Rehabilitation of operation regimes in aged irrigation schemes based on hydraulic simulation

The selection and employment of proper methods in water distribution causes increasing in water productivity and the level of satisfaction of water users. It is faced with more difficulties in aged irrigation projects due to temporal changes such as changes in the crop patterns, development of the command area and destruction of canals and hydraulic structures. The plan of operation methods have some hydraulic and social complexities and therefore is usually simplified or implemented experimentally. This research investigates the best options for water distribution to the paddy fields in a subunit of Sefidroud irrigation scheme based on field survey, recording real data and hydraulic simulation with employing SOBEK hydrodynamic model. Different operation scenarios were defined and then simulated in the current physical state of the scheme through replacing the exhausted intake structures with sluice gates. Finally, the better operation scenarios during the irrigation season were suggested based on the distribution indices. The results show that in spite of the current situation, water loss could reach the minimum by employing modification scenarios and indices of adequacy and equity of water distribution improve.

Comparing Sentinel-1, Sentinel-2, and Landsat-8 data in the early recognition of irrigated areas in central Italy

This study evaluated the effectiveness of various remote sensing (RS) data (Sentinel-1, Sentinel-2, and Landsat 8) in the early recognition of irrigated areas in a densely cultivated area of central Italy. The study was based on crop data collected on more than 2000 plots in 2016 and 2017, characterized by quite different climatic conditions. The different RS data sources were used both alone and combined and with precipitation to define corresponding random forest (RF) classifiers whose overall accuracy (OA) was assessed by gradually increasing the number of available features from the beginning of the irrigation season. All tested RF classifiers reach stable OAs (OA 0.9) after 7-8 weeks from the start of the irrigation season. The performance of the radar indexes slightly improves when used in combination with precipitation data, but three weeks of features are required to obtain OA above 80%. The optical indices alone (Sentinel-2 and Landsat 8) reach OA ≈85% in the first week of observation. However, they are ineffective in cloudy conditions or when rainfed and irrigated fields have similar vigour. The most effective and robust indices are those based on combined sources (radar, optical, and meteorological), allowing OAs of about 92% and 96% at the beginning and in the middle of the irrigation season, respectively.

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

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 RMSE=0.0292 (cm3/cm3) and R2=0.92 for the Sentinel-2 derived SSM and RMSE=0.0317 (cm3/cm3) and R2=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 (pvalue=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%.

Monitoring of Emerging Water Stress Situations by Thermal and Vegetation Indices in Different Almond Cultivars

In recent years, the area dedicated to modern irrigated almond plantations has increased significantly in Spain. However, the legal irrigation allocations are lower than the maximum water requirements of the crop in most cases. Therefore, almond growers are forced to implement regulated deficit irrigation strategies on their farms, applying water stress in certain resistant phenological periods and avoiding it in sensitive periods. Given the need to monitor the water status of the crop, especially in the most sensitive periods to water stress, the objective of this work was to evaluate the sensitivity of two UAV-based crop water status indicators to detect early water stress conditions in four almond cultivars. The field trial was conducted during 2020 in an experimental almond orchard, where two irrigation strategies were established: full irrigation (FI), which received 100% of irrigation requirements (IR), and regulated deficit irrigation (RDI), which received 70% of IR during the whole irrigation period except during the kernel-filling stage when received 40% IR. The UAV flights were performed on four selected dates of the irrigation season. The Crop Water Status Index (CWSI) and the Normalized Difference Vegetation Index (NDVI) were derived from thermal and multispectral images, respectively, and compared to classical water status indicators, i.e., stem water potential (Ψstem), stomatal conductance (gs), and photosynthetic rate (AN). Of the four flights performed, three corresponded to mild water stress conditions and a single flight was performed under moderate water stress conditions. Under mild water stress, CWSI was not able to capture the differences between FI and RDI trees that were observed with Ψstem. Under moderate stress conditions, CWSI was sensitive to the water deficit reached in the trees and showed significant differences among both irrigation treatments. No differences were observed in the CWSI and NVDI response to water stress among cultivars. Although NDVI and CWSI were sensitive to water stress, the low signal intensity observed in NDVI makes this index less robust than CWSI to monitor crop water stress. It can be concluded that UAV-based CWSI measurements are reliable to monitor almond water status, although for early (mild) levels of water stress, Ψstem seems to be the preferred option.

Modification of Portable Power Tiller for Small Scale Weeding Operation

Weeds are unwanted and undesirable plant that interfere with the utilization of land and water resources and adversely affect crop production. After preliminary study, it was found out that power tiller could be adopted for weeding. Therefore, the study aimed at improving its performance through modification of some major component such as: weeding blades and depth gauge. Three sets of pairs of blade gang of four, six and eight were made from 3 mm mild steel sheet metal. The fabrication was carried out at the Department of Agricultural and Bio-Resources Engineering, Ahmadu Bello University, Zaria. The modified machine was evaluated based on weeding efficiency, field capacity, Plant Damage and Fuel consumption in the maize field during 2017/2018 irrigation season at Institute for Agricultural Research, IAR, Ahmadu Bello University, Zaria research farm. Four levels of blade types ‘B’ and three levels of weeding depth ‘D’ were considered. The field was laid in a 4×3 Randomized Complete Block Design (RCBD) at two (2) Weeks After Sowing (2WAS). DMRT was used for mean separation ran in SAS package. The results showed effects of blade types and weeding depth were significant on the weeding performance of the machine.

Methodology adaptation and development to assess salt content dynamics and salt balance of soils under secondary salinization

The effect of irrigation with saline water (above 500 mg L-1) is considered a problem of small-scale farmers growing vegetable crops with high water demand in the hobby gardens characteristic of the Hungarian Great Plain. In order to simulate the circumstances of such hobby garden, we set up an experiment including five simple drainage lysimeters irrigated with saline water in the Research Institute of Karcag IAREF UD in 2019. We regularly measured the electric conductivity (EC) of the soil referring to its salt content and the soil moisture content with mobile sensors. Before and after the irrigation season, soil samples from the upper soil layer (0-0.6 m) were taken for laboratory analysis and the soil salt balance (SB) was calculated. The actual salt balance (SBact) was calculated of the upper soil layer (0-0.6 m) based on the salt content of the obtained soil samples. The theoretical salt balance (SBth) was calculated by the total soluble salt content of the irrigation water and leachates. During the irrigation season, we experienced fluctuating EC in the topsoil in close correlation with the soil moisture content. Based on the performed in-situ EC measurements, salts were leached from the upper soil layer resulting in a negative SB. Combining SBact and SBth of the soil columns of the lysimeters, we estimated the SB of the deeper (0.6-1.0 m) soil layer. We quantified 12% increase of the initial salt mass due to accumulation. We consider this methodology to be suitable for deeper understanding secondary salinization, which can contribute to mitigating its harmful effect. By repeating our measurements, we expect similar results proving that saline irrigation waters gained from the aquifers through drilled wells in Karcag are potentially suitable for irrigation if proper irrigation and soil management are applied.

Livestock and Small-Scale Irrigation Scheme Interactions as a Key Source for Sedimentation during the Irrigation Season: Four Case Studies from South-West Shoa, Ethiopia

Small-scale irrigation (SSI) development can play a major role in Ethiopia’s economic development, but sedimentation is a major threat to its sustainability. The focus of the dominant discourse around the sedimentation of SSI schemes lies in upstream catchment protection during the rainy season, neglecting both protection against erosion through overland flow along the margins of the canal network and sedimentation caused by livestock disturbances. Remedies against the latter causes of sedimentation during the irrigation season have been ineffective due to erroneous assumptions regarding its cause. This study aimed to identify the sources and extent of sedimentation in SSI schemes. The accumulated sediment in the canal pre-irrigation season was measured from four SSI schemes and suspended sediment samples during irrigation season were collected from one SSI scheme. The accumulated sediment in the canal pre-irrigation season was measured from four SSI and suspended sediment samples during irrigation season were collected from one SSI scheme. The extent of sedimentation in the canals during the pre-irrigation season in relation to canal capacity was 100% of lined and unlined canals in abandoned, 68% in a lined, and 84% unlined canals in heavily sedimented and 38% in a lined and 46% of unlined canals lightly sedimented schemes. Livestock interactions with the SSI schemes were found to be the major sediment source before and during the irrigation, hence, attention should be given to integrating livestock as a part of the system.

Irrigation Scheduling of Maize Grown on a Vertisol Soil Under Changing Climate of Sofia’s Field

The purpose of this study is to evaluate the impact of climate uncertainties on maize irrigation requirements, grown on a Vertisol soil, Sofia’s field, Bulgaria. Through the validated WinIsareg model, four irrigation scheduling alternatives are simulated for the years of “very high“, “high“ and “average“ irrigation demands of past (1952–1984) and present (1970–2004) climate. Adaptation of irrigation scheduling to the present climate conditions during the “very dry“ years (P I ≤12%) consists of an extension of the irrigation season by 15–20 days and a need of additional irrigation relative to alternative 1 and two irrigation events at alternatives 2 and 3. During the past climate alternatives 2 and 3 led to savings of 30 mm of water, while up to the current climate conditions the three irrigations alternatives should provide 360 mm of irrigation water. To obtain maximum yields in “dry“ (P I = 12–30%) years, irrigation season should end by 05/09, as in the present climate, irrigation season has shifted about a week earlier for the three alternatives. In the “average“ (P I = 30–60%) years the adaptation consist in accurately determination of the last allowed date for irrigation.