithm with calibration criteria based on glacier mass balance and daily and interannual variations of discharge. The individual contributions to the overall streamflow trends from changes in glacier geometry, temperature, and precipitation were assessed using simulation experiments with a constant glacier geometry and with detrended temperature and precipitation time series. The results showed that the observed changes in streamflow were consistent with the changes in temperature and precipitation. In the Sari‐Djaz catchment, increasing temperatures and related increase of glacier melt were identified as the dominant driver, while in the Kakshaal catchment, both increasing temperatures and increasing precipitation played a major role. Comparing the two approaches, an advantage of the simulation‐based approach is the fact that it is based on process‐based relationships implemented in the hydrological model instead of statistical links in the regression model. However, data‐based approaches are less affected by model parameter and structural uncertainties and typically fast to apply. A complementary application of both approaches is recommended.

In data sparse mountainous regions it is difficult to derive areal precipitation estimates. In addition, their evaluation by cross validation can be misleading if the precipitation gauges are not in representative locations in the catchment. This study aims at the evaluation of precipitation estimates in data sparse mountainous catchments. In particular, it is first tested whether monthly precipitation fields from downscaled reanalysis data can be used for interpolating gauge observations. Secondly, precipitation estimates from this and other methods are evaluated by comparing simulated and observed discharge, which has the advantage that the data are evaluated at the catchment scale. This approach is extended here in order to differentiate between errors in the overall bias and the temporal dynamics, and by taking into account different sources of uncertainties. The study area includes six headwater catchments of the Karadarya Basin in Central Asia. Generally the precipitation estimate based on monthly precipitation fields from downscaled reanalysis data showed an acceptable performance, comparable to another interpolation method using monthly precipitation fields from multi-linear regression against topographical variables. Poor performance was observed in only one catchment, probably due to mountain ridges not resolved in the model orography of the regional climate model. Using two performance criteria for the evaluation by hydrological modelling allowed a more informed differentiation between the precipitation data and showed that the precipitation data sets mostly differed in their overall bias, while the performance with respect to the temporal dynamics was similar. Our precipitation estimates in these catchments are considerably higher than those from continental-or global-scale gridded data sets. The study demonstrates large uncertainties in areal precipitation estimates in these data sparse mountainous catchments. In such regions with only very few precipitation gauges but high spatial variability of precipitation, important information for evaluating precipitation estimates may be gained by hydrological modelling and a comparison to observed discharge.

Glaciers are significant fresh water storages in Central Asian high mountains and are considered to substantially contribute to the summer runoff of Central Asian Rivers. We present a comprehensive study of the glacier area changes in the Naryn catchment located in the Tien Shan Mountains. The catchment with a size of 55,944 km(2) is a major tributary of the Syrdarya River which is heavily used for water supply and irrigation. We analysed the glacier retreat based on Landsat MSS, TM and ETM + imagery for the mid-1970s, late 1990s and mid-2000s and based on a SPOT scene for 2007. Our results show a decreasing glacierisation within the catchment, shrinking from 1210 +/- 30 km(2) (2.2% glacierisation) in the 1970s to 1019 +/- 25 km(2) (1.8% glacierisation) in the late 1990s and further down to 926 +/- 23 km(2) (1.7% glacierisation) in the mid-2000s, corresponding to an area loss of 23% in total. The analysis reveals spatially heterogeneous area loss within the catchment. This can be associated with different hypsometries, size distributions, aspects and presences of debris cover. Small glaciers (with an area <1 km(2)) suffered from a strong area loss within the 30-years investigation period.Trends in air temperature, precipitation and positive degree days (PDD) at climate stations suggest that the glacier retreat is likely to be driven by the increasing summer (April-September) temperature, rather than Changes in precipitation: In the period from 1960 to 2007, both summer air temperature and PDDs increased significantly at a rate of 0.19 degrees C/decade and 3.9 degrees C/decade respectively, whilst for precipitation no consistent trends were detected. However, rigorous attribution of changes is complicated by the variable glacier response times. In the two headwater sub-catchments of the Naryn basin, Small and Big Naryn, positive trends in spring and autumn discharge were detected and are likely to be associated with the enhanced snow and glacier melt driven by increasing temperatures in those seasons. However, no discharge trends in August the month with the largest expected glacier contribution - were detected. The strong, significantly positive trends in winter and early spring runoff are associated with strongly increasing winter temperatures and number of days with maximum daily temperature above the freezing point causing snow melt. Hence, increasing glacier area reduction can be explained by the prolongation of the melting season reducing accumulation rather than by increasing annual mean temperatures. Despite the high relative changes, the absolute increase in winter discharge is very small. (C) 2013 Elsevier B.V. All rights reserved.

A glacier inventory referring to the year 2007 was created for the Big Naryn basin based on satellite imagery. The 507 glaciers had a total area of 471km². Compared to the Soviet glacier inventory based on data from the mid 20th century, the total glacier area decreased by 23.4%. The shrinkage varies from 14% to 42% between individual mountain ranges. We discuss the possible causes for this considerable variation by analyzing and interpreting topographic parameters and differences between seven sub-regions.

Central Asian countries depend highly on water resources from snow and glacier melt, which has to be studied thoroughly to estimate water availability. However, the observation network in Central Asia is poor to carry out such studies in detail. Observations from space using remote sensing techniques might fill this observation gap, which needs to be validated. Therefore, this study evaluates the Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover product in Central Asia. For the evaluation, in situ snow depth data from 30 meteorological stations and higher resolution Landsat data are used. The results show an overall snow agreement between MODIS and ground observations of 93.1 and 92.7% for MODIS Terra and MODIS Aqua snow products, respectively. The agreement between MODIS and Landsat is 91.9% when considering snow and land agreements. The snow fraction product from MODIS is also validated using Landsat data, and varying accuracies are obtained. The main disadvantage of the MODIS snow cover product are the cloud induced gaps. Therefore, cloud covered pixels are eliminated using the ModSnow algorithm. Using the in situ data, the snow agreement of cloud removed snow cover data is checked, and an accuracy of 84.4% is achieved.