Given the heightened competition for water in energy,food,and the environment in Africa,it is essential to implement sound integrated plans for basin or regional sustainable development.Zambezi River Basin(ZRB),one of...Given the heightened competition for water in energy,food,and the environment in Africa,it is essential to implement sound integrated plans for basin or regional sustainable development.Zambezi River Basin(ZRB),one of the least developed basins in the world,is under development with great ambition for hydropower and irrigation infrastructure.Here,we proposed a framework to assess different water usage trajectories for agricultural and hydropower development scenarios with data derived from big earth data method.Three future scenarios were set for irrigaiton expansion and development hydropower construction according to current plan,global average and high level,respectively.Using spatial analysis methods,average evapotranspiration(ET)difference before and after irrigation expansion and reservoir construction was used to estimate water usage trajectories.Results show that the total available water resource for ZRB is estimated as 111.8 km3.Due to irrigation and reservoirs construction,additional annual water consumption is estimated to be 0.9 and 14.2 km3 for 2017,respectively.By analyzing the water-energy-food-environment(WEFE)nexus given water availability constraints,we found that the water development boundary in the ZRB could support increases in both irrigation proportion and dam density to global average levels of 20%and 0.56/104 km2,respectively,without degrading the environment.The proposed paradigm for assessing water resources has the potential to endow the ZRB with significant capacity to support the achievement of relevant Sustainable Development Goals(SDGs).展开更多
Drought is one of the most destructive disasters in the Lancang River Basin, which is an ungauged basin with strong heterogeneity on terrain and climate. Our validation suggested the version-6 monthly TRMM multi-satel...Drought is one of the most destructive disasters in the Lancang River Basin, which is an ungauged basin with strong heterogeneity on terrain and climate. Our validation suggested the version-6 monthly TRMM multi-satellite precipitation analysis （TMPA; 3B43 V.6） product during the period 1998 to 2009 is an alternative precipitation data source with good accuracy. By using the standard precipitation index （SPI）, at the grid point （0.25°×0.25°） and sub-basin spatial scales, this work assessed the effectiveness of TMPA in drought monitoring during the period 1998 to 2009 at the 1-month scale and 3-months scale; validated the monitoring accuracy of TMPA for two severe droughts happened in 2006 and 2009, respectively. Some conclusions are drawn as follows. （1） At the grid point spatial scale, in comparison with the monitoring results between rain gauges （SPIlg） and TMPA grid （SPIls）, both agreed well at the 1-month scale for most of the grid points and those grid points with the lowest critical success index （CSI） are distributed in the middle stream of the Lancang River Basin. （2） The same as SPIls, the consistency between SPI3s and SPI3g is good for most of the grid points at the 3-months scale, those grid points with the lowest were concentrated in the middle stream and downstream of the Lancang River Basin. （3） At the 1-month scale and 3-months scale, CSI ranged from 50% to 76% for most of the grid points, which demonstrated high accuracy of TMPA in drought monitoring. （4） At the 3-months scale, based on TMPA basin-wide precipitation estimates, though we tended to overestimate （underestimate） the peaks of dry or wet events, SPI3s detected successfully the occurrence of them over the five sub-basins at the most time and captured the occurrence and development of the two severe droughts happened in 2006 and 2009. This analysis shows that TMPA has the potential for drought monitoring in data-sparse regions.展开更多
This study designed an approach to derive land-cover in the South Africa with insufficient ground samples, and made a case demonstration in Nzhelele and Levhuvu catchments, South Africa. The method was developed based...This study designed an approach to derive land-cover in the South Africa with insufficient ground samples, and made a case demonstration in Nzhelele and Levhuvu catchments, South Africa. The method was developed based on an integration of Landsat 8, Sentinel-1, and Shuttle Radar Topography Mission(SRTM) Digital Elevation Model(DEM), and the Google Earth Engine(GEE) platform. Random forest classifier with 300 trees is employed as land-cover classification model. In order to overcome the defect of insufficient ground data, the stratified sampling method was used to generate the training and validation samples from the existing land-cover product. Likewise, in order to recognize different land-cover categories, the percentile and monthly median composites were employed to expand input metrics of random forest classifier. Results showed that the overall accuracy of the land-cover of Nzhelele and Levhuvu catchments, South Africa in 2017–2018 reached to 76.43%. Three important results can be drawn from our research. 1) The participation of Sentinel-1 data can slightly improve overall accuracy of land-cover while its contribution on land-cover classification varied with land types. 2) Under-fitting problem was observed in the training of non-dominant land-cover categories using the random sampling, the stratified sampling method is recommended to make sure the classification accuracy of non-dominant classes. 3) When related reflectance bands participated in the training process, individual Normalized Difference Vegetation index(NDVI), Enhanced Vegetation Index(EVI), Soil Adjusted Vegetation Index(SAVI), Normalized Difference Built-up Index(NDBI) have little effect on final land-cover classification result.展开更多
针对在测试资源紧张的情况下所面临的不同测试技术中测试方法选择问题,阐明了对基于结构覆盖和基于状态识别的测试生成技术进行实验评估的必要性,以10个有限状态机(finite state machine,FSM)应用实例为实验对象,从测试开销和错误覆盖...针对在测试资源紧张的情况下所面临的不同测试技术中测试方法选择问题,阐明了对基于结构覆盖和基于状态识别的测试生成技术进行实验评估的必要性,以10个有限状态机(finite state machine,FSM)应用实例为实验对象,从测试开销和错误覆盖能力两方面对这两种技术进行了实证研究,为FSM一致性测试中这两种技术的选择应用提供了经验性的参考建议。展开更多
基金Under the auspices of National Natural Science Foundation of China(No.41861144019,W2412015,42301409)。
文摘Given the heightened competition for water in energy,food,and the environment in Africa,it is essential to implement sound integrated plans for basin or regional sustainable development.Zambezi River Basin(ZRB),one of the least developed basins in the world,is under development with great ambition for hydropower and irrigation infrastructure.Here,we proposed a framework to assess different water usage trajectories for agricultural and hydropower development scenarios with data derived from big earth data method.Three future scenarios were set for irrigaiton expansion and development hydropower construction according to current plan,global average and high level,respectively.Using spatial analysis methods,average evapotranspiration(ET)difference before and after irrigation expansion and reservoir construction was used to estimate water usage trajectories.Results show that the total available water resource for ZRB is estimated as 111.8 km3.Due to irrigation and reservoirs construction,additional annual water consumption is estimated to be 0.9 and 14.2 km3 for 2017,respectively.By analyzing the water-energy-food-environment(WEFE)nexus given water availability constraints,we found that the water development boundary in the ZRB could support increases in both irrigation proportion and dam density to global average levels of 20%and 0.56/104 km2,respectively,without degrading the environment.The proposed paradigm for assessing water resources has the potential to endow the ZRB with significant capacity to support the achievement of relevant Sustainable Development Goals(SDGs).
基金Basic work of the Ministry of Science and Technology of China,No.2008FY110300-01
文摘Drought is one of the most destructive disasters in the Lancang River Basin, which is an ungauged basin with strong heterogeneity on terrain and climate. Our validation suggested the version-6 monthly TRMM multi-satellite precipitation analysis （TMPA; 3B43 V.6） product during the period 1998 to 2009 is an alternative precipitation data source with good accuracy. By using the standard precipitation index （SPI）, at the grid point （0.25°×0.25°） and sub-basin spatial scales, this work assessed the effectiveness of TMPA in drought monitoring during the period 1998 to 2009 at the 1-month scale and 3-months scale; validated the monitoring accuracy of TMPA for two severe droughts happened in 2006 and 2009, respectively. Some conclusions are drawn as follows. （1） At the grid point spatial scale, in comparison with the monitoring results between rain gauges （SPIlg） and TMPA grid （SPIls）, both agreed well at the 1-month scale for most of the grid points and those grid points with the lowest critical success index （CSI） are distributed in the middle stream of the Lancang River Basin. （2） The same as SPIls, the consistency between SPI3s and SPI3g is good for most of the grid points at the 3-months scale, those grid points with the lowest were concentrated in the middle stream and downstream of the Lancang River Basin. （3） At the 1-month scale and 3-months scale, CSI ranged from 50% to 76% for most of the grid points, which demonstrated high accuracy of TMPA in drought monitoring. （4） At the 3-months scale, based on TMPA basin-wide precipitation estimates, though we tended to overestimate （underestimate） the peaks of dry or wet events, SPI3s detected successfully the occurrence of them over the five sub-basins at the most time and captured the occurrence and development of the two severe droughts happened in 2006 and 2009. This analysis shows that TMPA has the potential for drought monitoring in data-sparse regions.
基金Under the auspices of National Natural Science Foundation of China(No.4171101213,41561144013,41991232)National Key R&D Program of China(No.2016YFC0503401,2016YFA0600304)International Partnership Program of Chinese Academy of Sciences(No.121311KYSB20170004)。
文摘This study designed an approach to derive land-cover in the South Africa with insufficient ground samples, and made a case demonstration in Nzhelele and Levhuvu catchments, South Africa. The method was developed based on an integration of Landsat 8, Sentinel-1, and Shuttle Radar Topography Mission(SRTM) Digital Elevation Model(DEM), and the Google Earth Engine(GEE) platform. Random forest classifier with 300 trees is employed as land-cover classification model. In order to overcome the defect of insufficient ground data, the stratified sampling method was used to generate the training and validation samples from the existing land-cover product. Likewise, in order to recognize different land-cover categories, the percentile and monthly median composites were employed to expand input metrics of random forest classifier. Results showed that the overall accuracy of the land-cover of Nzhelele and Levhuvu catchments, South Africa in 2017–2018 reached to 76.43%. Three important results can be drawn from our research. 1) The participation of Sentinel-1 data can slightly improve overall accuracy of land-cover while its contribution on land-cover classification varied with land types. 2) Under-fitting problem was observed in the training of non-dominant land-cover categories using the random sampling, the stratified sampling method is recommended to make sure the classification accuracy of non-dominant classes. 3) When related reflectance bands participated in the training process, individual Normalized Difference Vegetation index(NDVI), Enhanced Vegetation Index(EVI), Soil Adjusted Vegetation Index(SAVI), Normalized Difference Built-up Index(NDBI) have little effect on final land-cover classification result.
文摘针对在测试资源紧张的情况下所面临的不同测试技术中测试方法选择问题,阐明了对基于结构覆盖和基于状态识别的测试生成技术进行实验评估的必要性,以10个有限状态机(finite state machine,FSM)应用实例为实验对象,从测试开销和错误覆盖能力两方面对这两种技术进行了实证研究,为FSM一致性测试中这两种技术的选择应用提供了经验性的参考建议。
