Water resource carrying capacity (WRCC) is essential for characterizing the harmony between humans and water resources in an area. Investigation of the WRCC is useful for guiding the sustainable development of a region. The northern slope of the Tianshan Mountains is an important area for the economic development of Xinjiang, China. In recent years, the supply of water in the area barely satisfies the demand. To quantitatively evaluate the WRCC, data for four indicators including the water resources, social and economic development, and ecological environment of the area were utilized. The comprehensive weighting method, which combines the entropy and analytic hierarchy processes, was used to assess these indicators. A fuzzy comprehensive evaluation model was employed to evaluate the urban WRCC of the northern slope of the Tianshan Mountain for 2018. The results showed urban WRCC values varying between good and moderate for the northern slope of the Tianshan Mountains, and this indicates that the study area is in a loadable state. Although the water supply can meet the development of cities on the northern slope of the Tianshan Mountains to a certain extent at this stage, because it is located in the arid region of western China, the shortage and uneven distribution of water resources are one of the biggest limiting factors for the future development of this region. The findings of the present study provide a basis for the development, rational allocation, and sustainable utilization of urban water resources on the northern slope of the Tianshan Mountains.

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.

Measuring evapotranspiration (ET) components in cotton fields under mulched drip irrigation is needed to improve water use efficiency and promote the development of water-saving agriculture. In this study, an Eddy Covariance (EC) system was used to observe the water-carbon fluxes of cotton fields under mulched drip irrigation in an arid region during two years (2021–2022). The Underlying Water Use Efficiency (uWUE) method was used to partition the ET into transpiration (T) and evaporation (E) in order to reveal the changing characteristics of ET and its components in cotton fields under mulched drip irrigation and analyze the effects of environmental factors on each component. The results showed that the diurnal variation of ET was the same as gross primary productivity (GPP), and their course of change showed a bimodal curve at budding, blooming, and boll stages. The relationship of T at different growth stages was the same as ET, which is blooming and boll stage > budding stage > boll opening stage > seedling stage. ET and its components were mainly affected by temperature (T_air) and net radiation (R_n). This study can provide a theoretical and practical basis for the application of uWUE in cotton fields under mulched drip irrigation and a scientific basis for the rational allocation of water resources and the formulation of a scientific water-saving irrigation system for farmland in an arid region.

Aiming at the problems that need to be solved urgently in the current operation of a multireservoir in Kuitun River Basin, such as the uneven distribution of water resources in time and space, the large workload of manual operation calculation, and low coordination level, the paper takes the optimal operation of water resources in the basin as the main goal and carries out the research on the optimal operation model of the multireservoir in combination with the complex characteristics of local water resources system. Firstly, based on the generalization of hydraulic engineering in Kuitun River Basin, a water resources optimal operation model of the multireservoir is established and is solved by the graph theory. Then, the actual data of typical years were selected to test the model. The test results show that, compared with the actual water distribution, the water shortage rate of 2015 and 2016 in high flow years decreased by 98.57% and 100%, respectively; the water shortage rate of 2013 and 2014 in normal flow years decreased by 92.65% and 96.38%, respectively; and the water shortage rate of 2009 in a low flow year decreased by 87.78%. The model can provide the optimal operation scheme for the optimal operation of the multireservoir in the basin. And it can solve the problems such as the uneven distribution of water resources and the large workload of manual operation calculation and can provide technical support for the optimal operation of water resources of the multireservoir in Kuitun River Basin in the future.

(1) Background: Aiming at low-accuracy and unclear parameter differentiation of snowmelt ice melting, rainstorm and mixed flood simulation in Northwest Chinese arid inland river basins, this study aimed to improve complex flood simulation ability and support arid area flood prediction via HEC-HMS model optimization and classification standard innovation. (2) Method: A distributed HEC-HMS model was built using topography, soil and land use data. A “meteorology, hydrology, underlying surface” flood classification method was developed, and runoff generation-concentration parameters were calibrated via trial-and-error and Latin hypercube sampling for 36 historical floods (12 each type) to verify model applicability. (3) Result: The classification accuracy reached 92%. All three flood types met simulation standards: flood peak and runoff depth error ≤ ±20%, peak time error < 3 h, average NSE = 0.76 (snowmelt: 0.82, rainstorm: 0.76, mixed: 0.70). Parameters showed gradient differences: snowmelt (CN = 65, I_a = 20 mm, k = 0.3), rainstorm (CN = 80, I_a = 10 mm, k = 0.5), mixed (parameters in between). (4) Conclusions: After parameter optimization, the HEC-HMS model is suitable for multi-source flood simulation in arid areas, and the revealed parameter laws provide a quantitative basis for flood forecasting in similar basins.

Flood disaster is one of the natural disasters which cause the most serious economic losses, the most casualties, and the greatest social impact. Flood frequency analysis is very important for reducing flood disaster. In this paper, based on the flood data of Manas River and tools of Box–Cox and Johnson normal transformation, the nonparametric statistical method for flood frequency analysis is studied in order to analyze the adaptability between it and the rivers in arid region of north-western China. The calculation result of the fitness index is divided into two parts: high flood discharge and low flood discharge. One of the two evaluation indexes has an advantage in fitting, and the number of advantages of the three methods in each part has been counted. After analysis, for the flood peak discharge frequency of rivers in arid region of north-western China, the frequency curve of Johnson transformation fits best with empirical data. The high flood discharge advantage is 6, and the low flood discharge is 4. For the flood volume frequency of rivers in arid region of north-western China, Box–Cox transform fits well with empirical data at the high flood discharge frequency curve, and its advantage is 12; Johnson transformation has a better fit between the low flood discharge frequency curve and empirical data, and its advantage is 12. Therefore, it is the way of improving the precision of flood frequency analysis to use the method of P-III distribution and normal transformation comprehensively.