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This research aims to provide the scientific methodologies which are required to analyze the availability and variability of water resources in the arid and semi-arid region of the Tarim river basin in north-west China. The methods consist of a combination of lumped conceptual and more detailed spatially distributed hydrological models, statistical analysis techniques and remotely sensed (RS) data. They can be applied by the local water authorities to obtain an improved understanding of the water system responses to human activities and as decision support tools (scenario analysis of water management alternatives). The impacts of different alternative management strategies can be simulated and optimal choices made in support of a sustainable development of the local society. The developed methodologies and tools were applied to study the past and future evolutions in the surface and groundwater resources for two headwater basins and along the downstream river reaches. Given the exclusive geographical, meteorological and hydrological features of the Tarim basin, and the limited data availability, major challenges were faced in the development of the methodologies. Based on the specific features of lumped conceptual models and spatially distributed models, the subbasins of the headwaters of the Tarim basin were simulated based on lumped conceptual models, while the downstream area of the main Tarim river was modelled by means of a spatially distributed model. In the downstream area, the runoff contributions from the headwaters cumulate and affect the downstream flow conditions, water availability for irrigation, groundwater resources and vegetation/ecosystems. The construction of the lumped conceptual model was based on a top-down approach, using a step-wise model-structure identification and calibration procedure. This procedure makes use of the results of statistical time series processing (runoff subflow filtering, quick and slow flow hydrograph separation) applied to the available river flow series. The procedure has been extended to account for the seasonal snow melting and permanent glacier melting in the headwater basins. The seasonal snow melting submodel was added according to an adjusted degree-day equation. The submodel of the permanent glacier melting is based on the cumulative thermal input above a critical temperature value. The advantages of the lumped conceptual models are the fast computations, calibration and validation, its flexible structure and less strict data requirement. The lumped conceptual model is also restricted by its own character that the simulated areas have to own sufficient observation records at their outlets. The spatially distributed model is based on a larger amount of physical information and provides spatially variable results on runoff discharges, groundwater levels, soil water content, etc., but has disadvantages due to the long computational times, the time consuming calibration process, huge (spatial) data needs and related overparameterization. To overcome the data limitation problem, data from the traditional gauging stations were complemented with remotely sensed data from multiple sources. The spatially distributed model was calibrated in the conventional way based on the station data. In a second step, the station based (SB) time series of precipitation and evapotranspiration were replaced by remotely sensed (RS) based series without changing the calibrated parameter values. Additional RS products, for snow cover, LAI and land surface temperature, were used as validation reference or for estimation of specific parameter sets. By comparing the results from the SB and RS based inputs, it was shown that the RS inputs enable replacement of the SB data. The spatially distributed model is also used to simulate the interaction between the channel flow and the groundwater. This required a full hydrodynamic model to be implemented for the downstream Tarim river and linked to the spatially distributed model. It was found that the channel flow is the unique source to recharge the aquifer. After construction and validation of the hydrological and hydrodynamic models, they were considered useful for scenario impact analysis of climate and landuse changes. Climate scenarios were constructed based on an ensemble approach after statistical analysis of a large set of General Circulation Model (GCM) simulation results (IPCC AR4 Archive). After simulation in the models, the impact results of both the lumped conceptual model and spatially distributed model show a significant increase of the daily flow peaks. This is due to snow melting as a result of temperature rise and increase in precipitation in the winter season. Daily low flows show increasing or decreasing trends depending on the climate change scenario considered, hence the low flow changes being highly uncertain. Although the impact results for the two types of models are similar, there are some differences due to the difference in model structure. The lumped conceptual model impact results show a lower variation in flow changes in comparison with the spatially distributed model results; hence showing the importance to consider both the uncertainties in the climate scenarios and the influence of differences in model or model type. The landuse change scenarios were derived from historical remotely sensed images of the years of 1972, 1990, 2000 and 2007. They were implemented in the spatially distributed model to investigate the landuse change impact on the water availability by emanating the relationship between groundwater storage vs. cumulative leaf area index (LAI) and irrigation area vs. river flow availabilities. It was concluded that the cumulative leaf area index (LAI) / surface vegetation cover highly depends on the groundwater storage. The efficiency to restore the local ecosystem by artificial water assignment is much less than under natural conditions. The expansion of the irrigated farmlands since the 1950s strongly affected the availability of water resources in a negative way, and boosted relocation of farmland in order to acquire sufficient water resources.

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