County-Level Cultivated Land Quality Evaluation Using Multi-Temporal Remote Sensing and Machine Learning Models: From the Perspective of National Standard DOI Creative Commons

Dingding Duan,

Xinru Li, Yanghua Liu

и другие.

Remote Sensing, Год журнала: 2024, Номер 16(18), С. 3427 - 3427

Опубликована: Сен. 15, 2024

Scientific evaluation of cultivated land quality (CLQ) is necessary for promoting rational utilization and achieving one the Sustainable Development Goals (SDGs): Zero Hunger. However, CLQ system proposed in previous studies was diversified, methods were inefficient. In this study, based on China’s first national standard “Cultivated Land Quality Grade” (GB/T 33469-2016), we constructed a unified county-level by selecting 15 indicators from five aspects—site condition, environmental physicochemical property, nutrient status field management—and used Delphi method to calculate membership degree indicators. Taking Jimo district Shandong Province, China, as case compared performance three machine learning models, including random forest, AdaBoost, support vector regression, evaluate using multi-temporal remote sensing data. The comprehensive index reveal spatial distribution CLQ. results showed that data model efficient reliable, had significant positive correlation with crop yield (r 0.44, p < 0.001). proportions high-, medium- poor-quality 27.43%, 59.37% 13.20%, respectively. western part study area better, while it worse eastern central parts. main limiting factors include irrigation capacity texture configuration. Accordingly, series targeted measures policies suggested, such strengthening construction farmland water conservancy facilities, deep tillage soil continuing construct well-facilitated farmland. This fast reliable evaluating CLQ, are helpful promote protection ensure food security.

Язык: Английский

The Development of a Coupled Soil Water Assessment Tool-MODFLOW Model for Studying the Impact of Irrigation on a Regional Water Cycle DOI Open Access

Fuli Liang,

Sheng Li,

Feilong Jie

и другие.

Water, Год журнала: 2023, Номер 15(20), С. 3542 - 3542

Опубликована: Окт. 11, 2023

In regions with arid and semi-arid climates, water consumption for agricultural irrigation is much higher than that used urban industrial purposes. Intensive plays a vital role in influencing the interaction between groundwater surface water. Understanding impact of on local hydrological cycle great significance maintaining regional food production -security. order to study cycle, present employed SWAT-MODFLOW coupled model analyze Weigan River Basin from 2002 2016. modeling process, detailed management measures were considered, including zoning crop types, amount different crops, methods, sources Before coupling, each was set, calibrated, validated separately. After pumps drainage units mapped SWAT automatic subbasins. Calibration validation studies showed could simulate river flow levels well. The simulation results soil included (1147.5 mm) (68.4 mm), as well precipitation snowmelt recharge (97.62 mm). balance influenced by leakage (75.6 lateral inflow surrounding areas (3.6 unsaturated zone infiltration (197.7 pumping (1275 When compared scenario without irrigation, runoff, infiltration, moisture content, evapotranspiration increased 7.9%, 3.2%, 4.1%, 2.3%, respectively. Irrigation activities content permeability, resulting more evaporation, runoff. This provides guidance evaluating drought systems future sustainable resource management.

Язык: Английский

Процитировано

6

Framework for Assessing Collective Irrigation Systems Resilience to Climate Change—The Maiorga Case Study DOI Creative Commons
Rita Esteves,

Maria João Calejo,

João Rolim

и другие.

Agronomy, Год журнала: 2023, Номер 13(3), С. 661 - 661

Опубликована: Фев. 24, 2023

In order to increase water productivity at the Collective Irrigation System (CIS) level it is crucial adapt existing irrigation infrastructure, enhancing intake source, as well its transport and delivery efficiency. Rehabilitation may involve structural changes thus, a large capital investment. This investment should be proportionate in climate resilience associated different rehabilitation alternatives. A methodology framework was developed evaluate CIS change considering The assessed components were: (i) crop production systems; (ii) on-farm (iii) project alternatives for conveyance distribution of from source farmer fields. applied Maiorga CIS, central Portugal, test performance assessing impacts on supply-demand balance proposed their resilience, representative concentration pathways, RCP4.5 RCP8.5, two time periods, 2041–2070 2071–2100. For each scenario, period, alternative, requirements (demand) stream flows (supply) were computed performed. Projected increases demand varied between 5.5% RCP4.5/2071–2100 35.7% RCP8.5/2071–2100. RCP4.5, 11% (2050) 9% (2080) reductions supply projected, while RCP8.5 reduction ranges 13% 30% (2080). determined that just one type without flow regularization with open channel farmer’s field, have proved unviable due low change.

Язык: Английский

Процитировано

4

Health variability based on SPI and estimating median and mean health indices in watersheds and townships of Kermanshah Province, Iran DOI
Seyed Hamidreza Sadeghi,

Reza Chamani,

Mahin Kalehhouei

и другие.

Environment Development and Sustainability, Год журнала: 2024, Номер unknown

Опубликована: Апрель 18, 2024

Язык: Английский

Процитировано

1

Evaluation of barley genotypes for drought adaptability: based on stress indices and comprehensive evaluation as criteria DOI Creative Commons

Ruijiao Song,

Shi PeiChun,

Xiang Li

и другие.

Frontiers in Plant Science, Год журнала: 2024, Номер 15

Опубликована: Авг. 26, 2024

The prevalence of drought events worldwide emphasizes the importance screening and cultivating drought-adapted crops. In this study, 206 germplasm resources were used as materials, dry weight target trait, two genotyping methods criteria to evaluate adaptability at seedling establishment stage. results showed a significant decrease in average tested (from 746.90 mg 285.40 mg) rich variation responses among each genotype (CV=61.14%). traditional evaluation method, resistance coefficient (DC), geometric mean productivity index (GMP), (MP), stress susceptibility (SSI), tolerance (STI), (TOL) also exhibited diversity genotypes (CV&gt;30%). However, these indices varying degrees explanation for under non-stress environments failed differentiate clearly. new four developed quantify barley production stability capacities. Compared indices, (SI) explained more comprehensively conditions ( R 2 = 0.98), while ideal (II) better 0.89). Furthermore, potential (PI) elasticity (EI) eliminated disparities clarified contribution capacity stress. Ultimately, through grading cluster analysis, effectively categorized, 11 identified suitable cultivation arid areas. Overall, comprehensive method based on newly surpasses crops serves vital tool identifying high-stability high-production capacities various environments, which is expected provide practical guidance planting breeding

Язык: Английский

Процитировано

1

County-Level Cultivated Land Quality Evaluation Using Multi-Temporal Remote Sensing and Machine Learning Models: From the Perspective of National Standard DOI Creative Commons

Dingding Duan,

Xinru Li, Yanghua Liu

и другие.

Remote Sensing, Год журнала: 2024, Номер 16(18), С. 3427 - 3427

Опубликована: Сен. 15, 2024

Scientific evaluation of cultivated land quality (CLQ) is necessary for promoting rational utilization and achieving one the Sustainable Development Goals (SDGs): Zero Hunger. However, CLQ system proposed in previous studies was diversified, methods were inefficient. In this study, based on China’s first national standard “Cultivated Land Quality Grade” (GB/T 33469-2016), we constructed a unified county-level by selecting 15 indicators from five aspects—site condition, environmental physicochemical property, nutrient status field management—and used Delphi method to calculate membership degree indicators. Taking Jimo district Shandong Province, China, as case compared performance three machine learning models, including random forest, AdaBoost, support vector regression, evaluate using multi-temporal remote sensing data. The comprehensive index reveal spatial distribution CLQ. results showed that data model efficient reliable, had significant positive correlation with crop yield (r 0.44, p < 0.001). proportions high-, medium- poor-quality 27.43%, 59.37% 13.20%, respectively. western part study area better, while it worse eastern central parts. main limiting factors include irrigation capacity texture configuration. Accordingly, series targeted measures policies suggested, such strengthening construction farmland water conservancy facilities, deep tillage soil continuing construct well-facilitated farmland. This fast reliable evaluating CLQ, are helpful promote protection ensure food security.

Язык: Английский

Процитировано

1