Chunying Wang

How cropping systems and fertilization interactively affect deep nitrate accumulation and vertical distribution in highland agroecosystems remains poorly understood. We evaluated soil nitrate nitrogen (NO₃⁻-N), dissolved organic carbon (DOC), and dissolved organic nitrogen (DON) in 0–300 cm soil profiles sampled in 2006 and 2019 from a 35-year long-term experiment established in 1984 on the Chinese Loess Plateau. Mineral N, DOC, and DON were measured in air-dried samples from both years. The experiment included unfertilized fallow (FW) and three cropping systems with different fertilizer treatments. Continuous winter wheat (WC) and grain–legume rotation (GLR) included unfertilized control (CK), phosphorus (P), chemical NP, and NP combined with manure (NPM), whereas continuous alfalfa (AC) included CK, P, and NPM. When averaged across the two sampling years, NO₃⁻-N stocks across the 0–300 cm profile were significantly lower in the three cropping systems than in fallow, with reductions of 102.3–110.0 kg N ha⁻¹. In the GLR and WC systems, both NP and NPM increased subsoil NO₃⁻-N accumulation, with a greater increase under NPM. Under NPM, NO₃⁻-N stocks across the 0–300 cm profile increased by 1426.9 kg N ha⁻¹ in the GLR system and 908.9 kg N ha⁻¹ in the WC system, but by only 93.9 kg N ha⁻¹ in the AC system. NO₃⁻-N accumulated mainly in deep soil in the GLR and WC systems, whereas the AC system maintained concentrations below 3.0 mg kg⁻¹ at depths below 60 cm. The annualized changes in the NO₃⁻-N profile center of mass under NPM were 4.2, 0.8, and −0.2 cm yr⁻¹ in AC, GLR, and WC, respectively, indicating contrasting changes in nitrate vertical distribution within the sampled profile. The effects of NPM on subsoil NO₃⁻-N differed among cropping systems and were associated with soil moisture, DOC, and the DOC/DON ratio. Overall, continuous alfalfa limited deep NO₃⁻-N accumulation even under NPM, highlighting the potential of deep-rooted perennial cropping systems and improved coordination of N and C inputs to limit nitrate accumulation in deep soil.

Simulation of future climate changes, especially temperature and rainfall, is critical for water resource management, disaster mitigation, and agricultural development. Based on the category-wise indicator method, two preferred Global Climate Models (GCMs) for the Ishikari River basin (IRB), the socio-economic center of Hokkaido, Japan, were examined from the newly released Coupled Model Intercomparison Project Phase 6 (CMIP6). Climatic variables (maximum/minimum temperature and precipitation) were projected by the Statistical DownScaling Model (SDSM) under all shared socioeconomic pathway-representative concentration pathway (SSP-RCP) scenarios (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, SSP5-3.4OS, and SSP5-8.5) in two phases: 2040–2069 (2040s) and 2070–2099 (2070s), with the period of 1985–2014 as the baseline. Predictors of SDSM were derived from CMIP6 GCMs and the reanalysis dataset NOAA-CIRES-DOE 20th Century Reanalysis V3 (20CRv3). Results showed that CMIP6 GCMs had a significant correlation with temperature measurements, but could not represent precipitation features in the IRB. The constructed SDSM could capture the characteristics of temperature and precipitation during the calibration (1985–1999) and validation (2000–2014) phases, respectively. The selected GCMs (MIROC6 and MRI-ESM-2.0) generated higher temperature and less rainfall in the forthcoming phases. The SSP-RCP scenarios had an apparent influence on temperature and precipitation. High-emission scenarios (i.e., SSP5-8.5) would project a higher temperature and lower rainfall than the low-emission scenarios (e.g., SSP1-1.9). Spatial–temporal analysis indicated that the northern part of the IRB is more likely to become warmer with heavier precipitation than the southern part in the future. Higher temperature and lower rainfall were projected throughout the late twenty-first century (2070s) than the mid-century (2040s) in the IRB. The findings of this study could be further used to predict the hydrological cycle and assess the ecosystem's sustainability.

Climate change can impact the yield and water footprint of crops. Therefore, assessing such impacts carries great significance for regional water and food security. This study validated and verified the variety parameters of winter wheat for the Decision Support System for Agrotechnology Transfer (DSSAT) model, using the long-term (1993–2013) growth and yield data observed from six agricultural experiment stations in the Haihe River Basin (HRB), China. The growth process was simulated under three representative concentration pathways (RCPs), named RCP2.6, RCP4.5, and RCP8.5—climate scenarios driven by the HadGEM2-ES model. The variety parameters of winter wheat showed high accuracy in the simulation of the anthesis and maturity dates, and could be used for long-term prediction of the growth process. The trends of climate change had positive impacts on the water footprint of winter wheat but adverse impacts on the yield. The growing period was shortened by 3.6 days, 4.7 days, and 5.0 days per decade in the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively, due to the rapid accumulation of heat. The yield would be increased in lower emissions scenarios (17% in RCP2.6), but decreased in high-emissions scenarios due to high temperatures, which may restrict the growth of wheat. The water footprint was decreased by 10%, 11%, and 13% in the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively, indicating that the water-use efficiency could be improved in the future. The results showed broad application prospects of the DSSAT model in simulating the response of crop growth to climate change.

Simulating future climate changes (like temperature and rainfall) is critical for water resource management, disaster mitigation, and agricultural development. Based on the category-wise indicator method, two preferred Global Climate Models (GCMs) for the Ishikari River basin (IRB), the socio-economic center of Hokkaido, Japan, were examined from the newly released Coupled Model Intercomparison Project Phase 6 (CMIP6). Climatic variables (maximum/minimum temperature and precipitation) were projected by the Statistical DownScaling Model (SDSM) under all shared socioeconomic pathway-representative concentration pathway (SSP-RCP) scenarios (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, SSP5-3.4OS, and SSP5-8.5) in two phases: 2040–2069 (2040s) and 2070–2099 (2070s), with the period of 1985-2014 as the baseline. Predictors of SDSM were derived from CMIP6 GCMs and the reanalysis dataset NOAA-CIRES-DOE 20th Century Reanalysis V3 (20CRv3). Results showed that CMIP6 GCMs had a significant correlation with temperature measurements, but could not represent precipitation features in the IRB. The constructed SDSM could capture the characteristics of temperature and precipitation during the calibration (1985-1999) and validation (2000-2014) phases, respectively. The selected GCMs (MIROC6 and MRI-ESM-2.0) generated higher temperature and less rainfall in the forthcoming phases. The SSP-RCP scenarios had an apparent influence on temperature and precipitation. High-emission scenarios (like SSP5-8.5) would project a higher temperature and lower rainfall than the low-emission scenarios (like SSP1-1.9). Spatial-temporal analysis indicated that the northern part of the IRB is more likely to become warmer with heavier precipitation than the southern part in the future. Higher temperature and lower rainfall were projected during the late 21st century (2070s) than the mid-century (2040s) in the IRB.

Hydrological processes at basin scale are driven by climate and land-use changes. Hiso River watershed (HRW) is within a radiocesium contaminated area caused by the disaster in Fukushima Daiichi nuclear power plant (FDNPP). It’s urgently needed to make evaluations on how changes of climate and land-use bring impacts on hydrological processes, which control pollutants transport in watershed. This study applied a combination method of Statistical DownScaling Model (SDSM) and Soil and Water Assessment Tool (SWAT) to generate future climatic and hydrologic variables. Future climate data was obtained from three Representative Concentration Pathway (RCP2.6, 4.5 and 8.5) scenarios of a single General Circulation Models (GCMs) in three future periods of 2030s, 2060s and 2090s (2010-2039, 2040-2069, 2070-2099), with a baseline period (1980-2009). Furthermore, according to land-use change in HRW during 2013-2017, three land-use change scenarios under the three future climate scenarios were established. Results suggested that SDSM showed good capabilities in capturing daily maximum/minimum temperature and precipitation. The SWAT model presented good performances in simulating monthly and yearly streamflow. Results also suggested projected higher temperatures and lower rainfall led to decreased annual water yield and evapotranspiration (ET). The annual water yield and ET decreased in most seasons while had a slight increase in spring. RCP8.5 scenario always generated larger magnitudes for climatic variables and water balance components compared with other climate scenarios. Land-use changes had strong impact on surface runoff and groundwater flow. These findings could provide reference for decontamination and revitalization policy-making under complicated land use and climate change conditions.

A modified Green-Ampt model was developed to simulate water infiltration in fine-textured soil with a coarse interlayer. Because under such a soil structure, the two soils may not be fully saturated during infiltration, the model introduced two parameters—that is, the saturation coefficients a and b, to reflect the incomplete saturation condition and their influence on infiltration processes. In order to analyze the variation pattern of the two parameters in the above proposed model, scenarios were set for soil column infiltration in fine-textured soil with a coarse interlayer under different buried depths. A Richards equation-based model (RE-Model) was built for simulating the above scenarios and to obtain the evolution of soil water content along the soil profiles. Simulation results show that the infiltration rate decreased to a constant value when the wetting front crossed the upper interface between the fine and coarse soil layer. The soil matrix suction (ψ₂) at the upper interface remained unchanged after the wetting front advanced into the coarse layer, and the steady value of ψ₂ showed a linear relationship with the buried depth of the coarse layer. Based on the simulation results of the RE-Model, a method was proposed to determine the saturation coefficients related to the relative hydraulic conductivity and water content at ψ₂ in the modified Green-Ampt model. Then, the modified model was tested under various infiltration conditions with different soil layered structures, and the results showed good agreement with the experimental data.

In the globalized world, water utilization and carbon emissions are two important indicators for water and energy resources evaluation. This paper investigates the inter-sectoral linkage and external trade of virtual water (water embodied in products) and embodied carbon emissions in China based on input–output tables during 1997–2015. Results indicate that: inside China, agriculture, the electric and water industry are major virtual water suppliers, while heavy industrial sectors including the metal products industry, the petrochemical industry, other nonmetallic mineral products industry, and the mining industry are major embodied carbon emissions suppliers. China is the net exporter of virtual water (137.15 × 10⁹ m³) and embodied carbon emissions (16.05 × 10⁸ t). From the perspective of industrial chain, about 81% of virtual water export come from agriculture, the electric and water industry ultimately, and about 85% of embodied carbon emissions export come from the mining industry, the petrochemical industry, other nonmetallic mineral products industry, the metal products industry, and the electric and water industry ultimately.