Aridity index, as the ration of potential evapotranspiration and precipitation, is an important indicator of regional climate. GIS technology, Morlet wavelet, Mann-Kendall test, and principal component analysis are utilized to investigate the spatial-temporal variation of aridity index and its impacting factors in China on basis of climate data from 599 stations during 1960–2013. Results show the following. (1) Boundaries between humid and semihumid region, and semihumid and semiarid region coincide with 400 mm and 800 mm precipitation contour lines. (2) Average annual aridity index is between 3.4 and 7.5 and shows decrease trend with a tendency of –0.236 per decade at 99% confidence level. (3) The driest and wettest month appear in December and July, respectively, in one year. (4) Periods of longitudinal and latitudinal shift of aridity index 1, 1.5, and 4 contours coordinate are 10 and 25 years, 6 and 26 years, and 5 and 25 years, respectively. (5) Four principal components which affect aridity index are thermodynamic factors, water and radiation factors, geographical and air dynamic factors, and evaluation factor, respectively.

Assessing the water footprint (WF) of crops is key to understanding the agricultural water consumption and improving water use efficiency. This study assessed the WF of wheat and maize in the Haihe River Basin (HRB) of Northern China over the period1956–2015, including rain-fed, sufficient, and insufficient irrigation conditions by different irrigation intensity to understand the agricultural water use status. The major findings are as follows: (1) The annual average total WF of wheat and maize production is 20.1 (52% green, 29% blue, and 19% grey) and 15.1 (73% green, 3% blue, and 24% grey) billion m³ year⁻¹, respectively. The proportion of grey WF is much larger than the world average; (2) Wheat has larger unit WF (1580 m³ t⁻¹) than maize (1275 m³ t⁻¹). The unit WF of both wheat and maize shows exponentially decreasing trends, indicating that water use efficiency has been improved. The unit WF is heterogeneous in space, which is larger in Tianjin and Huanghua and smaller in the Southern HRB; (3) Rain-fed crops have the largest unit WF, followed by crops under insufficient and sufficient irrigation conditions for both wheat and maize. To improve the sustainability of water resources, the application of fertilizer must be reduced, and irrigation is an effective way to improve water use efficiency in water-abundant areas.

The People's Victory Canal Irrigation Area is a large gravity irrigation area in the middle and lower reaches of the Yellow River. Groundwater hydrochemistry is controlled by geochemical weathering, precipitation, irrigation from the Yellow River diversion, and artificial exploitation. The Piper diagram, hierarchical cluster analysis, Gibbs diagram, and ion proportion coefficient were applied to improve our understanding of the hydrogeochemical evolution. Our results indicated that groundwater ion concentration has prominent spatial zonation characteristics in the study area. The groundwater ion components in the low salinity area are mainly a result of silicate and carbonate weathering, with the major hydrochemical type being HCO₃·Cl–Na·Mg and HCO₃–Na·Ca. The soil salt content in the low salinity area is low. The main effect of precipitation on groundwater chemical composition is a reduction in groundwater ion concentration by recharge. The groundwater ion concentration near the canal is similar to the Yellow River water. The groundwater ionic components in the high salinity area are mainly affected by weathering, silicate dissolution, and evaporative salt rocks. The water chemical type is SO₄·Cl–Na·Mg. Expectedly, the soil salt content is high in the high salinity area. The Yellow River recharge decreased the ion concentration of groundwater near the canal. In addition, the groundwater exploitation increase results in a change in the flow field, affecting the local groundwater chemistry. The groundwater ion concentration increases as the groundwater flow from the high salinity area to the low salinity area. In contrast, the groundwater ion concentration in the high salinity area decreases. We further discuss these results in the context of the complex influence of precipitation, Yellow River diversion irrigation, and artificial exploitation on the hydrogeochemical evolution.

Based on statistical analysis, baseflow separation and wavelet analysis, this research was carried out in Shibetsu River Watershed (SRW), Eastern Hokkaido, Japan, to investigate the integrated effects of land use and topography on streamflow response to precipitation. The agriculture-dominated sub-watershed (AW) showed coupled flat topography/agriculture characteristics, the forest-dominated sub-watershed (FW) had coupled steep topography/forest characteristics, and the mixed agriculture-forested sub-watershed (AFW) had mixed flat topography/agriculture and steep topography/forest characteristics. Precipitation variability is characterized by 6-months and 1-year periods. Coupled forest land/steep topography of the FW can increase surface runoff due to forest surface soil water repellency and steep slope, and might receive more external water and higher precipitation that resulted in the highest baseflow and total streamflow compared with other sub-watersheds. Coupled forest land/steep topography can cause higher monthly streamflow variability than coupled agricultural land/flat topography. The FW streamflow is characterized by 3–4 months, 6 months, and 1-year periods. The AW streamflow is only characterized by 3–4 months and 6 months periods. Coupled agricultural land/flat topography produced similar magnitude of baseflow during snowmelt season (March–May) and rainfall season (July–September), which resulted in the losing of annual periodicity in AW streamflow. The coupled forest land/steep topography can increase synchronicity in precipitation and streamflow at annual and monthly scales than coupled agricultural land/flat topography, except in 2007 under wet antecedent conditions when pasture land has lower rainfall interception and lower surface soil infiltration capacity. The coupled forest land/steep topography can increase time lags between precipitation and streamflow compared to coupled agricultural land/flat topography.

In the case study of Tangshan city, Hebei Province, China, this paper analyzes temporal change of blue agricultural water footprint (WF) during 1991–2016 and discusses the applicability of different climate change models during 2017–2050. Results show effective rainfall, wind speed and maximum temperature are leading factors influencing the blue agricultural WF. Relative error analysis indicates that the HadGEM2-ES model is the most applicable for climate change projections in the period of 2017–2050. Agricultural blue WF is about 1.8 billion m³ in RCP2.6, RCP4.5 and RCP8.5 emission scenarios which is almost the same equal to the average value during 1991–2016.