Evolution patterns and spatial sources of water and sediment discharge over the last 70 years in the Yellow River, China: A case study in the Ningxia Reach

Changes in sediment load in the Lower Yellow River and its driving factors from 1919 to 2021

Rivers are not only an essential component of the development of civilization and the carbon cycle worldwide, but also a main contributor to natural disasters, especially the Lower Yellow River (LYR). With the functional degradation of the water-sediment regulation scheme (WSRS), LYR has reached a new stage. Thus, the changes in the sediment load in the Suspended River and its driving factors have significant practical applications. In this study, the sediment load in the LYR was analyzed from 1919 to 2021 based on improved sediment identity factor decomposition, wavelet analysis, and a double cumulative curve. The results showed that the changes in discharge and sediment exhibited poor synchronicity at different timescales. The sediment load decreased significantly, with evident periodicity of 9-10 years (years denoted as 'a') since 1950, and 69-a, 32-a, and 9-a since 1919. The changes in the sediment load can be divided into four phases: 1919-1959, 1960-1979, 1980-1998, and 1999-2021. Artificial levees can effectively constrain water flow and enhance sediment transport when the levee spacing is less than 6 km. To restrain deposition of the LYR, large dams control the incoming sediment coefficient so as to not exceed 0.009 kg∙s m-6. However, the WSRS reached its limit in 2010, and the wandering reach showed a deteriorating trend. Human activities control the changes in the sediment load. The reduction in the sediment load was mainly attributed to decreases in effective water yield capacity (53 %-75 %) before 1999 and sediment concentrations (46 %-65 %) after 1999. These results can provide a reference for further management of the suspended river.

Interpretable machine learning guided by physical mechanisms reveals drivers of runoff under dynamic land use changes

Human activities continuously impact water balances and cycling in watersheds, making it essential to accurately identify the responses of runoff to dynamic changes in land use types. Although machine learning models demonstrate promise in capturing the intricate interplay between hydrological factors, their "black box" nature makes it challenging to identify the dynamic drivers of runoff. To overcome this challenge, we employed an interpretable machine learning method to inversely deduce the dynamic determinants within hydrological processes. In this study, we analyzed land use changes in the Ningxia section of the middle Yellow River across four periods, laying the foundation for revealing how these changes affect runoff. The sub-watershed attributes and meteorological characteristics generated by the Soil and Water Assessment Tool (SWAT) model were used as input variables of the Extreme Gradient Boosting (XGBoost) model to simulate substantial sub-watershed rainfall runoff in the region. The XGBoost was interpreted using the SHapley Additive exPlanations (SHAP) to identify the dynamic responses of runoff to the land use changes over different periods. The results revealed increasingly frequent interchanges between the land use types in the study area. The XGBoost effectively captured the characteristics of the hydrological processes in the SWAT-derived sub-watersheds. The SHAP analysis results demonstrated that the promoting effect of agricultural land (AGRL) on runoff gradually weakens, while forests (FRST) continuously strengthen their restraining effect on runoff. Relevant land use policies provide empirical support for these findings. Furthermore, the interaction between meteorological variables and land use impacts the runoff generation mechanism and exhibits a threshold effect, with the thresholds for relative humidity (RH), maximum temperature (MaxT), and minimum temperature (MinT) determined to be 0.8, 25 °C, and 15 °C, respectively. This reverse deduction method can reveal hydrological patterns and the mechanisms of interaction between variables, helping to effectively addressing constantly changing human activities and meteorological conditions.

Changes of Tamarix austromongolica forests with embankment dams along the Laizhou bay

Background

Embankment dams were built south of the Laizhou bay in China for controlling storm surge disasters, but they are not enough to replace coastal forests in protecting the land. This study was designed to evaluate the effects of embankment dams on natural forests dominated by Tamarix austromongolica and test whether the dam-shrub system is a preferable updated defense.

Methods

Coastal forests on two typical flats, one before and one behind embankment dams, were investigated using quadrats and lines. Land bareness, vegetation composition and species co-occurrence were assessed; structures of T. austromongolica populations were evaluated; and spatial patterns of the populations were analyzed using Ripley's K and K1,2 functions.

Results

In the area before embankment dams, 84.8% of T. austromongolica were juveniles (basal diameter ≤ 3 cm), and 15.2% were adults (basal diameter > 3 cm); behind the dams, 52.9% were juveniles, and 47.1 were adults. In the area before the dams, the land bareness was 13.7%, four species occurred, and they all were ready to co-occur with T. austromongolica; behind the dams, the land bareness was 0%, and 16 species occurred whereas they somewhat resisted co-occurrence with T. austromongolica. In the area before the dams, the T. austromongolica population was aggregated in heterogeneous patches, and the juveniles tended to co-occur with the adults; behind the dams, they were over-dispersed as nearly uniform distributions, while the juveniles could recruit and were primarily independent of the adults. These results indicate that the T. austromongolica species did not suffer from the unnatural dams, but benefited somehow in population expansion and development. Overall, the T. austromongolica species can adapt to artificial embankment dams to create a synthetic defense against storm surges.

Spatiotemporal evolution of runoff and sediment and their dominant driving factors in the Lower Jinsha River basin

The Jinsha River Basin (JRB) contributes a significant amount of sediment to the Yangtze River; however, an imbalance exists between runoff and sediment. The underlying mechanisms and primary factors driving this imbalance remain unclear. In this study, the Shapley Additive Explanation (SHAP) and Geographical Detector Model (GDM) were employed to quantify the importance of the driving factors for water yield (WYLD) and sediment yield (SYLD) using the Soil and Water Assessment Tool (SWAT) model in the JRB. The results indicated that the SWAT model performed well in simulating runoff and sediment, with R2 > 0.61 and NSE > 0.5. Based on the simulated data, SYLD exhibited strong spatiotemporal linkages with WYLD. Temporally, both sediment and runoff showed decreasing trends, with the sediment decrease being more pronounced. Spatially, WYLD and SYLD displayed similar distribution patterns, with low values in the southwest and high values in the northeast. By quantifying the driving factors, we found that climatic factors, including precipitation and potential evapotranspiration, were the main influencing factors for WYLD and SYLD across the entire region, though their contributions to the two variables differed. For WYLD, climatic factors accounted for 70 % of the total influencing factors, whereas their contribution to SYLD was 50 %. Furthermore, soil type and land-use type played significant roles in the SYLD, with importance values of 16 % and 12 %, respectively. Under the influence of surface conditions, the proportion of SYLD in the JRB to the total SYLD in the Yangtze River Basin was greater than that of WYLD. The findings of this study provide scientific evidence and technical support for local environmental impact assessments and the formulation of soil and water conservation plans.

Drainage ditches are significant sources of indirect N2O emissions regulated by available carbon to nitrogen substrates in salt-affected farmlands

Agriculture is a main source of nitrous oxide (N2O) emissions. In agricultural systems, direct N2O emissions from nitrogen (N) addition to soils have been widely investigated, whereas indirect emissions from aquatic ecosystems such as ditches are poorly known, with insufficient data available to refine the IPCC emission factor. In this contribution, in situ N2O emissions from two ditch water‒air interfaces based on a diffusion model were investigated (almost once per month) from June 2021 to December 2022 in an intensive arable catchment with high N inputs and salt-affected conditions in the Qingtongxia Irrigation District, northwestern China. Our results implied that agricultural ditches (mean 148 μg N m-2 h-1) were significant sources for N2O emissions, and were approximately 2.1 times greater than those of the Yellow River directly connected to ditches. Agronomic management strategies increased N2O fluxes in summer, while precipitation events decreased N2O fluxes. Agronomic management strategies, including fertilization (294--540 kg N hm-2) and irrigation on farmland, resulted in enhanced diffuse N loads in drain water, whereas precipitation diluted the dissolved N2O concentration in ditches and accelerated the ditch flow rate, leading to changes in the residence time of N-containing substances in water. The spatial analysis showed that N2O fluxes (202-233 μg N m-2 h-1) in the headstream and upstream regions of ditches due to livestock and aquaculture pollution sources were relatively high compared to those in the midstream and downstream regions (100-114 μg N m-2 h-1). Furthermore, high available carbon (C) relative to N reduced N2O fluxes at low DOC:DIN ratio levels by inhibiting nitrification. Spatiotemporal variations in the N2O emission factor (EF5) across ditches with higher N resulted in lower EF5 and a large coefficient of variation (CV) range. EF5 was 0.0011 for the ditches in this region, while the EF5 (0.0025) currently adopted by the IPCC is relatively high. The EF5 variation was strongly controlled by the DOC:DIN ratio, TN, and NO3--N, while salinity was also a nonnegligible factor regulating the EF5 variation. The regression model incorporating NO3--N and the DOC:DIN ratio could greatly enhance the predictions of EF5 for agricultural ditches. Our study filled a key knowledge gap regarding EF5 from agricultural ditches in salt-affected farmland and offered a field investigation for refining the EF5 currently used by the IPCC.

Effects of irrigation on the fate of microplastics in typical agricultural soil and freshwater environments in the upper irrigation area of the Yellow River

Agricultural activities are among the most significant sources of microplastics (MPs) in water. However, few studies have explored the effect of irrigation on the fate of MPs in agricultural systems. This study investigated the distribution of MPs in agricultural soil, surface water, and sediment of adjacent rivers, as well as the "MP communities" in various environments before and after irrigation in a typical agricultural irrigation area of the Yellow River. MPs were detected in all of the examined sites. The number of MPs in surface water and sediment increased after irrigation, whereas those in the surface soil of croplands decreased. In the vertical direction, irrigation accelerated the migration of MPs (< 100 µm) deep into the soil. The vertical mobility of fibers in soil was faster than that of other types of MPs. Moreover, irrigation decreased the correlation between soil properties and MPs in soils. MP community analysis indicated that irrigation enhanced the differences between MP communities among adjacent environments. Collectively, our findings confirmed that river water irrigation caused secondary MP pollution in the soil environment and accelerated MP pollution in deep soil. Therefore, this study provides a theoretical basis for the development of strategies for MP pollution control in agricultural soil.