•We analyzed change trends of the climate variables ET0 and AI in an arid region of China over the past 50years.•We identified the sensitivity of ET0 and AI to the main climate variables.•We ...quantified the contributions of climate variables to the changes in ET0 and AI.•Contribution of wind speed decline to decrease of ET0 is larger than other climate variables.•The increase of precipitation contributes more than the decrease of ET0 to decrease of AI.
Temporal variations in reference evapotranspiration (ET0) and aridity index (AI) were comprehensively investigated for 23 meteorological stations during 1955–2008 in the northwest China. The quantitative contributions of the major meteorological variables to the ET0 and AI trends were evaluated and the possible causes were also investigated. The results showed that in the past 50years annual temperature, humidity and precipitation had significant increasing trends with time, and wind speed and radiation had decreasing trends. ET0 had a significant decreasing trend with an averagely value of about 3mm per year, and AI had also witnessed a decreasing trend; For ET0, wind speed was the most sensitive meteorological variable, followed by relative humidity, temperature and radiation and for AI, precipitation was the most sensitive meteorological variable. The contribution of wind speed to the decrease of ET0 is more than that of other meteorological variables. The increase of precipitation contributes more than the decrease of ET0 to decrease of AI in past 50years. This study provides an understanding of the effect of recent climate change on drought in arid northwest China.
Alternate wetting and drying (AWD) irrigation is a reliable and widespread water-saving technology for rice production. This review aimed to comprehensively assess the changes in water use, yield, ...nitrogen use efficiency (NUE), and greenhouse gas (GHG) emissions after AWD adoption and explore the optimal AWD water thresholds. Based on abundant data obtained from contrasting experiments between AWD and continuous flooding (CF) irrigation, the effects of AWD were quantified by stepwise multiple linear regression (MLR). The quantitative indices are the changes in total irrigation water (ΔIW), water productivity (ΔWP), grain yields (ΔGY), NUE indices, global warming potential (ΔGWP), and yield-scaled global warming potential (ΔYGWP) between AWD and CF. It was found that the ΔC-A (i.e. the difference between the CF and AWD thresholds) and soil types were the most noteworthy indicators affecting IW, water productivity, yield and partial factor productivity of N (PFPN). Meanwhile, the ΔC-A and fertilizer-N rates (NR) were two key indicators affecting GHG emissions. Thereafter, for different soil types, a group of optimization models were established to explore the optimal AWD water thresholds for optimizing ΔIW and ΔWP simultaneously without yield, NUE, and GHG emissions penalties. The results showed that the optimal upper limit of AWD (UAWD) should be equal to the upper limit of the CF (UCF), and the optimal lower limit of AWD (LAWD) can be obtained by the model. Taking the clay paddy field as an example, the min ΔIW were −41% to −8%, and the max ΔWP were 11%–54% after adopting optimal AWD water managements. The corresponding ΔGY, ΔPFPN, ΔGWP, ΔYGWP were 0%–1%, 0%–1%, −66% to −15% and −52% to −12%, respectively. This review provides a novel way to estimate the performance of AWD and provide guidance for proper AWD water management.
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•Effects of AWD on water use, yield, NUE and GHG emissions were reviewed and analyzed.•ΔC-A and soil types were critical indicators for IW, water productivity, yield and PFPN.•ΔC-A and NR were key indicators affecting changes in GHG emissions after AWD adoption.•The optimal water thresholds of AWD were assessed by a novel optimization model.•The optimal UAWD was equal to UCF, and optimal LAWD was obtained by the model.
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•Biochar and composted chicken manure (CCM) were used to remediate six NEOs in soil.•The combined use of biochar and CCM had excellent immobilization effect on NEOs.•NEOs-abiotic ...degradation was enhanced by biochar, CCM and their combination.•The combined use selectively stimulated the NEOs-degraders.•The combined use simplified -NO2-containing NEOs dissipation, but inhibited -C≡N-containing NEOs.
Neonicotinoid (NEO) pesticides have become a potential risk to ecological safety and human health after application. The combined use of biochar and organic fertilizer (OF) is a promising approach to reduce pesticide adverse effects and improve soil fertility in agricultural soils. However, the combined remediation effects of biochar and OF on immobilization and dissipation of NEOs in soils have not previously been systematically investigated. In this study, biochars derived from peanut shell prepared at low/high pyrolysis temperatures (PS400 and PS900) were combined with composted chicken manure (CCM) as an example for OF to remediate contaminated soils toward six typical NEOs, nitenpyram (NIT), thiamethoxam (THIA), clothianidin (CLO), imidacloprid (IMI), acetamiprid (ACE), thiacloprid (THI). Results shown that both biochars and CCM were effective in improving soil sorption capacity and immobilization efficiency. The Freundlich affinity parameters (Kf) of NEOs in soils increased 7.2–12.0 times after the combined remediation of biochar and CCM, and the Kf of six NEOs had negative correlation with their lipophilicity (p < 0.05), which followed by THI > ACE ≈ IMI > CLO > THIA > NIT. Meanwhile, NEOs-abiotic degradation was accelerated by biochar, CCM and their combined addition by adjusting soil pH and stimulating hydrolysis action. Biotic degradation was dominant in NEOs dissipation processes in amended soils, and the contribution ratios of biotic degradation (CRbio) were in the range of 25.4–99.0%. The combined use of biochar and CCM selectively stimulated the relative abundance of NEOs-degraders, which simplified abiotic degradation of -NO2-containing NEOs (viz., NIT, THIA, CLO, and IMI), but inhibited -C≡N-containing NEOs (viz., ACE and THI). The combined remediation provided a strategy for immobilizing NEOs and facilitating dissipation of -NO2-containing NEOs in soils. The results in this study provide valuable information for policymakers and decision-makers to choose appropriate soil remediation approaches with respect to the NEO types.
•Soil water and salt, relative maize yield can be predicted acceptably by the SWAP model.•Effect of irrigation on relative yield is unobvious for maize on the saline soil.•Salt amount and accumulated ...range vary with irrigation water quantity and salinity.•Irrigation schedules are evaluated for 50% hydrologic year.•Long term prediction of soil water-salt and relative yield is performed by SWAP model.
Soil salinization and water quality deterioration severely limit the development of irrigation agriculture in arid areas. Transient numerical models such as the agro-hydrological Soil-Water-Atmosphere-Plant (SWAP) model have played an important role in agricultural irrigation management. In order to find the optimal irrigation practices for spring maize grown on saline soil in Shiyang River Basin, the SWAP model was calibrated and validated to simulate water-salt transport and relative yield based on field experiments in 2008 and 2009. The average annual precipitation in this area is about 164mm. Experimental observations of soil water content, soil salinity and maize growth were made in lysimeters filled with disturbed loam soil having saturation extract water salinity (ECe) around 5.76dSm−1. Six irrigation treatments altogether including three levels of irrigation water amount: 100%, 67% and 50% ETc (evapotranspiration, 510mm) and two levels of irrigation water salinity: 0.65 and 3.2dSm−1 were arranged, each treatment with 3 replications for each treatment. The acceptable root mean square error (RMSE), mean relative error (MRE), the Nash and Sutcliffe model efficiency (NSE), the coefficient of determination (R2) between simulation and observation of soil water content, salt concentration and relative yield demonstrated that the calibrated SWAP model was applicable to irrigation management evaluation for maize grown on saline soil. Based on the analysis of simulated water and salt balance, relative yield and relative water use efficiency, the optimal irrigation schedule of maize grown on the saline soil for 50% hydrologic year was irrigation amount of 460mm with four times, for both fresh water 0.65dSm−1 (80Fr) and slight saline water 3.2dSm−1 (80Sal3). Compared to fresh irrigation treatment, higher soil water content and salt concentration, and lower relative yield and relative water use efficiency were obtained by saline irrigation treatment. However, for the maize grown on saline soil, the effect of irrigation amount at high level on relative yield and water use efficiency was unobvious with the difference less than 4%. Relative yield with 0.74 and 0.63 can be obtained by 80Fr and 80Sal3 every year after soil water-salt reached balance.
•GLUE method with LHS was used to evaluate the uncertainty of RZWQM2.•The CL function was introduced in GLUE analysis.•Output of RZWQM2 is sensitive to soil parameters including Ksat, ANIT, ADEN, ...AHYD.
Quantitatively ascertaining and analyzing the effects of model uncertainty on model reliability is a focal point for agricultural–hydrological models due to more uncertainties of inputs and processes. In this study, the generalized likelihood uncertainty estimation (GLUE) method with Latin hypercube sampling (LHS) was used to evaluate the uncertainty of the RZWQM-DSSAT (RZWQM2) model outputs responses and the sensitivity of 25 parameters related to soil properties, nutrient transport and crop genetics. To avoid the one-sided risk of model prediction caused by using a single calibration criterion, the combined likelihood (CL) function integrated information concerning water, nitrogen, and crop production was introduced in GLUE analysis for the predictions of the following four model output responses: the total amount of water content (T-SWC) and the nitrate nitrogen (T-NIT) within the 1-m soil profile, the seed yields of waxy maize (Y-Maize) and winter wheat (Y-Wheat). In the process of evaluating RZWQM2, measurements and meteorological data were obtained from a field experiment that involved a winter wheat and waxy maize crop rotation system conducted from 2003 to 2004 in southern Beijing. The calibration and validation results indicated that RZWQM2 model can be used to simulate the crop growth and water–nitrogen migration and transformation in wheat–maize crop rotation planting system. The results of uncertainty analysis using of GLUE method showed T-NIT was sensitive to parameters relative to nitrification coefficient, maize growth characteristics on seedling period, wheat vernalization period, and wheat photoperiod. Parameters on soil saturated hydraulic conductivity, nitrogen nitrification and denitrification, and urea hydrolysis played an important role in crop yield component. The prediction errors for RZWQM2 outputs with CL function were relatively lower and uniform compared with other likelihood functions composed of individual calibration criterion. This new and successful application of the GLUE method for determining the uncertainty and sensitivity of the RZWQM2 could provide a reference for the optimization of model parameters with different emphases according to research interests.
This study proposed a new mobile‐immobile model (MIM) to describe reactive solute transport with scale‐dependent dispersion in heterogeneous porous media. The model was derived from the conventional ...MIM but assumed the dispersivity to be a linear or exponential function of travel distance. The linear adsorption and the first‐order degradation of solute were also considered in the model. The Laplace transform technique and the de Hoog numerical Laplace inversion method were applied to solve the developed model. Solute breakthrough curves (BTCs) obtained from MIM with scale‐dependent and constant dispersions were compared, and a constant effective dispersivity was provided to reflect the lumped scale‐dependent dispersion effect. The effective dispersivity was calculated by arithmetically averaging the distance‐dependent dispersivity. With this effective dispersivity, MIM could produce similar BTC as that from MIM with scale‐dependent dispersion in porous media with moderate heterogeneity. The applicability of the proposed new model was tested with concentration data from a 1,250‐cm long and highly heterogeneous soil column. The simulation results indicated that MIM with constant and linear distance‐dependent dispersivities were unable to adequately describe the measured BTCs in the column, while MIM with exponential distance‐dependent dispersivity satisfactorily captured the evolution of BTCs.
The Wuwei oasis, situated in the upper reaches of the Shiyang River basin in the arid inland of northwest China, is intensively cultivated using both groundwater and irrigation water originating from ...the Qilian Mountains. Groundwater levels are declining due to overuse of irrigation water. To estimate the decline over the entire Wuwei oasis, eight different interpolation methods were used for interpolating groundwater levels over 3 years, i.e. starting in 1983, followed by 1988 and ending with 1992. Cross-validation and orthogonal-validation were applied to evaluate the accuracy of the different methods. Root mean squared error and the correlation coefficient (R ²) were calculated for each of the interpolation methods and years. Three kriging methods (simply, ordinary, and universal) gave the best fit. Modified ordinary kriging was found better than simple and universal kriging methods with a smaller number of points having large differences (>50 m) between estimated and predicted values. Based on the groundwater surfaces determined by the ordinary kriging as modified by Yamamoto, the groundwater decline was found from 1983 to 1992 to be a modest 2.1 m in average.
Straw returning is an important measurement to determine the utilization of straw resources. Understanding the decomposition process and nutrient release process of straw is of great significance to ...the efficient utilization of straw resources and the sustainable development of the agricultural economy. In this study, the literature published in the CNKI and WOS from 2002 to 2022 was used as the data pool, and a keyword co-occurrence network map was drawn with the CiteSpace (6.2.R4) software. Visual analyses were based on the straw returning literature (1998 articles) and straw decomposition agent literature (125 articles), and the decomposition and nutrient release of straw under the action of a decomposition agent were analyzed using a straw decomposition characterization experiment. In general, returning straw can effectively improve soil fertility conditions and provide nutrients for crop growth, and the use of a straw decomposition agent can further improve soil conditions and increase crop yield. The straw decomposition characterization experiment further showed that Pseudomonas could effectively increase the decomposition rate and increase the nutrient release rate of straw. According to the above results, determining how to improve the utilization efficiency of straw resources via decomposable bacteriological agents according to local conditions will become a research hotspot in the future.
► Seepage tests compared different anti-seepage liners on a multi-layered canal bed. ► Seepage and soil water response were modelled using HYDRUS-2D. ► Further analysis and simulations were performed ...using the validated model. ► Soil layering produces distinct moisture zones with discontinuous wetting fronts. ► A low permeability soil layer is crucial for limiting canal seepage.
Ponding tests were conducted in the Shiyang River Basin in Northwest China to assess canal leakage characteristics. Four anti-seepage constructions (concrete lining, pebble lining, clay lining plus compacted canal bed, compacted canal bed only) were performed on four canal sections, which were situated in multi-layered soils. The canal sections were tested using a two-stage approach: First, a stable water level was maintained; second, a stage where the water level in the canal section was permitted to drop. The canal seepage rate and the soil water content near the canal bed were monitored during each stage and in each canal section. Soil texture, bulk density and hydraulic conductivity were determined in each canal section and soil layer. Double ring infiltration tests were performed to investigate infiltration behaviour from the canal sections. The saturated–unsaturated flow model HYDRUS-2D was applied to simulate canal seepage and the local soil water response. The simulation results compared well with the monitored data, indicating that the model can reliably simulate canal seepage under these complex soil structures and different canal liners. Both experimental results and numerical modelling show that the clay lining plus compacted canal bed provides the best anti-seepage performance, followed by compacted canal bed only, then pebble and concrete lining. Simulation results also predicted that the soil water content was discontinuous at the interface of distinct soil layers, and that the range and form of wetting front varied greatly in the four canal sections, with a larger wetted area for the more permeable canal. Simulations were performed to study the sensitivity of canal seepage to the permeability of each soil layer and canal liner. The results, confirmed by the double-ring infiltration tests, indicated that the canal lining is not the only factor affecting canal seepage: The soil permeability can also influence the seepage, especially where there is a low permeability layer (e.g., compacted soil layer) close to the canal.
Harmful algal blooms in eutrophic lakes pose significant challenges to the aquatic environment. Aerobic composting is an effectively method for processing and reusing dewatered algal sludge. The ...fungal communities are the main driver of composting. However, their relationship with carbon loss and the humification process during algal sludge composting remains unclear. In this study, the succession of fungal communities in algal sludge composting was investigated via internal transcribed spacer (ITS) rRNA amplicon sequencing analysis. Overall, no significant differences were observed with the α-diversity of fungal communities at different stages. The composition of the fungal communities changed significantly before and after compost maturation and became more stable after the compost maturation. Redundancy analysis showed that the fungal communities were significantly correlated with physicochemical properties, including humic acid (HA)/fulvic acid (FA), temperature, pH, humic acid, microcystins, and CO2. The co-occurrence network showed that different fungal community modules had different relationships with physicochemical properties. Structural equation modeling further revealed that different metabolic or transformation processes may be mainly driven by different fungi modules. The microcystin degradation, carbon loss, and humification during composting were mainly mediated by fungal communities which were mainly influenced by temperature. Humification was influenced not only by fungal communities but also by the microcystin levels. These results show that changes in the fungal community composition and interaction and their relationship with physicochemical properties could represent a useful guide for optimizing the composting process.
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