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

<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>

Estimating Soil Water Content and Evapotranspiration of Winter Wheat under Deficit Irrigation Based on SWAP Model

Deficit irrigation strategy is essential for sustainable agricultural development in arid regions. A two−year deficit irrigation field experiment was conducted to study the water dynamics of winter wheat under deficit irrigation in Guanzhong Plain in Northwest China. Three irrigation levels were implemented during four growth stages of winter wheat: 100%, 80% and 60% of actual evapotranspiration (ET) measured by the lysimeter with sufficient irrigation treatment (CK). The agro−hydrological model soil−water−atmosphere−plant (SWAP) was used to simulate the components of the farmland water budget. Sensitivity analysis for parameters of SWAP indicated that the saturated water content and water content shape factor n were more sensitive than the other parameters. The verification results showed that the SWAP model accurately simulated soil water content (average relative error (MRE) < 21.66%, root mean square error (RMSE) < 0.07 cm3 cm−3) and ET (R2 = 0.975, p < 0.01). Irrigation had an important impact on actual plant transpiration, but the actual soil evaporation had little change among different treatments. The average deep percolation was 14.54 mm and positively correlated with the total irrigation amount. The model established using path analysis and regression methods for estimating ET performed well (R2 = 0.727, p < 0.01). This study provided effective guidance for SWAP model parameter calibration and a convenient way to accurately estimate ET with fewer variables.

Evaluating the Impact of Climate Change on Water Productivity of Maize in the Semi-Arid Environment of Punjab, Pakistan

Impact assessments on climate change are essential for the evaluation and management of irrigation water in farming practices in semi-arid environments. This study was conducted to evaluate climate change impacts on water productivity of maize in farming practices in the Lower Chenab Canal (LCC) system. Two fields of maize were selected and monitored to calibrate and validate the model. A water productivity analysis was performed using the Soil–Water–Atmosphere–Plant (SWAP) model. Baseline climate data (1980–2010) for the study site were acquired from the weather observatory of the Pakistan Meteorological Department (PMD). Future climate change data were acquired from the Hadley Climate model version 3 (HadCM3). Statistical downscaling was performed using the Statistical Downscaling Model (SDSM) for the A2 and B2 scenarios of HadCM3. The water productivity assessment was performed for the midcentury (2040–2069) scenario. The maximum increase in the average maximum temperature (Tmax) and minimum temperature (Tmin) was found in the month of July under the A2 and B2 scenarios. The scenarios show a projected increase of 2.8 °C for Tmax and 3.2 °C for Tmin under A2 as well as 2.7 °C for Tmax and 3.2 °C for Tmin under B2 for the midcentury. Similarly, climate change scenarios showed that temperature is projected to decrease, with the average minimum and maximum temperatures of 7.4 and 6.4 °C under the A2 scenario and 7.7 and 6.8 °C under the B2 scenario in the middle of the century, respectively. However, the highest precipitation will decrease by 56 mm under the A2 and B2 scenarios in the middle of the century for the month of September. The input and output data of the SWAP model were processed in R programming for the easy working of the model. The negative impact of climate change was found under the A2 and B2 scenarios during the midcentury. The maximum decreases in Potential Water Productivity (WPET) and Actual Water Productivity (WPAI) from the baseline period to the midcentury scenario of 1.1 to 0.85 kgm−3 and 0.7 to 0.56 kgm−3 were found under the B2 scenario. Evaluation of irrigation practices directs the water managers in making suitable water management decisions for the improvement of water productivity in the changing climate.

Modeling Soil Water–Heat Dynamic Changes in Seed-Maize Fields under Film Mulching and Deficit Irrigation Conditions

The Soil–Water–Atmosphere–Plant (SWAP) model does not have a mulching module to simulate the effect of film mulching on soil water, heat dynamics and crop growth. In this study, SWAP model parameters were selected to simulate the soil water–heat process and crop growth, taking into account the effect of film mulching on soil evaporation, temperature, and crop growth, in order to predict the influence of future climate change on crop growth and evapotranspiration (ET). A most suitable scheme for high yield and water use efficiency (WUE) was studied by an experiment conducted in the Shiyang River Basin of Northwest China during 2017 and 2018. The experiment included mulching (M1) and non-mulching (M0) under three drip irrigation treatments, including full (WF), medium (WM), low (WL) water irrigation. Results demonstrated that SWAP simulated soil water storage (SWS) well, soil temperature at various depths, leaf area index (LAI) and aboveground dry biomass (ADB) with the normalized root mean square error (NRMSE) of 16.2%, 7.5%, 16.1% and 16.4%, respectively; and yield, ET, and WUE with the mean relative error (MRE) of 10.5%, 12.4% and 14.8%, respectively, under different treatments on average. The measured and simulated results showed film mulching could increase soil temperature, promote LAI during the early growth period, and ultimately improve ADB, yield and WUE. Among the treatments, M1WM treatment with moderate water deficit and film mulching could achieve the target of more WUE, higher yield, less irrigation water. Changes in atmospheric temperature, precipitation, and CO2 concentration are of worldwide concern. Three Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP4.5, RCP8.5) showed a negative effect on LAI, ADB and yield of seed-maize. The yield of seed-maize on an average decreased by 33.2%, 13.9% under the three RCPs scenarios for film mulching and non-mulching, respectively. Predicted yields under film mulching were lower than that under non-mulching for the next 30 years demonstrating that current film mulching management might not be suitable for this area to improve crop production under the future climate scenarios.

Physical-mathematical modeling of multiyear dynamics of water-balance and snow-reserve components in Ob-Irtysh river basin

The possibility of use of the previously developed calculation technique of the North Rivers flow hydraulic records for the Ob River, the largest river in Russia by basin area, flowing under severe conditions in West Siberia was examined. The calculation technique is based on the model of heat and moisture exchange of the geological substrate with the Earth’s atmosphere, the Soil-Water–Atmosphere–Plants (SWAP) model, in conjunction with information support based on global databases of geological-substrate parameters and information obtained from observational data collected by weather stations within the Ob River basin. Uncertainty of the Ob River flow was assessed. Additionally, the ability of the SWAP model to reproduce multiyear dynamics from average values of snow reserves in the Ob-Irtysh basin was examined.

Simulation of Saline Water Irrigation for Seed Maize in Arid Northwest China Based on SWAP Model

Water resource shortages restrict the economic and societal development of China’s arid northwest. Drawing on groundwater resources for irrigation, field experiments growing seed maize (Zea mays L.) were conducted in 2013 and 2014 in the region’s Shiyang River Basin. The Soil–Water–Atmosphere–Plant (SWAP) model simulated soil water content, salinity, and water–salt transport, along with seed maize yield, in close agreement with measured values after calibration and validation. The model could accordingly serve to simulate different saline water irrigation scenarios for maize production in the study area. Waters with a salinity exceeding 6.0 mg/cm3 were not suitable for irrigation, whereas those between 3.0 and 5.0 mg/cm3 could be acceptable over a short period of time. Brackish water (0.71–2.0 mg/cm3) could be used with few restrictions. Long-term (five years) simulation of irrigation with saline water (3.0–5.0 mg/cm3) showed soil salinity to increase by over 9.5 mg/cm3 compared to initial levels, while seed maize yield declined by 25.0% compared with irrigation with brackish water (0.71 mg/cm3). An irrigation water salinity of 3.0–5.0 mg/cm3 was, therefore, not suitable for long-term irrigation in the study area. This study addressed significance issues related to saline water irrigation and serves as a guide for future agricultural production practices.

Intercropping Simulation Using the SWAP Model: Development of a 2×1D Algorithm

Intercropping is a common cultivation system in sustainable agriculture, allowing crop diversity and better soil surface exploitation. Simulation of intercropped plants with integrated soil–plant–atmosphere models is a challenging procedure due to the requirement of a second spatial dimension for calculating the soil water lateral flux. Evaluations of more straightforward approaches for intercrop modeling are, therefore, mandatory. An adaptation of the 1D model Soil, Water, Atmosphere and Plant coupled to the World Food Studies (SWAP/WOFOST) to simulate intercropping (SWAP 2×1D) based on solar radiation and water partitioning between plant strips was developed and the outcomes are presented. An application of SWAP 2×1D to maize–soybean (MS) strip intercropping was evaluated against the monocropping maize (M) and soybean (S) simulated with the 1D model SWAP/WOFOST, and a sensitivity analysis of SWAP 2×1D was carried out for the intercropping MS. SWAP 2×1D was able to simulate the radiation interception by both crops in the intercropping MS and also to determine the effect of the radiation attenuation by maize on soybean plants. Intercropped plants presented higher transpiration and resulted in lower soil evaporation when compared to their equivalent monocropping cultivation. A numerical issue involving model instability caused by the simulated lateral water flux in the soil from one strip to the other was solved. The most sensitive plant parameters were those related to the taller plant strips in the intercropping, and soil retention curve parameters were overall all significantly sensitive for the water balance simulation. This implementation of the SWAP model presents an opportunity to simulate strip intercropping with a limited number of parameters, including the partitioning of radiation by a well-validated radiation sharing model and of soil water by simulating the lateral soil water fluxes between strips in the 2×1D environment.

Simulating of snow cover formation by the model of interaction between the land surface and the atmosphere (SWAP)

In framework of the project «The Earth system Models – Snow Models Intercomparison Project» (ESMSnowMIP), calculations of snow storages were carried out on ten experimental sites organized for longterm monitoring of the snow cover variability in various regions of the globe. The calculation method is based on the physical and mathematical description of heat and moisture exchange processes occurring within the system «ground water – soil – vegetation cover/snow cover – surface layer of the atmosphere», and it is implemented in the form of the model of interaction between the land surface and the atmosphere (SWAP). The model was developed at the Institute of water problems (IWP) of Russian Academy of Sciences. The model makes possible to calculate components of water and heat balances and different characteristics of the hydrological regime of terrestrial ecosystems and river basins having different spatial scales and located in different natural conditions. Good quality of reproduction of the snow storages variability on all considered sites is reached that allows consideration of the SWAP model as one of the best models of the snow cover formation. Thus, the SWAP model has a sufficiently optimal degree of complexity of the algorithm for reproducing the dynamics of snow cover, which is necessary and sufficient in global and regional hydrological models describing formation of the water balance of the land in the cold regions of the planet, and can be used to create scenario forecasts of snow dynamics (as the important part of the cryosphere). This conclusion is verified by the results of using the SWAP model to reproduce long-term variability of snow storages in basins of the River Lena and the River Ob (with its tributary Irtysh) which are the two largest rivers of the Russian Federation. The calculated and measured characteristics of snow cover dynamics for these basins are shown to be in good agreement.