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Drought prediction plays an important guiding role in drought risk management. The standardized precipitation index (SPI) is a popular meteorological drought indicator to measure the degree of drought. The SPI time series is non-stationary, whereas the conventional artificial neural network (ANN) model has limitations to predict non-stationary time series. To overcome this limitation, it is essential to investigate input data preprocessing to improve the ANN model. In this paper, a hybrid model coupled with singular spectrum analysis (SSA) and backpropagation ANN is proposed (SSA-BP-ANN). The advantage of this model is that the SSA of finite-length SPI sequences does not require the adoption of boundary extensions to suppress boundary effects, while the most predictable components of the SPI can be efficiently extracted and incorporated into the model. The proposed SSA-BP-ANN model is tested in case studies at three meteorological stations in Northern Shannxi Province, China. The results show that the SSA-BP-ANN model can produce more accurate predictions than the BP-ANN model. In addition, the performance improvement of SSA on the BP-ANN model is slightly better than wavelet decomposition and empirical mode decomposition. This new hybrid prediction model has great potential for promoting drought early warning in arid regions. [ABSTRACT FROM AUTHOR]

Whether there is a transition underway, from a warm-dry climate to a warm-wet climate in Northwest China remains a controversial and scientifically significant issue. Will this trend continue in the future? Another hot issue is whether the climate in Northwest China will continue to be warm and humid over the next few decades. In this paper, eight CMIP6 models were employed to investigate temperature and precipitation changes under five principal Shared Socioeconomic Pathway (SSP) scenarios (from 2015 to 2099) to project the future warming and humidification in Northwest China using the SPEI (standardized precipitation evapotranspiration index) method. The results revealed that (1) the simulated temperature and precipitation of eight CMIP6 models were consistent with that of observed data during 1961-2014, which showed an increase of approximately 28.2 mm, while simulated data revealed an increase of approximately 9.4 mm. The annual precipitation gradually decreased from Eastern Inner Mongolia and the Southern Northwest Mongolia region (.700 mm) to the Central Northwest Mongolia region (,100 mm) from 1961 to 2014; (2) the MME significantly overestimated the temperature and slightly underestimated the precipitation in Northwest Mongolia. The temperature difference between the simulated and observed data was approximately 0.4 °C. The observed data showed an increase of approximately 0.9 °C from 1961 to 2014, whereas the simulated data revealed an increase of approximately 0.7 °C; (3) in the SSP5-8.5 scenario, the percentage of precipitation anomalies at 1.5, 2, 3, and 4 °C were 166.64, 190.58, 226.44, and 274.56%, respectively; thus, alleviating the drought situation while facilitating the warm-dry to warm-wet climate transition; (4) the water balance between rising temperatures and increased evapotranspiration resulting from increased precipitation suggested that not all sites will be wet in the future. There was still a drying trend in some areas, where drought was more severe under the high emissions scenario than the low emissions scenario. [ABSTRACT FROM AUTHOR]

This paper reviews 110 years of global runoff estimation. By employing the method of ordinary least square regression on a sample region's runoff coefficient, an empirical formula of a runoff coefficient is calculated for China. Based on this empirical formula applied with a high-resolution grid of precipitation, runoff is calculated resulting in an equally high-resolution map of global runoff using a geographic information system (GIS). The main results are (1) the global total runoff volume is 47,884 km³, (2) the average runoff depth is 359 mm, (3) the interior drainage region's runoff volume is 1,663 km³, and (4) the average runoff depth is 58.4 mm. The results are compared with the results of the existing literature on global runoff. This study emphasizes the importance of runoff and groundwater recharge in arid and semi-arid regions where the estimation value of runoff depth is significantly increased. [ABSTRACT FROM AUTHOR]

The quantity of available water resources has been recognized as the key limiting factor for development of most of the arid regions. This paper focuses on the simulation-optimization for conjunctive use of surface water and groundwater on a large scale. In this study, Hetao Irrigation District in China, one of the largest irrigation districts in the Yellow River basin, is selected as a representative study area. The conjunctive management model of water resources is developed by means of dynamically coupling a large-scale hydrological model with an optimal allocation model. A groundwater level is adopted in the coupled model as the constraint condition and the optimal conjunctive utilization quantity of surface water and groundwater is set as the objective function. Finally, the coupled model is applied to calculate the optimal water supply quantity of surface water and groundwater and sustainable utilization scheme of water resources for 2020 and 2030 in Hetao Irrigation District. The modeling results demonstrate the conjunctive management model of water resources is an effective tool for appraising water resources in large-scale arid regions. [ABSTRACT FROM AUTHOR]

This paper presents the results of the study undertaken at the Tarim River Basin in Northwest China to analyze impacts of flooding on water quality. It was shown that irregular rainfall was the cause of flash floods that affected many ecosystems and eroded soils. Simulation results and the existence of relationships between flood volume and flood peak allowed potential model application that included flood peak estimation. The analysis of water pollution through sample sediment was helped by spectroscopy techniques and it was found that the flood was the main cause of many chemical elements in water. The floods affected the quality of water in the Tarim River where it was slightly basic with pH = 8.1 before flooding and acidic with pH = 6.9 after flooding. [ABSTRACT FROM AUTHOR]