Arid zone ecosystems, integral to terrestrial systems, exhibit relatively low stability and are prone to influences from human activities and climate change. To elucidate the influence on the ecological environment of the arid zone by climate change and human activities, the paper takes normalized difference vegetation index (NDVI) as an evaluation index of the ecosystem and uses trend analysis to evaluation of NDVI variation characteristics in the Shiyang River Basin (SRB) from 1990 to 2020. Simultaneously using methods such as partial correlation analysis and residual analysis to evaluate the impact of climate change and human activities on NDVI changes. This study yielded several key findings: (1) The NDVI in the SRB exhibits an increasing trend of 0.034/10a in the interannual variation. (2) The relation cooperatives between NDVI and the deviation of precipitation and temperature in the SRB range from −0.735 to 0.770 and −0.602 to 0.773, respectively. (3) The changes in land use and groundwater depth in the SRB have a certain impact on NDVI changes. (4) The proportion of areas with significant contributions (contribution rate greater than 60%) from climate change and human activities to NDVI change is 33.5% and 22.5%, respectively.

In water shortage regions, water rights trading would be much useful for increasing water use inefficiency through changing users’ water demand. In this study, a water optimal allocation modelling system is proposed by considering water rights trading and other governmental policies such as water prices, water savings and industrial policies. An agent-based model was developed to describe the behaviors and goals of individual agents using complex adaptive system theory, information transfers, and functional mechanisms between agents. The developed model was applied to Bayannur City, which suffers from severe water shortages. The water prices for different industries, the water rights transaction price, and the behaviors of various agents in 2020 were forecasted. The results reveal that the water resources optimal allocation model applied in this study can help realize the reasonable allocation of regional water resources under limited water supply. It is also valuable to guide the government in making water resources allocation policies and provide a practical reference for the formulation and adjustment of a water market transaction price.

Meteorological factors and human activities are important factors affecting vegetation change. The change in the Upper Yellow River Basin’s (UYRB’s) ecological environment greatly impacts the ecological environment in the middle and lower reaches of the Yellow River. The purpose of this study was to evaluate remotely sensed imageries and vegetation indices as tools for accurately quantifying the driving forces of vegetation distribution. To accomplish this, we utilized the normalized difference vegetation index (NDVI) to examine the temporal and spatial variability of the vegetation distribution in the UYRB between 2000 and 2020. Based on the geographic detector method, the spatial differentiation, driving force, interaction, and suitability of the NDVI were detected. From 2000 to 2020, the estimated annual NDVI value of the UYRB was 0.515, with notable geographic variation in the distribution. The NDVI showed an obvious upward trend with a rate of 0.038 per 10 years. The vegetation coverage significantly improved. However, the vegetation coverage at the source area of the Yellow River marginally deteriorated. The primary driving factors affecting the spatial distribution of the NDVI were yearly precipitation, elevation, soil type, vegetation type, and annual average temperature, with a predictive power of 47%, 46%, 44%, 41%, and 40%, respectively. The interplay of the components had a stronger impact on the NDVI, and the interaction between the yearly precipitation and the soil type had the highest predictive power, reaching 61%. Natural factors and human activities influence NDVI change, with natural factors playing a significant role. Therefore, we should continue to implement the project of returning farmland to forest (grass), increase the efficiency of vegetation precipitation use, and promote the growth of vegetation so that ecological restoration continues to be effectively improved.

The performances of hydrological simulations for the Pearl River Basin in China were analysed using the Coupled Land Surface and Hydrological Model System (CLHMS). Three datasets, including East Asia (EA), high-resolution gauge satellite-merged China Merged Precipitation Analysis (CMPA)-Daily, and the Asian Precipitation Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) daily precipitation were used to drive the CLHMS model to simulate daily hydrological processes from 1998 to 2006. The results indicate that the precipitation data was the most important source of uncertainty in the hydrological simulation. The simulated streamflow driven by the CMPA-Daily agreed well with observations, with a Pearson correlation coefficient (PMC) greater than 0.70 and an index of agreement (IOA) similarity coefficient greater than 0.82 at Liuzhou, Shijiao, and Wuzhou Stations. Comparison of the Nash-Sutcliffe efficiency coefficient (NSE) shows that the peak flow simulation ability of CLHMS driven with the CMPA-Daily rainfall is relatively superior to that with the EA and APHRODITE datasets. The simulation results for the high-flow periods in 1998 and 2005 indicate that the CLHMS is promising for its future application in the flood simulation and prediction.

Water-rights trade has proved to be an effective method for coping with water shortages through the transfer of water resources between users. The water allocation system is classified into two categories based on information transparency and water rights transaction goals: administered system (AS) and market-based system (MS). A multi-agent and multi-objective optimal allocation model, built on a complex adaptive system, was introduced to direct the distribution of water resources under an AS in the Shiyang River Basin; it was compared with a market-based water rights transaction model using the bulletin-board approach. Ideal economic agent equations played a dominant role in both models. The government and different water users were conceptualized as agents with different behaviors and goals in water allocation. The impact of water-saving cost on optimal water allocation was also considered. The results showed that an agent’s water-saving behavior was incentivized by high transaction prices in the water market. Under the MS, the highest bid in the quotation set had a dominant influence on how trade was conducted. A higher transaction price will, thus, result in a better benefit ratio, and a lower one will result in inactivity in terms of water rights trade. This will significantly impact the economic benefit to the basin.