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Sustainable Irrigation Strategies for Improving Crop Water Productivity

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".

Deadline for manuscript submissions: closed (31 July 2021) | Viewed by 44082

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Special Issue Editor

Dr. Koffi Djaman

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Department of Plant and Environmental Science, New Mexico State University, Las Cruces, NM 88003, USA
Interests: cropping systems; irrigation technology; water conservation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The world’s population is growing with an increasing demand for food and fiber. However, freshwater resources for agriculture are decreasing due to climate change, with more pronounced extreme events like floods and drought. Improper irrigation management may also cause agricultural land salinization, jeopardizing crop production mostly in some coastal river deltas. For sustainable irrigated agriculture, it is necessary to produce more food and fiber with the unit quantity of water to be able to meet food and fiber demands through precision irrigation strategies, soil moisture sensor-based irrigation scheduling, crop choice to meet the available water. This Special Issue calls for contributions, but not limited to, the following topics: irrigation strategies for improving crop water productivity while minimizing negative impact on the environment, irrigation water management and modeling, crop evapotranspiration measurement and estimation/modeling, advanced irrigation technologies for improving irrigation water use efficiency, precision irrigation, variable rate irrigation.

Dr. Koffi Djaman
Guest Editor

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Keywords

Deficit irrigation strategies
Partial root-zone drying irrigation
Variable-rate irrigation
Precision irrigation
Irrigation scheduling and management
Soil moisture sensors
Irrigation water use efficiency
Sustainable irrigation
Irrigation and environmental
Efficiency of the energy use in irrigation
Alternate wetting and drying
Crop water productivity
Crop evapotranspiration
Sustainable irrigation
Water use efficiency
Climate-smart agriculture

Published Papers (9 papers)

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Research

Jump to: Review

17 pages, 5966 KiB

Open AccessArticle

A Method to Estimate Surface Soil Moisture and Map the Irrigated Cropland Area Using Sentinel-1 and Sentinel-2 Data

by Saman Rabiei, Ehsan Jalilvand and Massoud Tajrishy

Sustainability 2021, 13(20), 11355; https://0-doi-org.brum.beds.ac.uk/10.3390/su132011355 - 14 Oct 2021

Cited by 10 | Viewed by 3224

Abstract

Considering variations in surface soil moisture (SSM) is essential in improving crop yield and irrigation scheduling. Today, most remotely sensed soil moisture products have difficulties in resolving irrigation signals at the plot scale. This study aims to use Sentinel-1 radar backscatter and Sentinel-2 multispectral imagery to estimate SSM at high spatial (10 m) and temporal resolution (at least 5 days) over an agricultural domain. Three supervised machine learning algorithms, multilayer perceptron (MLP), a convolutional neural network (CNN), and linear regression models, were trained to estimate changes in SSM based on the variation in surface reflectance and backscatter over five different crops. Results showed that CNN is the best algorithm as it understands spatial relations and better represents two-dimensional images. Estimated values for SSM were in agreement with in-situ measurements regardless of the crop type, with

R M S E = 0.0292 ({cm}^{3} / {cm}^{3})

and

R^{2} = 0.92

for the Sentinel-2 derived SSM and

R M S E = 0.0317 ({cm}^{3} / {cm}^{3})

and

R^{2} = 0.84

for the Sentinel-1 soil moisture data. Moreover, a time series of estimated SSM based on Sentinel-1 (SSM-S1), Sentinel-2 (SSM-S2), and SSM derived from SMAP-Sentinel1 was compared. The developed SSM data showed a significantly higher mean SSM state over irrigated agriculture relative to the rainfed cropland area during the irrigation season. The multiple comparisons (fisher LSD) were tested and found that these two groups are different (

p_{v a l u e} = 0.035

in 95% confidence interval). Therefore, by employing the maximum likelihood classification on the SSM data, we managed to map the irrigated agriculture. The overall accuracy of this unsupervised classification is 77%, with a kappa coefficient of 65%. Full article

(This article belongs to the Special Issue Sustainable Irrigation Strategies for Improving Crop Water Productivity)

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25 pages, 6463 KiB

Open AccessArticle

Dry Bean [Phaseolus vulgaris L.] Growth and Yield Response to Variable Irrigation in the Arid to Semi-Arid Climate

by Abhijit Rai, Vivek Sharma and Jim Heitholt

Sustainability 2020, 12(9), 3851; https://0-doi-org.brum.beds.ac.uk/10.3390/su12093851 - 08 May 2020

Cited by 15 | Viewed by 3173

Abstract

Understanding the crop growth and yield response to variable irrigation and the relationship between crop eco-physiological and morphological parameters is critical for identifying a balanced irrigation management strategy and developing decision support systems for early detection and information for on-ground decisions. Experiments were conducted to evaluate the effect of variable irrigation treatments on dry bean [Phaseolus vulgaris L.] growth traits (plant height, leaf area index, normalized difference vegetation index), seed yield (SY), and yield components (pods plant⁻¹, seeds pod⁻¹, 100-seed weight (SW), and pod harvest index (PHI)) and to develop empirical models between dry bean growth and environmental conditions, SY, and yield components. Five irrigation treatments i.e., FIT (full irrigation treatment), 125% FIT, 75% FIT, 50% FIT, and 25% FIT were investigated. Water deficit at the beginning of the crop growth [vegetative growth (V1-V2) stage], dramatically reduced dry bean growth and development and resulted in a significant reduction in SY. However, the degree to which vegetative growth and SY was reduced depends on the weather conditions. Reducing irrigation by 25% below FIT resulted in an average reduction of 30% in SY. This reduction in SY was significantly correlated with a decline in pods plant⁻¹ and SW. Moreover, the empirical models between growth traits and growing degree days (GDD) have a strong correlation, while growth traits and SY and yield components are moderately correlated. The data and empirical models presented in this research provide valuable information in predicting and estimating dry bean SY in-season and allow for corrective management decisions. Full article

(This article belongs to the Special Issue Sustainable Irrigation Strategies for Improving Crop Water Productivity)

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9 pages, 1295 KiB

Open AccessCommunication

Evidence of Arithmetical Uncertainty in Estimation of Light and Water Use Efficiency

by Meetpal S. Kukal and Suat Irmak

Sustainability 2020, 12(6), 2271; https://0-doi-org.brum.beds.ac.uk/10.3390/su12062271 - 14 Mar 2020

Cited by 4 | Viewed by 2958

Abstract

It was demonstrated that conventional resource use efficiency (RUE) estimation methodology is largely subject to arithmetic weakness. Extensive field research data on aboveground biomass (AGB), absorbed photosynthetically active radiation (APAR), and crop evapotranspiration (ET_c) in maize, soybean, sorghum, and winter wheat confirmed this methodological bias for light use efficiency (LUE) and water use efficiency (WUE) estimation. LUE and WUE were derived using cumulated (data aggregates across samplings) and independent (data increments across samplings) approaches. Use of cumulated data yielded strong-but-false correlation between AGB and APAR or ET_c, being a statistical artefact. RUE values from an independent approach were substantially lower than that from a cumulated approach with greater standard errors. Overall, a cumulated approach tends to oversimplify the complex interactions among carbon and resource coupling in agroecosystems, which is accurately represented when employing an independent approach instead. Full article

(This article belongs to the Special Issue Sustainable Irrigation Strategies for Improving Crop Water Productivity)

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26 pages, 5431 KiB

Open AccessArticle

Irrigation-Yield Production Functions and Irrigation Water Use Efficiency Response of Drought-Tolerant and Non-Drought-Tolerant Maize Hybrids under Different Irrigation Levels, Population Densities, and Environments

by Suat Irmak, Ali T. Mohammed, William Kranz, C.D. Yonts and Simon van Donk

Sustainability 2020, 12(1), 358; https://0-doi-org.brum.beds.ac.uk/10.3390/su12010358 - 02 Jan 2020

Cited by 7 | Viewed by 4041

Abstract

Irrigation-yield production functions (IYPFs), irrigation water use efficiency (IWUE), and grain production per unit of applied irrigation of non-drought-tolerant (NDT) and drought-tolerant (DT) maize (Zea mays L.) hybrids were quantified in four locations with different climates in Nebraska [Concord (sub-humid), Clay Center (transition zone between sub-humid and semi-arid); North Platte (semi-arid); and, Scottsbluff (semi-arid)] during three growing seasons (2010, 2011, and 2012) at three irrigation levels (fully-irrigated treatment (FIT), early cut-off (ECOT), and rainfed (RFT)) under two plant population densities (PPDs) (low-PPD; 59,300 plants ha⁻¹; and, high-PPD, 84,000 plants ha⁻¹). Overall, DT hybrids’ performance was superior to NDT hybrid at RFT, ECT, and FIT conditions, as confirmed by the yield response, IYPF and IWUE when all locations, years, and PPDs were averaged. The yield response to water was greater with the high-PPD than the low-PPD in most cases. The magnitude of the highest yields for DT hybrids ranged from 7.3 (low-PPD) to 8.5% (high-PPD) under RFT, 3.7 (low-PPD) to 9.6% (high-PPD) under ECOT, and 3.9% (high-PPD) under FIT higher than NDT hybrid. Relatively, DT hybrids can resist drought-stress conditions longer than NDT hybrid with fewer penalties in yield reduction and maintain comparable or even higher yield production at non-stress-water conditions. Full article

(This article belongs to the Special Issue Sustainable Irrigation Strategies for Improving Crop Water Productivity)

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19 pages, 2643 KiB

Open AccessArticle

Development and Application of a Performance and Operational Feasibility Guide to Facilitate Adoption of Soil Moisture Sensors

by Meetpal S. Kukal, Suat Irmak and Kiran Sharma

Sustainability 2020, 12(1), 321; https://0-doi-org.brum.beds.ac.uk/10.3390/su12010321 - 31 Dec 2019

Cited by 26 | Viewed by 5236

Abstract

Soil moisture sensors can be effective and promising decision-making tools for diverse applications and audiences, including agricultural managers, irrigation practitioners, and researchers. Nevertheless, there exists immense adoption potential in the United States, with only 1.2 in 10 farms nationally using soil moisture sensors to decide when to irrigate. This number is much lower in the global scale. Increased adoption is likely hindered by lack of scientific support in need assessment, selection, suitability and use of these sensors. Here, through extensive field research, we address the operational feasibility of soil moisture sensors, an aspect which has been overlooked in the past, and integrate it with their performance accuracy, in order to develop a quantitative framework to guide users in the selection of best-suited sensors for varying applications. These evaluations were conducted for nine commercially available sensors under silt loam and loamy sand soils in irrigated cropland and rainfed grassland for two different installation orientations [sensing component parallel (horizontal) and perpendicular (vertical) to the ground surface] typically used. All the sensors were assessed for their aptness in terms of cost, ease of operation, convenience of telemetry, and performance accuracy. Best sensors under each soil condition, sensor orientation, and user applications (research versus agricultural production) were identified. The step-by-step guide presented here will serve as an unprecedented and holistic adoption-assisting resource and can be extended to other sensors as well. Full article

(This article belongs to the Special Issue Sustainable Irrigation Strategies for Improving Crop Water Productivity)

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15 pages, 1158 KiB

Open AccessArticle

FAO CROPWAT Model-Based Irrigation Requirements for Coconut to Improve Crop and Water Productivity in Kerala, India

by U. Surendran, C. M. Sushanth, E. J. Joseph, Nadhir Al-Ansari and Zaher Mundher Yaseen

Sustainability 2019, 11(18), 5132; https://0-doi-org.brum.beds.ac.uk/10.3390/su11185132 - 19 Sep 2019

Cited by 17 | Viewed by 5681

Abstract

The irrigation requirements for coconut in Kerala are general in nature. This study determined the irrigation requirements for coconut, using CROPWAT based on agro-ecological zones (AEZs) for proposing the recommendations. The irrigation recommendations are generated based on the climatic, soil, and crop characteristics. The results showed that the irrigation requirements varied with the locations. Overall, for the state of Kerala, the irrigation requirements varied from 350 to 900 L of water per coconut palm, with the irrigation intervals ranging from three to nine days based on the AEZs. Moreover, this study also confirmed the variation of the water requirements observed within the districts. The quantity of water required per palm varied between 115 to 200 liters per day (LPD) per palm, which is lower than the existing recommendations of 175 to 300 LPD per palm. The proposed irrigation requirements appraised with the presently followed recommendations of the Kerala state, and its advantages discussed for improving the crop and water productivity. In nutshell, if the current recommendation is adopted, 30% of the water used for irrigation can be saved, as well as leading to an improvement in crop production. Full article

(This article belongs to the Special Issue Sustainable Irrigation Strategies for Improving Crop Water Productivity)

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18 pages, 4639 KiB

Open AccessArticle

Effects of Severe Water Stress on Maize Growth Processes in the Field

by Libing Song, Jiming Jin and Jianqiang He

Sustainability 2019, 11(18), 5086; https://0-doi-org.brum.beds.ac.uk/10.3390/su11185086 - 17 Sep 2019

Cited by 80 | Viewed by 5985

Abstract

In this study, we investigated the effects of water stress on the growth and yield of summer maize (Zea mays L.) over four phenological stages: Seedling, jointing, heading, and grain-filling. Water stress treatments were applied during each of these four stages in a water-controlled field in the Guanzhong Plain, China between 2013 and 2016. We found that severe water stress during the seedling stage had a greater effect on the growth and development of maize than stress applied during the other three stages. Water stress led to lower leaf area index (LAI) and biomass owing to reduced intercepted photosynthetically active radiation (IPAR) and radiation-use efficiency (RUE). These effects extended to the reproductive stage and eventually reduced the unit kernel weight and yield. In addition, the chlorophyll content in the leaf remained lower, even though irrigation was applied partially or fully after the seedling stage. Severe and prolonged water stress in maize plants during the seedling stage may damage the structure of the photosynthetic membrane, resulting in lower chlorophyll content, and therefore RUE, than those in the plants that did not experience water stress at the seedling stage. Maize plants with such damage did not show a meaningful recovery even when irrigation levels during the rest of the growth period were the same as those applied to the plants not subjected to water stress. The results of our field experiments suggest that an unrecoverable yield loss could occur if summer maize were exposed to severe and extended water stress events during the seedling stage. Full article

(This article belongs to the Special Issue Sustainable Irrigation Strategies for Improving Crop Water Productivity)

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Review

Jump to: Research

21 pages, 929 KiB

Open AccessReview

Irrigation-Water Management and Productivity of Cotton: A Review

by Komlan Koudahe, Aleksey Y. Sheshukov, Jonathan Aguilar and Koffi Djaman

Sustainability 2021, 13(18), 10070; https://0-doi-org.brum.beds.ac.uk/10.3390/su131810070 - 08 Sep 2021

Cited by 12 | Viewed by 4809

Abstract

A decrease in water resources, as well as changing environmental conditions, calls for efficient irrigation-water management in cotton-production systems. Cotton (Gossypium sp.) is an important cash crop in many countries, and it is used more than any other fiber in the world. With water shortages occurring more frequently nowadays, researchers have developed many approaches for irrigation-water management to optimize yield and water-use efficiency. This review covers different irrigation methods and their effects on cotton yield. The review first considers the cotton crop coefficient (Kc) and shows that the FAO-56 values are not appropriate for all regions, hence local Kc values need to be determined. Second, cotton water use and evapotranspiration are reviewed. Cotton is sensitive to limited water, especially during the flowering stage, and irrigation scheduling should match the crop evapotranspiration. Water use depends upon location, climatic conditions, and irrigation methods and regimes. Third, cotton water-use efficiency is reviewed, and it varies widely depending upon location, irrigation method, and cotton variety. Fourth, the effect of different irrigation methods on cotton yield and yield components is reviewed. Although yields and physiological measurements, such as photosynthetic rate, usually decrease with water stress for most crops, cotton has proven to be drought resistant and deficit irrigation can serve as an effective management practice. Fifth, the effect of plant density on cotton yield and yield components is reviewed. Yield is decreased at high and low plant populations, and an optimum population must be determined for each location. Finally, the timing of irrigation termination (IT) is reviewed. Early IT can conserve water but may not result in maximum yields, while late IT can induce yield losses due to increased damage from pests. Extra water applied with late IT may adversely affect the yield and its quality and eventually compromise the profitability of the cotton production system. The optimum time for IT needs to be determined for each geographic location. The review compiles water-management studies dealing with cotton production in different parts of the world, and it provides information for sustainable cotton production. Full article

(This article belongs to the Special Issue Sustainable Irrigation Strategies for Improving Crop Water Productivity)

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19 pages, 385 KiB

Open AccessReview

Irrigation Management in Potato (Solanum tuberosum L.) Production: A Review

by Koffi Djaman, Suat Irmak, Komlan Koudahe and Samuel Allen

Sustainability 2021, 13(3), 1504; https://0-doi-org.brum.beds.ac.uk/10.3390/su13031504 - 01 Feb 2021

Cited by 45 | Viewed by 8012

Abstract

Limited water resources coupled with the increase of the human population calls for more efficient use of water in irrigated agriculture. Potato (Solanum tuberosum L.) is one of the most widely grown crops worldwide and is very sensitive to water stress due to its shallow rooting system. With the dilemma of potato sensitivity to drought and limited available water resources restricting crop production, researchers and crop growers have been investigating different approaches for optimizing potato yield and improving crop water use efficiency under different irrigation methods. While potato response to water is affected by other management practices such as fertilizer management, the present review is focused on the potato response to water under different environments and different irrigation methods and the impact on potato quality and potato diseases. Variable results obtained from research studies indicate the non-transferability of the results from one location to another as potato cultivars are not the same and potato breeders are still making effort to develop new high-yielding varieties to increase crop production and or develop new varieties for a specific trait to satisfy consumers exigence. This review is a valuable source of information for potato growers and scientists as it is not only focused on the impact of irrigation regimes on potato yield and water productivity as most reviews on water management, but it also presents the impact of irrigation regime on diseases in potatoes, tuber specific gravity, metabolite content of the tubers and the quality of the processed potato products. Full article

(This article belongs to the Special Issue Sustainable Irrigation Strategies for Improving Crop Water Productivity)

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