Agricultural Water Management

Journal: Agricultural Water Management

Abbreviation

Agric. water manag.

Publisher

Elsevier

ISSN

0378-3774
1873-2283

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Publications 1 - 10 of 13

Making water productivity operational
Bluemling, Bettina; Yang, Hong; Pahl-Wostl, Claudia (2007)
Agricultural Water Management
Agricultural intensification can no longer ignore water conservation – A systemic modelling approach to the case of tomato producers in Morocco
Benabderrazik, Kenza; Kopainsky, Birgit; Tazi, Lina; et al. (2021)
Agricultural Water Management
Agricultural-food production systems are facing the challenging task to provide food and socio-economic welfare while preserving natural resources in the long-term. In Morocco, the Green Moroccan Plan steered the promotion of groundwater-based drip irrigation. Over the last decade, the Plan encouraged producers to shift to cash crop production. This is how tomato became a main agri-food export commodity mostly produced in greenhouses in the Souss-Massa region and produced intensively in open-fields for local demand in the Northern part of the country. However, water resources are expected to become particularly scarce over the next decades, increasing the vulnerabilities of tomato farmers in face of unforeseen changes and shocks. The main purpose of this study is to show a) how global and local tomato value chains respond to irrigation schemes and b) what the environmental consequences are. By means of a system dynamics model, and a survey conducted among a sample of 244 producers, we describe and outline the major interactions between agricultural, ecological and socio-economic dimensions of the tomato production systems. The results of the model simulations highlight how overexploitation of groundwater tables negatively affects crop production and farmers’ welfare. The model shows that in the near future, water scarcity will have long-lasting consequences on the producers, such as reduced productivity and losses in cash flow. Our model results highlight that measures need to be taken in the coming years in order to prevent the predicted irremediable water shortage in 2030. We conclude that the current groundwater management will, in the long-term, lead to irreversible groundwater depletion which will enhance already existing inequalities between the two types of producers. Urgent actions have to be taken in order to sustainably manage water while supporting farmers in the long-term.
Dendrometer as a water stress indicator for apple trees
Waldburger, Thainná; Walter, Achim; Cockburn, Marianne; et al. (2025)
Agricultural Water Management
The use of dendrometers to measure the stem diameter (SD) of trees provides information about their actual water stress levels. The Scholander chamber is currently the gold standard for measuring stem water potential and thus for quantifying the water status of trees, despite being a laborious method, especially for apple trees. The aim of this study was to analyze dendrometer data to assess the water stress in drip-irrigated 'Gala' apple trees (Malus x domestica Borkh). A trial was performed in Grens, Switzerland, during the 2022 season. Three different irrigation treatments were applied (T1 = 100 % soil moisture-based irrigation, T2 = 30 % less than T1, and T3 = without irrigation). The irrigation treatments notably affected fruit production. Trees in T3 exhibited a significant yield loss of 26 %, whereas treatment T2 yielded 13 % less than the reference treatment T1. Although daily changes in the SD correlated with vapor pressure deficit (VPD) (r2 = 0.84), limiting the amount of water available to the plant disrupted this correlation (r2 = 0.27), with stem water potentials dropping by -1.7 MPa and a noticeable shift in stem movement (shrinking/expanding). Finally, we developed a suitable linear regression model that compared the shift in slope and offset of regression lines fitted for SD and VPD during initial non-stressed conditions (reference) with those under stressed conditions in order to estimate stem water potential. By integrating dendrometer parameters with VPD, the model effectively predicted stem water potential values. These findings suggest that dendrometers are effective indicators of water stress in apple trees. Further refinement of the model in field conditions could enhance the use of these sensors for irrigation management, providing more precise guidance on the timing and amount of water applied.
Effects of pre-anthesis drought, nitrogen fertilizer rate, and variety on grain yield, yield components, and harvest index of tropical maize
Moser, Samuel B.; Feil, Boy; Jampatong, Sansern; et al. (2006)
Agricultural Water Management
Comparison of hydrological and vegetation remote sensing datasets as proxies for rainfed maize yield in Malawi
Anghileri, Daniela; Bozzini, Veronica; Molnar, Peter; et al. (2022)
Agricultural Water Management
Weather Index-based Insurances (WIIs) have emerged as a promising risk coping mechanism to compensate for weather-induced damage to rainfed agriculture. Remote sensing may provide cost-effective information capable of discriminating the weather spatial variability thus reducing the spatial basis risk, i.e., the mismatch between the weather-based index triggering the insurance payout and the actual damage experienced by the farmers, which is often one of the causes hindering the wide implementation of WIIs. In this work we assess which indices based on remote sensing datasets are the best proxy indicators for rainfed maize yield in Malawi. We analyse the spatial (district scale) and temporal (monthly) correlations of historical maize yield data and several remote sensing datasets including the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset, the ESA CCI Soil Moisture combined dataset (version 4.2), the Evaporative Stress Index (ESI) from the Atmosphere-Land Exchange Inversion model (ALEXI), the MOD13Q1 Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). With respect to the previous literature, this work exploits a historical crop yield dataset at the sub-national level which allows us to analyse the correlation of the hydro-meteorological and vegetation variables at a higher spatial resolution than what is commonly done (i.e., at the national level using FAO national yield statistics) and ultimately explore the issues related to WII spatial basis risk. Results show that the correlations between crop yield and satellite datasets show high spatial and temporal variability, making it difficult to identify a unique WII index that is at the same time simple and effective for the entire country. Precipitation, particularly the standardized March precipitation anomaly, has the highest correlations with maize yield (with Pearson correlation values higher than 0.55), in Central and South Malawi. Soil moisture and NDVI do not add much value to precipitation in anticipating historical maize yield at the district scale. From a methodological perspective, our work shows that WII indexes are best identified by: i) considering datasets with fine spatial resolution, whenever possible; ii) accounting for the vulnerability of the different crop growing stages to water-stress; iii) distinguishing between water scarce and water abundant events.
Aquifer recharge estimation and its origins in intensive irrigated agriculture
Polo Molina , María José; Soliva , Lucas; Alcaraz , Mar; et al. (2025)
Agricultural Water Management
Intensive agriculture often occurs in water-scarce regions, relying on diverse water sources such as imported non-local water–water transfers, treated wastewater, desalination, and groundwater. Efficient water use is crucial to minimize aquifer losses and fertilizer leachates. Understanding the contributions of these sources to both irrigation and aquifer recharge is essential due to differences in volume, quality, and cost. This study presents a methodology combining: i) a spatially distributed approach using the water-table-fluctuation (WTF) method to estimate total aquifer recharge and ii) an experimental assessment of precipitation and irrigation water contributions via mixing calculations. The method is validated through unsaturated flow and stable water isotope transport modeling, applied to the Campo de Cartagena aquifer (SE Spain). Findings reveal that irrigated area contributes ∼ 30 % of total recharge — ∼ 26 % in wet years and ∼ 41 % in dry years— primarily from annual row crops. Groundwater supplies 49 ± 13 % of crop water needs. Recharge contributions from different sources within the irrigated area include precipitation (16 %), Water Transfer (29 %), shallow aquifer (26 %), and the underlying confined aquifer (29 %). These results underscore the importance of quantifying individual water source contributions to irrigation and aquifer recharge, especially if the aquifer is one more water source, for improved water resource management at the catchment scale.
Effects of timing and duration of brackish irrigation water on fruit yield and quality of late summer melons
Bustan, Amnon; Cohen, Shabtai; Malach, Yoel De; et al. (2005)
Agricultural Water Management
Modeling wheat yield and crop water productivity in Iran
Faramarzi, Monireh; Yang, Hong; Schulin, R.; et al. (2010)
Agricultural Water Management
Automated irrigation of apple trees based on dendrometer sensors
Waldburger, Thainná; Anken, Thomas; Cockburn, Marianne; et al. (2025)
Agricultural Water Management
This study evaluates the efficiency of an automated irrigation system using dendrometer sensors in apple orchards and compares it to a standard grower commercial irrigation approach based on soil moisture sensors. An algorithm was developed to balance daily stem shrinkage (water loss) and expansion (water uptake), aiming for a stable dendrometer signal. The dendrometer-based irrigation system (DENDRO) significantly reduced water use-by 38 % in 2022 and more than 45 % in 2023-while maintaining yields similar to those of the soil moisture-based system (SOIL). The DENDRO responded quite well to plant water stress, as indicated by stem water potential (WP). Although the tested algorithm proved to be efficient, the results also indicated the potential for optimization. One example is shortening the averaging period used to calculate stem recovery ($R_∆$). The SOIL method was effective in fruit production but proved to be less efficient in reflecting water needs. Alternative approaches, including FAO-based irrigation (FAO) and a linear regression model combining dendrometer parameters and climatic data (MODEL), were also assessed. The FAO method tended to overestimate water requirements, while the MODEL method showed promise for dynamic irrigation adjustment based on climatic conditions and dendrometer values. Overall, the findings highlight the advantage of integrating plantbased sensors, such as dendrometers, for more precise irrigation management in orchard systems, leading to more sustainable water use without compromising crop yield.
Effects of agricultural management on measurements, prediction, and partitioning of evapotranspiration in irrigated grasslands
Graham, Scott L.; Kochendorfer, John; McMillan, Andrew M.S.; et al. (2016)
Agricultural Water Management

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Journal: Agricultural Water Management

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