Regional hydrology heterogeneity and the response to climate and land surface changes in arid alpine basin, northwest China

While the Budyko framework has been a simple and convenient tool to assess runoff (Q) responses to climatic and surface changes, it has been unclear how parameters of a Budyko function represent the vertical land-atmosphere interactions. Here, we explicitly derived a two-parameter equation by correcting a boundary condition of the Budyko hypothesis. The correction enabled for the Budyko function to reflect the evaporative demand (Ep) that actively responds to soil moisture deficiency. The derived two-parameter function suggests that four physical variables control surface runoff; namely, precipitation (P), potential evaporation (Ep), wet-environment evaporation (Ew), and the catchment properties (n). We linked the derived Budyko function to a definitive complementary evaporation principle, and assessed the relative elasticities of Q to climatic and land surface changes. Results showed that P is the primary control of runoff changes in most of river basins across the world, but its importance declined with climatological aridity. In arid river basins, the catchment properties play a major role in changing runoff, while changes in Ep and Ew seem to exert minor influences on Q changes. It was also found that the two-parameter Budyko function can capture unusual negative correlation between the mean annual Q and Ep. This work suggests that at least two parameters are required for a Budyko function to properly describe the vertical interactions between the land and the atmosphere.

Download Full-text

Preliminary Evaluation of the Two Collection 6 Modis Land Surface Temperature Products in an Arid Area of Northwest China

IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.2018.8517282 ◽

2018 ◽

Author(s):

Hua Li ◽

Yikun Yang ◽

Yongming Du ◽

Biao Cao ◽

Qinhuo Liu

Keyword(s):

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Northwest China ◽

Arid Area ◽

Preliminary Evaluation ◽

Modis Land Surface Temperature

Download Full-text

Thermal and moisture response to land surface changes across different ecosystems over Heilong-Amur River Basin

The Science of The Total Environment ◽

10.1016/j.scitotenv.2021.151799 ◽

2021 ◽

pp. 151799

Author(s):

Tingxiang Liu ◽

Lingxue Yu ◽

Kun Bu ◽

Jiuchun Yang ◽

Fengqin Yan ◽

...

Keyword(s):

River Basin ◽

Land Surface ◽

Amur River Basin ◽

Amur River ◽

Surface Changes

Download Full-text

Temporal and spatial variations of sandstorm and the related meteorological influences over northern China in the 21st century

10.5194/egusphere-egu21-14615 ◽

2021 ◽

Author(s):

Jie Yang ◽

Tianliang Zhao

Keyword(s):

Land Surface ◽

Source Region ◽

Northern China ◽

Northwest China ◽

Gobi Desert ◽

Taklimakan Desert ◽

Observation Data ◽

Average Wind Speed ◽

Modis Ndvi ◽

Temporal And Spatial

In this study, we used the sandstorm data of 233 meteorological stations in northern China, conventional meteorological observation data and MODIS-NDVI data in the 40 years from 1980 to 2019 to analyze the spatio-temporal variation of sandstorms in northern China and its related meteorological effects in this century.The results show that: 1) The average number of sandstorm days in northern China has been fluctuating and decreasing since the beginning of this century, and increasing from 2017 to 2019. Spring is the main season of dust storm, and the springtime proportion of sandstorm days decreases year by year. 2) In the 1980s and 1990s, sandstorms covered almost covered the whole northwest region; Since the beginning of this century, the range of sandstorm days in the whole Northwest China has shown an obvious decadal downward trend. The spatial pattern of sandstorm days in northern China has been shrinking and moving westward since 2000, and the dominant position of the Gobi Desert in the Asian dust source region has been decreasing year by year. The high sandstorm days were located in the Taklimakan Desert with the increasing trend of sandstorm days year by year. 3) The temporal and spatial variation of sandstorm days in northern China is closely related to the increase of vegetation cover with the greenness and wetness of the land surface, the decreases of average wind speed and gale days, and the significant increase of annual precipitation in northern China after 2000.

Download Full-text

Improvement of Clustering Methods for Modelling Abrupt Land Surface Changes in Satellite Image Fusions

Remote Sensing ◽

10.3390/rs11151759 ◽

2019 ◽

Vol 11 (15) ◽

pp. 1759 ◽

Cited By ~ 4

Author(s):

Detang Zhong ◽

Fuqun Zhou

Keyword(s):

Land Surface ◽

Satellite Image ◽

Weighted Average ◽

Clustering Methods ◽

Fusion Model ◽

Dynamic Prediction ◽

New Methods ◽

Satellite Sensors ◽

Spectral Mixing ◽

Surface Changes

A key challenge in developing models for the fusion of surface reflectance data across multiple satellite sensors is ensuring that they apply to both gradual vegetation phenological dynamics and abrupt land surface changes. To better model land cover spatial and temporal changes, we proposed previously a Prediction Smooth Reflectance Fusion Model (PSRFM) that combines a dynamic prediction model based on the linear spectral mixing model with a smoothing filter corresponding to the weighted average of forward and backward temporal predictions. One of the significant advantages of PSRFM is that PSRFM can model abrupt land surface changes either through optimized clusters or the residuals of the predicted gradual changes. In this paper, we expanded our approach and developed more efficient methods for clustering. We applied the new methods for dramatic land surface changes caused by a flood and a forest fire. Comparison of the model outputs showed that the new methods can capture the land surface changes more effectively. We also compared the improved PSRFM to two most popular reflectance fusion algorithms: Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and Enhanced version of STARFM (ESTARFM). The results showed that the improved PSRFM is more effective and outperforms STARFM and ESTARFM both visually and quantitatively.

Download Full-text

Evaluation of Collection-6 MODIS Land Surface Temperature Product Using Multi-Year Ground Measurements in an Arid Area of Northwest China

Remote Sensing ◽

10.3390/rs10111852 ◽

2018 ◽

Vol 10 (11) ◽

pp. 1852 ◽

Cited By ~ 13

Author(s):

Lei Lu ◽

Tingjun Zhang ◽

Tiejun Wang ◽

Xiaoming Zhou

Keyword(s):

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Northwest China ◽

Bare Soil ◽

Vegetation Monitoring ◽

Modis Land Surface Temperature ◽

Global Circulation Models ◽

In Situ Data

Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) products are widely used in ecology, hydrology, vegetation monitoring, and global circulation models. Compared to the collection-5 (C5) LST products, the newly released collection-6 (C6) LST products have been refined over bare soil pixels. This study aims to evaluate the C6 MODIS 1-km LST product using multi-year in situ data covering barren surfaces. Evaluation using all in situ data shows that the MODIS C6 LSTs are underestimated with a root-mean-square error (RMSE) of 2.59 K for the site in the Gobi area, 3.05 K for the site in the sand desert area, and 2.86 K for the site in the desert steppe area at daytime. For nighttime LSTs, the RMSEs are 2.01 K, 2.88 K, and 1.80 K for the three sites, respectively. Both biases and RMSEs also show strong seasonal signals. Compared to the error of C5 1-km LSTs, the RMSE of C6 1-km LST product is smaller, especially for daytime LSTs, with a value of 2.24 K compared to 3.51 K. The large errors in the sand desert region are presumably due to the lack of global representativeness of the magnitude of emissivity adjustment and misclassification for the barren surface causing error in emissivities. It indicates that the accuracy of the MODIS C6 LST product might be further improved through emissivity adjustment with globally representative magnitude and accurate land cover classification. From this study, the MODIS C6 1-km LST product is recommended for applications.

Download Full-text

Quantifying the parameters that control turbulent land–atmosphere energy exchange over the Dunhuang Gobi land surface, northwest China

Environmental Earth Sciences ◽

10.1007/s12665-015-4447-y ◽

2015 ◽

Vol 74 (6) ◽

pp. 4745-4750

Author(s):

Chao Wang ◽

Zhigang Wei ◽

Zhenchao Li ◽

Tiangui Xiao

Keyword(s):

Land Surface ◽

Energy Exchange ◽

Northwest China

Download Full-text

Blockchain-Aware Distributed Dynamic Monitoring: A Smart Contract for Fog-Based Drone Management in Land Surface Changes

Atmosphere ◽

10.3390/atmos12111525 ◽

2021 ◽

Vol 12 (11) ◽

pp. 1525

Author(s):

Abdullah Ayub Khan ◽

Zaffar Ahmed Shaikh ◽

Asif Ali Laghari ◽

Sami Bourouis ◽

Asif Ali Wagan ◽

...

Keyword(s):

Land Surface ◽

P2p Network ◽

Dynamic Monitoring ◽

Distributed Data ◽

Distributed Monitoring ◽

Distributed Data Management ◽

Smart Contract ◽

Simulation Results ◽

Stored Information ◽

Surface Changes

In this paper, we propose a secure blockchain-aware framework for distributed data management and monitoring. Indeed, images-based data are captured through drones and transmitted to the fog nodes. The main objective here is to enable process and schedule, to investigate individual captured entity (records) and to analyze changes in the blockchain storage with a secure hash-encrypted (SH-256) consortium peer-to-peer (P2P) network. The proposed blockchain mechanism is also investigated for analyzing the fog-cloud-based stored information, which is referred to as smart contracts. These contracts are designed and deployed to automate the overall distributed monitoring system. They include the registration of UAVs (drones), the day-to-day dynamic captured drone-based images, and the update transactions in the immutable storage for future investigations. The simulation results show the merit of our framework. Indeed, through extensive experiments, the developed system provides good performances regarding monitoring and management tasks.

Download Full-text