Energy is consumed at every stage of the cycle of water production, distribution, end use, and recycled water treatment. Understanding the nexus of energy and water may help to minimize energy and water consumption and reduce environmental emissions. However, the interlinkages between water and energy have not received adequate attention. To address this gap, this paper disaggregates and quantifies the energy consumption of the entire water cycle process in Beijing. The results of this study show that total energy consumption by water production, treatment and distribution, end use, and recycled water reuse amounts to 55.6 billion kWh of electricity in 2015, or about 33% of the total urban energy usage. While water supply amount increased by only 10% from 2005 to 2015, the related energy consumption increased by 215% due to water supply structural change. The Beijing municipal government plans to implement many water saving measures in the area from 2016 to 2020, however, these policies will increase energy consumption by 74 million kWh in Beijing. This study responds to the urgent need for research on the synergies between energy and water. In order to achieve the goal of low-energy water utilization in the future, water and energy should be integrated in planning and management.

This study applies a hydroeconomic optimization method for water resources management in the highly water stressed Haihe River basin. A multi-objective, multi-temporal deterministic hydroeconomic optimization model has been built to quantify the economic trade-offs and reveal “minimum cost strategies” when reducing groundwater abstraction to sustainable levels. A complex basin representation, with ~140,000 decision variables is formulated where each decision variable represents a flow-path from a water source to a sink. Available water sources are runoff generated by the sub-basins upstream the nine major surface water reservoirs, the inter-basin transfers from Yellow River and South to North Water Transfer Project (SNWTP) and the natural groundwater recharge to the three main groundwater aquifers. Water demands, i.e. sinks, are aggregated for each model sub-basin in categories of the major agricultural users, domestic, industrial and ecological water demands. Each demand is associated with a curtailment cost and groundwater abstraction with a pumping cost. Groundwater overdraft is constrained in each model scenario, ranging from unlimited overdraft in the plain area groundwater aquifer to sustainable abstractions over an 8-year period. Inflow upstream Yuqiao reservoir, and the inter-basin transfers from SNWTP and Yellow River are identified as the water resources with the highest increase in average shadow prices when limiting groundwater overdraft. An increase in inflow shadow prices of 37.5% indicates that these water sources will be most valuable if sustainable groundwater abstraction should be achieved. The shadow prices of water sources reveal when and where in the Haihe River basin users are curtailed if water resources are managed in the most optimal way. Average shadow prices of 1.6 yuan/m³ for all surface water sources in the sustainable abstraction scenarios shows that overdraft can be avoided by curtailment of users with a willingness-to-pay ≤1.6 yuan/m³. The shadow prices of the existing surface water reservoirs represented in the model shows that no costs can be saved from expanding their capacities. Finally, the cost of achieving sustainable groundwater abstraction with present water resource availability is found to be minimum 8.2 billion yuan/year.

Potential evapotranspiration (ET₀) is vital for hydrologic cycle and water resource assessments as well as crop water requirement and irrigation demand assessments. The Beijing-Tianjin-Hebei region (Jing-Jin-Ji)-an important, large, regional, economic community in China has experienced tremendous land use and land cover changes because of urbanisation and ecological restoration, affecting the hydrologic cycle and water resources of this region. Therefore, we analysed ET₀ in this region using climate data from 22 meteorological stations for the period 1991-2015 to understand this effect. Our findings show that ET₀ increased significantly at a rate of 7.40 mm per decade for the region. Based on the major land use type surrounding them, the meteorological stations were classified as urban, farmland, and natural stations using the 2015 land use dataset. The natural stations in the northern mountainous area showed a significant increase in ET₀, whereas most urban and farmland stations in the plain area showed a decrease in ET₀, with only a few of the stations showing an increase. Based on the different ET₀ trends for different land use types, these stations can be ranked as follows: urban stations (trend value: -4.663 to -1.439) > natural stations (trend value: 2.58 to 3.373) > farmland stations (trend value: -2.927 to -0.248). Our results indicate that land use changes affect meteorological parameters, such as wind speed and sunshine duration, which then lead to changes in ET₀. We noted that wind speed was the dominant parameter affecting ET₀ at all the natural stations, and wind speed and sunshine duration were the dominant parameters affecting ET₀ at most of the urban stations. However, the main controlling parameters affecting ET₀ at the farmland stations varied. These results present a scope for understanding land use impact on ET₀, which can then be applied to studies on sustainable land use planning and water resource management.

Based on the MODIS NDVI data and Landsat TM/ETM data of 2002 and 2012, this paper extracts the planting area of winter wheat-summer maize, single spring maize, cotton and forest/fruit trees, vegetable and paddy, and made the agricultural land use map of the North China Plain (NCP). Agricultural land use area accounted for 63.32% compared to the total area of the NCP in 2002. And it increased to 65.66% in 2012, which mainly caused by the vegetables and forest/fruit trees increasing. Planting areas of winter wheat-summer maize, cotton, single spring maize, forest/fruit trees, vegetables and paddy were 5031.21×10³, 865.90×10³, 1226.10×10³, 1271.17×10³, 648.02×10³, 216.51×10³ ha in 2012. Rank of changes was: vegetables (+45%) > forest/fruit trees (+27.4%) > paddy (-23.7%) > cotton (-20.4%) > single spring maize (+17.3%) > winter wheat-summer maize (-0.6%). In developed region like Beijing and Tianjin, planting area of crops with high economic benefit (such as fruit trees and vegetables) increased significantly. Government policies for groundwater protection caused obvious decline of winter wheat cultivation in Hebei Province. Cotton planting in Shandong Province decreased more than 200,000 ha during 2002-2012. The data products will be published in the website: http://hydro.sjziam.ac.cn/Default.aspx. To clarify the agricultural land use in the NCP will be very helpful for the regional agricultural water consumption research, which is the serious problem in the NCP.

The North China Plain is one of the most water-stressed areas in China. Irrigation of winter wheat mainly utilizes groundwater resources, which has resulted in severe environmental problems. Accurate estimation of crop water consumption and net irrigation water consumption is crucial to guarantee the management of agricultural water resources. An actual crop evapotranspiration (ET) estimation model was proposed, by combining FAO Penman-Monteith method with remote sensing data. The planting area of winter wheat has a significant impact on water consumption; therefore, the planting area was also retrieved. The estimated ET showed good agreement with field-observed ET at four stations. The average relative bias and root mean square error (RMSE) for ET estimation were -2.2% and 25.5 mm, respectively. The results showed the planting area and water consumption of winter wheat had a decreasing trend in the Northern Hebei Plain (N-HBP) and Southern Hebei Plain (S-HBP). Moreover, in these two regions, there was a significant negative correlation between accumulated net irrigation water consumption and groundwater table. The total net irrigation water consumption in the N-HBP and S-HBP accounted for 12.9×10⁹ m³ and 31.9×10⁹ m³ during 2001-2016, respectively. Before and after 2001, the decline rate of groundwater table had a decreasing trend, as did the planting area of winter wheat in the N-HBP and S-HBP. The decrease of winter wheat planting area alleviated the decline of groundwater table in these two regions while the total net irrigation water consumption was both up to 28.5×10⁹ m³ during 2001-2016 in the Northwestern Shandong Plain (NW-SDP) and Northern Henan Plain (N-HNP). In these two regions, there was no significant correlation between accumulated net irrigation water consumption and groundwater table. The Yellow River was able to supply irrigation and the groundwater table had no significant declining trend.

From a critical zone perspective, the present paper aims to present the magnitude of groundwater recharge under different agricultural land-use types, reveal the process of water and solute transport in thick vadose zone, evaluate the “time lag” effect of recharge, and underscore the role of thickening vadose zone in recharge. The results indicated that different agricultural land-use types need to be further considered in recharge rate estimate. Under the typical irrigation condition in the piedmont plain, the recharge rate under flood irrigated winter wheat and summer maize (W/M_F), maize (M), non-cultivation (NC), native vegetation (NV), vegetables (V), and orchards (O) is 206.4, 149.7, 194.1, 46.4, 320.0, and 48.6 mm/yr, respectively. In the central plain, the value under W/M_F, M, NC, V, and cotton (C) is 92.8, 50.8, 85.0, 255.5, and 26.5 mm/yr, respectively. Soil water residence time (several years) and groundwater level response time (several months) should be distinguished to further understand the processes of groundwater recharge, because the soil water displacement velocities range from 0.2 to 2.2 m/yr while the rate of wetting front propagation is approximately 47 m/yr in the piedmont plain. The thickening vadose zone would prolong residence time of soil water and contaminant, which could postpone the time of or alleviate groundwater pollution, but have no significant influence on the magnitude of recharge in a long time scale. Recharge coefficient based on shorter time span (e.g. 2 or 3 years) should be used with caution as a parameter for groundwater resources evaluation, because it varies with total water input and target soil depth. Uncertainties in evapotranspiration and other water balance components should be evaluated in recharge estimation and the impact of land-use types on recharge should be emphasized. The critical zone science would greatly improve the understanding of groundwater recharge processes. The results of the present study will be helpful in sustainable groundwater resources management.

Spatio-temporal patterns of drought from 1961 to 2013 over the Beijing-Tianjin-Hebei (BTH) region of China were analyzed using the Palmer Drought Severity index (PDSI) based on 21 meteorological stations. Overall, changes in the mean-state of drought detected in recent decades were due to decreases in precipitation and potential evapotranspiration. The Empirical Orthogonal Functions (EOF) method was used to decompose drought into spatio-temporal patterns, and the first two EOF modes were analyzed. According to the first leading EOF mode (48.5%), the temporal variability (Principal Components, PC1) was highly positively correlated with annual series of PDSI (r=+0.99). The variance decomposition method was further applied to explain the inter-decadal temporal and spatial variations of drought relative to the total variation. We find that 90% of total variance was explained by time variance, and both total and time variance dramatically decreased from 1982 to 2013. The total variance was consistent with extreme climate events at the inter-decadal scale (r=0.71, p<0.01). Comparing the influence of climate change on the annual drought in two different long-term periods characterized by dramatic global warming (P1: 1961-1989 and P2: 1990-2013), we find that temperature sensitivity in the P2 was three times more than that in the P1.