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[Display omitted] • SIF is an effective proxy of vegetation productivity strongly related to VPD and SM. • Accelerated vegetation greening concurred with a decrease in VPD and an increase in SM. • The respective effects of SM and VPD were disentangled by equal-width data binning. • VPD played a dominant role in vegetation productivity in China during 2001–2016. • The dominant factor of vegetation productivity has shifted from VPD to SM since 2007. Although evidence of ecosystem productivity to vapor pressure deficit (VPD) and soil moisture (SM) is abundant, their respective effects remain unclear due to tightly land-atmosphere interactions. In China, the spatial heterogeneity in eco-hydrosphere has further impeded our understanding of ecosystem productivity in response to climate change. This study aimed to assess ecosystem productivity in China during 2001 to 2016 using solar-induced chlorophyll fluorescence (SIF). SIF corresponded well with gross primary productivity (GPP) and was strongly related to VPD and SM. The land-atmosphere interaction mechanism was more notable near the agro-pastoral ecotone, which was reflected in the stronger SM-VPD coupling effect on vegetation and more significant effect of VPD suppressing SIF and SM promoting SIF. We decoupled SM and VPD by equal-width binning of percentiles at a monthly scale. SIF tended to increase and decrease with increasing VPD in SM bins, accounting for 47.59% and 52.41% of the total vegetated area, respectively, whereas photosynthesis tended to increase and decrease with increasing SM in VPD bins, accounting for 62.18% and 37.82% of the total vegetated area, respectively. During 2001 to 2016, VPD and SM had a dominant effect on SIF in 52.31% and 47.69% of China, respectively, which occurred along a latitudinal gradient. However, since 2007, which was identified as the point of accelerated vegetation greening in China, the dominant factor of vegetation productivity has shifted from VPD to SM in terms of respective contributions and dominated areas. Our results emphasize an increasingly important role of SM in China, though the additive effects of VPD cannot be negligible. We conclude that the clarification of the shifting roles of SM and VPD in terrestrial ecosystem allows for more accurate prediction of vegetation productivity at a regional scale and provides greater insights into interactions between vegetation and climate. [ABSTRACT FROM AUTHOR]

Continuous applications of lignite bioorganic fertilizer (LBF) to the field have achieved substantial improvements in soil physicochemical properties and crop yields in multiple regions throughout China. However, the effects of LBF on crop growth, and water and fertilizer productivity in saline-sodic farmlands were scarcely understood. Thus, in this study, a two-year field experiment with six treatments including a control treatment without any organic fertilizer (CK), a treatment amended with 21 t ha−1sheep manure (SM), and four treatments amended with 1.5 (LBF1), 3 (LBF2), 4.5 (LBF3), and 7.5 t ha−1 (LBF4) LBF, was conducted in 2019 and 2020 in the Hetao Irrigation District (HID), an area known for its saline-sodic conditions located at the upper Yellow River basin, China. The results showed that the LBF2 and LBF3 treatments improved plant height, leaf area index, and dry biomass by 8–76.7 cm, 0.3–2.4, and 309–402 g plant−1, respectively, in comparison with the CK treatment. The root length, root surface area, and root volume in the LBF2 and LBF3 treatment was 18.3–99.7 m, 464.6–2022.6 cm2, and 7.6–46.4 cm3 larger than that in the CK treatment, respectively. Average yield, water productivity, partial nitrogen productivity, and economical gain in the LBF treatments were up to 2.2 t ha−1, 0.4 kg m−3, 23.6 kg kg−1, and 6100 Chinese Yuan ha−1, respectively, substantially higher than those of the CK treatment. In addition, compared with SM treatment, the LBF2 and LBF3 treatments also significantly improved sunflower growth and water and nitrogen productivity. The results of structural equation model analysis and linear regression analysis showed that LBF2 and LBF3 treatments improved sunflower root growth mainly through improving absorption of soil nitrogen. Furthermore, the root indices had a significant positive relation with the sunflower yield, water productivity, and partial nitrogen productivity. The partial nitrogen productivity, water productivity, yield, and economic profits showed a quadratic relationship with the application rate of LBF. A comprehensive assessment of the partial nitrogen productivity, water productivity, yield, and cost versus economic suggested that an application rate of 3.0–4.0 t ha−1 of the lignite bioorganic fertilizer is optimal for achieving a sustainable improvement of crop yield, water productivity, and partial nitrogen productivity in saline-sodic farmlands. • Sunflower growth in saline-sodic soil was improved by lignite bioorganic fertilizer. • Application of lignite bioorganic fertilizer increased sunflower nitrogen absorption. • Water and nitrogen productivity of sunflower increased by lignite bioorganic fertilizer. • 3.0–4.0 t ha−1 is the optimal application rate of lignite bioorganic fertilizer in the study area. [ABSTRACT FROM AUTHOR]

Summary 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. [ABSTRACT FROM AUTHOR]

Summary Water saving in irrigation is a key issue in the upper Yellow River basin. Excessive irrigation leads to water waste, water table rising and increased salinity. Land fragmentation associated with a large dispersion of crops adds to the agro-hydrological complexity of the irrigation system. The model HYDRUS-1D, coupled with the FAO-56 dual crop coefficient approach (dualKc), was applied to simulate the water and salt movement processes. Field experiments were conducted for maize, sunflower and watermelon crops in the command area of a typical irrigation canal system in Hetao Irrigation District during 2012 and 2013. The model was calibrated and validated in three crop fields using two-year experimental data. Simulations of soil moisture, salinity concentration and crop yield fitted well with the observations. The irrigation water use was then evaluated and results showed that large amounts of irrigation water percolated due to over-irrigation but their reuse through capillary rise was also quite large. That reuse was facilitated by the dispersion of crops throughout largely fragmented field, thus with fields reusing water percolated from nearby areas due to the rapid lateral migration of groundwater. Beneficial water use could be improved when taking this aspect into account, which was not considered in previous researches. The non-beneficial evaporation and salt accumulation into the root zone were found to significantly increase during non-growth periods due to the shallow water tables. It could be concluded that when applying water saving measures, close attention should be paid to cropping pattern distribution and groundwater control in association with irrigation scheduling and technique improvement. [ABSTRACT FROM AUTHOR]

Stemflow is important for analyzing soil water dynamics and plant growth in regions with limited rainfall. The objective of this study was to determine the amount of stemflow in relation to plant and rainfall properties. In this study, stemflow was measured using a high water adsorption sheet method during the period of maize plant height growth approximately from 100 cm to 230 cm when the leaf area index increases from 1.0 to 4.5. There were 28 rainfall events with rainfall amounts for each event ranging from 0.4 to 12.6 mm and rainfall intensities ranging from 0.4 to 35 mm/h. The results show that stemflow increased with increasing total rainfall and leaf area index but decreased with increasing rainfall intensity. Throughout a maize season, stemflow amounts ranged from 10 to 70 mm when the total rainfall amounts ranged from 30 to 135 mm, with a mean stemflow rate of 0.42. These results may help farmers in irrigation scheduling of maize under surface-mulching conditions in arid region. [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]

Soil moisture and salinity are two key factors for crop production in arid irrigation districts. It is critical to modify soil water-salt dynamics and crop growth on a regional scale for the sustainable agriculture. In this paper, a distributed agro-hydrological model that well considers the spatial variability of soil and hydrological factors was developed to simulate soil water movement, solute transport and crop growth process on the regional scale. Jiefangzha Irrigation System (JIS) of the Hetao Irrigation District was selected as the study area. The JIS was divided into 201 homogeneous simulation units based on the combinations of weather-soil-crop-irrigation. In this way, the one-dimensional agro-hydrological model--HYDRUS-EPIC (HYDRUS-1D coupled with EPIC crop growth module), was used and expanded to the regional scale. Field experiments were conducted in 2012 and 2013. The dataset of soil moisture, soil solute concentration, leaf area index (LAI) and crop yield were collected at 40 monitoring points, and used for model calibration and validation. Simulated soil moisture and salinity concentration in the root zone showed good agreement with the measured values. During the calibration process, root mean square error (RMSE), mean relative error (MRE) and coefficient of determination (R²) for soil moisture were 0.03 cm³/cm³, 0.3% and 0.67, respectively. For salinity concentration, RMSE, MRE and R² were 2.72 g/L, -13.5% and 0.53. LAI and crop yields were fitted well with the observations. MRE values for the estimated and measured LAI and crop yields were 1.0% and 1.1%, and R² were both larger than 0.90 for these two items. During the validation process, RMSE, MRE, and R² were 0.04 cm³/cm³, 2.6%, 0.57 for soil moisture, and 2.62 g/L, -4.5%, 0.51 for salinity concentration, respectively. And MRE and R² were 9.1%, 0.88 for LAI, and -1.9%, 0.92 for crop yields. These results showed that the distributed agro-hydrological model was able to simulate the soil water flow, salt transport, and crop growth process in JIS with accuracy. The calibrated and validated model was then applied to predict spatial distribution of soil moisture, salinity concentration, crop evaporation and crop yields of the study area in present irrigation water management practices. Effective saturation and salinity concentration in the root zone were chosen to represent soil water and salinity stress on crop growth. Results showed that effective saturation ranged from 0.44 to 0.90 with an average of 0.7 for the JIS. In most areas, soil water could meet crop water consumption needs. In the areas where groundwater depth (GWD) was less than 1.3 m, root water uptake was limited due to waterlogging. The average salinity concentration in the root zone varied from 3.1 g/L in the northwest to 13.5 g/L in the northeast with an average of 6.4 g/L for the whole district. High soil salinity concentration limited crop production seriously. Corresponding to the spatial distribution of salinity concentration in the root zone, crop relative yield (ratio of actual yield and average yield of JIS) ranged from 0.33 to 1.33. The results suggested that for the northeastern part, where GWDs were larger than 2.0 m, more irrigation was needed for leaching salt. It was also better to plant more salt tolerant crops in these areas. In northwestern and southwestern parts, shallow groundwater levels intensified waterlogging or salinity accumulation problems. The study indicated that it is better to keep the groundwater depth not shallower than 1.3 m for maintaining the crop yields. [ABSTRACT FROM AUTHOR]

Irrigation is essential for agriculture in the middle Heihe River basin, Northwest China, due to water scarcity and dryness of climate. The diverted river water for agriculture is being gradually reduced which requires an increased water use performance to meet crop water requirements and to maintain crop yields. It is therefore crucial to better know about the present agro-hydrological processes, irrigation performance and water productivity, and to further investigate the potential water saving on a regional scale. In this study, a distributed agro-hydrological model was developed by close coupling of an agro-hydrological model (SWAP-EPIC) and ArcInfo geographic information system. Combined effects of weather, crop, soil and irrigation factors were considered. The Yingke Irrigation District (YID), in the middle Heihe River basin, was chosen as case study, where experiments were conducted at both field and regional scales in 2012–2013. Parameters relative to soils and crops were first calibrated with field observed data and the model was later used in a distributed manner to simulate the agro-hydrological process of YID. Results showed that water productivity was spatially varied and quite small due to excessive irrigation water use. Crop evapotranspiration averaged 589 mm and deep percolation was 125 mm on average, which accounted for 21% of total irrigation. Analysis of the target scenario simulation indicated that the improvement of water conveyance and irrigation scheduling could lead to a 30% reduction of deep percolation, and save 15% of irrigation water without negative effects on crop yields. [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]

Irrigation is a prerequisite for the sustainable development of agricultural production. With the existing of water resources shortage and climate change, it is of great importance to explore the variation of crop irrigation water requirement (IWR) in the Yellow River Basin (YRB). Based on 1974–2017 meteorological dataset from 96 stations, we analyzed the spatio-temporal variation characteristics of meteorological factors and crop IWR during the growing seasons of four main crops including spring wheat, winter wheat, spring maize and summer maize, respectively. Furthermore, we explored the dominant meteorological factors of the crop IWR variation. The results indicated that daily mean temperature (T) had a significant upward trend, while the effective precipitation (P eff) did not change significantly during the growing season of each crop in the past 44 years. Crop IWR had increasing trend with 9.9 mm/decade, 4.3 mm/decade, 6.4 mm/decade for spring wheat, winter wheat, spring maize respectively, while a slight decreasing trend with − 1.7 mm/decade for summer maize. It is noted that extremely significant increase in crop IWR were mostly located in Ningxia, southern Gansu and eastern Qinghai. Moreover, P eff , net radiation (R n) and relative humidity (RH) were identified as the dominant meteorological factors influencing variations of IWR for all crops. In the context of significant increase in T and uncertain future precipitation patterns, IWR for spring wheat, winter wheat and spring maize in the YRB has shown an upward trend which is not favorable to the sustainable development of water resources. It is urgent to take effective water-saving measures to hedge the adverse impact of climate change on agriculture. These findings can provide scientific basis for rational allocation of agricultural water resources in the YRB. • Irrigation water requirements of main crops in the Yellow River Basin were quantitatively evaluated. • The spatio-temporal variation of meteorological factors during the crop growing seasons was investigated. • The spatial distribution and changing trend of crop irrigation water requirements were characterized. • The dominant meteorological factors of crop irrigation water requirements variation were found out. • It is urgent to take effective water-saving measures to hedge the adverse impact of climate change on agriculture. [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]

In this study, seven widely used potential evapotranspiration (ETo) methods were evaluated by comparing with the FAO-56 Penman-Monteith method (PM method) to provide useful information for selecting appropriate ETo equations under data-limited condition in Beijing, China. Statistical methods and parameters, namely linear regression, root mean squared error (RMSE) and mean bias error (MBE), were used to evaluate the seven ETo methods. Results showed that ETo estimated using Kimberly-Penman method have fairly close agreement with the PM method (referring to standard ETo), considering the coefficient of determination (R²) of 0.96, RMSE of 0.42 mm/day, and a coefficient of efficiency (E) of 0.96. Locally calibrated Penman and Doorenbos-Pruitt methods also have better agreement with the PM method, correspondingly with R² of 0.99 and 0.95, RMSEs of 0.24 mm/day and 0.21 mm/day, and coefficients of efficiency of 1.02 and 0.99, respectively. The ETo is the most sensitive to vapor pressure deficit (VPD) and net radiation in the Beijing area. Hence, the VPD-based and VPD-radiation combined ETo methods were developed and calibrated. Results showed that the two developed methods performed well in ETo estimation. By fully considering the data-limit situation, the calibrated Turc method, VPD-based method and VPD-radiation-combined method may be attractive alternatives to the more complex Penman–Monteith method in Beijing. [ABSTRACT FROM AUTHOR]

• Agro-ecohydrological processes were simulated in an arid region with shallow groundwater. • An enhanced agro-hydrological model (SWAT-AG) were employed. • Regional characteristics of agro-ecohydrological processes were presented and analyzed. • Water use efficiency was low with considering water applied during non-growing period. • A large proportion of non-beneficial water use was found during growing period. High water consumption in large irrigation districts has resulted in large river water diversion and serious water use conflicts in the Yellow River basin (YRB). The excessive water applied is also a cause of the dual problems of soil salinity and water logging in the upper YRB, which further negatively impacts crop yields. This study is aimed at modeling and analyzing the agro-ecohydrological processes and water use performance in large irrigation districts of the YRB. The Hetao Irrigation District (Hetao), a super-large irrigation district located in the upper YRB, was selected as a typical research area. A watershed hydrological model (SWAT-AG) with enhanced capacity for simulating regional agro-ecohydrological processes was adopted in this study. We simulated the agro-ecohydrological processes in Hetao and analyzed the regional characteristics of depth to groundwater table, soil moisture and salt content, evapotranspiration and crop yield. Water accounting was further carried out to interpret water cycle processes and evaluate water use performance in Hetao. Results indicated that Hetao was characterized by shallow depth to groundwater table, high soil moisture and high evapotranspiration. For farmland, there was a decreasing trend for both soil moisture and evapotranspiration from the upper to lower regions in Hetao, but this decreasing trend was not found for natural land. Further, results showed soil salt content has strong spatial variations with land use type, crops and shallow groundwater environments. Correspondingly, crop yields presented a decreasing trend from the upper to lower regions of Hetao, with large spatial variabilities closely related to the spatial distribution of soil water and salt conditions across Hetao. It was worth noting that the regional water use efficiency was relatively low in Hetao, especially with large proportions of non-beneficial water consumption to total water consumption. Overall, this study provided a thorough understanding of agro-ecohydrological processes and their regional characteristics, and the current situation of irrigation water use issues in the whole Hetao district, and further provided valuable insights in improving water use and management in large irrigation districts of the upper YRB. [ABSTRACT FROM AUTHOR]

Highlights: [•] We analyzed change trends of the climate variables ET 0 and AI in an arid region of China over the past 50years. [•] We identified the sensitivity of ET 0 and AI to the main climate variables. [•] We quantified the contributions of climate variables to the changes in ET 0 and AI. [•] Contribution of wind speed decline to decrease of ET 0 is larger than other climate variables. [•] The increase of precipitation contributes more than the decrease of ET 0 to decrease of AI. [ABSTRACT FROM AUTHOR]

Abstract: A two-year field experiment was conducted with drip irrigation and plastic mulch to investigate an appropriate irrigation management strategy for chili pepper (Capsicum annuum L.). Five treatments, with the soil matric potential (SMP) threshold range of −10 to −50kPa at intervals of 10kPa, were applied in this study and are correspondingly referred to as T1 to T5. Leaf area index, plant height, soil water content, yield, and total soluble solids (TSS) were measured, and seasonal crop evapotranspiration (ET), water productivity (WP), and irrigation water productivity (IWP) were computed regularly. Results showed that the differences in leaf area index, plant height, above-ground biomass, and crop yield in treatments T1 though T4 were similar (P >0.05), but higher (P <0.05) than those of treatment T5. Irrigation amount and crop ET generally decreased with decreasing SMP threshold. Threshold values with SMPs from −10kPa to −30kPa caused a reduction of irrigation amount by 22–43% and crop ET reduction by 11–25%. Higher TSS, larger percentage of marketable fruits, and higher WP and IWP were found for treatments T3 and T4 in both growing seasons. The highest SMP threshold (−10kPa) and lowest SMP threshold (−50kPa) greatly reduced the WP and IWP. Therefore, a SMP threshold range of −30kPa to −40kPa at 20cm depth was recommended for irrigation management of chili pepper under mulched-drip irrigation conditions in the arid region of Northwest China. [Copyright &y& Elsevier]

Summary: This study combined the mobile–immobile model (MIM) with an asymptotic dispersivity function of travel distance to embrace the concept of scale-dependent dispersion during solute transport in finite heterogeneous porous media. The proposed MIM with an asymptotic scale-dependent dispersivity (MIMA) was analytically solved by the Laplace transform technique and the extended power series method. The developed semi-analytical solution of MIMA was compared with the Laplace transformed finite-difference numerical solution, and they agreed well with each other. The applicability of MIMA was tested with concentration data from a 1250-cm long and highly heterogeneous soil column. The transport process was also simulated by the MIM with a constant dispersivity (MIMC) for comparison. The simulation results of MIMC were found to depart significantly from the measured breakthrough curves (BTCs) in the column, whereas the fitting of MIMA with measured BTCs improved substantially as it considered that the increase of dispersivity with distance was limited. Our results indicated that MIMA was efficient to capture the evolution of scale-dependent dispersion behavior, and it was more useful for describing anomalous solute transport in heterogeneous porous media. We also generally evaluated the advantages and limitations of MIMA with respect to other up-scaling models for describing solute transport in heterogeneous media, and indicated several issues deserving further investigation for MIMA. [Copyright &y& Elsevier]

Abstract: Streamflow model including rainfall–runoff and river flow models play an important role in water resources management, especially in arid inland area. Traditional conceptual models have the disadvantage of requirement of spatial variation parameters about the physical characteristics of the catchments. To overcome this difficulty, in this study, several integrated Artificial Neural Networks (ANNs) were presented to estimate monthly river flow, and the models include the semi-distributed forms of ANNs that can explore spatial variation in hydrological process (such as rainfall distribution and evaporation distribution) and no requirement of physical characteristic parameters of the catchments. In an arid inland basin of Northwest, integrated ANNs were developed using hydrological and agricultural data, and its performance was compared with that of lumped ANN and local linear regression model (LLR). Results showed that the integrated ANNs perform well to estimate the monthly streamflow at outlet of mountain with Root Mean Square Error (RMSE) of 0.36×107 m3 and Relative Error (RE) of 9%. Similarly, the integrated ANNs can also accurately estimate the monthly river flow downstream of the basin with RMSE of 0.35–0.38×107 m3 and RE of 22–27%. When compared with integrated ANNs, the lumped ANN and LLR models have lower precision to simulate monthly streamflow in arid inland basin. Presented integrated ANN models retain the advantages of the semi-distributed models considering the heterogeneity and spatial variation of hydrological factors and the physical characteristics in the catchment, while taking advantage of the potential of ANNs as an effective tool in nonlinear mapping or functional relationship establishment. In contrast to traditional models either in the lumped ANN or in empirical regression forms, the new approach of integration of Artificial Neural Networks has shown great potential in streamflow modeling. [Copyright &y& Elsevier]

Abstract: The North China Plain (NCP) is one of the main productive regions for winter wheat (Triticum aestivum L.) and summer maize (Zea mays L.) in China. However, water-saving irrigation technologies (WSITs), such as sprinkler irrigation technology and improved surface irrigation technology, and water management practices, such as irrigation scheduling have been adopted to improve field-level water use efficiency especially in winter wheat growing season, due to the water scarcity and continuous increase of water in industry and domestic life in the NCP. As one of the WSITs, sprinkler irrigation has been increasingly used in the NCP during the past 20 years. In this paper, a three-year field experiment was conducted to investigate the responses of volumetric soil water content (SWC), winter wheat yield, evapotranspiration (ET), water use efficiency (WUE) and irrigation water use efficiency (IWUE) to sprinkler irrigation regimes based on the evaporation from an uncovered, 20-cm diameter pan located 0–5cm above the crop canopy in order to develop an appropriate sprinkler irrigation scheduling for winter wheat in the NCP. Results indicated that the temporal variations in SWC for irrigation treatments in the 0–60-cm soil layer were considerably larger than what occurred at deeper depths, whereas temporal variations in SWC for non-irrigation treatments were large throughout the 0–120-cm soil layer. Crop leaf area index, dry biomass, 1000-grains weight and yield were negatively affected by water stress for those treatments with irrigation depth less than 0.50E, where E is the net evaporation (which includes rainfall) from the 20-cm diameter pan. While irrigation with a depth over 1.0E also had negative effect on 1000-grains weight and yield. The seasonal ET of winter wheat was in a range of 206–499mm during the three years experiments. Relatively high yield, WUE and IWUE were found for the irrigation depth of 0.63E. Therefore, for winter wheat in the NCP the recommended amount of irrigation to apply for each event is the total 0.63E that occurred after the previous irrigation provided total E is in a range of 30–40mm. [Copyright &y& Elsevier]

Summary: This study compared five different models for evaluating solute transport in a 1250-cm long, saturated and highly heterogeneous soil column. The five models were: the convection–dispersion equation (CDE), the mobile–immobile model (MIM), the convective lognormal transfer function model (CLT), the spatial fractional advection–dispersion equation (FADE) and the continuous time random walk model (CTRW). Each of these models was used to fit the breakthrough curve (BTC) at each distance individually and was also used to fit the BTCs at different distances simultaneously. Dependence of estimated parameters on distance was investigated. The estimated parameters at 200cm were used to make predictions at subsequent distances. Highly anomalous transport behavior was observed in the column as the BTCs demonstrated significantly irregular shape and long tailing. This study indicated that CDE, CLT and FADE were unable to describe the anomalous BTCs adequately and their parameters changed with transport distance significantly. Compared to CDE, CLT and FADE, MIM better captured the evolution of anomalous BTCs. However, MIM did not explain the distinct BTC tailing satisfactorily. In contrast to MIM, CTRW better simulated the long tails of BTCs. The spreading parameter (β) of CTRW was close to one and remained approximately constant at different travel distances. To make the comparison of these five models more general beyond the specific transport condition in the soil column, a generic evaluation of the advantages and disadvantages of these five models was presented in terms of their theory framework and a priori knowledge of the model behaviors. [Copyright &y& Elsevier]

• We investigated the interaction of evaporation, salt crystallization and the internal structure of porous material. • The architecture of salt efflorescence differs in porous media with different grain morphologies. • Evaporation-induced salt subflorescence has clearly impact on the internal pore structure packed with angular and round grains. • Salt subflorescence decreases the intrinsic permeability and vapor diffusion coefficient of porous media. Evaporation from porous media in the presence of dissolved salts is an important topic in relation to several environmental issues. In this study, we investigated the interaction of evaporation, salt crystallization and the internal structure of the porous material. Porous columns with different internal structures were generated through random packing of angular quartz sand and round glass beads. Evaporation-induced salt efflorescence on the surface of porous media was recorded by a camera with micro lens. The internal pore structure before and after salt crystallization was visualized using the x-ray computed tomography and quantified by the extracted pore networks. Hydraulic properties in the absence/presence of salt crystals were simulated numerically using the pore-network approach and partially measured experimentally. The evaporative water loss ratio in the angular quartz sand was greater than that in the glass beads with the same sieving size. The evaporation of saline water in angular quartz sand and round glass beads can be separated into three stages similar to water evaporation. Salt efflorescence was generated a crust dome architecture on the surface of the angular sand, but was in tight patchy contact with the round glass beads. The presence of salt crust interrupted the exchange of vapor between the porous media and atmosphere, hindering evaporation. Salt subflorescence clogged some of the pores, and the pore size distribution shifted to smaller sizes part. The porosity decreased and the geometric tortuosity of the porous materials increased owing to salt subflorescence. The presence of subflorescence salt crystals decreased the intrinsic permeability and relative diffusion coefficient of different porous media. The relationship between the vapor diffusion coefficients and porosity is linear in the presence/absence of salt crystallization, considering the geometric tortuosity. The findings indicate that the feedback of salt precipitation on hydraulic properties and vapor diffusion must be considered to accurately quantify hydrological processes, particularly in arid and semi-arid areas where intensive evaporation is accompanied by soil salinization and water shortage. [ABSTRACT FROM AUTHOR]

• A simulation-based regional irrigation water optimization model (SRIOP) is developed. • The model tightly links an agro-hydrological model with a regional optimization. • A three-level optimization framework is formulated for model coupling and solution. • The impacts of climate condition changes and resulting uncertainty are considered. • Process-based optimal spatial allocation of irrigation water use can be obtained. It is attractive and advantageous to realize process-based optimization of irrigation water use on large scales. In this study, a simulation-based regional irrigation water optimization model (SRIOP) was developed for watershed-scale optimal spatial allocation based on dynamic responses of agro-hydrological process and its spatial differences. The SRIOP model tightly linked a field-scale agro-hydrological model (SWAP-EPIC) with an optimization algorithm (NSGA-II) in a regional multi-level optimization framework. It performed at three levels that sequentially dealt with optimal irrigation water allocation on field, irrigation district and irrigated watershed scales, with two objectives of maximizing yield/benefit and minimizing irrigation water. The model was tested with a case study in the major irrigation system (MIS) of middle reaches of the Heihe River basin, northwest China. The optimal spatial distribution of irrigation water showed a decreased variation coefficient (0.17) and increased irrigation benefit (9.8% higher) as compared with that of the present year, and better reflected the effects of multi-level collaboration and crop-soil field distribution. The impacts of climate condition changes on optimized results and resulting uncertainty were also quantified and evaluated through optimizations in different climate years. The case study indicated that the model is a computationally efficient and feasible approach for process-based optimization on large scales with considering impacts of climate condition changes. [ABSTRACT FROM AUTHOR]

Rice is the high-water consumption crop that feeds more than half of the world population. The planting area of cold region rice is expanded rapidly in recent years due to the high market values, also resulting in increasing water shortages and eco-environmental problems on a regional scale. Pursuing high benefits and increasing water use efficiency become more significant both for stakeholders and managers. To understand the yield variation and water-saving potential, the specific rice model-ORYZA2000 was adopted to predict the responses of rice growth/yield and water use to the various climatic and irrigation conditions in a typical cold region of northeast China. Field experiments were conducted for the Japonica rice in cold regions (JRC) during 2018 and 2019, with detailed observations on rice growth and development. The ORYZA2000 was calibrated and validated using two-year experimental data. Simulated ponded water depth, various organ development and yield fitted well with field observations. A set of recommended values of crop parameters for JRC was obtained through the systematic parametrization, showing very specific and different characters from the varieties in warmer regions. The irrigation scheduling module was modified for adapting to the various irrigation regimes. After that, the scenario simulation with 30-year different climatic data (i.e. 1990–2019) and three different irrigation regimes (i.e. traditional flood irrigation (TFI), shallow-wet irrigation (SWI) and controlled irrigation (CTI)) were conducted using the calibrated model. Status evaluation and scenario analyses indicated that the crop yield of JRC varied significantly due to relatively large fluctuations of photothermal conditions in different years. The inter-annual potential yield varied from 6790 to 9516 kg ha−1, with an average of 8210 kg ha−1. Evaluation on water-saving scenarios indicated that adopting SWI and CTI regimes could averagely save up to 90 mm and 140 mm (20% and 30%) of irrigation water in dry years, respectively, compared with TFI regime. Overall, the obtained set of parameters for JRC could efficiently complement the parameter database for rice modeling in cold regions; meanwhile, the yield and water-saving evaluation could provide very useful information and the basis for supporting the future JRC production and water-saving management. • ORYZA model was calibrated and validated using two-year detailed experimental data. • Crop parameter values were specific and recommended for cold region rice. • Irrigation scheduling module was modified to adapt to various irrigation regimes. • Yield variation of JRC was obtained through predictions with 30-year climatic data. • Water-saving potential was evaluated for JRC with three irrigation regimes. [ABSTRACT FROM AUTHOR]

Shallow groundwater often presents multiple behaviors in supporting the sustainability of arid agroecosystems. The behaviors are especially important and complicated for the arid irrigated areas with fragmented land-use types. In the view of understanding the role of shallow groundwater in such areas, the MODFLOW and MT3DMS (with the assistance of HYDRUS-1D) were used to simulate groundwater flow and salt transport in a typical observation site of the arid upper Yellow River basin (YRB). The original MODFLOW was modified with introducing a variable expression of specific yield, aiming to improve the modeling accuracy in shallow groundwater environments. The model was calibrated and validated using the observation data of groundwater depth and drainage in 2013 and 2012, respectively. Groundwater evapotranspiration and lateral water-salt exchange among different land-use types were simulated and analyzed; meanwhile, the dry drainage effect of non-cultivated natural land was quantitatively interpreted. Results indicated that the fragmented land-use/planting pattern (with different irrigation scheduling) resulted in significant lateral groundwater flow and water/salt redistribution among different land-use fields during irrigation. The groundwater evapotranspiration ranged at about 160–220 mm for different land-use types, reaching to 0.30–0.45 of plant evapotranspiration (ET pt) during the growing seasons. This effectively supplemented the plant water use in arid climate, especially for the unirrigated cultivated land (during some stages) and the non-irrigated natural land. Meanwhile, the lateral groundwater flow drove salt migrating from the cultivated land to the natural land. The natural land accumulated 27–40% of salts introduced by irrigation, playing a significant role in accommodating salts (i.e. the dry drainage effect). Moreover, our modeling work further implied that the reliable groundwater modeling in arid and shallow groundwater areas required a more detailed model conceptualization and more accurate information of land-use distribution, irrigation scheduling, and local microrelief than the general understanding in the past. • A detailed local-scale groundwater model was established for a typical observation site. • Multiple roles of shallow groundwater system with fragmented land use was elucidated. • Groundwater evapotranspiration and lateral water-salt exchange dynamics were analyzed. • Dry drainage effect of non-cultivated natural lands was quantitatively interpreted. • Implication for improving accuracy of the previous modeling work was proposed. [ABSTRACT FROM AUTHOR]

Scenario analysis is the basis of developing rational water management practices (WMPs) for watersheds. How to predict future hydrological responses on a regional-scale is still a challenge for modeling work in irrigated watersheds with shallow groundwater environments. Therefore, this paper presents an efficient realization of predicting regional agroecosystem responses and searching for appropriate WMPs, through using a water balance-based, semi-distributed hydrological model (SWAT-AG). The scenario case study is carried out in the Jiyuan Irrigation System located in the Hetao of upper Yellow River basin, based on the calibrated and validated modeling work in our previous companion paper. Eight scenarios of water-saving practices (WSPs) are proposed, with consideration for reducing irrigation depth and controlling initial groundwater depth. Then the coupled responses of agroecosystem processes to various WSPs are predicted for the case study region in 2012 and 2013, mainly related to the groundwater depth, root zone soil water and salinity, and crop yield/natural vegetation biomass. Based on the analysis for proposed scenarios, the 100% of present irrigation depth combined with increasing initial GWD by 50 cm are recommended as appropriate WSPs for dry years, and the 80% of present irrigation depth combined with increasing initial GWD by 100 cm are recommended for wet years, in order to maintain good environmental conditions for both crops and natural vegetation. In addition, results show that SWAT-AG could overcome the scale/function limitations of traditional soil/crop models and also avoid computational issues of numerical models. We further point out that the scenarios in reality will be more complicated and comprehensive in time and space, and thus the predictions should be updated accordingly. Overall, this case study fully presents the feasibility and practicality of using the SWAT-AG model to realize the scenario response analysis and water management decision-making on a region scale for irrigated watersheds with shallow groundwater environments. • Regional realization of predicting agroecosystem responses was carried out. • Scenario study predicted the coupled responses to water-saving practices. • Appropriate water-saving management was suggested for maintaining agroecosystems. • Approach showed high potential in supporting water use in arid irrigated areas. [ABSTRACT FROM AUTHOR]

Despite the importance of energy efficiency (EE) in promoting economic growth (EG), the empirical evidence about the growth effect of EE is quite thin. This research intends to examine the heterogeneous impacts of EE, renewable energy consumption (REC), and other factors on EG of BRICS countries for 1990–2014. The empirical results unveil that EE in BRICS countries is an important source for EG. The findings of fixed-effect panel quantile regression analysis clearly explain that the effects of all the selected components of EG are heterogeneous along the quantiles. The effect of EE is significantly positive across all the quantiles, but the positive effect is more robust at 50th and 60th quantiles of EG. REC significantly decreases the EG in BRICS economies, but the negative influence is more robust at the upper quantiles of EG (0.60–0.90). Moreover, the results obtained from Dumitrescu-Hurlin (D-H) heterogeneous panel causality test approve the feedback hypothesis between EE and EG in BRICS countries. The findings also provide the bidirectional causal relationship between REC and EG. Furthermore, a causal association is observed from EE to REC. It suggests that EE is also beneficial to enhance REC in BRICS countries. The study suggests that more prolific use of energy can stimulate EG in BRICS countries by improvement in EE and renewable energy (RE). • Heterogeneous impact of energy efficiency and renewable energy use on the economic growth of BRICS countries. • Fixed effect panel quantile regression analysis is used to capture the heterogeneous effects. • Energy efficiency is an important source of economic growth in BRICS countries. • The feedback hypothesis exists between energy efficiency and economic growth. [ABSTRACT FROM AUTHOR]

Despite the importance of energy efficiency (EE) in promoting economic growth (EG), the empirical evidence about the growth effect of EE is quite thin. This research intends to examine the heterogeneous impacts of EE, renewable energy consumption (REC), and other factors on EG of BRICS countries for 1990–2014. The empirical results unveil that EE in BRICS countries is an important source for EG. The findings of fixed-effect panel quantile regression analysis clearly explain that the effects of all the selected components of EG are heterogeneous along the quantiles. The effect of EE is significantly positive across all the quantiles, but the positive effect is more robust at 50th and 60th quantiles of EG. REC significantly decreases the EG in BRICS economies, but the negative influence is more robust at the upper quantiles of EG (0.60–0.90). Moreover, the results obtained from Dumitrescu-Hurlin (D-H) heterogeneous panel causality test approve the feedback hypothesis between EE and EG in BRICS countries. The findings also provide the bidirectional causal relationship between REC and EG. Furthermore, a causal association is observed from EE to REC. It suggests that EE is also beneficial to enhance REC in BRICS countries. The study suggests that more prolific use of energy can stimulate EG in BRICS countries by improvement in EE and renewable energy (RE). • Heterogeneous impact of energy efficiency and renewable energy use on the economic growth of BRICS countries. • Fixed effect panel quantile regression analysis is used to capture the heterogeneous effects. • Energy efficiency is an important source of economic growth in BRICS countries. • The feedback hypothesis exists between energy efficiency and economic growth. [ABSTRACT FROM AUTHOR]

• Equivalent water productivity (WP) was proposed and proved to be useful in WP assessment. • WP is scale dependent due to water reuse through shallow groundwater systems. • Natural vegetation should not be ignored when considering water productivity of a whole region. • Water reuse reduces WP compared with direct use in salt affected areas. • Efficient irrigation systems are needed for WP improvement in salt affected areas. Water productivity (WP) expressed as the yield produced per unit volume of water is an important indicator of water use in arid and semi-arid areas. Due to complex plant cover and hydrological processes, the quantification and assessment of WP are usually difficult to determine, especially at the regional scale. In this study, an arid irrigated agro-ecosystem in the upper Yellow River basin was selected as a case study area. Based on field observation and model simulation results, the WP of irrigation water (WP I), water applied (WP (I + P)) and evapotranspiration (WP ET) were calculated. Equivalent water productivity (EWP) of irrigation water (EWP I), water applied (EWP (I + P)) and evapotranspiration (EWP ET) were proposed and calculated to unify the disparate WP for various crops and natural vegetation. Results showed WP I and WP (I + P) decreased with the increase of water application for all plants except watermelon, indicating supplemental irrigation to watermelon is urgent to improve its production and WP (I + P). The spatially averaged WP ET (kg m−3) was 2.47 for maize, 0.80 for sunflower, 12.3 for watermelon, 1.39 for wheat and 0.65 for natural vegetation. WP ET for natural vegetation was usually lower in this salt stressed area compared with other water stressed areas. The EWP revealed the rank order of WP for different crops and natural vegetation: watermelon > wheat > maize > sunflower for EWP I ; natural vegetation > wheat > watermelon > maize > sunflower for EWP (I + P) ; and wheat > sunflower > watermelon > maize > natural vegetation for EWP ET. The relationship between EWP (I + P) and EWP ET was scale dependent due to the water reuse phenomena among different land cover types and the canals through the shallow groundwater system. Ignoring natural vegetation will result in considerable bias in the estimation of the regional scale water productivity (16 % in this study). WP improvement strategies such as transferring irrigation water from less productive (sunflower) areas to productive (vegetable and natural vegetation) areas, reducing bare soil evaporation and constructing a timely and accurate irrigation-drainage system were provided. [ABSTRACT FROM AUTHOR]

• J s was modified considering sapwood width and insertion direction. • Groundwater table rise due to canal infiltration increased J s by 5.5–25.8% • Impact of ET o and groundwater on J s was quantified. • The threshold of groundwater table depth to support J s is about 3.6 m. Shelterbelts play an important ecological function in arid irrigation land, while competing for water which otherwise supports crop growth. Estimation of shelterbelt water consumption from groundwater is essential to better manage shelterbelts in irrigation districts, but often a challenging task due to its geometry and varying accessibility to groundwater. In the study, sap flow of Populus popularis planted along an irrigation canal was measured during two growing seasons (2016–2017) to investigate its response to varying shallow groundwater. Considering the radial pattern of sap flux density (J s) and measurement azimuthal effect, corrected J s was adopted to better represent transpiration. The results indicate that increased soil moisture and groundwater table during irrigation periods with water flowing in the canal enhance relative J s of shelterbelt by 5.5–25.8% from the non-irrigation intervals. The threshold of groundwater depth (3.6 m) is identified, beyond which transpiration of the seven-year-old shelterbelt becomes very low. Greenbelt transpiration strongly depends on groundwater within the threshold, and can be estimated through an exponential function of the ratio of atmospheric demand and groundwater depth. Besides, with the decrease of reference evapotranspiration from June to September, the sensitivity of shelterbelt transpiration response to groundwater table depth was increased. This study provides necessary information to evaluate farmland shelterbelt transpiration for rational water resource allocation to meet the ecological water requirement in arid areas with shallow groundwater. [ABSTRACT FROM AUTHOR]

Household sector is the end consumer in the socio-economic water cycle and consumes a large amount of water in both physical and virtual ways. The life cycle water consumption by households, also denoted as Blue Water Footprint (BWF), is mostly affected by consumption expenditure and varies among different household groups. This study assessed the household BWF in China by integrating the input-output model with a national survey of household consumption expenditure. The logarithmic mean divisia index method was employed to examine the influencing factors in BWF disparity among the different household groups. We found that 1) per capita BWF, on national average, increased from 157 m3 in 2012 to 176 m3 in 2018; 2) in 2012, urban households, on average, consumed 185 m3 of water per capita annually, while rural households consumed 126 m3 per capita; there is a significant difference in dietary between rural and urban households, e.g., starchy foods predominate in rural dietary while animal-based foods are more preferred in urban regions; 3) BWF shows distinctive regional characteristics, e.g., more water was consumed on clothes in cold regions and on aquatic products in coastal regions; 4) income disparity is a key factor in causing the BWF difference. Although BWF has a positive correlation with income, its marginal growth diminishes, because of the fading consumption propensity and the switch of consumption pattern from water-consuming to water-saving, e.g., rich households are inclined to spend most of the money on education and recreation rather than food. This study is of significance in understanding how the BWF varies among different households, and how the BWF is affected by the influencing factors, including income, propensity to consume, consumption pattern, and virtual water intensity. Image 1 [ABSTRACT FROM AUTHOR]

Greenhouse gas emissions from agricultural soil are strongly affected by the field practices including fertilization, irrigation and cultivation model. Understanding the mechanism of greenhouse gas emissions from soil and their impact factors is essential for cleaner agricultural production and global greenhouse gas mitigation. This paper investigated greenhouse gas emissions from soil of mulching cultivated maize (Zea mays L.) field under different irrigation and fertilization regimes. Border and drip irrigation with different schedules were implemented in the upper reaches of Yellow River, China. Border irrigation included three different irrigation depths (180, 315 and 450 mm), and drip irrigation was controlled by a tensiometer and triggered by three different matric potentials (−15, −25 and −35 kPa). Three nitrogen fertilizer levels (350, 250 and 150 kg ha−1) were applied for the drip irrigation triggered by the matric potential of −25 kPa. Soil acted as a sink of CH 4 in the semiarid site regardless of irrigation and nitrogen fertilization regimes. Irrigation scheduling had no significant influence on CO 2 emissions, but the irrigation method did have. Cumulative CO 2 emissions increased by 24.7% for drip irrigation compared with border irrigation at the same water and nitrogen fertilizer levels. Cumulative CO 2 emissions for the high nitrogen fertilizer treatment (350 kg ha−1) increased by 19.3% in comparison with the medium and low levels under drip irrigation. N 2 O emissions were positively related to the irrigation depth under both drip and border irrigation. Cumulative N 2 O emissions reduced by 23.5% for drip irrigation compared with border irrigation at the same water and nitrogen fertilizer levels. N 2 O emissions increased with the increase in nitrogen fertilizer application under drip irrigation. Drip irrigation with high frequency (−15 kPa) and medium nitrogen fertilization (250 kg ha−1) obtained the best economic and environmental performance through comprehensive evaluation of the yield, water and fertilizer productivity, global warming potential, greenhouse gas intensity and net ecosystem economic budget. The findings can provide an opportunity for greenhouse gas mitigation without crop yield reduction following the proper irrigation and fertilization regimes in the semiarid region. • Soil acts as a sink of CH 4 in dry land regardless of irrigation and N fertilization. • N 2 O emissions are positively related to quantity of irrigation and N fertilization. • Irrigation scheduling had a minor impact on CO 2 emissions in soils with low organic matter. • We estimated the net ecosystem economic budget considering global warming potential. [ABSTRACT FROM AUTHOR]

• Fate of N fertilizer in different irrigation and fertilization regimes is quantified. • Water and N use efficiencies of mulching cultivated maize were analyzed under different regimes. • A proper irrigation and fertilization regime was proposed for maize in arid region. Irrigation and fertilizer management are essential for sustainable development of agriculture in the arid and semiarid regions. In order to obtain high yield production, over irrigation and fertilization are frequently conducted by the farmer which results in a series of environmental problems in particular in the shallow groundwater areas. In this paper, two-year field experiments were conducted to investigate the effect of irrigation and fertilization regimes on grain yield, water and nitrogen productivity of mulching cultivated maize (Zea mays L.) in the Hetao Irrigation District of China. Two irrigation methods, i.e., drip and border irrigation, with different schedules were manipulated in silt loam soil. The border irrigation included two/three different water levels and drip irrigation was triggered by a tensiometer located at a depth of 25 cm with different matric potentials (−15, −25 and −35 kPa). Three different nitrogen fertilization levels (350, 250 and 150 kg ha−1) were applied under drip irrigation controlled by the matric potential of −25 kPa. Soil water storage variation indicated that the active root zone concentrated at a depth of 35−60 cm in the border irrigated plots and 25−45 cm in the drip irrigated plots. Around 16 % of irrigated water (71 out of 450 mm) and 18 % of supplied nitrogen fertilizer (64 out of 350 kg ha−1) were percolated into deeper zone for the farmer's irrigation and fertilization schedules. Border irrigation water reduced from 450 to 315 mm could decrease the deep percolation without yield reduction. Almost no deep percolation was detected in drip irrigation for three different matric potential controls. The highest yield, water and nitrogen productivity obtained from the drip irrigated plots triggered by matric potential of −15 kPa. Considering yield, water and nitrogen productivity, environmental factors and farmer's net-profit, drip irrigation at the matric potential of −15 kPa with 250 kg ha−1 nitrogen fertilizer or border irrigation of 315 mm is recommended for mulching cultivated maize in silt loam soil in the Hetao Irrigation District. The nitrogen fertilizer schedule in border irrigation is desirable for optimal application. [ABSTRACT FROM AUTHOR]

• For seasonal and diurnal variations, LE accounted for the highest proportion of R n. • Energy fluxes and ET a were affected by maize LAI with a threshold around 4 m2 m-2. • Irrigation and the decreasing WTD from about 2.2 to 1.2 m increased LE/R n or LE. • The inter-seasonal variation of ET a was more dependent on water conditions than ET 0. • Average WTD of 1.52 and 1.76 m contributed to 36.3 % and 26.2 % ET a in 2017 and 2018. Precise estimations of energy fluxes and evapotranspiration for cropland in arid areas with shallow groundwater are necessary but limited. There is also a need to better understand the contribution of groundwater for meeting crop water consumptive use. In this study, considering the environmental conditions, such as meteorological variables, crop growth and water regimes, energy fluxes and actual evapotranspiration (ET a) in an irrigated maize field with shallow groundwater were examined using eddy covariance system during two growing seasons. Due to the energy imbalance of the eddy covariance method, latent heat (LE) was adjusted using the Bowen ratio preservation of energy principle and subsequently very close (R2 = 0.94) to that measured by the Bowen-ratio-energy-balance system. For seasonal and diurnal variations, LE accounted for the highest proportion of net radiation (R n) from the jointing stage. While LE / R n was a little lower in 2018 than that in 2017 which may be because of the deeper groundwater table depth (WTD) in 2018. The negative sensible heat in the afternoon implied the occurrence of heat advection in the irrigated cropland. Energy fluxes and ET a were significantly affected by crop development when leaf area index was less than about 4 m2 m-2. Moreover, the increasing WTD from 1.2 to 2.2 m decreased LE by about 70 % and increased daily average Bowen ratio. From the jointing stage, total ET a was 522.1 and 453.8 mm in 2017 and 2018, respectively. The inter-seasonal variation in ET a was more dependent on water conditions than the potential evaporative demand. The water balance result showed that average WTD of 1.52 and 1.76 m for the growing period contributed to 36.3 % and 26.2 % ET a in 2017 and 2018, respectively. Besides, daily groundwater contribution between two seasons was different because of the differences in irrigation allocation and WTD. These results highlight the key effect of shallow groundwater to energy fluxes and water exchange of agroecosystem in arid areas. [ABSTRACT FROM AUTHOR]

• An agro-hydrological model was established in the middle oasis of Heihe River basin. • The effects of CO 2 on stomatal conductance and leaf area were considered in the model. • The impacts of climate change and water-saving on crop growth and WP were evaluated. • Adaptive strategies to climate change were proposed. Climate change and associated elevated atmospheric CO 2 concentration and rising temperature have become a great challenge to agricultural production especially in arid and semiarid regions, and a great concern to scientists worldwide. Thus, it is very important to assess the response of crop growth and water productivity to climate change projections, which in turn can help devise adaptive strategies to mitigate their impact. An agro-hydrological model with well consideration of CO 2 effects on both the stomatal conductance and leaf area was established. The model was well calibrated and validated using the data collected from the middle oasis of Heihe River basin, northwest China, which was selected as a typical arid region. Simulations of soil water contents and crop growth matched well with observations. Then various scenarios were designed with considering three climate change alternatives (RCP 2.6, RCP 4.5 and RCP 8.5) and three agricultural water-saving alternatives in the context of irrigation water availability being constant. Responses of crop growth and water productivity were predicted for thirty years from 2018 to 2047. As compared to current situation, there would be a reduction of 3.4–8.6% in crop yield during the period of 2018–2027 and an increase of 1.5–18.7% in crop yield during the period of 2028–2047 for seed corn, and an increase of 7.4–26.7% in crop yield during the period of 2018–2047 for spring wheat, respectively. Moreover, results showed an increase in water productivity ranged from 14.3% to 44.5% for seed corn and from 34.7% to 52.0% for spring wheat, respectively. Furthermore, adaptive strategies to climate change were recommended for the seed corn and spring wheat, respectively. Our results are expected to provide implications for devising adaptive strategies to changing environments in other arid and irrigation-fed areas. [ABSTRACT FROM AUTHOR]

• Prophylactic anti-depressive therapies following acute stroke were shown to reduce the incidence of depression in the patients. The effectiveness remained significant even in the follow-up period. • Prophylactic anti-depressive therapies following acute stroke were shown to improve symptoms of depression, improve motor function and neurological function. • The anti-depressive therapies showed no effects on mortality and adverse events incidence. To explore the necessity and feasibility of early anti-depressive therapies in acute stroke patients, we conducted a meta-analysis of currently available randomized control studies (RCTs). Literature search in six databases was done with keywords of cerebrovascular accident, depression and prevention. Only RCTs that met the inclusion criteria were enrolled for further analysis. Twelve eligible studies were included in this meta-analysis. Prophylactic anti-depressive therapies following acute stroke were shown to reduce the incidence of depression in the patients (RR = =0.33, 95% CI: 0.25 to 0.43, p < 0.001), improve symptoms of depression (WMD: 5.73, 95% CI: 4.18 to 7.29, p < 0.001), improve motor function (WMD: 12.56, 95%CI: 9.07 to 16.04, p < 0.001) and neurological function (WMD: 1.13, 95%CI: 0.57 to 1.69, p < 0.001). However, anti-depressive therapies showed no effects on mortality (RR = 1.63, 95%CI: 0.55 to 4.85, p = 0.377) and adverse events incidence (RR = 0.93, 95%CI: 0.53 to 1.64, p = 0.806). Anti-depressive therapies following acute stroke is effective thus deserves to be advocated. [ABSTRACT FROM AUTHOR]

Soil salinization is one of the most common land degradation processes that impacts agricultural production, environmental health, and economic welfare. The first task in managing soil salinity is to understand its spatiotemporal characteristics, causal factors and influences, both over large regions and within individual fields. In this study, a typical irrigated agro-ecosystem located in the upper Yellow River basin, suffering from long-term soil salinization problems, was selected as the case study area. Field sampling experiments and investigations related to soil layer salt content, groundwater, irrigation and ground elevation were carried out at three scales (field scale, canal scale and regional scale) covering both croplands and natural vegetation patches during 2016 and 2017. Spatiotemporal characteristics of soil salinity were analyzed for the three scales based on sampling data, remote sensing, geostatistical analysis and model simulation. Results showed that, at the regional scale, the soil salinity distribution was dominated by topography and groundwater depth; at the canal scale, it was dominated by irrigation and cropping pattern; at the field scale, it was dominated by micro-topography and the uniformity of field irrigation. Scale-dependent soil salinity management strategies should be adopted to maintain agricultural production and the sustainability of natural ecosystems. It can be concluded that using integrated approaches including multi scale soil sampling, model simulation and other modern techniques is an effective way for thorough understanding and management of soil salinity. • Soil sampling, GIS/RS and dynamic model were integrated for salinity analysis. • Salinity characteristics and their causal factors were scale dependent. • The proportion of salt-affected soil increased by 14% during the growing season. • Multiple modern techniques are needed for salt prediction and management. [ABSTRACT FROM AUTHOR]

Capillary rise from shallow groundwater can decrease the need for irrigation water. However, simple techniques do not exist to quantify the contribution of capillary flux to crop water use. In this study we develop the Agricultural Water Productivity Model for Shallow Groundwater (AWPM-SG) for calculating capillary fluxes from shallow groundwater using readily available data. The model combines an analytical solution of upward flux from groundwater with the EPIC crop growth model. AWPM-SG was calibrated and validated with 2-year lysimetric experiment with maize. Predicted soil moisture, groundwater depth and leaf area index agreed with the observations. To investigate the response of model, various scenarios were run in which the irrigation amount and groundwater depth were varied. Simulations shows that at groundwater depth of 1 m capillary upward supplied 41% of the evapotranspiration. This reduced to 6% at groundwater depth of 2 m. The yield per unit water consumed (water productivity) was nearly constant for 2.3 kg/m3. The yield per unit water applied (irrigation water productivity) increased with decreasing irrigation water because capillary rise made up in part for the lack of irrigation water. Consequently, using AWPM-SG in irrigation scheduling will be beneficial to save more water in areas with shallow groundwater. [ABSTRACT FROM AUTHOR]