ABSTRACT
Groundwater irrigation districts, which play a crucial role in the Earth's critical zone, are confronted with numerous challenges, including water scarcity, pollution, and ecological degradation. These issues come from multiple systems and are linked to a groundwater-dominated water-food-environment-ecosystem nexus problem related to agricultural activities (WFEE). There is a pressing need for the scientific characterization and evaluation of the WFEE nexus in groundwater irrigation districts to assure high-quality, sustainable development. Furthermore, it is critical to provide practical and efficient regulations at the farmer level to uphold the health of this nexus. This paper presents a mapping network that focuses on groundwater irrigation districts. The network aims to convert the restriction indicators utilized to maintain the health of the WFEE nexus (at the irrigation district scale) into the targets employed to manage farmers' living and agricultural activities (at the farmer scale). Additionally, a system dynamics model is created to track and manage the interacting relationships between the WFEE nexus and farmers' living and agricultural activities. This proposed model employs a structured parameter system comprising targets, state parameters, regulatory parameters, and evaluation parameters. This system can get insight into the status of the WFEE nexus at the farmer level using state parameters, induce tailored management and regulation measures using regulatory parameters, assess the effectiveness of various measures using the evaluation parameters, and finally provide decision support to enhance the health of the WFEE nexus. The findings from the research conducted in the Yong'an groundwater irrigation district demonstrated that the model accurately described the relationship between the WFEE nexus and farmers' activities in groundwater irrigation districts. Furthermore, the model responded strongly to a variety of improvement strategies, including adjustments in planting area, optimization of planting pattern, improvement of irrigation method, and implementation of agronomic measures. As a result, it provided farmers with decision support for applying agricultural management methods and addressing the WFEE nexus problem in groundwater irrigation areas.
ABSTRACT
The purpose of this study is to illustrate intrinsic correlations and their temporal evolution between hydro-meteorological elements by building three-element-composed system, including precipitation (P), runoff (R), air temperature (T), evaporation (pan evaporation, E), and sunshine duration (SD) in the Wuding River Basin (WRB) in Loess Plateau, China, and to provide regional experience to correlational research of global hydro-meteorological data. In analysis, detrended partial cross-correlation analysis (DPCCA) and temporal evolution of detrended partial-cross-correlation analysis (TDPCCA) were employed to demonstrate the intrinsic correlation, and detrended cross-correlation analysis (DCCA) coefficient was used as comparative method to serve for performance tests of DPCCA. In addition, a novel way was proposed to estimate the contribution of a variable to the change of correlation between other two variables, namely impact assessment of correlation change (IACC). The analysis results in the WRB indicated that (1) DPCCA can analyze the intrinsic correlations between two hydro-meteorological elements by removing potential influences of the relevant third one in a complex system, providing insights on interaction mechanisms among elements under changing environment; (2) the interaction among P, R, and E was most strong in all three-element-composed systems. In elements, there was an intrinsic and stable correlation between P and R, as well as E and T, not depending on time scales, while there were significant correlations on local time scales between other elements, i.e., P-E, R-E, P-T, P-SD, and E-SD, showing the correlation changed with time-scales; (3) TDPCCA drew and highlighted the intrinsic correlations at different time-scales and its dynamics characteristic between any two elements in the P-R-E system. The results of TDPCCA in the P-R-E system also demonstrate the nonstationary correlation and may give some experience for improving the data quality. When establishing a hydrological model, it is suitable to only use P, R, and E time series with significant intrinsic correlation for calibrating model. The IACC results showed that taking pan evaporation as the representation of climate change (barring P), the impacts of climate change on the non-stationary correlation of P and R was estimated quantitatively, illustrating the contribution of climate to the correlation variation was 30.9%, and that of underlying surface and direct human impact accounted for 69.1%.
