ALBERT

Description: With the implementation of the Grain for Green Project, the apple plantation area is increasing in Loess Plateau. However, due to severe water scarcity, the sustainability of apple tree growth is threatened. In this paper, we used meteorological data (1990–2013) and forecasted climate data (2019–2050) to estimate water demand and establish a water suitability model to study the water balance between available water and water consumption of the apple trees. The results show that: (i) the order of the average water demand of apple plantation in each subarea is Shaanxi Province 〉 Yuncheng area 〉 Gansu Province 〉 Sanmenxia Region, ranging from 500 to 950 mm; (ii) the temporal variability of water suitability from 1990 to 2013 is large, and the higher values are concentrated in the late growth stage of the apple trees and the lower values are concentrated in the early growth stage; (iii) the temporal and spatial distribution of water suitability is relatively stable and even in the Loess Plateau in the period of 2019–2050; (iv) the water suitability is mainly affected by effective precipitation and reference evapotranspiration and the reference evapotranspiration is mainly affected by the solar radiation (36%) and average temperature (38%). Furthermore, due to the joint influence of precipitation increases and solar radiation (average temperature) increases, the future water suitability of the apple plantation area in the Loess Plateau is showing a non-significant downward trend under RCP4.5 scenario.

Description: The accurate assessment of profile soil moisture for spatial domains is usually difficult due to the associated costs, strong spatial-temporal variability, and nonlinear relationship between surface and profile moisture. Here we attempted to use observation operators built by Cumulative Distribution Frequency (CDF) matching method to directly upscale surface observations to profile soil moisture based on multi-station in situ measurements from the Soil and Climate Analysis Network (SCAN). We first analyzed the effects of temporal resolution (hourly, daily and weekly) and data length (half year in non-growing season, half year in growing season, one year, two years and four years) on the performance of observation operators. The results showed that temporal resolution had a negligible influence on the performance of observation operators. However, data length significantly changed the prediction accuracy of observation operators; prediction errors decreased as data length increased from half year (non-growing season) to two years, but accuracy did not further improve at longer interval. A dataset with a two-year duration was therefore used to test the robustness of observation operators in three primary climates (humid continental, humid subtropical and semiarid) of the continental USA, with the popular exponential filter employed as a reference approach. The results indicated that observation operators generally performed better than exponential filter method in both calibration and validation periods. This suggests that observation operators are a robust statistical tool for upscaling soil moisture from surface to profile. The findings here may be applied in the prediction of profile soil moisture from surface measurements obtained via various means, including remote sensing techniques.

Description: Jointly influenced by natural factors and artificial protection measures in recent years, the vegetation coverage of the Loess Plateau has significantly increased. However, extensive vegetation recovery can result in massive water consumption and a severe soil water deficit, which poses a great threat to the sustainable development of the regional ecological system. Maintaining the balance between precipitation and water consumption is an important foundation of ecological security in the Loess Plateau. Based on this, the present study used the GRACE (Gravity Recovery and Climate Experiment) gravity satellite data to simulate the annual actual water consumption from 2003 to 2014 and to analyze the temporal and spatial evolution of the regional precipitation and the actual evapotranspiration (AET). This study also applied the newly developed rainwater utilization potential index (IRUP) to quantify the sustainability of the water balance in the Loess Plateau. The spatial-temporal patterns of precipitation, potential evapotranspiration, and AET from 2003 to 2014 in the Loess Plateau were all analyzed in this study. Based on the results, the annual average precipitation (AAP) and AET in the entire Loess Plateau had significant increasing trends. The analysis of the spatial distribution reveals that the AET was decreasing from the southeast to the northwest in the Loess Plateau. However, the average values of potential evapotranspiration did not obviously change. Based on the estimated AET result, it was determined that the average IRUP had an increasing trend. The increase in the IRUP is due to an increased rate of precipitation that is statistically higher than that of the AET. Consequently, the Loess Plateau experienced a wetting trend during the period of 2003–2014, especially after the Grain for Green project was implemented. The results in this paper were proven by using three different depths of ERA-Interim (a global atmospheric reanalysis product created by the European Centre for Medium-Range Weather Forecasts) soil water content data from the same period and the observed runoff data from 18 different hydrological sites. Consequently, it seems that the vegetation could maintain a sustainable growth with the implementation of the Grain for Green Project.

Description: The accurate assessment of profile soil moisture for spatial domains is usually difficult due to the associated costs, strong spatial-temporal variability, and nonlinear relationship between surface and profile moisture. Here we attempted to use observation operators built by Cumulative Distribution Frequency (CDF) matching method to directly predict profile soil moisture from surface measurements based on multi-station in situ observations from the Soil and Climate Analysis Network (SCAN). We first analyzed the effects of temporal resolution (hourly, daily and weekly) and data length (half year in non-growing season, half year in growing season, one year, two years and four years) on the performance of observation operators. The results showed that temporal resolution had a negligible influence on the performance of observation operators. However, data length significantly changed the prediction accuracy of observation operators, and a two-year interval was identified as the optimal data length in building observation operators. A dataset with a two-year duration was therefore used to test the robustness of observation operators in three primary climates (humid continental, humid subtropical and semiarid) of the continental USA, with the popular exponential filter employed as a reference approach. The results indicated that observation operators reliably predicted profile soil moisture for the majority of stations in both calibration and validation periods and performed almost equally well with the exponential filter method. This suggests that observation operators are a feasible statistical tool for depth scaling of soil moisture. The findings here have the potential to be applied in profile soil moisture prediction from surface measurements at a range of environments if the target site has long enough (two years) soil moisture observations even with coarse temporal resolutions.

Description: Water issues in many river basins associated with droughts, water over-exploitation and pollution are increasingly being driven by remote pressures through intensified virtual water (VW) flows. However, little attention has been paid to the internal trade-offs between the (physical and virtual) water flows and the associated economic benefits and incomes that the water generated. Here we estimate the concomitant reversed flows of economic benefits and values to the physical and VW flows in crop production and consumption at a basin level, by taking the Yellow River Basin (YRB) in both current three typical years (2003, 2004, and 2006, which were dry, average, and wet, respectively) and possible four scenarios for 2050 under climate-socio-economic changes as the study case. An algorithm for estimation of the economic net benefits of green and blue water use for crop production based on the water footprint (WF) accounting is developed. Results show that the net benefit of blue water (irrigation) was 13–42 % lower than that of green water used in irrigated croplands in the basin. Cropping pattern has defined the spatial heterogeneity in the levels of net benefits of water used for crops within the YRB. Provinces located in the relatively drier upper and middle reaches had high irrigation withdrawal rates while a low economic return to farmers because of growing relatively cheap crops. The YRB got increasingly net income due to exports of wheat, cotton and apples even though as a crop-related net VW importer associated to the intra-national trades. Considered scenarios for 2050 suggested that the economic returns of crop-related physical and VW flows were more sensitive than the quantity levels of corresponding water flows. This study implies the importance of managing the internal trade-offs or mutual effects between the water resources consumption and economic returns, in order to get a win-win situation in maximizing both the water use efficiency and economic productivities per drop of water flows.