Assessing farmers’ irrigation practices under drought conditions in semi-arid area: Combining remote sensing data and agro-hydrological modeling

2021 ◽  
Author(s):  
Adnane Labbaci ◽  
Youssef Brouziyne ◽  
Jamal Hallam ◽  
Lahoussaine Bouchaou
Keyword(s):  
Hydrological Modeling ◽  
Irrigation Management ◽  
Condition Index ◽  
Irrigation Scheduling ◽  
Irrigated Agriculture ◽  
Landsat 8 ◽  
Soil Pressure ◽  
Swap Model ◽  
Sustainable Irrigation ◽  
Irrigation Practices

<p>Drought is a serious natural hazard with far-reaching impacts including modification of biodiversity and other ecosystem functions, economic disruption, and a threat to human livelihoods and health through food systems alteration. Climate models project robust increases in drought and dryness in the Mediterranean region because of changing climate conditions.  Despite the scarcity of water, irrigated agriculture plays a major socio-economic role in groundwater-dependent irrigated regions of Morocco. Strategic sectors such as citrus rely on irrigation to maintain or even increase production and citrus stakeholders put sustainable irrigation management at the top priorities. This study aims to assess seasonal drought severity in the Souss plain, the largest citrus’ growing area in Morocco, using VCI (Vegetation Condition Index), TCI (Temperature Condition Index), and VHI (Vegetation Health Index) based on Sentinel-2 and Landsat 8 data. We explored the benefits of using the Soil Water Atmosphere Plant (SWAP) agro-hydrological model to optimize irrigation water management of a citrus orchard. The SWAP model was applied over three growing seasons from 2016 to 2019 to optimize seasonal water supply based on different criteria (e.g., critical soil pressure head and allowable daily stress), particularly during the drought episodes. The VHI was estimated and classified into five classes: extreme, severe, moderate, mild, and no drought. Key outputs of the SWAP model show that the farmers’ irrigation practices did not compensate for the lack of rainfall in the spring, which led to long-term unavailable water during crop development. The SWAP predictive model determined the optimal amount of water and irrigation scheduling systems to make efficient use of while maintaining appropriate yields. The developed algorithm simulation uses the minimal sufficient seasonal amount of water. The designed approach helps prevent critical stress in citrus orchards together with sustainable water distribution in accordance with best agronomic practices.</p><p><strong>Keywords</strong>: Citrus, drought, water scarcity, sustainable irrigation management, VHI, VCI, TCI, SWAP, Souss plain</p>

scholarly journals High Plains Aquifer–State of Affairs of Irrigated Agriculture and Role of Irrigation in the Sustainability Paradigm

2020 ◽  
Vol 12 (9) ◽  
pp. 3714 ◽  
Author(s):  
Ali Ajaz ◽  
Sumon Datta ◽  
Scott Stoodley
Keyword(s):  
Irrigation Management ◽  
Irrigation Scheduling ◽  
Irrigated Agriculture ◽  
Groundwater Depletion ◽  
High Plains ◽  
High Plains Aquifer ◽  
Soil Moisture Sensors ◽  
Pumping Rates ◽  
Subsurface Drip ◽  
State Of Affairs

Groundwater depletion is a serious issue in the southern and central parts of the High Plains Aquifer (HPA), USA. A considerable imbalance exists between the recharge process and groundwater extractions in these areas, which threatens the long-term sustainability of the aquifer. Irrigated agriculture has a major share in the economy, and it requires high pumping rates in regions vulnerable to large groundwater level declines. A literature review has been conducted to understand the state of affairs of irrigated agriculture in the HPA, along with the dynamics of groundwater decline and recharge using statistical and remote-sensing based datasets. Also, three irrigation management and technology-based approaches have been discussed from the perspective of sustainability. The southern and central parts of the HPA consist mostly of non-renewable groundwater formations, and the natural water storage is prone to exhaustion. Moreover, the aforementioned regions have comparatively higher crop water requirement due to the climate, and irrigating crops in these regions puts stringent pressure on the aquifer. The upper threshold of irrigation application efficiency (IAE) is high in the HPA, and could reach up to 95%; however, considerable room for improvement in irrigation water management exists. In general, the practices of irrigation scheduling used in the HPA are conventional and a small proportion of growers use modern methods to decide about irrigation timing. Among numerous ways to promote sustainable groundwater use in the HPA, deficit irrigation, use of soil moisture sensors, and subsurface drip irrigation can be considered as potential ways to attain higher lifespans in susceptible parts of the aquifer.

scholarly journals Middleware to Operate Smart Photovoltaic Irrigation Systems in Real Time

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1508 ◽  
Author(s):  
Rafael González Perea ◽  
Aida Mérida García ◽  
Irene Fernández García ◽  
Emilio Camacho Poyato ◽  
Pilar Montesinos ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Real Time ◽  
Precision Agriculture ◽  
Renewable Energy Sources ◽  
Irrigation Management ◽  
Irrigation Scheduling ◽  
Real Field ◽  
Energy Sources ◽  
Irrigated Agriculture ◽  
Irrigation Season

Climate change, water scarcity and higher energy requirements and electric tariff compromises the continuity of the irrigated agriculture. Precision agriculture (PA) or renewable energy sources which are based on communication and information technologies and a large amount of data are key to ensuring this economic activity and guaranteeing food security at the global level. Several works which are based on the use of PA and renewable energy sources have been developed in order to optimize different variables of irrigated agriculture such as irrigation scheduling. However, the large amount of technologies and sensors that these models need to be implemented are still far from being easily accessible and usable by farmers. In this way, a middleware called Real time Smart Solar Irrigation Manager (RESSIM) has been developed in this work and implemented in MATLABTM with the aim to provide to farmers a user-friendly tool for the daily making decision process of irrigation scheduling using a smart photovoltaic irrigation management module. RESSIM middleware was successfully tested in a real field during a full irrigation season of olive trees using a real smart photovoltaic irrigation system.

scholarly journals Implementing Sustainable Irrigation in Water-Scarce Regions under the Impact of Climate Change

Agronomy ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 1120 ◽  
Author(s):  
Georgios Nikolaou ◽  
Damianos Neocleous ◽  
Anastasis Christou ◽  
Evangelini Kitta ◽  
Nikolaos Katsoulas
Keyword(s):  
Climate Change ◽  
Water Scarcity ◽  
Water Productivity ◽  
Irrigation Management ◽  
Irrigated Agriculture ◽  
Cultivation Systems ◽  
Protected Cultivation ◽  
Water Scarce ◽  
Sustainable Irrigation ◽  
The Impact

The sustainability of irrigated agriculture is threatening due to adverse climate change, given future projections that every one in four people on Earth might be suffering from extreme water scarcity by the year 2025. Pressurized irrigation systems and appropriate irrigation schedules can increase water productivity (i.e., product yield per unit volume of water consumed by the crop) and reduce the evaporative or system loss of water as opposed to traditional surface irrigation methods. However, in water-scarce countries, irrigation management frequently becomes a complex task. Deficit irrigation and the use of non-conventional water resources (e.g., wastewater, brackish groundwater) has been adopted in many cases as part of a climate change mitigation measures to tackle the water poverty issue. Protected cultivation systems such as greenhouses or screenhouses equipped with artificial intelligence systems present another sustainable option for improving water productivity and may help to alleviate water scarcity in these countries. This article presents a comprehensive review of the literature, which deals with sustainable irrigation for open-field and protected cultivation systems under the impact of climatic change in vulnerable areas, including the Mediterranean region.

scholarly journals Performance Assessment of Five Different Soil Moisture Sensors under Irrigated Field Conditions in Oklahoma

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3786 ◽  
Author(s):  
Sumon Datta ◽  
Saleh Taghvaeian ◽  
Tyson Ochsner ◽  
Daniel Moriasi ◽  
Prasanna Gowda ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Cropping Systems ◽  
Irrigation Management ◽  
Clay Content ◽  
Field Capacity ◽  
Irrigation Scheduling ◽  
Irrigated Agriculture ◽  
Undisturbed Soil ◽  
Soil Moisture Sensors ◽  
Rosetta Model

Meeting the ever-increasing global food, feed, and fiber demands while conserving the quantity and quality of limited agricultural water resources and maintaining the sustainability of irrigated agriculture requires optimizing irrigation management using advanced technologies such as soil moisture sensors. In this study, the performance of five different soil moisture sensors was evaluated for their accuracy in two irrigated cropping systems, one each in central and southwest Oklahoma, with variable levels of soil salinity and clay content. With factory calibrations, three of the sensors had sufficient accuracies at the site with lower levels of salinity and clay, while none of them performed satisfactorily at the site with higher levels of salinity and clay. The study also investigated the performance of different approaches (laboratory, sensor-based, and the Rosetta model) to determine soil moisture thresholds required for irrigation scheduling, i.e., field capacity (FC) and wilting point (WP). The estimated FC and WP by the Rosetta model were closest to the laboratory-measured data using undisturbed soil cores, regardless of the type and number of input parameters used in the Rosetta model. The sensor-based method of ranking the readings resulted in overestimation of FC and WP. Finally, soil moisture depletion, a critical parameter in effective irrigation scheduling, was calculated by combining sensor readings and FC estimates. Ranking-based FC resulted in overestimation of soil moisture depletion, even for accurate sensors at the site with lower levels of salinity and clay.

scholarly journals Towards Monitoring Waterlogging with Remote Sensing for Sustainable Irrigated Agriculture

2021 ◽  
Vol 13 (15) ◽  
pp. 2929
Author(s):  
Nadja den Besten ◽  
Susan Steele-Dunne ◽  
Richard de Jeu ◽  
Pieter van der Zaag
Keyword(s):  
Remote Sensing ◽  
Spatial Information ◽  
Stomatal Closure ◽  
Irrigation Management ◽  
Ground Effect ◽  
Crop Productivity ◽  
Irrigation Scheduling ◽  
Irrigated Agriculture ◽  
Water Deficit Stress ◽  
Ancillary Data

Waterlogging is an increasingly important issue in irrigated agriculture that has a detrimental impact on crop productivity. The above-ground effect of waterlogging on crops is hard to distinguish from water deficit stress with remote sensing, as responses such as stomatal closure and leaf wilting occur in both situations. Currently, waterlogging as a source of crop stress is not considered in remote sensing-based evaporation algorithms and this may therefore lead to erroneous interpretation for irrigation scheduling. Monitoring waterlogging can improve evaporation models to assist irrigation management. In addition, frequent spatial information on waterlogging will provide agriculturalists information on land trafficability, assist drainage design, and crop choice. This article provides a scientific perspective on the topic of waterlogging by consulting literature in the disciplines of agronomy, hydrology, and remote sensing. We find the solution to monitor waterlogging lies in a multi-sensor approach. Future scientific routes should focus on monitoring waterlogging by combining remote sensing and ancillary data. Here, drainage parameters deduced from high spatial resolution Digital Elevation Models (DEMs) can play a crucial role. The proposed approaches may provide a solution to monitor and prevent waterlogging in irrigated agriculture.

scholarly journals A Decade of Unmanned Aerial Systems in Irrigated Agriculture in the Western U.S.

2020 ◽  
Vol 36 (4) ◽  
pp. 423-436 ◽  
Author(s):  
José Luis Chávez ◽  
Alfonso F Torres-Rua ◽  
Wayne E. Woldt ◽  
Huihui Zhang ◽  
Christopher C Robertson ◽  
...  
Keyword(s):  
Soil Water ◽  
Irrigation Management ◽  
The United States ◽  
Irrigation Scheduling ◽  
Irrigated Agriculture ◽  
Unmanned Aerial Systems ◽  
Multi Scale ◽  
Processing Software ◽  
Aerial Systems ◽  
Precision Irrigation

Highlights Unmanned aerial systems (UAS) are able to provide data for precision irrigation management. Improvements are needed regarding UAS platforms, sensors, processing software, and regulations. Integration of multi-scale imagery into scientific irrigation scheduling tools are needed for technology adoption. Abstract . Several research institutes, laboratories, academic programs, and service companies around the United States have been developing programs to utilize small unmanned aerial systems (sUAS) as an instrument to improve the efficiency of in-field water and agronomical management. This article describes a decade of efforts on research and development efforts focused on UAS technologies and methodologies developed for irrigation management, including the evolution of aircraft and sensors in contrast to data from satellites. Federal Aviation Administration (FAA) regulations for UAS operation in agriculture have been synthesized along with proposed modifications to enhance UAS contributions to irrigated agriculture. Although it is feasible to use sUAS technology to produce maps of actual crop coefficients, actual crop evapotranspiration, and soil water deficits, for irrigation management, the technology and regulations need to evolve further to facilitate a successful wide adoption and application. Improvements and standards are needed in terms of cameras’ spectral (bands) ranges, radiometric resolutions and associated calibrations, fuel/power technology for longer missions, better imagery processing software, and easier FAA approval of higher altitudes flight missions among other issues. Furthermore, the sUAS technology would play a larger role in irrigated agriculture when integrating multi-scale data (sUAS, ground-based or proximal, satellite) and soil water sensors is addressed, including the need for advances on processing large amounts of data from multiple and different sources, and integration into scientific irrigation scheduling (SIS) systems for convenience of decision making. Desirable technological innovations, and features of the next generation of UAS platforms, sensors, software, and methods for irrigated agriculture, are discussed. Keywords: Agricultural water management, Irrigation prescription mapping, Irrigation scheduling, Precision irrigation, Remote sensing, Sensors, Spatial crop evaOotranspiration, Unmanned aerial systems.

Citrus Irrigation Management

EDIS ◽  
2017 ◽  
Vol 2017 (5) ◽  
Author(s):  
Davie Mayeso Kadyampakeni ◽  
Kelly T. Morgan ◽  
Mongi Zekri ◽  
Rhuanito Ferrarezi ◽  
Arnold Schumann ◽  
...  
Keyword(s):  
Water Stress ◽  
Physiological Activity ◽  
Irrigation Management ◽  
Fruit Size ◽  
Irrigation Scheduling ◽  
Leaf Expansion ◽  
Tree Canopy ◽  
Limiting Factor ◽  
Irrigation Frequency ◽  
Citrus Production

Water is a limiting factor in Florida citrus production during the majority of the year because of the low water holding capacity of sandy soils resulting from low clay and the non-uniform distribution of the rainfall. In Florida, the major portion of rainfall comes in June through September. However, rainfall is scarce during the dry period from February through May, which coincides with the critical stages of bloom, leaf expansion, fruit set, and fruit enlargement. Irrigation is practiced to provide water when rainfall is not sufficient or timely to meet water needs. Proper irrigation scheduling is the application of water to crops only when needed and only in the amounts needed; that is, determining when to irrigate and how much water to apply. With proper irrigation scheduling, yield will not be limited by water stress. With citrus greening (HLB), irrigation scheduling is becoming more important and critical and growers cannot afford water stress or water excess. Any degree of water stress or imbalance can produce a deleterious change in physiological activity of growth and production of citrus trees.  The number of fruit, fruit size, and tree canopy are reduced and premature fruit drop is increased with water stress.  Extension growth in shoots and roots and leaf expansion are all negatively impacted by water stress. Other benefits of proper irrigation scheduling include reduced loss of nutrients from leaching as a result of excess water applications and reduced pollution of groundwater or surface waters from the leaching of nutrients. Recent studies have shown that for HLB-affected trees, irrigation frequency should increase and irrigation amounts should decrease to minimize water stress from drought stress or water excess, while ensuring optimal water availability in the rootzone at all times.

scholarly journals Irrigation Scheduling with Soil Gas Diffusivity as a Decision Tool to Mitigate N2O Emissions from a Urine-Affected Pasture

Agriculture ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 443
Author(s):  
Camille Rousset ◽  
Timothy J. Clough ◽  
Peter R. Grace ◽  
David W. Rowlings ◽  
Clemens Scheer
Keyword(s):  
Irrigation Management ◽  
Irrigation Treatment ◽  
Irrigation Scheduling ◽  
Soil Gas ◽  
N2o Emissions ◽  
Irrigation Frequency ◽  
Water Demands ◽  
Gas Diffusivity ◽  
Matter Production ◽  
Access To Water

Pastures require year-round access to water and in some locations rely on irrigation during dry periods. Currently, there is a dearth of knowledge about the potential for using irrigation to mitigate N2O emissions. This study aimed to mitigate N2O losses from intensely managed pastures by adjusting irrigation frequency using soil gas diffusivity (Dp/Do) thresholds. Two irrigation regimes were compared; a standard irrigation treatment based on farmer practice (15 mm applied every 3 days) versus an optimised irrigation treatment where irrigation was applied when soil Dp/Do was ≈0.033 (equivalent to 50% of plant available water). Cow urine was applied at a rate of 700 kg N ha−1 to simulate a ruminant urine deposition event. In addition to N2O fluxes, soil moisture content was monitored hourly, Dp/Do was modelled, and pasture dry matter production was measured. Standard irrigation practices resulted in higher (p = 0.09) cumulative N2O emissions than the optimised irrigation treatment. Pasture growth rates under treatments did not differ. Denitrification during re-wetting events (irrigation and rain) contributed to soil N2O emissions. These results warrant further modelling of irrigation management as a mitigation option for N2O emissions from pasture soils, based on Dp/Do thresholds, rainfall, plant water demands and evapotranspiration.

scholarly journals Combined simulation and optimization framework for irrigation scheduling in agriculture fields

2021 ◽  
Author(s):  
Mireia Fontanet ◽  
Daniel Fernàndez-Garcia ◽  
Gema Rodrigo ◽  
Francesc Ferrer ◽  
Josep Maria Villar
Keyword(s):  
Crop Yields ◽  
Root Zone ◽  
Growing Season ◽  
Irrigation Scheduling ◽  
Irrigated Agriculture ◽  
Traditional Methods ◽  
Simulation And Optimization ◽  
Optimization Framework ◽  
Net Margin ◽  
Combined Simulation

AbstractIn the context of growing evidence of climate change and the fact that agriculture uses about 70% of all the water available for irrigation in semi-arid areas, there is an increasing probability of water scarcity scenarios. Water irrigation optimization is, therefore, one of the main goals of researchers and stakeholders involved in irrigated agriculture. Irrigation scheduling is often conducted based on simple water requirement calculations without accounting for the strong link between water movement in the root zone, soil–water–crop productivity and irrigation expenses. In this work, we present a combined simulation and optimization framework aimed at estimating irrigation parameters that maximize the crop net margin. The simulation component couples the movement of water in a variably saturated porous media driven by irrigation with crop water uptake and crop yields. The optimization component assures maximum gain with minimum cost of crop production during a growing season. An application of the method demonstrates that an optimal solution exists and substantially differs from traditional methods. In contrast to traditional methods, results show that the optimal irrigation scheduling solution prevents water logging and provides a more constant value of water content during the entire growing season within the root zone. As a result, in this case, the crop net margin cost exhibits a substantial increase with respect to the traditional method. The optimal irrigation scheduling solution is also shown to strongly depend on the particular soil hydraulic properties of the given field site.

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