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Identifying important parameters in crop models is critical for model application. This study conducted a sensitivity analysis of 23 selected parameters of the advanced rice model ORYZA-N using the Extended FAST method. The sensitivity analysis was applied for three rice types (single-season rice in cold regions and double-season rice (early rice and late rice) in subtropical regions) and two irrigation regimes (traditional flood irrigation (TFI) and shallow–wet irrigation (SWI)). This study analyzed the parameter sensitivity of six crop growth outputs at four developmental stages and yields. Furthermore, we compared the variation in parameter sensitivity on model outputs between TFI and SWI scenarios for single-season rice, early rice, and late rice. Results indicated that parameters RGRLMX, FRPAR, and FLV0.5 significantly affected all model outputs and varied over developmental stages. Water stress in paddy fields caused by water-saving irrigation had more pronounced effects on single-season rice than on double-season rice. [ABSTRACT FROM AUTHOR]

Winter wheat production in the North China Plain (NCP) relies mainly on irrigation. To assess the effect irrigation management practices on crop production, the HYDRUS-1D model was modified by incorporating the crop growth module adopted from the EPIC model. The modified HYDRUS-1D model was calibrated and validated by using data collected from 2006/2007 and 2007/2008 winter wheat growing seasons in Beijing area. The predicted values for soil water content, soil nitrate concentration, crop growth, yield, and evapotranspiration showed good agreements with the measured values. The calibrated model was then used to evaluate the yield and water use efficiency (WUE) under different hydrologic years. The WUE for different irrigation depth was considered as the criterion for investigating the appropriate irrigation management practices. Results showed that the appropriate irrigation depth per application could be determined as 62.5% of the difference between 20 cmpan evaporation and precipitation for hydrologic years with 75%, 50% and 25% probability of rainfall occurrence, respectively, under the recommended nitrogen application rate in Beijing area. And the corresponding total irrigation amount was 244.7, 213.8 and 192.5 mm. The results of this study provide scientific implications for water management of winter wheat under sprinkler irrigation in the NCP and those areas with similar climatic and cropping practice conditions. [ABSTRACT FROM AUTHOR]

Reduction of water diversion from the Yellow River will intensify water shortage problems in the Yinbei Irrigation District (YID). Reasonable use of groundwater for irrigation is helpful to maintain the agricultural production. Groundwater exploitation may cause groundwater level declines in local areas. This helps to reduce the salinity accumulation in the root zone but decreases the capillary rise. Thus, it is important to figure out the responses of soil water-salt dynamics and crop yields to groundwater table fluctuations for salinity control and stable yields. In this study, HYDRUS-1D model was modified by coupling with the EPIC (erosion-productivity impact calculator) crop growth module for simulating agro-hydrological processes. The new crop module could simulate crop height, leaf area index (LAI), above-ground biomass and crop yield. The information between HYDRUS-1D and EPIC was exchanged by daily step. Root water uptake under water and salt stress was calculated with HYDRUS-1D and imported to EPIC to limit crop growth. EPIC module estimated crop height, LAI and root depth for HYDRUS-1D to calculate soil water-solute dynamics. HYDRUS-1D assumed that soil evaporation remained at the potential rate unless pressure head of the soil surface decreased to a prescribed value. After then this prescribed value was set as a constant head to renew the top boundary condition. However, it cannot reasonably reflect the decrease stage of soil evaporation when using the constant head boundary. This may overestimate soil evaporation. Therefore, a new soil evaporation module, estimating soil evaporation reduction coefficient using soil water content of the top layer (0-10 cm), was added for better describing the soil evaporation under shallow water tables. With the experimental data collected from the maize field in 2008, the model was calibrated by the data of groundwater irrigation treatment and validated by the data of canal irrigation treatment. Simulated soil water content and solute concentration in the root zone (0-90 cm) showed good agreement with the measured values. Root mean square error (RMSE), mean relative error (MRE) and coefficient of determination for soil moisture were 0.03 cm3/cm3, 3.4% and 0.78, respectively. For solute concentration, RMSE, MRE, coefficient of determination were 1.6 g/L, 1.3% and 0.29, respectively. LAI and above-ground biomass values were fitted well with the observations. MRE values for estimated and measured LAI and above-ground biomass were 5.9% and 10.6%, and R2 were both larger than 0.95 for these two items. The model was then used to assess the impacts of groundwater table and irrigation changes on soil water-salt dynamics and maize yields. Nine groundwater depth (GWD) scenarios (100, 110, 125, 140, 155, 170, 185, 200 and 250 cm) and 6 irrigation treatments (0.6, 0.8, 1.0, 1.2, 1.4 and 1.6 times of the present irrigation) were considered. The results showed that soil water content and salt storage in the root zone declined with the reduction of groundwater level and irrigation amount. Due to the decrease of groundwater contribution and soil moisture, lowering groundwater depth resulted in a gradual increase of the average solute concentration in the root zone. Maize yields increased first and then decreased as the groundwater table declined. Generally, the maximum yields were achieved when GWD was between 140 and 155 cm. The maize yields may decrease with reducing the irrigation amount, therefore water-saving strategies were not recommended for local farmers with low incomes. Finally, the optimum groundwater depth of 140-155 cm was suggested, and three irrigations with an amount of 900 m3/hm2 for each will be applied during maize growing period. [ABSTRACT FROM AUTHOR]

Highlights: [•] A 2D dynamic root water uptake model was developed based on Vrugt model. [•] The interaction between root water uptake and crop growth was considered. [•] A new coupled model was developed based on the CHAIN_2D and EPIC. [•] Crop yield and LAI can be simulated by the coupled model. [•] Using the coupled model to investigate appropriate irrigation management practices. [ABSTRACT FROM AUTHOR]

• Four data assimilation methods are compared to estimate time-varying parameters. • Parameter correction method is not sensitive to parameter update order. • Partitioned update parameter correction method has higher assimilation stability. The hydraulic properties of the soil top layer may change during the growth period due to various factors such as wetting and drying cycles, tillage practices, and crop root growth. In this study, the potential of the assimilation method to estimate time-varying soil hydraulic parameters is explored. Four assimilation schemes, including the simultaneous update state augmentation method, the partitioned update state augmentation method, the simultaneous update parameter correction method, and the partitioned update parameter correction method, are compared. The performance of four assimilation schemes on parameter estimations and soil moisture simulations is tested first using the synthetic case. The influence of initial parameter values and a parameter update order on assimilation is also analyzed. Finally, the partitioned update parameter correction method is applied to a real case involving a field drip irrigation experiment. The results show that when the analyzed parameter has either a periodical or a linear variation, there is a time lag between the assimilation value and the true value. The assimilation method can respond immediately to an abrupt change of the parameter value. Using the simultaneous update method leads to an obvious parameter correlation problem. In contrast, the partitioned update method can relieve the parameter correlation problems, thereby improving the accuracy of parameter estimations and pressure head simulations. However, when the initial values of the parameters deviate from their true values to a certain extent, the partitioned update method cannot obtain accurate parameter estimations. Compared with the partitioned update state augmentation method, the partitioned update parameter correction method is not sensitive to the parameter update order. The partitioned update parameter correction method has higher computational efficiency and assimilation stability, and it can obtain more accurate parameter estimations and soil moisture predictions in comparison with the traditional state augmentation method. The partitioned update parameter correction method provides an assimilation tool for improving the predictions of soil moisture by considering the time-varying parameters. [ABSTRACT FROM AUTHOR]

Efficient parameter identification is an important issue for mechanistic agro-hydrological models with a complex and nonlinear property. In this study, we presented an efficient global methodology of sensitivity analysis and parameter estimation for a physically-based agro-hydrological model (SWAP-EPIC). The LH-OAT based module and the modified-MGA based module were developed for parameter sensitivity analysis and inverse estimation, respectively. In addition, a new solute transport module with numerically stable schemes was developed for ensuring stability of SWAP-EPIC. This global method was tested and validated with a two-year dataset in a wheat growing field. Fourteen parameters out of the forty-nine total input parameters were identified as the sensitive parameters. These parameters were first inversely calibrated by using a numerical case, and then the inverse calibration was performed for the real field experimental case. Our research indicates that the proposed global method performs successfully to find and constrain the highly sensitive parameters efficiently that can facilitate application of the SWAP-EPIC model. [ABSTRACT FROM AUTHOR]

Water-saving irrigation is becoming more important in the upper Yellow River basin (YRB) due to reduced water allocation and growing water scarcity. However, drip irrigation as an efficient irrigation method, has not gained as much acceptance as one might expect. In this study, integrated approaches involving field experiments, agro-ecosystem modeling, and financial analysis were proposed to evaluate the multiple benefits of two irrigation methods. Field experiments on maize irrigated with border irrigation and drip irrigation under plastic mulching (i.e., BI-M and DI-M) were conducted in the Hetao Irrigation District (Hetao) of the upper YRB during 2021 and 2022. The AHC model was calibrated and validated using two-year experimental data, performing well in simulations of soil water-salt-nitrogen (N) dynamics and crop growth. An irrigation scheduling module was newly incorporated into AHC. Then the model was applied to analyze scenarios consisting of three classes of groundwater depth (GWD) and five N application levels. Optimal irrigation and N-fertilization strategies were suggested; and DI-M showed significant advantages over BI-M in terms of water-saving (56–66 mm), labor-saving, environmental benefits (50 kg ha−1 less N fertilizer and 19–25 kg ha−1 less N loss), and crop yields (<4%), both in experimental and scenario cases. However, the financial analysis revealed that the current smallholder BI-M could achieve higher net returns (about 12%) compared to DI-M, since the family labor is often not counted as a cost in smallholder farming. Additionally, the widespread adoption of BI-M is also partly attributed to its easy operation. Lastly, results indicated a trend where the advantages of drip irrigation would become more significant in the future, with the increasing agricultural population aging and rising labor costs in the YRB. • Experiments, surveys and AHC model were combinedly used for irrigation evaluation. • Water-salt-nitrogen fate and economic benefits were evaluated under various scenarios. • Optimal water-nitrogen strategies were suggested for border and drip irrigation. • Smallholder BI-M achieves higher net returns due to exclusion of family labor cost. • Drip irrigation has clear advantages in water, labor and eco-environmental benefits. [ABSTRACT FROM AUTHOR]

• Coupling AHC and SHAW models simulates year-round agro-hydrological processes in cold arid areas. • Coupled model performance was evaluated with two-year field experiments. • The impacts of various irrigation and groundwater management strategies were assessed. • Appropriate irrigation and groundwater management strategies for farmland were suggested. Quantitatively assessing the impact of irrigation and groundwater management strategies is crucial for improving water productivity and soil salinity control in cold arid areas with shallow groundwater tables (CAASGT). However, existing studies often focus on specific periods, either the crop growth period or the freeze–thaw period, due to the lack of appropriate models that can accurately represent both soil freeze–thaw and crop growth processes. This limited focus results in incomplete year-round insights, given the significant differences and interactions in hydrological processes during these two periods. In this study, we coupled the agro-hydrological model (i.e., the AHC model) and the cold region hydrological model (i.e., the SHAW model) to simulate the year-round agro-hydrological processes and crop growth in CAASGT. The coupled model was rigorously calibrated and validated using two years of field experiment data collected from a maize field in the upper Yellow River basin (YRB). Subsequently, the validated model was employed to analyze the effect of different irrigation and groundwater management scenarios on crop yield, soil salinity, and water productivity in two hydrological years (dry and wet years). Results indicated that increasing groundwater depth was beneficial for soil salinity control in all scenarios but reduced maize yield at low irrigation levels. Autumn irrigation proves essential for soil salinity control, with reducing the irrigation amount in autumn irrigation period having a more significant impact on maize yield than that in growing season. Additionally, soil thawing time significantly affects soil salt accumulation and crop yield, with earlier thawing time leading to more severe salt accumulation at the end of the freeze–thaw period, restraining maize seedling growth and decreasing maize yield. These results are expected to offer year-round insights into improving water productivity and soil salinity control in CAASGT. [ABSTRACT FROM AUTHOR]

Highlights • A new model system (named AHC) was proposed for agro-ecosystem simulation. • AHC is suitable for both salinity and nitrogen issues and other various conditions. • AHC provides mature functions to efficiently handle the parameter calibration. • AHC is well tested using a salinity case and a nitrogen case as exemplifications. Abstract This article introduces the AHC model as a new tool for modeling and assessing the agroecosystem processes. The AHC, as a one-dimensional numerical physical model, simulates the soil water and salt/nitrogen dynamics, heat transport, and crop growth and yield in various soil-crop environments. The key features of the AHC include that it provides the optional function for simulating the fate of salt or nitrogen; it has an efficient global method for sensitivity analysis and parameter estimation; and it is useful in a wide range of field conditions, especially for those in northern China. A menu-driven program is developed as a user-friendly interface for efficient data manipulation. This paper primarily describes the main structures and algorithms of the AHC and presents its field applicability. Model testing and application was conducted with two cases: (1) a salinity case with maize growing in salt-affected fields under arid and shallow groundwater environments (Hetao, upper Yellow River basin, northwest China); and (2) a nitrogen case with a wheat-maize rotation system in the semihumid monsoon region (Tai'an, North China Plain). Good agreement was obtained between the simulated and observed data, including the soil water contents, salt/nitrogen contents, and crop growth indicators. The soil water and salt/nitrogen dynamics, crop growth processes, and their complex interactive effects were also well interpreted using the AHC. Rational simulation proves the good applicability of the AHC for practical field use. [ABSTRACT FROM AUTHOR]

Due to water scarcity, water saving practices (WSPs) are being implemented in the irrigation districts of the upper Yellow River basin, causing a series of consequences, e.g. the reduction of field irrigation amount and groundwater depth (GWD) increase. The impacts of irrigation water reduction and GWD increase in canal systems with heterogeneous land covers is complex and remains unclear, thus the need to be elucidated to efficiently promote WSPs. Based on the two-year field observations in 2012 and 2013 and former studies, the HYDRUS-dualKc model, which has been well calibrated and validated in a typical canal system in Hetao, was used to predict the changes in transpiration, evaporation and salt accumulation considering scenarios with various GWDs and irrigation strategies. Results showed that under present irrigation scheduling, plant transpiration of maize, watermelon, tamarisk and sunflower had an initial slight increase, then reached a peak value, and finally decreased in the two years with GWD increase, while soil evaporation and salt accumulation both declined continuously. Based on integration results from the three crops and the natural vegetation simulation scenarios, an optimum GWD of between 1.7–2.3 m for the crop fields and 1.4–2.0 m for the natural land was recommended. With optimum GWD, 15%–30% of water diversion from the Yellow River during the growing season can be saved each year. When considering the irrigation strategies, salt accumulation increased and crop transpiration declined with irrigation reduction, yet the impact on soil evaporation was limited. It also showed that only sunflower had the potential to reduce irrigation amount (about 20%). Future water saving should pay more attention to the water delivery process and the optimization of irrigation during the non-growing season. An additional irrigation to watermelon during its development stage and a pre-season irrigation to tamarisk can largely improve their growth, and the recommended irrigation depths were 100 mm and 250 mm, respectively. These results can be reference criterion for the further implementation of WSPs. [ABSTRACT FROM AUTHOR]

Soil salinization, severe NO 3 --N leaching and low water-fertilizer use efficiency are constraints to sustainable maize production in the upper Yellow River basin (YRB) of Northwest China. Agro-hydrological models have been proven to be a promising decision tool for water and fertilizer management of farmland. In this paper, the AHC (Agro-Hydrological & Chemical and Crop Systems Simulator) model was calibrated and validated by measured soil water, salt, nitrogen (N) and crop growth data and used for scenario analysis to search for the appropriate irrigation and N fertilization strategies for drip-irrigated saline maize farmland. The scenarios were designed with different soil matric potential thresholds (SMPT) for irrigation, different saline degrees (i.e., slightly and moderately saline soils), and with or without additional salt leaching (ASL) in different hydrological years (wet, normal and dry). The results indicated that increasing SMPT and ASL increased the frequency and total amount of irrigation, thus favoring soil salt leaching. NO 3 --N was leached out of the root zone soil as SMPT exceeded –20 kPa, especially for the cases with ASL. For the case of –20 kPa SMPT, compared with the irrigation scenario without ASL, the irrigation scenario with ASL could significantly increase maize yield and water use efficiency (WUE) in moderately saline farmland. However, for the case of –15 kPa SMPT, the irrigation scenario with ASL caused a significant decrease in WUE for both saline farmlands. Maize yield increased as the N application rate increased from 150 kg ha–1 to 250 kg ha–1 and remained stable as the N application rate continuously increased, resulting in high NO 3 --N leaching and low partial factor productivity of N fertilizer (PFP n). Comprehensively considering crop yield, WUE, PFP n , soil desalting and environmental impacts, in wet and normal years, the appropriate irrigation and N fertilization strategy is irrigation under –20 kPa SMPT and a 250 kg ha–1 N application rate without ASL for slightly saline maize farmland and with ASL for moderately saline maize farmland, respectively. In dry years, the appropriate irrigation and N fertilization strategy is irrigation without ASL under –15 kPa SMPT and a 250 kg ha–1 N application rate for both slightly and moderately saline maize farmlands in the study and relevant areas. • Increasing additional salt leaching favored soil desalting and maize production. • Excessive high soil matric potential thresholds caused severe NO3--N leaching. • Irrigation practices were optimized for two salinized soils in three hydrological years. • Proper nitrogen input rate was determined for food-resource-environmental trade-offs. [ABSTRACT FROM AUTHOR]

Numerical simulation is an efficient approach for investigating the salt and water movement through soil profile and predicting of crop response to soil water deficit and salinity. In this study a coupled model that describes the soil water and solute transport by means of HYDRUS-1D model and crop growth process by means of growth module of EPIC was used. The model was calibrated and validated against field data, collected during two growing seasons in field plots of winter wheat irrigated with four levels of irrigation amount and water salinity of 5 ds m −1 at the Fengqiu State Key Agro-Ecological Experimental Station, in North China Plain. The model was also used to evaluate the salinity stress on evapotranspiration (ET), grain yield and water use efficiency (WUE) and long-term use of saline water on grain yield and salt accumulation. Visual inspection and the obtained statistical parameters values showed that good agreement between measured and simulated data of soil water content, salt concentration, ET and grain yield. Evapotranspiration values of winter wheat were reduced under salinity stress conditions, mainly by reducing crop transpiration. The grain yields were reduced due to salinity stress, but the change trend of WUE was associated with precipitation amount. Increasing per saline water irrigation amount is an effective way to reduce the WUE decline rate under the low rainfall growing season as like that in simulation year. The average of ten years grain yield confirmed that a yield potential exceeding 86% could be maintained by saline water with 5 ds m −1 when per irrigation volume more than 0.8 E, E denotes evaporation from an uncovered, 20 cm diameter pan positioned 0–5 cm above the crop canopy. There has a slight salt build-up after ten years simulation, and the quantity of salt accumulation decreased with the increase of irrigation volume. Thus, more attention should be paid to the sustainability of irrigated agriculture with low irrigation volume when using saline water irrigation. On the whole, field observations combined with the coupled model could be used to evaluate different agricultural managements on grain yield and soil salinity. [ABSTRACT FROM AUTHOR]

• An enhanced soil-water-nitrogen-crop coupling model (named ORYZA-N) was proposed. • Soil temperature, solute transport, and soil C&N modules were newly developed. • ORYZA-N was tested and applied in N simulation for the JRC with two years of data. • Nitrogen (N) parameter values were specific and recommended for cold region rice. • N dynamics, balance, and use efficiency were quantitatively analyzed with ORYZA-N. This article introduces ORYZA-N as an enhanced soil-water-nitrogen-plant coupling model to simulate agro-hydrological processes and crop growth in rice paddy fields. The model is developed based on the ORYZA2000 (a widely-used rice model with an open-source code) with significant improvements in modeling the nitrogen (N) fate and related processes. Three new modules were designed in ORYZA-N for simulating N transport and transformation processes, including a soil temperature module, a solute module for ammonium nitrogen (NH 4 -N) and nitrate nitrogen (NO 3 -N) transport, and a soil nitrogen module for organic carbon and nitrogen turnover. The mechanics of root water uptake and soil water drainage also were improved to better describe the soil water movement and its effects on root N uptake. The ORYZA-N model was then tested and applied in simulating the fate of water and nitrogen and crop growth for Japonica rice in cold regions (JRC) in the Northeast China Plain (NECP), for a two-year field experiment (during 2018 and 2019). Model evaluation shows a good performance was achieved with the ORYZA-N model. The simulated values for pond water depths, N uptake and partitions, and various organ productions were in particularly good agreement with the observed values (R2 > 0.68, NSE > 0.50); meanwhile, the simulated fluctuation trends for NH 4 -N and NO 3 -N concentrations were reasonable as well. The calibrated/obtained nitrogen-related parameters for JRC were obviously different from those for rice varieties in warmer regions, which can efficiently complement the parameter dataset for rice modeling in cold regions. Finally, the N dynamics, balance, and utilization efficiency were interpreted and assessed for the two experimental years, and possible improvement measures for N use for JRC were proposed. The total aboveground N content was about 160 kg N ha−1 at harvest, while the N content in the stems, green leaves, dead leaves, and panicles accounted for about 15, 5, 25, and 55% of the total aboveground N content, respectively. Overall, rational simulation proved the enhanced functionality and practicality of ORYZA-N for modeling the N fate and utilization. [ABSTRACT FROM AUTHOR]

• An improved SPAC model (named SHAW-SC) is proposed based on modifying SHAW. • New crop module and modifications of ET and solute transport/leaching are included. • Coupled processes of soil heat-water-salt transport and crop growth are well described. • Continuous, dynamic simulation of SPAC was realized on an entire agr-year scale. • Water-salt dynamics and water use are quantitatively analyzed in ASF regions. The soil–plant-atmosphere continuum (SPAC) that is a dynamic, interactive and coupled system is particularly complicated in arid seasonally frozen regions (ASF regions) with the effects of soil freeze–thaw process and salinity. A quantitative understanding of heat-water-salt transport and crop growth in the SPAC over an entire agricultural year (agr-year) is an importance of promoting best practices for water use and crop production. In this paper, an improved coupled SPAC model (SHAW-SC) is presented and applied for continuously simulating the SPAC system of ASF regions over an agr-year. The model is developed based on modifying the SHAW model (version 3.0) and incorporating the EPIC crop growth module. The main new features of the SHAW-SC include extending the model capability for canopy growth and yield formation, improving the description of soil solute transport in the shallow groundwater systems, and providing functions to describe the effects of surface mulching on soil evaporation and salinity stress on crop growth and transpiration. Model testing and application were conducted with two agr-year data at the sunflower experimental field in irrigated areas of the upper Yellow River basin, northwest China (with an arid and cold climate). Simulations of soil water content, temperature, and crop growth indicators fitted well with the observations both in calibration and validation (with NSE > 0.64 and sufficiently small RMSE); meanwhile, simulation of salinity concentration was also satisfactory (NSE: 0.32 and 0.83; RMSE: 1.09 and 2.44 g L−1), despite the complexity of salt transport and the measurement difficulty. In addition, the comparison with previous experimental results also showed the reasonability of modeling results. Then, a comprehensive and quantitative analysis of the SPAC dynamics was conducted over an agr-year, with identifying five characteristic periods (i.e. pre-freezing, soil-freezing, soil-thawing, pre-planting and crop growth periods). Results provided a fuller understanding of the characteristics of water-salt dynamics and balance components, and the related issues of crop stress, water use and salinity control on an entire agr-year scale. Model testing and application proved that the proposed SHAW-SC was an efficient tool to simulate coupled processes of heat-water-salt transport and crop growth for ASF regions, and as well an enhancement of current SPAC models for practical field applications. [ABSTRACT FROM AUTHOR]

Land degradation is one of the world's most pressing environmental problems and a constraint to agricultural production. Application of diverse organic amendments provides a management strategy to compensate for soil organic carbon depletion and reduce land degradation. The objective of this study was to investigate the effects of different organic amendments on soil properties, crop growth and water-fertilizer productivity under arid conditions. Soil in a maize field located in the upper reaches of Yellow River was amended with sheep manure compost and maize stover respectively. Five different application rates (2, 4, 6, 8 and 10 t ha-1) were carried out for the compost, and maize stover (6 t ha-1) combined with two different decomposing agents were implemented. Main component of the decomposing agent was Bacillus subtilis and Trichoderma harzianum , respectively. Soil aggregation and physical-chemical properties were generally improved with the incorporation of compost and maize stover. The addition of compost and maize stover reduced the bulk density and increased the field capacity, soil organic matter, aggregate stability and the saturated hydraulic conductivity. The emergence rate and maize growth properties improved in the organic materials amended plots. However, soil properties and crop growth non-monotonically varied with application rate of compost. The addition of different decomposing agents in maize stover amended plots did not show significant impact on most soil properties, but improved soil nutrient status, crop growth and yield with different levels compared with maize stover alone. Comprehensive analysis of yield, crop water productivity and partial factor productivity for nitrogen, incorporation of compost at a rate of 5–6 t ha-1 or 6 t ha-1 maize stover combined with Bacillus subtilis was recommended as a proper strategy in loamy soil under arid conditions. • The application of compost and maize-stover improved soil aggregation and physical-chemical properties. • Soil aggregation, saturated hydraulic conductivity and crop productivity non-monotonically vary with the application rate of compost. • Organic amendment improved water-fertilizer productivity through changes in soil aggregation. • Compost showed better performance on soil properties and crop productivity than the same amount of maize stover under arid conditions. [ABSTRACT FROM AUTHOR]

Remotely sensed evapotranspiration (ET) with high spatial and temporal resolution is frequently required to understand the regional hydrological processes, particularly in agricultural areas with complex planting structures. Most of the existing spatio-temporal fusion models lacked the fusion of ET because they ignored the physiological characteristics of the vegetation moisture condition. Therefore, we propose a classification-based spatiotemporal adaptive fusion model (CSAFM) for the evaluation of remotely sensed ET in an irrigated agricultural area with a complex planting structure. This model combines the unmixing-based and weight-based fusion approaches to produce ET maps with high spatiotemporal resolution. It uses the mainstream weight-based fusion algorism—the spatial and temporal adaptive reflectance fusion model (STARFM)—in the fusion step. However, in contrast to the existing reflectance-based fusion algorithms, the CSAFM considers the effects of soil moisture and crop category on evapotranspiration rates. It replaces the unmixing window with an irregular hydrological response unit (HRU) containing homogeneous meteorological and irrigation conditions, and then unmixing the mixed pixels using a planting structure map. Moreover, an ET correction method was proposed in CSAFM to restore the spatial heterogeneity. The performance of CSAFM was compared to that of two mainstream fusion models using Landsat-ET and MODIS-ET based on the surface energy balance algorithm for land (SEBAL): the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) and the flexible spatiotemporal data fusion method (FSDAF). The models were validated with ground-based ET monitored by eddy covariance observed ET and Landsat inverted ET. It was found that the CSAFM model (mean MAE: 0.40 mm/day) beat the ESTARFM model (mean MAE: 0.49 mm/day) and the FSDAF (mean MAE: 0.53 mm/day) in accurately fusion ET and reproduce the details of complex surface landscapes. Additionally, CSAFM (RMSE: 0.66–1.10 mm/day) is less sensitive to the update frequency of input data in the crop growing season than ESTARFM (RMSE: 0.79–1.36 mm/day) and FSDAF (RMSE: 0.79–1.17 mm/day), indicating its suitability in areas with limited input dataset. Overall, the proposed CSAFM model can greatly improve the ET fusion accuracy in irrigated agricultural areas. • A new spatiotemporal fusion model is proposed for remote sensing ET in irrigated agriculture. • The model takes into account the differences and similarities of different crops at the growth stage. • The model alleviates the boundary effect and soil spatial heterogeneity in the decomposition process. • The new model has better fusion accuracy and less sensitivity to the integrity of the basic remote sensing data. [ABSTRACT FROM AUTHOR]

• Stomatal conductance (g s) of sunflower leaves decreased with increasing soil salinity. • The sensitivity of leaf g s to soil salinity varied with the growth stages of sunflower. • An empirical model for the influence of salinity on g s was proposed. • The eddy covariance data was used to evaluate the model performance of canopy conductance (g c). Canopy conductance (g c) is the key parameter to quantify eco-hydrology processes. Salinity stress is one of the most important abiotic stresses to growth of crops in arid and semi-arid areas. Understanding the influence of salinity on stomatal movement and accurately describing g c under salt stress are of great significance to quantify agro-hydrology processes affected by salt. Therefore, we measured stomata conductance (g s) of sunflower leaves at different growth stages and soil salinity conditions in two consecutive years. At the same time, the evapotranspiration above canopy and the dynamic changes of soil moisture and salinity in root zone were continuously monitored. It was found that under the same meteorological conditions, leaf g s decreased with the increase of soil salt content. Relatively, g s was more sensitive to salt at seedling and maturity stages than at budding and flowering stages. Furthermore, an empirical formula describing the effect of soil salinity on g s was added to the Jarvis multi-factor multiplication g s model, which used leaf area index (LAI) as a parameter to express the salt tolerance of different growth stages. Effective LAI was used to upgrade the model from leaf scale to canopy scale. g c calculated by Penman-Monteith equation using the farmland canopy evapotranspiration measured by the eddy covariance system was used to evaluate the applicability of model. The results showed that the model could simulate g c well on both the half-hour and the daily average scale. Nash-Sutcliffe efficiency coefficient of the daily average scale model was about 0.65, and determination coefficient of the simulation results of different scales in two years were all above 0.66. Our findings could improve the understanding of influence of salinity on stomatal movement in such areas and provided a basis for simulating canopy evapotranspiration and photosynthesis under salt stress. [ABSTRACT FROM AUTHOR]

[Display omitted] • An integrated simulation-optimization framework is proposed for irrigation planning. • It makes dynamic decision of irrigation planning possible. • It achieves the maximum credibility level of the fuzzy objective function. • It controls salt accumulation at the end of crop growth period through constraints. An integrated simulation-optimization framework is developed under uncertainty to enhance irrigation water productivity and control salinity in an arid area. A full fuzzy dependent linear fractional programming approach is formulated by incorporating fuzzy dependent-chance programming, fuzzy credibility-constrained programming and linear fractional programming within a general framework of irrigation planning. Then, simulation module concerning water, salt balance process and crop water-salt production functions enables to quantify daily physical process of water and salt movement among the soil water, crop root zone and groundwater aquifers. Thus, this study can readily handle fuzzy uncertainty existing concurrently in the ratio objective (i.e., economic water productivity) through the concept of fuzzy dependent chance and double-sided constraints. It can also simultaneously provide the maximum credibility level that the objective is achievable and credibility levels implying that optimal solutions are believable. Besides, daily variations of simulated physical parameters are illustrated corresponding to management strategies. To demonstrate its applicability, it's then applied to a case study of irrigation planning in the Jiefangzha Irrigation Subarea in Hetao Irrigation District, northwest China. Results can clearly analyze tradeoffs among satisfaction degree of fuzzy objective, fuzzy constraints and optimal solutions. Moreover, by examining different management targets and salt accumulation constraints, this study demonstrates the merits and importance of the work to promote irrigation water productivity and control salinity. Dynamic decision making of irrigation planning is possibly made by coupling daily simulation and optimization modules. Therefore, these findings can support decision makers to identify appropriate solutions for irrigation planning. [ABSTRACT FROM AUTHOR]

• SWAT model was improved to consider additional paths and forms of soil nutrient losses. • Model simulation of water, nitrogen, phosphorus, sediments, leaf area index, and crop yield were assessed simultaneously. • The critical nitrogen and phosphorus loss paths, periods and forms were identified. • New insights were provided for reducing nutrient loads to surface and groundwater. Identifying the key processes and primary sources of water and nutrient losses is essential for water quantity and quality management in watersheds. This is especially true in the U.S. Corn Belt, which has been recognized as the primary region contributing nutrient loads to the Great Lakes and the Gulf of Mexico. A SWAT (Soil and Water Assessment Tool) model simulation was set up in an agricultural watershed with about 50% tile drainage area in the U.S. Corn Belt to study the water and nutrient balance components for the whole watershed and the corn-soybean rotation system. The SWAT model was improved to consider additional nitrogen and phosphorus loss paths from the soil. The model was comprehensively calibrated and validated for simulating monthly stream flow, total suspended solids (TSS), nutrient loads (including total Kjeldahl nitrogen (TKN), nitrate and nitrite nitrogen (NO x -N), total phosphorus (TP) and orthophosphate phosphorus (orthoP)), actual evapotranspiration (ET a), leaf area index (LAI) and annual crop yields in the watershed from 2011 to 2019. Results showed the model performance was very good for simulating the stream flow, TSS and ET a , and acceptable for nutrient loads, LAI and crop yields. ET a , surface runoff, lateral soil flow, tile drainage and percolation respectively accounted for 65%, 15%, 2%, 8% and 9% of the precipitation. Fertilizer was the main source of nitrogen and phosphorus input to the watershed, and harvested crops were the main paths removing nutrients. Surface runoff, tile drainage and percolation each contributed about 30% of total nitrogen losses to water, with surface runoff being dominated by organic nitrogen while tile drainage and percolation were dominated by nitrate nitrogen. Phosphorus losses were mainly through surface runoff, which resulted in 66% of the total losses and was dominated by organic phosphorus and soluble phosphorus. Representing about 49% of the watershed area, the corn-soybean rotation system contributed 83% and 88% of the total nitrogen and phosphorus inputs, respectively, to the watershed, as well as 64% and 46% of the nitrogen and phosphorus losses to the water system, respectively. The non-growing season (October to the next April) was identified as the critical period resulting in water and nutrient losses due to low evapotranspiration and plant uptake. Targeted management strategies for reducing nutrient loads in key hydrological paths were suggested. [Display omitted] [ABSTRACT FROM AUTHOR]