Spatial Analysis and Risk Assessment of Meteorological Disasters Affecting Cotton Cultivation in Xinjiang: A Comprehensive Model Approach DOI Open Access
Ping Zhang, Zhuo Chen,

Gang Ding

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(12), P. 4938 - 4938

Published: June 8, 2024

A systematic understanding of the spatial distribution meteorological disasters that affect cotton growth, such as rainstorms, gales, and hail, is important for reducing plant losses promoting sustainable development. Our study aimed to evaluate risk during growth analyze their driving factors. assessment model major cultivation in Xinjiang was established by integrating entropy weight methods an analytic hierarchy process. disaster index system, including vulnerability disaster-bearing bodies, hazards disaster-causing factors, exposure constructed using Google Earth Engine. We determined comprehensive levels various regions Xinjiang. Research shows selection indicators very important, crop with a clear body can make results more accurate. It necessary consider multiple species assessment. The revealed differences 2020. high risks accounted 42% planting area, mainly distributed Karamay, Tacheng, Kashgar, Changjizhou, Kezhou, Ilizhou. Consequently, this provides scientific basis Xinjiang, China.

Language: Английский

Prediction of drought trigger thresholds for future winter wheat yield losses in China based on the DSSAT-CERES-Wheat model and Copula conditional probabilities DOI Creative Commons
Cuiping Yang, Changhong Liu, Yanxin Liu

et al.

Agricultural Water Management, Journal Year: 2024, Volume and Issue: 299, P. 108881 - 108881

Published: May 18, 2024

Predicting the risk of diminished wheat yields caused by drought under future climate change is essential for long-term sustainability agriculture. Although studies have explored relationship between and crop yield loss, precise thresholds triggering losses in remain unclear. In this study, we established a conditional probability framework trigger at various loss levels China's winter regions based on copula functions. The primary drivers influencing dynamics were evaluated using random forest model. results revealed that projected baseline period (1981–2020), near (2021–2060), far (2061–2100) ranged from –2.1 to –1.2, –0.8 –0.6, –1.2 –1.0, respectively, implying firstly rises then declines. This trend was primarily due increased contribution precipitation (Pre) (from 24.0% 31.5%) threshold future, coupled with decrease temperature (Tmean) 37.1% 30.4%). shift suggested Pre might alleviate adverse effect high future. average higher Southwest (–1.0 –0.6) Xinjiang (–1.1 –0.7) regions, where mild occurrences led 30% (70th percentile). Tmean driving factor dynamic changes thresholds. research findings provide scientific guidance agricultural water resource allocation management.

Language: Английский

Citations

9
Probabilistic analysis of drought impact on wheat yield and climate change implications DOI Creative Commons
Bin Wang, Linchao Li, Puyu Feng

et al.

Weather and Climate Extremes, Journal Year: 2024, Volume and Issue: 45, P. 100708 - 100708

Published: July 14, 2024

Drought is projected to intensify under warming climate and will continuously threaten global food security. Assessing the risk of yield loss due drought key developing effective agronomic options for farmers policymakers. However, little has been known about determining likelihood reduced crop different conditions defining thresholds that trigger at regional scale in Australia. Here, we estimated dependence variation on identified 12 Australia's wheat producing regions with historical data by bivariate models based copula functions. These were used investigate statistics change an ensemble 36 from Coupled Model Intercomparison Project Phase 6 (CMIP6). We found drought-induced was region-specific. The leading same magnitude reduction smaller southern Queensland larger Western Australia mainly soil conditions. be more frequent affect areas future climates. Based our results, advocate management options, particularly where vulnerable This mitigate potential impacts production safeguard

Language: Английский

Citations

7
Prediction of Drought Thresholds Triggering Winter Wheat Yield Losses in the Future Based on the CNN-LSTM Model and Copula Theory: A Case Study of Henan Province DOI Creative Commons

Jianqin Ma,

Yan Zhao,

Bifeng Cui

et al.

Agronomy, Journal Year: 2025, Volume and Issue: 15(4), P. 954 - 954

Published: April 14, 2025

As global warming progresses, quantifying drought thresholds for crop yield losses is crucial food security and sustainable agriculture. Based on the CNN-LSTM model Copula function, this study constructs a conditional probability framework under future climate change. It analyzes relationship between Standardized Precipitation–Evapotranspiration Index (SPEI) winter wheat yield, assesses vulnerability of in various regions to stress, quantifies The results showed that (1) SPEI Zhoukou, Sanmenxia, Nanyang was significantly correlated with yield; (2) southern eastern higher than center, western, northern past (2000–2023) (2024–2047); (3) there were significant differences thresholds. loss below 30, 50, 70 percentiles (past/future) −1.86/−2.47, −0.85/−1.39, 0.60/0.35 (Xinyang); −1.45/−2.16, −0.75/−1.34, −0.17/−0.43 (Nanyang); −1.47/−2.24, −0.97/−1.61, 0.69/0.28 (Zhoukou); −2.18/−2.86, −1.80/−2.36, −0.75/−1.08 (Kaifeng), indicating threshold will reduce future. This mainly due different soil conditions Henan Province. In context change, droughts be more frequent. Hence, research provide valuable reference efficient utilization agricultural water resources prevention control risk change

Language: Английский

Citations

0
Drought risk assessment on arid region under different socioeconomic scenarios: A case of Loess Plateau, China DOI Creative Commons
Jinjun Guo, Dongyang Xiao, Xialing Sun

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 167, P. 112728 - 112728

Published: Oct. 1, 2024

Language: Английский

Citations

3
Developing a multivariate drought index to assess drought characteristics based on the SWAT-Copula method in the Poyang Lake basin, China DOI Creative Commons
Liping Guo, Fusheng Chen, Bin Wang

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 170, P. 113123 - 113123

Published: Jan. 1, 2025

Language: Английский

Citations

0
Predicting the risk and trigger thresholds for propagation of meteorological droughts to agricultural droughts in China based on Copula-Bayesian model DOI Creative Commons
Cuiping Yang, Changhong Liu, Xuguang Xing

et al.

Agricultural Water Management, Journal Year: 2025, Volume and Issue: 313, P. 109468 - 109468

Published: April 8, 2025

Language: Английский

Citations

0
Hazard assessment of compound drought and heat events on summer maize from agricultural and meteorological perspectives DOI Creative Commons
Qing Li, Peijuan Wang, Yang Li

et al.

Agricultural Water Management, Journal Year: 2025, Volume and Issue: 313, P. 109479 - 109479

Published: April 19, 2025

Language: Английский

Citations

0
Regional detection and assessment of chilling damage on maize considering land surface temperature, crop growth status and solar radiation changes DOI
Jingxiao Zhang, Jiabing Cai, Di Xu

et al.

Journal of Agronomy and Crop Science, Journal Year: 2024, Volume and Issue: 210(2)

Published: Feb. 5, 2024

Abstract Increased frequency and severity of chilling damage events pose potential risks to crop performance productivity due climate change. Accurate real‐time access is important for growth yield stability based on field's actual environment. To precisely identify regional evaluate the impacts crops, this study presents a model estimate field air temperature in view situations. Land surface temperature, enhanced vegetation index, solar‐induced chlorophyll fluorescence solar declination were involved model. With simultaneous continuous monitoring multisource fused remote sensing data, was calibrated validated Jiefangzha Irrigation Area (JIA) Changchun City (CC) North China, accompanied by determination coefficient ≥0.756, root mean square error ≤0.782°C, relative ≤0.041 consistency index ≥0.902. Meanwhile, sensitivities factors determined through path analysis, where performed according order >solar >land > index. Using model, maize further detected JIA CC from 2010 2020. Results showed that greater than JIA, along with sterile‐type occurring three seven CC, while delayed‐type only twice 2012 2016, but five times 2013, 2014, 2017 2019, respectively, being consistent local statistics. In response damage, demonstrated negative effects greenness light use efficiency fluorescence. Serious losses caused, yield‐reducing 5.00% (Dehui, 2013), 19.00% (Jiutai, 2014), 21.65% (Suburban district, 2016), 8.83% (Shuangyang, 2017) 2.19% 2019) CC. The linear relationship between growing degree days bit weakened varying 0.614 0.531. increasing rate decreased 20.365 kg/(°C·d) non‐chilling years 9.670 years. These findings indicate presented especially adaptive agricultural environments, enabling rapid precision detection crops at scales. It will provide references gauging impact finding efficient solutions stress ensuring sustainable development agriculture.

Language: Английский

Citations

1
Meteorological drought projections for Australia from downscaled high-resolution CMIP6 climate simulations DOI Creative Commons
Rohan Eccles, Ralph Trancoso, Jozef Syktus

et al.

Published: July 29, 2024

Abstract. Climate change is projected to lead changes in rainfall patterns, which, when coupled with increasing evapotranspiration, has the potential exacerbate future droughts. This study investigates impacts of climate on meteorological droughts Australia using downscaled high-resolution CMIP6 models under three Shared Socioeconomic Pathway (SSP) scenarios. The Standardised Precipitation Index (SPI) and Evapotranspiration (SPEI) were used assess frequency, duration, percent time, spatial extent There consistent increases for south-west Western Australia, southern Victoria, South western Tasmania SPI SPEI. significantly larger SPEI derived droughts, most country. largest occurred at end century high emissions scenario (SSP370), demonstrating influence extreme For instance, if reached levels by century, area subject drought prone Southern would be 2.8 greater than they kept low SPI, 4 times assessed insights generated from these results supplementary tailored datasets Australian Local Government Areas River Basins are essential better inform decision making adaptation strategies national, regional, local scales.

Language: Английский

Citations

1
Quantification Assessment of Winter Wheat Sensitivity under Different Drought Scenarios during Growth DOI Open Access
Shangming Jiang, Zheng Li, Hongwei Yuan

et al.

Water, Journal Year: 2024, Volume and Issue: 16(14), P. 2048 - 2048

Published: July 19, 2024

To effectively reveal the disaster-causing mechanism between water stress and yield loss under different drought combinations during multiple growth periods of winter wheat, based on biennial wheat experiments, a crop analysis method was used to quantitatively identify assess sensitivity. The results showed that there significant negative correlation total dry matter relative rate (RGR) daily average degree stress. determination coefficients logarithmic fitting for 2017 2018 were 0.7935 0.7683, respectively. Wheat accumulation differed combination scenarios. sensitivity response relationship decrease in RGR (relative no stress) could be identified by an S-shaped curve, R2 0.859 0.849, Mild at tillering stage stimulates adaptability has little effect yield. soil content (SWC) can controlled 65–75% field holding capacity; SWC jointing booting higher than capacity 55%. maintained level 75% heading flowering stages grain-filling milky achieve harmonization yields savings. In addition, production process, continuous severe should avoided. This study elucidates intensity drought-induced losses from perspective physical genesis, provides effective irrigation guidance regional planting, lays foundation construction quantitative agricultural risk curves, technical support predicting trend stresses.

Language: Английский

Citations

1