The statistical characteristics of precipitation play important roles not only in flood and drought risk assessments but also in water resource management. This paper implements a statistical analysis to study the spatial and temporal variability in precipitation in the upper reaches of the Hongshui River basin (UHRB), southwestern China, by analysing time series of daily precipitation from 18 weather stations during the period of 1959 to 2015. To detect precipitation concentrations and the associated patterns, three indices, the precipitation concentration index (PCI), precipitation concentration degree (PCD), and precipitation concentration period (PCP), were used. The relationships between the precipitation concentration indices (PCI, PCD, and PCP) and geographic variables (latitude, longitude, and elevation), large-scale atmospheric circulation indices, and summer monsoon indices were investigated to identify specific dependencies and spatial patterns in the precipitation distribution and concentration. The results show that high PCI values were mainly observed in the northeastern portion of the basin, whereas low PCI values were mainly detected in the southwest. The Mann-Kendall test results demonstrate that the majority of the UHRB is characterized by nonsignificant trends in the PCI, PCD, and PCP from 1959 to 2015. The PCP results reveal that rainfall in the UHRB mainly occurs in summer months, and the rainy season arrives earlier in the eastern UHRB than in the western UHRB. Additionally, the PCD results indicate that the rainfall in the western UHRB is more dispersed throughout the year than that in the eastern UHRB. Compared with other geographical factors, longitude is the most important variable that governs the spatial distribution and variations in annual precipitation and the precipitation concentration indices. Due to a combination of topography, the Indian subtropical high, and monsoon weakening, precipitation may be more concentrated in one period, especially in the eastern part of the basin, which increases the risk of drought.

The Nanliujiang catchment is one of major rice production bases of South China. Irrigation districts play an important role in rice production which requires a large quantity of water. There are potential risks on future climate change in response to rice production, agricultural irrigation water use and pollution control locally. The SWAT model was used to quantify the yield and water footprint (WF) of rice in this catchment. A combined method of automatic and manual sub-basin delineation was used for the model setup in this work to reflect the differences between irrigation districts in yield and water use of rice. We validated our simulations against observed leaf area index, biomass and yield of rice, evapotranspiration and runoff. The outputs of three GCMs (GFDL-ESM2M, IPSL-CM5A-LR and HadGEM2-ES) under three RCPs (RCP2.6, 4.5, 8.5) were fed to the SWAT model. The results showed that: (a) the SWAT model is an ideal tool to simulate rice development as well as hydrology; (b) there would be increases in rice yield ranged from +1.4 to +10.6% under climate projections of GFDL-ESM2M and IPSL-CM5A-LR but slight decreases ranged from −3.5 to −0.8% under that of HadGEM2-ES; (c) the yield and WFs of rice displayed clear differences in the catchment, with a characteristic that high in the south and low in the north, mainly due to the differences in climatic conditions, soil quality and fertilization amount; (d) there would be a decrease by 45.5% in blue WF with an increase by 88.1% in green WF, which could provide favorable conditions to enlarge irrigated areas and take technical measures for improving green water use efficiency of irrigation districts; (e) a clear rise in future grey WF would present enormous challenges for the protection of water resources and environmental pollution control in this catchment. So it should be to improved nutrient management strategies for the agricultural non-point source pollution control in irrigation districts, especially for the Hongchaojiang and Hepu irrigation districts.

Climate change is expected to have stronger effects on water resources in higher latitude regions. Despite intensive research on possible hydrological responses in those regions to a warmer environment, our knowledge on erosion and sediment yield induced by the climate change in high-latitude headwaters is still limited. In this study, we estimated suspended sediment yields from 2021 to 2050 in a typical headwater area of far Northeast China to elucidate potential impacts of future climate change on surface runoff and erosion in higher latitude regions. We first parameterized the Soil and Water Assessment Tool (SWAT) using historical measurements to estimate runoff from the river basin. The model performed well in both the calibration (2006–2011) and the validation (2012–2014) periods, with an R² of 0.85 and 0.88 and a Nash-Sutcliffe Efficiency (NSE) of 0.7 and 0.73, respectively. We also utilized historical measurements on sediment yields from the period 2006–2014 to develop a runoff-sediment yield rating curve, and the rating curve obtained an excellent goodness of fit (R² = 0.91, p < 0.001). We then applied the calibrated SWAT model to two climate change projections, also known as Representative Concentration Pathways (RCP4.5 and RCP8.5), for the period from 2021 to 2050 to obtain future runoff estimates. These runoff estimates were then used to predict future sediment yield by using the developed runoff-sediment yield rating curve. Our study found a significant increase of annual sediment yield (p < 0.05) for both climate change projections (RCP4.5 = 237%; RCP8.5 = 133%) in this, China’s high-latitude region. The increases of sediment yield were prevalent in summer and autumn, varying from 102–299% between the two RCPs scenarios. Precipitation was the dominated factor that determined the variation of runoff and sediment yield. A warming climate could bring more snowmelt-induced spring runoff and longer rainy days in autumn, hence leading to higher erosion. These findings demonstrate that under the changing climate, soils in this high-latitude headwater area would be eroded twice to three times that of the baseline period (1981–2010), indicating a potential risk to the downstream water quality and reservoir management.

Understanding the impact of climate change on runoff is essential for effective water resource management and planning. In this study, the regional climate model (RCM) RegCM4.5 was used to dynamically downscale near-future climate projections from two global climate models to a 50-km horizontal resolution over the upper reaches of the Yangtze River (UYRB). Based on the bias-corrected climate projection results, the impacts of climate change on mid-twenty-first century precipitation and temperature in the UYRB were assessed. Then, through the coupling of a large-scale hydrological model with RegCM4.5, the impacts of climate change on river flows at the outlets of the UYRB were assessed. According to the projections, the eastern UYRB will tend to be warm-dry in the near-future relative to the reference period, whereas the western UYRB will tend to be warm-humid. Precipitation will decreases at a rate of 19.05–19.25 mm/10 a, and the multiyear average annual precipitation will vary between − 0.5 and 0.5 mm/day. Temperature is projected to increases significantly at a rate of 0.38–0.52 °C/10 a, and the projected multiyear average air temperature increase is approximately 1.3–1.5 ℃. The contribution of snowmelt runoff to the annual runoff in the UYBR is only approximately 4%, whereas that to the spring runoff is approximately 9.2%. Affected by climate warming, the annual average snowmelt runoff in the basin will be reduced by 36–39%, whereas the total annual runoff will be reduced by 4.1–5%, and the extreme runoff will be slightly reduced. Areas of projected decreased runoff depth are mainly concentrated in the southeast region of the basin. The decrease in precipitation is driving this decrease in the southeast, whereas the decreased runoff depth in the northwest is mainly driven by the increase in evaporation.