With the acceleration of human economic activities and dramatic changes in climate, the validity of the stationarity assumption of flood time series frequency analysis has been questioned. In this study, a framework for flood frequency analysis is developed on the basis of a tool, namely, the Generalized Additive Models for Location, Scale, and Shape (GAMLSS). We introduced this model to construct a non-stationary model with time and climate factor as covariates for the 50-year snowmelt flood time series in the Kenswat Reservoir control basin of the Manas River. The study shows that there are clear non-stationarities in the flood regime, and the characteristic series of snowmelt flood shows an increasing trend with the passing of time. The parameters of the flood distributions are modelled as functions of climate indices (temperature and rainfall). The physical mechanism was incorporated into the study, and the simulation results are similar to the actual flood conditions, which can better describe the dynamic process of snowmelt flood characteristic series. Compared with the design flood results of Kenswat Reservoir approved by the China Renewable Energy Engineering Institute in December 2008, the design value of the GAMLSS non-stationary model considers that the impact of climate factors create a design risk in dry years by underestimating the risk.

A prerequisite for the rational development and utilization of regional water resources is the measurement of water stress. In this study, from the perspective of water footprints, we took the proportion of the agricultural water footprint within the total water resource usage of Xinjiang (hereafter referred to as XJ) as an example to measure its water stress index and explore the state of water stress in the region and its corresponding driving factors. The ESDA method was applied to characterize the spatial patterns of and correlations with water stress. The effects of different factors on the spatial differentiation between the water footprint and water stress were quantified using the LMDI and geoprobes, respectively. The results showed that (1) both the agricultural water footprint and the water stress index in XJ showed an upward trend, the spatial distribution of water stress was uneven, and the regional pressure difference between the east and the west was greater than that between the north and the south; (2) the water stress index has an obvious negative spatial correlation, fluctuations in its discrete nature have been enhanced, and the number of spatially correlated prefectures is decreasing; (3) water consumption of CNY 10,000 GDP, GDP per capita, and total CO₂ emissions have the most significant impact on the evolution of the agricultural water footprint in XJ. Meanwhile, spatial variations in water stress are mainly determined by the area of cultivation, the area of natural oasis, and the proportion of water used in agriculture. Analysis of the characteristics of and factors influencing water stress in XJ from the perspective of its agricultural water footprint provides a new perspective for further analyzing the actual state of the water footprint and water stress in XJ and supplies a reference basis for the decision-makers of the XJ government.

The Ebinur Lake Basin is an ecologically sensitive area in the arid region of northwest China. In recent years, the ecological environment in the basin has continued to deteriorate, and the ecosystem function has been seriously degraded. However, among the functions of the ecosystem in the Ebinur Lake Basin, the water production function is considered to be the core upholding the ecological equilibrium and security of the basin. Water production can reflect the environmental service function, which is essential for the economic vitality and ecological well-being of the basin. The factors that impact water yield are diverse; moreover, of these, climate change and land use conversion are particularly significant. Therefore, understanding how these changes affect water yield will help to formulate proper water management strategies in the basin. Using the InVEST model, this study examined how the water yield evolved and was distributed across the Ebinur Lake Basin between 2000 and 2020 while considering both the temporal and spatial dimensions. Using this foundation, the scenario analysis approach was utilized to explore the impact of climate change and land use conversion on water yield by controlling the variables, and the response of the water yield to climate and land use change was discussed. It was concluded that water yield was on an upward trend from 2000 to 2010, was on a downward trend from 2010 to 2020, and declined from 2000 to 2020 as a whole. Regarding the water yield distribution, higher-water-producing areas were found predominantly in the northwest and southeast and along the higher-altitude rim of the basin. Among the various land categories, the primary types were grassland and unused land, both of which equally and substantially contributed to the water yield, contributing over 85% to the overall water yield. The response of the water yield varied significantly among various land use types when their areas changed, and the land conversion over this period contributed to a slight decline in water yield across the basin. The influence of climate change on water yield in the Ebinur Lake Basin during the study period surpassed that of land use by a wide margin, constituting more than 86% of the total impact. This study can provide relevant information for relevant policies and decisions on the optimal allocation of land use in the Ebinur Lake Basin and can provide scientific development for the comprehensive evaluation of water resources and sustainable development of the basin.

With the warming and humidification process in the Northwest Arid Zone over the past 30 years, the runoff of a vast majority of rivers has been affected to different degrees. In this paper, the runoff from the Weigan River, a typical inland river in the arid zone of Northwest China, is taken as an example, and seven types of CMIP6 data are selected with the help of a SWAT model to predict the runoff volume of the Weigan River in the next 30 years under climate change. The results show that (1) the SWAT model can simulate the runoff from the Weigan River well and has good applicability in this study area. (2) With an increase in radiative forcing, the temperature, precipitation and runoff in the study area show an increasing trend. (3) Under the four radiative forcing scenarios in 2030 and 2050, the runoff from the Weigan River out of the mountain is predicted to be maintained at 25.68 to 30.89 × 10⁸ m³, which is an increase of 1.35% to 21.91% compared with the current runoff, of which the contribution to the increase in future runoff caused by the changes in temperature and precipitation is 68.71% and 27.24%, respectively. It is important to explore the impact of climate change on the runoff from the Weigan River to understand the impact of climate change on the Northwest Arid Region scientifically and rationally, and to provide a scientific basis for evaluating the risk of climate change and formulating policies to deal with it.

The commercial CFD package Fluent and the Reynolds stress model were used to simulate the hydraulic characteristics with three types of vegetation distribution: longitudinal, interlaced and patch. Each type was aggregated to the middle line l of the water flow in an equal proportion of 0.5, resulting in a total of nine landscape vegetation arrangements. The numerical model was verified and showed a high level of consistency with the experimental comparison; the results indicate the following: (1) As the distribution of landscape vegetation on both sides becomes increasingly concentrated from a loose state to the middle line l of the flow, the flow velocity declines and the maximum Reynolds stress rises, and the greater the Reynolds stress, the more powerful the shear layer, contributing to turbulence, generating mass and momentum exchange and enhancing the vertical transport of momentum. (2) Compared with the gap area, the flow velocity in the vegetation area is smaller, the turbulent kinetic energy is larger and the maximum Reynolds stress of the bottom flow is larger; the larger sediment particles tend to deposit in the gap area, while smaller sediments tend to deposit in the vegetation area. At the same time, the vegetation area is more prone to deposits than the gap area. (3) Under the same vegetation density, whether in the test area or the wake area, the water blocking capacity and the deposition capacity are in the following order: patch distribution pattern > interlaced distribution pattern > longitudinal distribution pattern.