Pute Wu’s research while affiliated with Northwest University and other places

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Publications (296)


Land use and climate change exacerbate the root zone maximum water deficit in the Loess Plateau
  • Article

June 2025

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46 Reads

Science China Earth Sciences

Zikun Zhao

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Root zone maximum water deficit (SRmax) refers to the maximum water consumption of the root zone during drought, which directly influences the partitioning of precipitation between infiltration and runoff. It is a key parameter in land surface hydrological modeling. Since the implementation of the Grain-for-Green Project (GFG) on the Loess Plateau (LP), vegetation restoration has achieved significant success, resulting in the “greening” of LP while simultaneously reducing surface runoff. However, the lack of consideration for the root zone, a key link between terrestrial ecological and hydrological processes, has hindered understanding of ecohydrological mechanisms and limited comprehensive assessments of regional water resource management and ecological engineering outcomes. This study analyzes the spatiotemporal dynamic of SRmax on the LP from 1982 to 2018 using multi-source datasets and the Mass Curve Technique. Additionally, we employ a hybrid machine learningstatistical attribution model to quantify the contributions of land use and climate change to the SRmax dynamic. The results indicate an average SRmax of 85.3 mm across the LP, with significant variations among land use types: natural forest (116.3 mm) > planted forest (104.6 mm) > grassland (87.0 mm) > cropland (78.8 mm). Following the implementation of GFG, SRmax increased by 37.7%, with an upward trend observed across all land use types, particularly in changed land type, which experienced the largest increases. The attribution model achieved a coefficient of determination (R2) of 0.92. The key factors driving SRmax variation varied by land use type: in unchanged land type, climate change accounted for 53.8% of the SRmax increase, whereas land use change explained 71.3% of the increase in changed land type, with GFG contributing 52.1%. These findings provide a scientific basis for enhancing drought resilience and implementing the “Water-for-Greening” strategy on the LP and similar regions under changing environmental conditions.


The framework for establishing the model of blue‐green WF for crop production with physical process interpretability.
Sensitivity index (SI) of each input parameter for the blue‐to‐total WF ratio of maize. Panels (a, b) show the boxplots of the SI of crop planting date (PD), crop coefficient (Kc ${K}_{c}$), reference evapotranspiration (ET0) and precipitation (PRE) at global annual and monthly scales. Panel (c) shows the bar chart of the SI of four input parameters for the top 10 countries (regions) in global maize production. Panels (d–g) show the spatial distribution pattern of SI values for PD, Kc ${K}_{c}$, ET0 and PRE.
Bias in the blue‐to‐total WF ratio of maize production between this study and WATNEEDS and WFN, respectively. The bias value is the blue‐to‐total WF ratio of maize production simulated by this model minus that of comparison databases. The results of comparison with WATNEEDS are shown in panels (a) (2000) and (b) (2016), and the results of comparison with WFN are shown in panel (c) (2000). The distribution map of maize harvested area in 2000 is shown in panel (d).
Comparison of simulated intermediate parameters and results against the WATNEEDS and Mialyk et al. (2024) data sets. Panel (a) shows the monthly R² values of blue and green evapotranspiration under both irrigated and rainfed conditions between this study and WATNEEDS. Panels (b, c) present the comparison and bias in monthly blue‐to‐total WF ratio of maize production at grid scale between WATNEEDS and this study, respectively. In these figures, the box plots show the distribution (maximum, minimum, quartiles, and median values) and black dots in panel (b) indicate R². Panel (d) illustrates the R² values of country‐scale uBWF, uGWF and uWF between this study and Mialyk et al. (2024), grouped by maize production levels: Low (<25 Mt), Medium (25–50 Mt), and High (>50 Mt).
Spatial‐temporal evolution of WF and blue‐to‐total WF ratio of maize production. Panels (a–d) show the global WF and blue WF for maize production in 2000 and 2021, respectively. Panels (e, f) show the global blue‐to‐total WF ratio of maize production in 2000 and 2021, respectively. Panels (g, h) show the temporal evolution of the uWF and blue‐to‐total WF ratio in the top 10 maize producing countries during the research period. Panels (i, j) show the relationship between the average annual production, harvested area, and the ratio of irrigated harvested area to total harvested area of maize in each country from 2000 to 2010 and 2011 to 2021, respectively. Among them, the size of circles represents the ratio of irrigated harvested area to total harvested area in each country, and the specific values are displayed next to circles.

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Accounting and Evolution of Global Spatial Explicit Blue and Green Water Footprint of Maize Production With Fewer Inputs
  • Article
  • Full-text available

May 2025

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34 Reads

Gridded data updating for crop water consumption differentiating blue (i.e., irrigation water) and green (i.e., soil water) components at global scale is too hysteretic because of heavy working load and time cost of physical‐based models to prompt understanding and management of water for food. This study constructs a model for crop blue‐green water footprint (WF) with interpretability of physical processes. The modeling performance was tested at 5 arcminute resolution with the case for maize over the period 2000–2021, showing higher reliability in WF estimates for countries with high maize production (R² = 0.67–0.89) and robustness under extreme climate conditions. Results indicate the total WF of global maize production reached 898.1 × 10⁹ m³ yr⁻¹ in 2021, a 50% increase since 2000. The current global average blue‐to‐total WF ratio was 13%. Markable spatiotemporal heterogeneities in the blue‐to‐total WF ratio of maize production are observed. Among major maize producers, South Africa experienced the most substantial increase in the blue‐to‐total WF ratio, rising from 1.3% in 2000 to 25.9% in 2021 (with highest blue uWF of 231 m³ t⁻¹), influenced by drought. This model provides a feasible approach to accounting and deviation of the non‐negligible variations between blue and green water consumption in crop production based on seven sets of data and fewer formulas.

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A Distributed Machine Learning Model for Blue and Green Water Resources With Transferable Applications in Similar Climatic Zones

May 2025

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134 Reads

Human activities profoundly impact the terrestrial water cycle and the spatiotemporal dynamics of blue and green water resources. Distributed hydrological models are essential for simulating the water resources within a basin. However, neither process‐based nor data‐driven hydrological models have fully captured the effects of human activities on the distribution of blue and green water resources in space and time. Here we construct a distributed machine learning model for monthly blue and green water resources, which is trained and calibrated for the Yellow River Basin (YRB) in China, and validated and tested for the transferability to similar climatic zones in the case for Colorado River Basin (CRB) in the United States. The modeling thoroughly accounts for the influence of human activities, incorporating 5 scales (grid, county, city, province, and cluster), 4 algorithms, and 2 model integration methods (Stacking and Bayesian). The R² values reached 0.84 and 0.97 for blue and green water models, respectively, during the test period in the YRB. The corresponding high modeling accuracy maintained with R² values of 0.72 and 0.97 when transferred to the CRB. The model performed better in regions with higher human activity intensity. Precipitation and spatial encoding are respectively the most sensitive feature variables for the green water and blue water models, while nighttime lights and population density are respectively the most significant human activity‐related features. The study highlights the non‐negligible impacts of socioeconomic factors on spatiotemporal dynamics of blue and green water resources, and the feasibility of machine learning modeling.





Water-saving irrigated area expansion hardly enhances crop yield while saving water under climate scenarios in China

April 2025

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78 Reads

Facing climate change risks of water shortages and crop yield losses, it is unclear in China that whether and how irrigated area expansion and technological yield improvement can increase production with less water. Here we used 2000–2018 as the baseline and simulated the grid responses of total crop water use, production, unit water footprint by cropping modes in 2030s–2090 s in 75 scenarios with considering each 5 levels of two adaptation measures under 3 climate change pathways. Compared with climate change alone, further irrigation expansion has limited effects on increasing production (below 20.8%) and decreasing water footprint (below 3.6%). Combined two adaptation measures magnifies their respective effects, with technological yield improvement dominating contributions to production (37.0–99.6%) and water footprint (90.4–102.3%). In comprehensive optimal scenario, water footprint will reduce with increased production. No water is saved with reduced green water (1.6–1.7%) and increased blue water (6.6–21.6%).





Citations (68)


... Recent studies have also shown that the interaction between soil moisture and soil texture can significantly influence the distribution and stability of soil aggregates. For example, Yang et al. [27] demonstrated that soil moisture content can alter the physicochemical properties of soil aggregates, thereby affecting their stability and distribution. Similarly, a study by Yang et al. [28] found that the combination of soil moisture and soil texture can influence the formation and stability of soil aggregates, highlighting the need to consider these factors in soil management practices. ...

Reference:

Evaluation of Soil Aggregate Sieving: The Impact of Field Moisture Content on Size Distribution and Stability
Effects of irrigation-mediated continuously moist and dry-rewetting pattern on soil physicochemical properties, structure and bacterial community
  • Citing Article
  • January 2025

Applied Soil Ecology

... (1) To effectively address the issue of economic factors being the main drivers of water and ecological footprints and to curb decoupling, policy suggestions include strengthening the management and planning of water and ecological resources, promoting the development of water-saving technologies and water-saving industries, and optimizing the industrial structure and layout to reduce resource consumption and environmental pollution [19]. Simultaneously, it is necessary to enhance policy guidance and market mechanism construction, raise public awareness of water conservation and environmental protection, and actively draw on international experience and participate in global governance to jointly promote sustainable development and achieve a favorable decoupling between resource consumption and economic growth [20]. ...

Nitrogen cycling and associated grey water footprint in croplands under different irrigation practices
  • Citing Article
  • November 2024

Journal of Cleaner Production

... Drip irrigation systems can precisely control the flow rate and water application, reducing water loss and directly supplying moisture to plant roots, thereby improving water use efficiency [11]. However, when applying Yellow River water in drip irrigation, the sand particles and suspended matter in water easily cause emitter clogging, which in turn affects irrigation effectiveness and the proper functioning of the system [12]. Therefore, addressing the problems caused by sediment deposition and clogging in drip irrigation systems has become a critical technical challenge that needs to be overcome. ...

Microporous ceramic emitter: A drip irrigation emitter suitable for high-sediment water
  • Citing Article
  • November 2024

Journal of Water Process Engineering

... Due to the direct association between blue and green water footprint and crop growth, research on the grey water footprint in agricultural water studies has been relatively limited. Currently, numerous researchers have extensively studied the water footprint of crop production across various spatial and temporal scales using different models [10][11][12][13]. ...

Water resource efficiency evaluation of crop production in arid and semi-arid regions based on water footprint and comparative advantage
  • Citing Article
  • October 2024

European Journal of Agronomy

... The two words: "nexus" and "circular economy" (CE) are a current topic when it comes to sustainability and sustainable development [12][13][14][15]. The WEF nexus can be considered as an integrated managing outlook of essential natural resources [16][17][18], which was introduced as a framework to balance the three elements (i.e., food, water, and energy) through a comprehensive approach [19][20][21]. Specifically, in the context of the sea food industry, the WEF nexus is discussed by Entrena-Barbero et al. [22]. ...

Developing a sustainable assessment framework for identifying industrial water suitability: Perspective on the water-energy-food nexus
  • Citing Article
  • October 2024

Agricultural Systems

... From a long-term perspective, subsurface drip irrigation presents a viable alternative to traditional surface irrigation methods [26]. Simultaneously, the development of cost-effective and easy-to-maintain drip irrigation systems is essential to support small-scale farmers [27]. Furthermore, due to the relatively high initial installation and operational costs (approximately 4713 USD ha −1 ), the adoption of subsurface drip irrigation technology in the North China region remains limited, accounting for less than 1% of the total irrigated area [28]. ...

Optimizing wolfberry crop productivity and economic sustainability using subsurface irrigation with ceramic emitters for smallholders: A four-year study
  • Citing Article
  • September 2024

European Journal of Agronomy

... They highlighted the effectiveness of DNN models in simulating daily maize transpiration due to their competitive advantage in modeling the complex relationship between transpiration and its driving factors (Fan et al. 2021). Furthermore, several studies successfully simulated plant evapotranspiration using machine learning models (Du et al. 2024;Fan et al. 2021;Guo et al. 2024;Hailegnaw et al. 2024;He et al. 2024;Lee et al. 2024;Li et al. 2020;Wang et al. 2024). ...

Modeling the dynamics of evapotranspiration of wolfberry (Lycium barbarum L.) under different cultivation methods on the Tibetan Plateau
  • Citing Article
  • August 2024

Journal of Hydrology

... Bo et al. (2022) found that NCF reduced the global warming potential (GWP) of CH 4 and N 2 O by 47% while maintaining crop yield based on 636 field trials. Gao et al. (2024) conducted a meta-analysis based on 437 literatures to explore the effect of AWD on crop yield and GHG emissions, reporting that there was a slight decrease in crop yield (1.56%), a decrease in CH 4 emissions (47.47%), and an increase in N 2 O emissions (52.20%). Overall, the existing meta-analysis studies have primarily focused on individual or limited components of the GHG equivalent, such as crop yield, GHG emissions (including CH 4 and N 2 O), without comprehensive evaluations of all the aspects of NCF's GHG equivalent and its NCS benefits. ...

Effects of alternate wetting and drying irrigation on yield, water-saving, and emission reduction in rice fields: A global meta-analysis
  • Citing Article
  • June 2024

Agricultural and Forest Meteorology

... In recent years, extensive research efforts have focused on greenhouse gas emissions from the planting industry at both the national and the global scales, examining areas such as carbon emission accounting methodologies and spatiotemporal dynamics [7,8], comprehensive analysis of driving factors [9,10], longitudinal trends in carbon emission evolution [11,12], and methodological applications of the Tapio decoupling model [13,14]. The scope of agricultural carbon emission accounting can be broadly divided into two primary dimensions: the input perspective, encompassing agricultural material inputs and land utilization practices [15][16][17], and the second dimension, which focuses on the production process, encompassing land utilization practices, methane (CH 4 ) emissions from rice paddies, and nitrous oxide (N 2 O) emissions from agricultural fields [18]. ...

Decoupling trend and drivers between grain water‑carbon footprint and economy-ecology development in China
  • Citing Article
  • May 2024

Agricultural Systems

... After all tests, all collected water sensitive paper were taken back to the laboratory and scanned one by one at high resolution (600 dpi) using a printer with an integrated scanner (Hewlett-Packard, Palo Alto, USA). The scanned water sensitive paper was then analyzed by using an open source image processing software ImagePy (Zhang et al., 2024), which can obtain data such as droplet coverage density (the number of water sensitive paper droplets per unit area), droplet deposition coverage (the ratio of the target surface area covered by droplets to the total target surface area) and droplet deposition amount (the deposition amount of droplet per unit area). ...

Comparative analysis of micro-physical characteristics of sprayed droplets using various measurement technologies

Irrigation Science