Reconstruction of Hydrometeorological Time Series and Its Uncertainties for the Kaidu River Basin Using Multiple Data Sources
2013-09-27
Xinjiang, a typical mountain–basin system that lies in the semiarid and arid areas of Northwest China, temperature, precipitation, and streamflow had increased obviously during the past 50 years. Climate change also significantly influenced streamflow of rivers located at the southern slope of Tianshan Mountains. Unfortunately, the recorded meteorological and hydrological data in Xinjiang prior to the 1950 are seldom available. Consequently, there is no exact and believable answer whether the time scale of climate or streamflow change is decadal or centennial.
However, in the past decades, few studies focus on drawing upon longer-term data available at nearby locations to study climate variability in Xinjiang. Based on the assessment of the relations between existing station data from the Kaidu River Basin and three sources of data including station data from Central Asia, Climatic Research Unit (CRU), and global climate model (GCM) data, this study tried to reconstruct the time series (TS) of monthly average temperature (MAT), monthly accumulated precipitation (MAP), and monthly accumulated runoff (MAR) during 1901–1960 in the Kaidu River Basin using the Delta method and the three-layered feed forward neural network with backpropagation algorithm (TLBP-FFNN) model.
The result found that the Delta method performed very well for calibrated and verified MAT in the Kaidu River Basin based on the monthly observed meteorological data from Central Asia, the monthly grid climatic data from CRU, and the Coupled Model Intercomparison Project Phase 3 (CMIP3) dataset from 1961 to 2000. Although calibration and verification of MAP did not perform as well as MAT, MAP at Bayinbuluke station, an alpine meteorological station, showed a satisfactory result based on the data from CRU and CMIP3, indicating that the Delta method can be applied to reconstruct MAT in the Kaidu River Basin on the basis of the selected three data sources and MAP in the mountain area based on CRU and CMIP3. MAR at Dashankou station, a hydrological gauge station on the verge of the Tianshan Mountains, from 1961 to 2000 was well calibrated and verified using the TLBP-FFNN model with structure (8,1,1) by taking MAT and MAP of four meteorological stations from observation; CRU and CMIP3 data, respectively, as inputs; and the model was expanded to reconstruct TS during 1901–1960. While the characteristics of annual periodicity were depicted well by the TS of MAT, MAP, and MAR reconstructed over the target stations during the period 1901–1960, different high frequency signals were captured also. The annual average temperature (AAT) showed a significant increasing trend during the 20th century, but annual accumulated precipitation (AAP) and annual accumulated runoff (AAR) do not.
Although some uncertainties exist in the hydrometeorological reconstruction, this work should provide a viable reference for studying long-term change of climate and water resources as well as risk assessment of flood and drought in the Kaidu River Basin, a region of fast economic development. The result was published in Theoretical and Applied Climatology in July 2013.
However, in the past decades, few studies focus on drawing upon longer-term data available at nearby locations to study climate variability in Xinjiang. Based on the assessment of the relations between existing station data from the Kaidu River Basin and three sources of data including station data from Central Asia, Climatic Research Unit (CRU), and global climate model (GCM) data, this study tried to reconstruct the time series (TS) of monthly average temperature (MAT), monthly accumulated precipitation (MAP), and monthly accumulated runoff (MAR) during 1901–1960 in the Kaidu River Basin using the Delta method and the three-layered feed forward neural network with backpropagation algorithm (TLBP-FFNN) model.
The result found that the Delta method performed very well for calibrated and verified MAT in the Kaidu River Basin based on the monthly observed meteorological data from Central Asia, the monthly grid climatic data from CRU, and the Coupled Model Intercomparison Project Phase 3 (CMIP3) dataset from 1961 to 2000. Although calibration and verification of MAP did not perform as well as MAT, MAP at Bayinbuluke station, an alpine meteorological station, showed a satisfactory result based on the data from CRU and CMIP3, indicating that the Delta method can be applied to reconstruct MAT in the Kaidu River Basin on the basis of the selected three data sources and MAP in the mountain area based on CRU and CMIP3. MAR at Dashankou station, a hydrological gauge station on the verge of the Tianshan Mountains, from 1961 to 2000 was well calibrated and verified using the TLBP-FFNN model with structure (8,1,1) by taking MAT and MAP of four meteorological stations from observation; CRU and CMIP3 data, respectively, as inputs; and the model was expanded to reconstruct TS during 1901–1960. While the characteristics of annual periodicity were depicted well by the TS of MAT, MAP, and MAR reconstructed over the target stations during the period 1901–1960, different high frequency signals were captured also. The annual average temperature (AAT) showed a significant increasing trend during the 20th century, but annual accumulated precipitation (AAP) and annual accumulated runoff (AAR) do not.
Although some uncertainties exist in the hydrometeorological reconstruction, this work should provide a viable reference for studying long-term change of climate and water resources as well as risk assessment of flood and drought in the Kaidu River Basin, a region of fast economic development. The result was published in Theoretical and Applied Climatology in July 2013.