Enhancing rice production sustainability and resilience via reactivating small water bodies for irrigation and drainage.

Rice farming threatens freshwater resources, while also being increasingly vulnerable to drought due to climate change. Rice farming needs to become more sustainable and resilient to climate change by improving irrigation drainage systems. Small water bodies, used to store drainage water and supply irrigation in traditional rice farming systems have gradually been abandoned in recent decades. This has resulted in a higher water footprint (WF) associated with rice farming due to increased freshwater usage and wastewater release, also leaving rice production more vulnerable to extreme weather events. Here, we propose how protecting and reactivating small water bodies for rice irrigation and drainage can decrease rice production WF in China by 30%, save 9% of China's freshwater consumption, increase irrigation self-sufficiency from 3% to 31%, and alleviate yield loss in dry years by 2-3%. These findings show that redesigning rice irrigation drainage systems can help meet water scarcity challenges posed by climate change.

Improved estimation of nitrogen dynamics in paddy surface water in China.

Paddy surface water is the direct source of artificial drainage and surface runoff leading to N loss from rice paddy fields. Quantifying the N dynamics in paddy surface water on a large scale is challenging because of model deficiencies and the limitations of field measurements. This study analyzed the N dynamics and the influencing factors in paddy surface water in the three main Chinese rice-growing regions: Northeast Plain, Yangtze River Basin, and Southeast Coast. An improved first-order kinetic model was proposed to evaluate the total nitrogen (TN) dynamics at a countrywide scale by improving the calculation method of the initial TN concentration (C0) and providing the optimum value of attenuation coefficient (k). The results show that: (1) the average reduction rate of TN concentration on the 7th day after fertilization increased with the growth period (85%, 90%, and 95% during the basal, tillering, and panicle fertilization periods, respectively); (2) the attenuation coefficient k for the growth periods was ranked as follows: panicle fertilization period > tillering fertilization period > basal fertilization period. The Yangtze River Basin had the highest average k value (0.31-0.34), followed by the Southeast Coast (0.24-0.41) and Northeast Plain (0.22-0.30); and (3) the improved first-order kinetic model performed well in the N dynamics estimation (R2 > 0.6). High TN concentration with high fertilizer application amounts and precipitation caused the Yangtze River Basin to have a high N runoff loss risk. The proposed universal model realizes the simulation of N dynamics from a single site to multi-sites while greatly saving multi-site monitoring costs. This study provides a basis for effectively optimizing N management and preventing N loss in rice paddies.

Real-time measurement of total nitrogen for agricultural runoff based on multiparameter sensors and intelligent algorithms.

Real-time monitoring of non-point source (NPS) pollution is challenging owing to the minute-scale change in runoff flow and concentration under rainfall condition. In this study, we proposed a real-time measurement method for total nitrogen (TN) by combining the timeliness of sensor detection and the accuracy of intelligent algorithms, based on the physical and chemical relationships between TN and sensor-measured indexes. Extra tree regression was selected as the TN inversion algorithm, which has high precision, high computational efficiency, and better ability in over-fitting control. The results show that: (1) the real-time inversion algorithm of TN can achieve the monitoring frequency at the minute scale (<5 min); (2) the method performs well (R2>0.9) when the training and testing datasets are from similar environmental backgrounds (fields or ditches); (3) in the case of partial variable missing, this method can still realize TN inversion, and the prediction accuracy is acceptable (R2>0.7) under the number of missing variables (n) ≤ 2, which makes up for the flaws of missing or abnormal data caused by sensor malfunctions. Overall, the proposed real-time measurement method of TN has stable data acquisition, high precision, and high monitoring frequency. In addition, the method is not limited by cloudy, rainy, or nighttime conditions. Compared with methods such as laboratory test, remote sensing inversion, and water quality automatic monitoring station, our method has obvious advantages in runoff monitoring of NPS pollution, which mainly occurs in small and micro water bodies. The new real-time measurement of TN for runoff may provide important technological support for pre-warning and emergency control of NPS pollution.

Preferred hierarchical control strategy of phosphorus from non-point source pollution at regional scale.

Spatiotemporal heterogeneity poses challenges on prevention and control of non-point source (NPS) pollution. Treating pollution sources sequentially by prioritizing the critical periods (CPs) and critical source areas (CSAs) is essential for effective control of regional NPS pollution. In this study, the gird-based dual-structure export empirical model (DSEEM) was used to simulate phosphorus losses in the Danjiangkou Reservoir Basin (DRB) on a monthly scale. Based on the co-analysis of CPs and CSAs coupled with the point density analysis (PDA), a preferred hierarchical control strategy, which was connected with regional management units, was proposed to improve the pertinence for phosphorus loss control. CPs, sub-CPs, and non-CPs were identified on the temporal scale; CSAs, sub-CSAs, and non-CSAs were identified on the spatial scale. The results showed that CPs (July, April, and September), sub-CPs (May, March, and August), and non-CPs contributed 62.8%, 31.1%, and 6.1% of the annual TP loads, respectively. Furthermore, we proposed a hierarchical control strategy for NPS pollution: class I (CSAs in CPs) → class II (sub-CSAs in CPs, CSAs in sub-CPs) → class III (non-CPs, non-CSAs, sub- and non-CSAs in sub-CPs). Class I covered the periods and areas with the highest loads, contributing 26.2% of the annual loads within 14.5% of the area and 25.0% of the time. This study provides a reference for the targeted control of NPS pollution at regional scale, especially in environmental protection with limited funds.

Evolution and restoration of water quality in the process of urban development: a case study in urban lake, China.

Urban development has positive and negative effects on the evolution of enclosed lake water quality. This study aims to quantitatively analyze the water quality evolution of a typical urban lake, the Sha Lake, in the process of urban development. The land use degree comprehensive index (I) was calculated to reveal the level of urban development; water quality index (Smid) and eutrophication index (Tmid) were used to evaluate the water quality changes by fuzzy comprehensive-quantifying assessment (FCQA) method. The urban construction process and the water quality changes in 2000-2018 in the Sha Lake Basin were divided into three stages: (1) in 2000-2006, with the slow urban development, water quality remained stable and the degree of eutrophication improved slightly; (2) in 2007-2009, I increased rapidly to reach 300, Smid and Tmid increased from 90.62 to 92.83 and 75.06 to 87.52, respectively. Water quality deteriorated because of the failure to implement environmental protection measures in time; (3) in 2010-2018, although urban development reached a high level (I > 300), the water network connection project, dredging project, exogenous pollutant control, and sewage pipe network renovation since 2009 were critical measures to improve water quality for a long time. Due to the lag effect on improving water quality, the implementation of environmental protection measures should be synchronized with or even before urban construction. The research results can provide a scientific basis for the urban lake water environment protection in the process of urban development.

Cooperative identification for critical periods and critical source areas of nonpoint source pollution in a typical watershed in China.

Critical periods (CPs) and critical source areas (CSAs) refer to the high-risk periods and areas of nonpoint source (NPS) pollution in a watershed, respectively, and they play a significant role in NPS pollution control. The upstream Daning River Basin is a typical watershed in the Three Gorges Reservoir area. In this study, a Hydrological Simulation Program-Fortran (HSPF) model was used to simulate phosphorus loss in the upstream Daning River Basin. Co-analysis of critical periods and critical source areas (CACC) is a quantitative collaborative analysis method for the identification of CSAs in CPs, and it was used to classify the periods and areas of NPS pollution as CPs, sub-CPs, non-CPs, CSAs, and non-CSAs. The CPs occurred in months 5-7 and accounted for 53.7% of the total phosphorus (TP) loads, and the sub-CPs occurred in months 1, 3, 4, and 8 and accounted for 29.2% of the TP loads. In CSAs, 49.4% of the TP loads occurred in 26.8% of the basin. Furthermore, we proposed the following multilevel priority control measure for NPS pollution in the upstream Daning River Basin: CSAs in CPs (with load-area rate of 1.4), CSAs in sub-CPs (0.7), CSAs in non-CPs (0.4), non-CSAs in CPs (0.3), non-CSAs in sub-CPs (0.2), and non-CSAs in non-CPs (0.1). CSAs in CPs accounted for 25.8% of the TP loads from 19.0% of the areas in only 3 months while 49.4% of the TP loads from similar areas over an entire year. These findings indicated that the CSAs in CPs located in farmland along the Daning, Dongxi, and Houxi Rivers should be prioritized for pollution management measures.