Research on the Prediction of Several Soil Properties in Heihe River Basin Based on Remote Sensing Images

Soil property monitoring is useful for sustainable agricultural production and environmental modeling. It is possible to automatically predict soil properties in a wide range based on remote sensing images. Heihe River Basin was chosen as the research area. Measurements on three soil properties, which were pH, organic carbon, and bulk density, were available there. Two kinds of attributes were extracted, which were the remote sensing index and terrain attributes. The prediction models were constructed by random forest algorithms. The features were determined by combining correlation statistics with prediction error, and different features were selected for each of the three properties. The validation experimental results are presented. The error results were as follows: pH (MAE = 0.28, RMSE = 0.39, R2 = 0.41), organic carbon (MAE = 4.75, RMSE = 8.26, R2 = 0.75), and bulk density (MAE = 0.11, RMSE = 0.13, R2 = 0.70). Through the analysis and comparison of the experimental results, it was proven that the algorithm in this paper had a good performance in the prediction of organic carbon and bulk density.

Spatial Representativeness of Gross Primary Productivity from Carbon Flux Sites in the Heihe River Basin, China

Studying the spatial representativeness of carbon flux measurement data for typical land cover types can provide important information for benchmarking Earth system models and validating multiple-scale remote sensing products. In our study, daily gross primary productivity (GPP) was firstly derived from eddy covariance observation systems and seasonal variations in field GPP were analyzed at nine flux tower sites for typical land cover types in the Heihe River Basin, China. Then, the real-time footprint distance and climate footprint distance of the field GPP were obtained by using a footprint source area model. Lastly, multiple-scale GPP products were validated at footprint scale, and the impacts (measurement height, surface roughness and turbulent state of the atmosphere) on the footprint distance of field GPP were analyzed. The results of this paper demonstrated that climate footprint distances ranged from about 500 m to 1500 m for different land cover types in the Heihe River Basin. The accuracy was higher when validating MODIS GPP products at footprint scale (R2 = 0.56, RMSE = 3.07 g C m−2 d−1) than at field scale (R2 = 0.51, RMSE = 3.34 g C m−2 d−1), and the same situation occurred in the validation of high-resolution downscaled GPP (R2 = 0.85, RMSE = 1.34 g C m−2 d−1 when validated at footprint scale; R2 = 0.82, RMSE = 1.47 g C m−2 d−1 when validated at field scale). The results of this study provide information about the footprints of field GPP for typical land cover types in arid and semi-arid areas in Northwestern China, and reveal that precision may be higher when validating multiple-scale remote sensing GPP products at the footprint scale than at the field scale.

Dynamic Patterns of the Vertical Distribution of Vegetation in Heihe River Basin since the 1980s

The vertical distribution of vegetation in Heihe River Basin has presented a significant dynamic change in the different elevation zones since the 1980s. To explore the dynamic patterns of vegetation types located in the different elevation zones of Heihe River Basin, this study collected 440 field sampling datapoints of vegetation types, remote sensing images, climatic observation data, and DEM and preprocessed them. On the basis of the vegetation distribution and the terrain characteristics of Heihe River Basin, this study classified the vertical distribution of vegetation in Heihe River Basin into six vegetation zones, namely, the oasis farmland and desert zone, desert-steppe zone, dry scrub-steppe zone, mountain forest-steppe zone, subalpine scrub-meadow zone, and alpine cold desert-meadow zone. Moreover, the mean annual biotemperature (MAB) and total annual average precipitation (TAP) were used to analyze the relationship between vegetation change and climate change in the different elevation zones. The results show that the change rate of vegetation was up to 25.75% in Heihe River Basin. The area of vegetation that changed in the oasis farmland and desert zone was the largest (7224 km2), and the rate of vegetation that changed in the mountain forest-steppe zone was up to 56.93%. The mean annual biotemperature (MAB) and total annual average precipitation (TAP) in the six elevation zones showed an increasing trend, in which the increased rate of TAP presented a downward trend with the increase of elevation, and that of MAB showed a continuous upward trend with the increase of elevation. The change rate of vegetation was generally higher than that of MAB and TAP in the low and middle vegetation zones. The influence intensity of human activities on vegetation change in the lower and middle elevation zones of Heihe River Basin was greater than that in the high elevation zone between the 1980s and the 2010s. MAB is the major impact factor to vegetation change in the alpine cold zone of Heihe River Basin.

Spatial Variation and Terrain Gradient Effect of Ecosystem Services in Heihe River Basin over the Past 20 Years

With the advent of large-scale development, extreme imbalance in the ecology of the Heihe River Basin (HRB) has caused a series of ecological problems. In order to explore the spatiotemporal variation of ecosystem services (ESs) and to assess the characteristics of ESs under the terrain gradient effect (TGE), the three key ESs were quantified based on the InVEST model using five series of land-use data obtained from remote sensing images from 2000 to 2020 in this study. The terrain index was used to analyze the influence of terrain on ESs. The results show that most of the ESs were in high numbers in the south and low numbers in the north, as well as high numbers in the middle and upper reaches and low numbers at downstream locations. It was found that high-quality habitats degrade to general-quality habitats, and poor-quality habitats evolve into general-quality habitats. It was also found that the water production volume continues to decline and soil conservation becomes relatively stable with little change. This study illustrates different ESs showing obvious TGE with changes in elevation and slope. These results indicate that the effect of land-use change is remarkable and TGE is highly important to ESs in inland watersheds. This research study can provide a scientific basis for the optimization of regional ecosystem patterns. The results are of great significance in terms of rational planning land use, constructing ecological civilizations, and maintaining the physical conditions of land cover at inland river basins.

Scenario-Based Analysis of Land Use Competition and Sustainable Land Development in Zhangye of the Heihe River Basin, China

Rapid economic growth has a significant impact on land use change, which would threaten the natural ecology. Zhangye city of the Heihe River Basin, China is an ecologically vulnerable region where land use changes significantly due to socioeconomic development and population increases. The study employed a computable general equilibrium of land use change (CGELUC) model to simulate land use change and then used a dynamic land system (DLS) model to spatialize land use change during 2015–2030 under three development scenarios in Zhangye city. The three development scenarios are the baseline scenario (BAU), the resource consumption scenario (RCS) and the green development scenario (GDS). We found that economic growth would lead to land demand increases in high value-added industries and decreases in low value-added industries. The cultivated land would decrease while the built-up area would increase. By 2030, the cultivated land will decrease by 8.16%, 10.89% and 4.16%, respectively, under BAU, RCS and GDS, while the built-up area will increase by 8.61%, 10.39% and 4.75%, respectively. The expansion of built-up area under RCS presents spatial characteristics of centralized distribution, while spatial characteristics of uniform discrete distributions are presented under GDS. The expansion of ecological land under GDS would be considerable, especially in the north of Sunan County and Gaotai County, and around the natural reserve of Ganzhou County. This paper provides a scientific reference for coordinating economic development and ecological protection in the rapidly developing urbanized areas in western China.

Spatial Pattern Analysis of a Water-Related Ecosystem Service and Evaluation of the Grassland-Carrying Capacity of the Heihe River Basin under Land Use Change

A key challenge to the sustainability and security of grassland capacity is the protection of water-related ecosystem services (WESs). With the change of land use, the supply of aquatic ecosystem services has changed, and the grassland-carrying capacity has been affected. However, the correlation mechanism between WESs and the grassland-carrying capacity is not clear. In this study, we used the InVEST(Integrated Valuation of Ecosystem Services and Tradeoffs) model to evaluate the impact of land-use change on WESs, and made a tradeoff analysis between WESs and grassland-carrying capacity. Considering that the Heihe River Basin (HRB) was an important grassland vegetation zone, which was a milestone for the development of animal husbandry in China, HRB was taken as a case. The main findings are as follows: (1) the spatial distribution of WESs shows the dissimilation rule, the upper reaches are the main water yield area, the soil retention is weakening in the middle and lower reaches, and the pollution has further increased in the middle and upper reaches. (2) The carrying capacity of animal husbandry decreased in the upper reaches, increased in Shandan County and Zhangye City in the middle reaches, and decreased sharply in other regions. (3) There was a positive correlation between the livestock-carrying capacity and nitrogen export in 2018, which was increasing. As the change of land use has changed the evapotranspiration structure, WESs have undergone irreversible changes. Meanwhile, the development of large-scale irrigated farmland and human activities would be the source of a further intensification of regional soil erosion and water pollution. Therefore, it is necessary to trade off the WESs and animal husbandry under land-use change. This paper revealed how WESs changed from 2000 to 2018, the characteristics of the changes in the spatial and temporal distribution, and the carrying capacity. It aims to provide a scientific basis for coordinating the contradiction between grassland and livestock resources, improving the regional ecological security situation, and carrying out ecosystem management.

River Basin Cyberinfrastructure in the Big Data Era: An Integrated Observational Data Control System in the Heihe River Basin

River basin cyberinfrastructure with the Internet of Things (IoT) as the core has brought watershed data science into the big data era, greatly improving data acquisition and sharing efficiency. However, challenges in analyzing, processing, and applying very large quantities of observational data remain. Given the observational needs in watershed research, we studied the construction of river basin cyberinfrastructure and developed an integrated observational data control system (IODCS). The IODCS is an important platform for processing large quantities of observational data, including automated collection, storage, analysis, processing, and release. This paper presents various aspects of the IODCS in detail, including the system’s overall design, function realization, big data analysis methods, and integrated models. We took the middle reaches of the Heihe River Basin (HRB) as the application research area to show the performance of the developed system. Since the system began operation, it has automatically received, analyzed, and stored more than 1.4 billion observational data records, with an average of more than 14 million observational data records processed per month and up to 21,011 active users. The demonstrated results show that the IODCS can effectively leverage the processing capability of massive observational data and provide a new perspective for facilitating ecological and hydrological scientific research on the HRB.