On the usefulness of remote sensing input data for spatially distributed hydrological modelling: case of the Tarim River basin in China

Abstract

Abstract:The ecological situation of the Tarim River basin in China seriously declined since the early 1950s, mainly due to a strong increase in water abstraction for irrigation purposes. To restore the ecological system and support sustainable development of the Tarim River basin region in China, more hydrological studies are demanded to properly understand the processes of the watershed and efficiently manage the water resources. Such studies are, however, complicated due to the limited data availability, especially in the mountainous headwater regions of the Tarim River basin. This study investigated the usefulness of remote sensing (RS) data to overcome that lack of data in the spatially distributed hydrological modelling of the basin. Complementary to the conventional station-based (SB) data, the RS products that are directly used in this study include precipitation, evapotranspiration and leaf area index. They are derived from raw image data of the Chinese Fengyun meteorological satellite and from the Moderate Resolution Imaging Spectroradiometer (MODIS). The MODIS land surface temperature was used to calculate the atmospheric temperature lapse rate to describe the temperature dependency on topographical variations. Moreover, MODIS-based snow cover images were used to obtain model initial conditions and as validation reference for the snow model component. Comparison of model results based on RS input versus conventional SB input exhibited similar results in terms of high and low river runoff extremes, cumulative runoff volumes in both runoff and snow melting seasons and spatial and temporal variability of snow cover. During summer time, when the snow cover shrinks in the permanent glacier region, it was found that the model resolution influences the model results dramatically, hence, showing the importance of detailed (RS based) spatially distributed input data.

Three perceptions of the evapotranspiration landscape: comparing spatial patterns from a distributed hydrological model, remotely sensed surface temperatures, and sub-basin water balances

“…But they agree with other researchers that incorporating additional site-specific information in a distributed hydrological model increases its robustness (Stisen et al, 2011). Especially remote sensing data are valued as a useful complement to station based time series (Finger et al, 2011;Liu et al, 2012).…”

Application of Remote Sensing Data to Constrain Operational Rainfall-Driven Flood Forecasting: A Review

“…The microwave satellite precipitation have also drawn increasing attention in hydrologic modelling. For example, the precipitation estimates from Chinese meteorological satellite Fengyun-2C were tested in the Tarim River Basin for streamflow simulation with the distributed MIKE SHE model, and it has been found that microwave satellite provided relatively high spatial resolution precipitation in sparsely gauged areas which exhibited positive impact on flow simulation especially during summer time [78].…”

Sensitivity analysis and implications for surface processes from a hydrological modelling approach in the Gunt catchment, high Pamir Mountains

“…Daniel (2011) gives a good comparison of different frequently used models but the number of different models is simply too large to be covered entirely. The integration of raster data sets has been implemented in different models such as the MIKE SHE (Cooper et al, 2006;Liu et al, 2012) or CREST (Khan et al, 2011) models, and several more examples of raster data input are available (Merritt et al, 2006;Stahl et al, 2008;Wood et al, 2004). While each of these models has specific qualities, none of them globally outperforms the others.…”

“…This is due to the high computational expense that is needed to create such data sets. The abundance and increasing accuracy in GCMs, RCMs, and remote sensing data has led to their greater use in hydrological modelling (Khan et al, 2011;Awange et al, 2011;Liu et al, 2012;Bookhagen and Burbank, 2010) and glacier evolution studies (Gardelle et al, 2012(Gardelle et al, , 2013Lutz et al, 2014;Sorg et al, 2012). In cold, arid, mountainous regions, GCMs are often favoured over remote sensing data.…”

“…Furthermore, direct measurement of ground air temperature from space is not possible. Remote sensing land surface temperatures (LSTs) are, however, being used, for example, to derive temperature lapse rates for interpolation of in situ data (Liu et al, 2012) or the calculation of evaporation (Samaniego et al, 2011). Use of LSTs as a proxy for ground air temperature has also been established, however only in lowlands (Deus et al, 2013).…”