Various investigations have been conducted to analyze the water-coverage area of the Aral Sea and the Aral Sea Basin(ASB). However, the investigations incorporated considerable uncertainty and the used water indices h...Various investigations have been conducted to analyze the water-coverage area of the Aral Sea and the Aral Sea Basin(ASB). However, the investigations incorporated considerable uncertainty and the used water indices had misclassification problem, which made different research groups present different results. Thus we first ascertain the boundaries of the ASB, the Syr and Amu river basins as well as their upper, middle and lower reaches. Then a four-band index for both liquid and solid water(ILSW) is proposed to address the misclassification problems of the classic water indices. ILSW is calculated by using the reflectance values of the green, red, near infrared, and thermal infrared bands, which combines the normalized difference water index(NDWI) and land surface temperature(LST) together. Validation results show that the ILSW water index has the highest accuracy by far in the Aral Sea Basin. Our results indicate that annual average decline of the water-coverage area was 963 km^(2) in the southern Aral Sea, whereas the northern Aral Sea has experienced little change. In the meanwhile, permanent ice and snow in upper reach of ASB has retreated considerably. Annual retreating rates of the permanent ice and snow were respectively 6233and 3841 km^(2) in upper reaches of Amu river basin(UARB) and Syr river basin(USRB). One of major reasons is that climate has become warmer in ASB. The climate change has caused serious water deficit problem. The water deficit had an increasing trend since the 1990s and its increasing rates was 3.778 billion m^(3) yearly on average. The total water deficit was 76.967 billion m^(3) on average in the whole area of ASB in the 2010s. However, up reaches of Syr river basin(USRB), a component area of ASB, had water surplus of 25.461 billion m^(3). These conclusions are useful for setting out a sustainable development strategy in ASB.展开更多
We propose a fundamental theorem for eco-environmental surface modelling(FTEEM) in order to apply it into the fields of ecology and environmental science more easily after the fundamental theorem for Earth’s surface ...We propose a fundamental theorem for eco-environmental surface modelling(FTEEM) in order to apply it into the fields of ecology and environmental science more easily after the fundamental theorem for Earth’s surface system modeling(FTESM). The Beijing-Tianjin-Hebei(BTH) region is taken as a case area to conduct empirical studies of algorithms for spatial upscaling, spatial downscaling, spatial interpolation, data fusion and model-data assimilation, which are based on high accuracy surface modelling(HASM), corresponding with corollaries of FTEEM. The case studies demonstrate how eco-environmental surface modelling is substantially improved when both extrinsic and intrinsic information are used along with an appropriate method of HASM. Compared with classic algorithms, the HASM-based algorithm for spatial upscaling reduced the root-meansquare error of the BTH elevation surface by 9 m. The HASM-based algorithm for spatial downscaling reduced the relative error of future scenarios of annual mean temperature by 16%. The HASM-based algorithm for spatial interpolation reduced the relative error of change trend of annual mean precipitation by 0.2%. The HASM-based algorithm for data fusion reduced the relative error of change trend of annual mean temperature by 70%. The HASM-based algorithm for model-data assimilation reduced the relative error of carbon stocks by 40%. We propose five theoretical challenges and three application problems of HASM that need to be addressed to improve FTEEM.展开更多
基金supported by the Key Program of National Natural Science Foundation of China(Grant No.42230708)the Strategic Priority Research Program of the Chinese Academy of Sciences,Pan-Third Pole Environment Study for a Green Silk Road(Grant No.XDA20060303)the K.C.Wong Education Foundation(Grant No.GJTD-2020-14)。
文摘Various investigations have been conducted to analyze the water-coverage area of the Aral Sea and the Aral Sea Basin(ASB). However, the investigations incorporated considerable uncertainty and the used water indices had misclassification problem, which made different research groups present different results. Thus we first ascertain the boundaries of the ASB, the Syr and Amu river basins as well as their upper, middle and lower reaches. Then a four-band index for both liquid and solid water(ILSW) is proposed to address the misclassification problems of the classic water indices. ILSW is calculated by using the reflectance values of the green, red, near infrared, and thermal infrared bands, which combines the normalized difference water index(NDWI) and land surface temperature(LST) together. Validation results show that the ILSW water index has the highest accuracy by far in the Aral Sea Basin. Our results indicate that annual average decline of the water-coverage area was 963 km^(2) in the southern Aral Sea, whereas the northern Aral Sea has experienced little change. In the meanwhile, permanent ice and snow in upper reach of ASB has retreated considerably. Annual retreating rates of the permanent ice and snow were respectively 6233and 3841 km^(2) in upper reaches of Amu river basin(UARB) and Syr river basin(USRB). One of major reasons is that climate has become warmer in ASB. The climate change has caused serious water deficit problem. The water deficit had an increasing trend since the 1990s and its increasing rates was 3.778 billion m^(3) yearly on average. The total water deficit was 76.967 billion m^(3) on average in the whole area of ASB in the 2010s. However, up reaches of Syr river basin(USRB), a component area of ASB, had water surplus of 25.461 billion m^(3). These conclusions are useful for setting out a sustainable development strategy in ASB.
基金supported by the National Natural Science Foundation of China (Grant Nos. 41930647, 41590844, 41421001 & 41971358)the Strategic Priority Research Program (A) of the Chinese Academy of Sciences (Grant No. XDA20030203)+1 种基金the Innovation Project of LREIS (Grant No. O88RA600YA)the Biodiversity Investigation, Observation and Assessment Program (2019–2023) of the Ministry of Ecology and Environment of China。
文摘We propose a fundamental theorem for eco-environmental surface modelling(FTEEM) in order to apply it into the fields of ecology and environmental science more easily after the fundamental theorem for Earth’s surface system modeling(FTESM). The Beijing-Tianjin-Hebei(BTH) region is taken as a case area to conduct empirical studies of algorithms for spatial upscaling, spatial downscaling, spatial interpolation, data fusion and model-data assimilation, which are based on high accuracy surface modelling(HASM), corresponding with corollaries of FTEEM. The case studies demonstrate how eco-environmental surface modelling is substantially improved when both extrinsic and intrinsic information are used along with an appropriate method of HASM. Compared with classic algorithms, the HASM-based algorithm for spatial upscaling reduced the root-meansquare error of the BTH elevation surface by 9 m. The HASM-based algorithm for spatial downscaling reduced the relative error of future scenarios of annual mean temperature by 16%. The HASM-based algorithm for spatial interpolation reduced the relative error of change trend of annual mean precipitation by 0.2%. The HASM-based algorithm for data fusion reduced the relative error of change trend of annual mean temperature by 70%. The HASM-based algorithm for model-data assimilation reduced the relative error of carbon stocks by 40%. We propose five theoretical challenges and three application problems of HASM that need to be addressed to improve FTEEM.
基金supported by the National Natural Science Foundation of China(41930647 and 62001260)the Strategic Priority Research Program(A)of the Chinese Academy of Sciences(XDA20030203)。
