Retrieving the irrigation actually applied at district scale: Assimilating high-resolution Sentinel-1-derived soil moisture data into a FAO-56-based model

Agricultural Water Management, Год журнала: 2024, Номер 293, С. 108704 - 108704

Опубликована: Фев. 2, 2024

Irrigation is the most water consuming activity in world. Knowing timing and amount of irrigation that actually applied therefore fundamental for managers. However, this information rarely available at all scales subject to large uncertainties due wide variety existing agricultural practices associated regimes (full irrigation, deficit or over-irrigation). To fill gap, we propose a two-step approach based on 15 m resolution Sentinel-1 (S1) surface soil moisture (SSM) data retrieve actual weekly scale over an entire district. In first step, S1-derived SSM assimilated into FAO-56-based crop balance model (SAMIR) each type both (Idose) threshold (SMthreshold) which triggered. do this, particle filter method implemented, with particles reset month provide time-varying SMthreshold Idose. second retrieved Idose values are used as input SAMIR estimate its uncertainty. The assimilation (SSM-ASSIM) tested 8000 hectare Algerri-Balaguer district located northeastern Spain, where situ integrating whole during 2019. For evaluation, performance SSM-ASSIM compared default FAO-56 module (called FAO56-DEF), sets critical value systematically fills reservoir event. 2019, observed annual 687 mm, (FAO56-DEF) shows root mean square deviation between 6.7 (8.8) mm week-1, bias +0.3 (−1.4) Pearson correlation coefficient 0.88 (0.78). great potential retrieving use extended areas any regime, including over-irrigation.

Язык: Английский

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Optimal allocation of water and land resources considering crop water demand process from the perspective of water-carbon-economy nexus

Journal of Hydrology, Год журнала: 2025, Номер unknown, С. 132831 - 132831

Опубликована: Фев. 1, 2025

Язык: Английский

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A crop-specific dynamic irrigation scheme in a regional land surface-hydrologic modeling framework for improving human water-use estimation and irrigation impact assessment

Journal of Hydrology, Год журнала: 2025, Номер unknown, С. 133322 - 133322

Опубликована: Апрель 1, 2025

Язык: Английский

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Methodologies for Water Accounting at the Collective Irrigation System Scale Aiming at Optimizing Water Productivity

Agronomy, Год журнала: 2023, Номер 13(7), С. 1938 - 1938

Опубликована: Июль 22, 2023

To improve water use efficiency and productivity, particularly in irrigated areas, reliable accounting methodologies are essential, as they provide information on the status trends irrigation availability/supply consumption/demand. At collective system level, (IWA) relies quantification of fluxes from diversion point to plants, at both conveyance distribution network field level. Direct measurement is most accurate method for IWA, but cases, there limited metering despite increasing pressure groundwater surface resources, hindering procedures. However, various methodologies, tools, indicators have been developed estimate IWA components, depending scale level detail being considered. Another setback wide implementation vast terminology used literature different scales levels application. Thus, main objectives this review, which focuses services, (i) demonstrate importance by showing its relationship with productivity efficiency; (ii) clarify concepts related IWA; (iii) an overview approaches obtain data demand side, on-farm systems. From it can be concluded that a need provides common base all stakeholders. Future work could include development user-friendly tools reduce bridge between technology available collect process components effective

Язык: Английский

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Irrigation Scheduling for Maize under Different Hydrological Years in Heilongjiang Province, China

Plants, Год журнала: 2023, Номер 12(8), С. 1676 - 1676

Опубликована: Апрель 17, 2023

Appropriate irrigation schedules could minimize the existing imbalance between agricultural water supply and crop requirements (ETc), which is severely impacted by climate change. In this study, different hydrological years (a wet year, normal dry an extremely year) in Heilongjiang Province were calculated frequency methods. Then, single coefficient method was used to calculate maize ETc, based on daily meteorological data of 26 stations from 1960 2020. Afterward, CROPWAT model effective precipitation (Pe) requirement (Ir), formulate under years. The results showed that ETc Ir decreased first then increased west east. Pe surplus deficit index east Province. Meanwhile, average values 171.14 mm, 232.79 279.08 334.47 mm respectively. divided into four zones according Last, quotas for year 0~180 20~240 60~300 80~430 This study provides reliable support practices Province, China.

Язык: Английский

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Estimating multi-scale irrigation amounts using multi-resolution soil moisture data: A data-driven approach using PrISM

Agricultural Water Management, Год журнала: 2023, Номер 290, С. 108594 - 108594

Опубликована: Ноя. 22, 2023

Irrigated agriculture is the primary driver of freshwater use and continuously expanding. Precise knowledge irrigation amounts critical for optimizing water management, especially in semi-arid regions where a limited resource. This study proposed to adapt PrISM (Precipitation inferred from Soil Moisture) methodology detect estimate events soil moisture remotely sensed data. was originally conceived correct precipitation products, assimilating Moisture (SM) observations into an antecedent index (API) formula, using particle filter scheme. novel application uses initial SM instances excess (not caused by precipitation) estimates amount irrigation, along with its uncertainty. newly approach does not require extensive calibration adaptable different spatial temporal scales. The objective this analyze performance estimation compare it current state-of-the-art approaches. To develop test methodology, synthetic conducted various noise levels simulate uncertainties resolutions. results indicated that high resolution (less than 3 days) crucial avoid underestimating due missing events. However, including constraint on frequency events, deduced system used at field level, could overcome limitation low significantly reduce underestimation amounts. Subsequently, developed applied actual satellite products scales (1 km 100 m) over same area. Validation performed situ data district level Algerri-Balaguer Catalunya, Spain, were available years. validation resulted total Pearson's correlation coefficient (r) 0.80 root mean square error (rmse) 7.19 mm∕week years 2017 2021. Additional Segarra-Garrigues profiles monitored. yielded bi-weekly r 0.81 rmse −9.34 mm∕14-days Overall, suggested can effectively remote sensing data, has potential be large scale without requiring or site-specific knowledge.

Язык: Английский

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PrISM at Operational Scale: Monitoring Irrigation District Water Use during Droughts

Remote Sensing, Год журнала: 2024, Номер 16(7), С. 1116 - 1116

Опубликована: Март 22, 2024

Efficient water management strategies are of utmost importance in drought-prone regions, given the fundamental role irrigation plays avoiding yield losses and food shortages. Traditional methodologies for estimating amounts face limitations terms overall precision operational scalability. This study proposes to estimate from soil moisture (SM) data by adapting PrISM (Precipitation Inferred Soil Moisture) methodology. The assimilates SM into a simple Antecedent Precipitation Index (API) model using particle filter approach, which allows creation estimation events. methodology is applied semi-arid region Ebro basin, located north-east Spain (Catalonia), 2016 2023. Multi-year drought, started 2020, particularly affected starting spring 2023, led significant reductions district allocations some areas region. demonstrates that approach can correctly identify where restrictions were adopted monitor usage with good performances reliable results. When compared situ 8 consecutive years, showed person’s correlation between 0.58 0.76 cumulative weekly root mean squared error (rmse) 7 11 mm. Additionally, was three districts different levels modernization, due predominant systems: flood, sprinkler, drip. analysis underlined strengths depending on techniques monitored. has irrigated sprinkler flood systems, while difficulties present over drip areas, very localized limited could not be detected observations.

Язык: Английский

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How to account for irrigation withdrawals in a watershed model

Hydrology and earth system sciences, Год журнала: 2024, Номер 28(1), С. 49 - 64

Опубликована: Янв. 3, 2024

Abstract. In agricultural areas, the downstream flow can be highly influenced by human activities during low-flow periods, especially dam releases and irrigation withdrawals. Irrigation is indeed major use of freshwater in world. This study aims at precisely taking these factors into account a watershed model. The Soil Water Assessment Tool (SWAT+) agro-hydrological model was chosen for its capacity to crop dynamics management. Two different models were compared terms their ability estimate water needs actual irrigation. first based on air temperature as main determining factor growth, whereas second relies high-resolution data from Sentinel-2 satellite monitor plant growth. Both are applied plot scale 800 km2 that characterized Results show including remote sensing leads more realistic modeled emergence dates summer crops. However, both approaches have proven able reproduce evolution daily withdrawals throughout year. As result, allowed us simulate with good accuracy, periods.

Язык: Английский

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Assessing irrigation impact on water quality conditions: A case study in the River Noguera Ribagorçana (NE Spain)

Agricultural Water Management, Год журнала: 2024, Номер 296, С. 108809 - 108809

Опубликована: Апрель 3, 2024

The need to feed an increasing population while limiting the environmental impact of agriculture is currently one greatest challenges relating food chain. One key factors involved in doing this irrigation, which has a downstream that can be minimised if nutrient and water management are efficiently undertaken. objective study was determine irrigation improvements done at field scale modern irrigated areas reduce its return flow impact. conducted Noguera Ribagorçana River basin, NE Spain, where almost 6000 ha land were brought into from 2000 2009. We based our on quality dataset, measured four different sites along 29 km2 stretch river over period 20 years. Our results show increase nitrate (from 1.7 mg·L−1 10.5 mg·L−1) salt concentrations (electrical conductivity 297 675 µS·m−1) course compared most upstream monitoring site. That exclusively associated with flows newly area. highest found during non-irrigation season corresponds local rainy season. To impact, better required. Autumn leaching could lowered by reducing volume applied final weeks crop cycles order allow soil retain received rainfall. deal issue, we propose methodology moisture end In way, ecosystems located further would reduced yields productivity area maintained.

Язык: Английский

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An integrated approach for multi-year irrigation benchmarking using satellites, surveys and on-farm measured data

Agricultural Water Management, Год журнала: 2024, Номер 302, С. 108962 - 108962

Опубликована: Июль 28, 2024

Benchmarking is an effective management tool to improve irrigation performance through comparison with other units; however, its application often limited by the data available support analysis. This study developed a benchmarking system that reduces reliance on local using satellite-based estimates and quantifies uncertainty due alternative sources. We benchmarked relative supply (RISsatellite) (i.e. ratio of crop net demand) for more than 300 farms growing corn/maize, cotton rice crops in Coleambally Irrigation Area Australia from 2011 2019. Three key inputs RISsatellite, namely irrigated cropping area (ICA), start end dates season (SOS/EOS) coefficient (Kc), were derived Landsat time series data. To understand benchmarking, RISsatellite was compared RISnon-satellite non-satellite datasets. The variation RIS respect input sources reliability also quantified. highly variable across any particular year, over-irrigation (RISsatellite>1) common. In addition, each farm tended have consistent ranking years, indicating role farmers' practice RIS. ICA different datasets contributed most random RIS, while presented reliable median absolute percentage error 5 %, which half survey-based ICA. conclude our overcoming limitations likely be systems survey can improved monitoring this district transferable areas information available.

Язык: Английский

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