. Water resources are essential to the ecosystem and social economy in the desert and oasis of the arid Tarim River basin, northwestern China, and expected to be vulnerable to climate change. It has been demonstrated that regional climate models (RCMs) provide more reliable results for a regional impact study of climate change (e.g., on water resources) than general circulation models (GCMs). However, due to their considerable bias it is still necessary to apply bias correction before they are used for water resources research. In this paper, after a sensitivity analysis on input meteorological variables based on the Sobol' method, we compared five precipitation correction methods and three temperature correction methods in downscaling RCM simulations applied over the Kaidu River basin, one of the headwaters of the Tarim River basin. Precipitation correction methods applied include linear scaling (LS), local intensity scaling (LOCI), power transformation (PT), distribution mapping (DM) and quantile mapping (QM), while temperature correction methods are LS, variance scaling (VARI) and DM. The corrected precipitation and temperature were compared to the observed meteorological data, prior to being used as meteorological inputs of a distributed hydrologic model to study their impacts on streamflow. The results show (1) streamflows are sensitive to precipitation, temperature and solar radiation but not to relative humidity and wind speed; (2) raw RCM simulations are heavily biased from observed meteorological data, and its use for streamflow simulations results in large biases from observed streamflow, and all bias correction methods effectively improved these simulations; (3) for precipitation, PT and QM methods performed equally best in correcting the frequency-based indices (e.g., standard deviation, percentile values) while the LOCI method performed best in terms of the time-series-based indices (e.g., Nash–Sutcliffe coefficient, R2); (4) for temperature, all correction methods performed equally well in correcting raw temperature; and (5) for simulated streamflow, precipitation correction methods have more significant influence than temperature correction methods and the performances of streamflow simulations are consistent with those of corrected precipitation; i.e., the PT and QM methods performed equally best in correcting flow duration curve and peak flow while the LOCI method performed best in terms of the time-series-based indices. The case study is for an arid area in China based on a specific RCM and hydrologic model, but the methodology and some results can be applied to other areas and models.

https://hess.copernicus.org/articles/19/2547/2015/hess-19-2547-2015.pdf

Comparing bias correction methods in downscaling meteorological variables for a hydrologic impact study in an arid area in China

Climate change and water resource issues are global problems of common concern to the international community, and they are major bottlenecks affecting the eco-environment and sustainable socio-economic development in the arid region of Northwest China. On the basis of results from previous studies, this paper points out that the unique landscape of Northwest China increases the complexity and uncertainty of the climate system. This paper analyzes the key constraints on socio-economic development and ecological security in the region, discusses the impact of climate change on water resources in Northwest China, identifies common themes and the main problems present in research on climate change and water resources in the arid northwest region, and finally, based on the importance and urgency of conducting research on the region’s water resources, proposes scientific problems that need to be addressed: first, the impact of climate change on the formation, conversion and future trends of water resources in the region; second, bidirectional coupling of high-resolution regional climate models and water cycle models of arid region land surface patterns; third, the impact of climate change and human activities on water resources of the arid northwest region. Through consideration and discussion of the above, this paper seeks to further clarify specific areas of research on pressing issues related to climate change and water resources in Northwest China, so as to establish a solid scientific basis for significantly enhancing our ability to respond to climate change and water shortages.

/pdf/water-resource-formation-and-conversion-and-water-security-zvka4pt5bf.pdf

Water resource formation and conversion and water security in arid region of Northwest China

Natural disasters often show highly heterogeneous character due to complex geo-environmental settings. The spatial distribution of landslides is generally clustered at different scales. In this paper, we proposed a methodology for landslide susceptibility mapping (LSM) with consideration of spatial correlation and distribution of clustered landslide data. To quantify the spatial correlation of landslides, a normalized spatial-correlated scale index (NSCI) was introduced. Based on the definition of landslide frequency ratio, calibrated landslide potential index (CLPI) was proposed to account for the effect of landslide clustering. Considering the fractal distribution of landslides, the variable fractal dimension model (VFDM) was introduced to measure the spatial association between clustered landslides and conditional factors. Based on the definition of fractal dimension (D), the weights of the factors were obtained from fractal perspective. We proposed a weighted calibrated landslide potential model (WCLPM), obtained by the combination of CLPI values and weights of the factors. The proposed method is illustrated by example in Xinjiang, NW China, where landslide points are clustered at regional scale. In the example, the landslides were randomly split into two groups: one for building landslide model (training dataset) and the other for validating the model (validating dataset). Five landslide conditional factors (lithology, tectonic faults, elevation, slope, aspect) were selected, processed, and analyzed in a geographic information system (GIS) environment. Predictive accuracy of the WCLPM was evaluated and compared based on the calculation of area under the prediction-rate curve (AUPRC). The example shows that the proposed WCLPM provides good prediction for the study area (AUPRC = 0.8700). This study provided a novel and practical method for LSM.

An integrated approach for landslide susceptibility mapping by considering spatial correlation and fractal distribution of clustered landslide data

Spatial and temporal characterization of standard duration-maximum precipitation over Black Sea Region in Turkey

The occurrence rates of floods in Tarim River basin, the largest arid basin in China, were estimated using the Peak-over-Threshold (POT) technique. The intra-annual, seasonal and inter-annual clustering of floods was then analyzed using the Cox regression model, month frequency method and dispersion index, respectively. Possible impacts of climate indices on the occurrence rates were also investigated. Both NAO and AO are selected as significant covariates to occurrence rates of floods in Tarim River basin by Cox regression model, suggesting occurrence of flood events is not independent, but exhibits temporal clustering in intra-annual scale. On the basis of the results of the station and region-wide modeling by Cox regression model, we suggest using a model in which the rate of occurrence depends on monthly averaged NAO or AO. The Cox regression model not only can be used to assess the time-varying rate of flood occurrence, but also has the capability to forecast the predictors. Flood occurrence time and probability of exceedance are changing with climate index from negative to positive on both station and region scale. In addition, seasonal clustering of station-based floods and regional observed floods are also identified with mainly concentrating from June to August. Meanwhile, dispersion index is used to evaluate the inter-annual clustering of annual number of flood occurrences both on station and region. We found that inter-annual clustering of regional floods is more evident than that of station-based floods, indicating that regional observed flood records are generally over-dispersed with a tendency for flood events to cluster in time.

/pdf/temporal-clustering-of-floods-and-impacts-of-climate-indices-2co6k46ifb.pdf

Temporal clustering of floods and impacts of climate indices in the Tarim River basin, China

We examined spatial distribution characteristics of extreme hydrological events in Xinjiang, China, using district data from 1901 to 2010. Frequency distribution showed a general symmetry along the Tianshan Mountains, with even distribution in Junggar Basin and Tarim Basin. Frequency was more in the north-west than in the south-east. The maximum incidence was in west Tianshan Mountains and generally decreased south-eastward. There were significant regional variations in type distribution. Rainstorm floods were more common in central Xinjiang. Hailstorms mainly occurred in the central Junggar Basin, the southern slope of the western Tianshan Mountains and north-west of Tarim Basin. Debris flow was mainly distributed in Ili Valley and the central northern Tianshan Mountains. Glacier lake outburst floods were more common in the Karakorum Mountains and southern slopes of the western Tianshan Mountains. Ice floods were mainly distributed in the western Tianshan Mountains. Snow hazards were mainly distributed in the wide northern areas, especially the Altai Mountains and Hamilton Basin. Snowmelt floods were mainly distributed in the Tacheng Basin and Ili Valley. The incidence of extreme hydrological events was greatly affected by weather systems and terrain features.

Spatial distribution of the extreme hydrological events in Xinjiang, north-west of China

We examined intra-annual characteristics and decadal change of extreme hydrological events occurring from 1901 to 2010 in Xinjiang, China, using concentration degree, concentration index, and Mann–Kendall tests The results indicated that the concentration index in Xinjiang reached a maximum in summer for all areas, demonstrating that extreme hydrological events occurred mainly during summer (although Altay also showed a high winter concentration index) Intra-annual distribution was most concentrated in Turpan and Urumqi, followed by Kuytun–Shihezi and Aksu, with the concentration degree smallest in Altay The frequency of extreme hydrological events exhibited an obvious increasing trend from 1901 to 2010, particularly post 1970s Based on the results obtained in this study, the frequency, magnitude, and intensity of extreme hydrological events are expected to increase over time In addition, the concentration degree and concentration index used to analyze intra-annual distribution of extreme hydrological events were proven to be reliable and will be useful for future studies

Intra-annual distribution and decadal change in extreme hydrological events in Xinjiang, Northwestern China

Water resources systems in arid regions are sensitive to climate change, which critically impacts the water cycle. In this study, we applied historical hydrometeorological data, CMIP5 data, and a large‐scale hydrological model (Community Land Model–Distributed Time‐Variant Gain Model [CLM–DTVGM]) to study the impact of climate change on the hydrological cycle (i.e., runoff, actual evapotranspiration (ETa), and terrestrial water storage [TWS]) under different scenarios at the Aksu River basin (ARB) located in the arid region of northwest China. The primary findings of this study: (a) As the determination coefficient (R2) and Nash–Sutcliffe efficiency coefficient (NSE) reached desirable levels (R2 ≥ 0.583, NSE ≥ 0.371, and root‐mean‐square error ≤ 155.727), the CLM–DTVGM achieved a better simulation of runoff in the ARB; under climate change, the runoff depth in the irrigation area became shallower and followed a decreasing trend, with a minimum depth of 0.5 mm and a significant decreasing trend of −8 mm·a−1. (b) Along with changes in the precipitation and temperature of the baseline period (i.e., 1980–2010), runoff, ETa, and TWS were predicted to change significantly in future scenarios. (c) Climate change significantly impacted the historical runoff from the Shaliguilanke and Xiehela hydrological stations, with correlation coefficients larger than 0.9; however, the runoff from the Alaer hydrological station was not affected. However, runoff, ETa, and TWS in the ARB were very closely correlated with climate change in the future scenarios, with correlation coefficients exceeding 0.9. Related research in the future would be important for guiding the sustainable development of the ARB.

Effects of climate change on major elements of the hydrological cycle in Aksu River basin, northwest China

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Spatial distribution of the extreme hydrological events in Xinjiang, north-west of China

Intra-annual distribution and decadal change in extreme hydrological events in Xinjiang, Northwestern China

Effects of climate change on major elements of the hydrological cycle in Aksu River basin, northwest China