Search Results (75)

In this case study, we used the Delta Simulation Model II (DSM2) to study the salt balance at the land–water interface in the river delta of California’s San Francisco Estuary. Drainage, a source of water and salt for adjacent channels in the study area, is affected by channel salinity. The DSM2 approach has been adopted by several hydrodynamic models of the estuary to enforce water volume balance between diversions, evapotranspiration and drainage at the land–water interface, but does not explicitly enforce salt balance. We found deviations from salt balance to be quite large, albeit variable in magnitude due to the heterogeneity of hydrodynamic and salinity conditions across the study area. We implemented a procedure that approximately enforces salt balance through iterative updates of the baseline drain salinity boundary conditions (termed loose coupling). We found a reasonable comparison with field measurements of drainage salinity. In particular, the adjusted boundary conditions appear to capture the range of observed interannual variability better than the baseline periodic estimates. The effect of the iterative adjustment procedure on channel salinity showed substantial spatial variability: locations dominated by large flows were minimally impacted, and in lower flow channels, deviations between baseline and adjusted channel salinity series were notable, particularly during the irrigation season. This approach, which has the potential to enhance the simulation of extreme salinity intrusion events (when high channel salinity significantly impacts drainage salinity), is essential for robustly modeling hydrodynamic conditions that pre-date contemporary water management infrastructure. We discuss limitations associated with this approach and recommend that—for this case study—further improvements could best be accomplished through code modification rather than coupling of transport and island water balance models. Full article

A detailed characterization of evapotranspiration (ET) patterns is of paramount importance for optimizing irrigation scheduling and enhancing water-use efficiency in the North China Plain. To delve into this, a two-season study was conducted at the National Experimental Station for Precise Agriculture in Beijing. Using 12 weighing lysimeters, the study compared two summer maize varieties with contrasting canopy sizes: Jingke 968 (JK), characterized by a large canopy, and CF 1002 (CF), with a small canopy. The comprehensive analysis yielded the following significant findings: (1) The daily average ET rates exhibited consistent trends across cultivars, yet with notable disparities in magnitude. JK consistently demonstrated higher water consumption throughout the growth seasons. In the first season, at the V13–R1 stage, the peak daily ET of JK and CF reached 5.91 mm/day and 5.52 mm/day, respectively. In the second season, during the R1–R3 stage, these values were 5.21 mm/day for JK and 5.22 mm/day for CF, highlighting the nuanced differences in water use between the varieties under varying growth conditions. (2) Regardless of canopy size, the hourly ET fluctuations across different growth stages followed similar temporal patterns. However, the most striking inter-varietal differences in ET emerged during the R1–R3 reproductive stages, when both cultivars had achieved peak canopy development (leaf area index, LAI > 4.5). Notably, the ET differences between JK and CF adhered to a characteristic diurnal “increase–decrease” pattern. These differences peaked during mid-morning (09:00–11:00) and early afternoon (13:00–15:00), while minimal divergence was observed at solar noon. This pattern suggests complex interactions between canopy structure, microclimate, and plant physiological processes that govern water loss over the course of a day. (3) Analysis of the pooled data pinpointed two critical time periods that significantly contributed to the cumulative ET differences between the varieties. The first period was from 12:00–17:00 during the R1–R3 (anthesis) stage, and the second was from 08:00–16:00 during the R3–R5 (grain filling) stage. JK maintained significantly higher transpiration rates (Tr) compared to CF, especially during the morning hours (09:00–12:00). On average, the Tr of JK exceeded that of CF by 5.3% during the pre-anthesis stage and by 16.0% during the post-anthesis stage. These observed Tr differentials strongly indicate that canopy architecture plays a pivotal role in modulating stomatal regulation patterns. Maize varieties with large canopies, such as JK, demonstrated enhanced morning photosynthetic activity, which likely contributed to increased transpiration. At the same time, both varieties seemed to employ similar midday water conservation strategies, possibly as an adaptive response to environmental stress. In summary, this study has comprehensively elucidated the intricate relationship between the leaf area index and the evapotranspiration of summer maize across multiple timescales, encompassing periodic, daily, and hourly variations. The findings provide invaluable data-driven insights that can underpin the development of precise and quantitative irrigation strategies, ultimately promoting sustainable and efficient maize production in the North China Plain. Full article

Floods are a major threat to human life and economic assets. Monitoring these events is therefore essential to quantify and minimize such losses. Remote sensing has been used to extract flooded areas, with SAR imagery being particularly useful as it is independent of weather conditions. This approach is more difficult when detecting flooded areas in semi-arid environments, without a reference permanent water body, than when monitoring the water level rise of permanent rivers or lakes. In this study, Random Forest is used to estimate flooded cells after 19 events in Campo de Cartagena, an agricultural area in SE Spain. Sentinel-1 SAR metrics are used as predictors and irrigation ponds as training areas. To minimize false positives, the pre- and post-event results are compared and only those pixels with a probability of water increase are considered as flooded areas. The ability of the RF model to detect water surfaces is demonstrated (mean accuracy = 0.941, standard deviation = 0.048) along the 19 events. Validating using optical imagery (Sentinel-2 MSI) reduces accuracy to 0.642. This form of validation can only be applied to a single event using a S2 image taken 3 days before the S1 image. A large number of false negatives is then expected. A procedure developed to correct for this error gives an accuracy of 0.886 for this single event. Another form of indirect validation consists in relating the area flooded in each event to the amount of rainfall recorded. An RF regression model using both rainfall metrics and season of the year gives a correlation coefficient of 0.451 and RMSE = 979 ha using LOO-CV. This result shows a clear relationship between flooded areas and rainfall metrics. Full article

Seasonal freeze–thaw irrigation areas face challenges of soil salinization and water scarcity, requiring a deep understanding of soil freeze–thaw dynamics under the interaction between irrigation and groundwater. An in situ lysimeter experiment was conducted in the winters of 2020–2021 and 2023–2024 to investigate the effects of autumn irrigation (AI) timing (late AI conducted in late November and icing AI conducted in early December) and quota (0, 35, 135, 270 mm) on soil water, heat, and salt transport under varying groundwater levels in the Hetao Irrigation District, Northwest China. Results showed that AI had a strong short-term effect on the groundwater depth and there was a significant negative correlation between groundwater depth and air temperature on a monthly scale. The quota and air temperature during AI were the key factors in utilizing the “refrigerator effect”—where irrigation water pre-cooled by frozen layer accelerates soil freezing—to regulate soil water and salt transport under freeze–thaw cycles. The drastic reduction in AI water consumption lowered the groundwater level, highlighting air temperature as the dominant driver of soil dynamics. Thus, icing AI with low quota (35 mm) can optimize water use (water saving of 77% compared to the traditional quota of 150 mm) while maintaining soil moisture (an increase of 17.4% in water storage) and salinity control (a decrease of 41.6% in salt storage) in the root zone (0–40 cm) through the “refrigerator effect”, demonstrating its potential for sustainable irrigation in water-scarce cold regions. Full article

The spatial and temporal distribution of water and nitrogen supply affects soil-borne nitrous oxide (N₂O) emissions. In this study, the effects of different irrigation technologies (no irrigation, sprinkler irrigation and drip irrigation) and nitrogen (N) application types (no fertilizer, broadcasted and within irrigation water) on N₂O flux rates and the quantities of functional genes involved in the N cycle in potato cropping were investigated over an entire season. The volume of irrigation water affected microbial N₂O production, with the highest N₂O flux rates found under sprinkler irrigation conditions, followed by drip and no irrigation. Nitrifier denitrification was identified as the potential pre-dominant pathway stimulated by fluctuations in aerobic-anaerobic soil conditions, especially under sprinkler irrigation. Regarding the different N application types, increased N use efficiency under fertigation was expected. However, N₂O flux rates were not significantly reduced compared to broadcasted N application under drip irrigation. On average, the N₂O fluxes were higher during the first half of the season, which was accompanied by a low N use efficiency of the potato crops. Potato crops mainly require N at later growth stages. Due to the different water and nutrient demand of potatoes, an adjusted application of fertilizer and water based on crop demand could reduce N₂O emissions. Full article

The Leaf Area Index (LAI) is a key physiological metric in viticulture, associated with vine health, yield, and responsiveness to environmental and management factors. This study, conducted in a Mediterranean Sauvignon Blanc vineyard (2017–2023), examines how irrigation and environmental variables affect LAI across phenological stages, and their impact on yield (clusters per vine, cluster weight, total yield) and pruning parameters (cane weight, pruning weight). Results show that irrigation is the primary driver of LAI, with increased water availability promoting leaf area expansion. Environmental factors, including temperature, vapor pressure deficits, and solar radiation, influence LAI dynamics, with chilling hours playing a crucial role post-veraison. Excessive LAI (>1.6–1.7) reduces yield due to competition between vegetative and reproductive sinks. Early-season LAI correlates more strongly with yield, while late-season LAI predicts pruning weight and cane growth. Machine learning models reveal that excessive pre-veraison LAI in one season reduces cluster numbers in the next. This study highlights LAI as a critical tool for vineyard management. While irrigation promotes vegetative growth, excessive LAI can hinder fruit set and yield, emphasizing the need for strategic irrigation timing, canopy management, and climate adaptation to sustain long-term vineyard productivity. Full article

The winter wheat and summer maize double cropping system is the primary cropping pattern for wheat and maize in dryland areas of China. The management of tillage in this system is typically conducted before wheat sowing. However, few studies have validated and quantified the impact of tillage methods before wheat sowing and irrigation practices during the wheat season on the yield formation and water use efficiency of summer maize. Therefore, this study hypothesized that subsoiling before wheat sowing improves maize yield and WUE by enhancing soil moisture retention and plant development. A three-year field experiment with a two-factor split-plot design was conducted at the junction of the Loess Plateau and the Huang-Huai-Hai Plain in China for validation, from 2019 to 2022. Three tillage methods before wheat sowing (RT: rotary tillage; PT: plowing, SS: subsoiling) were assigned to the main plots, and two irrigation practices during wheat growing season (W0: zero-irrigation; W1: one-off irrigation) were assigned to subplots. We measured the soil moisture, grain yield, dry matter accumulation, nitrogen (N), phosphorus (P), and potassium (K) accumulation, and water use efficiency of summer maize. The results indicated that subsoiling before wheat sowing increased soil water storage at the sowing of summer maize, thereby promoting dry matter and nutrient accumulation. Compared to rotary tillage and plowing, subsoiling before wheat sowing increased grain yield and water use efficiency of maize by an average of 19.5% and 21.8%, respectively. One-off irrigation during the wheat season had negative effects on pre-sowing soil water storage and maize productivity in terms of yield and dry matter accumulation. However, subsoiling before wheat sowing can mitigate these negative effects of one-off irrigation. Correlation analysis and path model results indicated that tillage methods before wheat sowing had a greater impact on soil water storage and maize productivity than irrigation practices during wheat growing season. The most direct factor affecting maize yield was dry matter accumulation, whereas the most direct factor affecting water use efficiency was nutrient accumulation. The technique for order preference by similarity to an ideal solution (TOPSIS) comprehensive evaluation indicated that subsoiling before wheat sowing was superior for achieving high maize yield and water use efficiency under the practice of one-off irrigation during the wheat season. These findings offer practical guidance for optimizing soil water use and maize productivity in drylands. Full article

Flumioxazin is crucial for peanut weed management across the United States with over 75% of growers applying it to control troublesome weed species. For maximum peanut yield, it is essential that weed control is maintained during weeks three through eight after planting. Peanut injury due to flumioxazin PRE applied has been noted under unfavorable moisture or weather conditions, but also due to delays in application as growers plant hundreds of hectares on their farms. Research in Georgia (GA) investigated the response of non-irrigated peanut to flumioxazin PRE applied from 0 to 107 g ai/ha at 0 to 14 d after planting for cultivar Georgia-16HO. Trends during the 2020 through 2022 growing seasons indicated that as rate and time after planting of application increased, injury increased. Over 50% injury was noted in Tift County and 24% in Sumter County during the 2021 growing season. Peanut pod yield decreased while flumioxazin rate increased and time of application after planting was delayed in Tift County, but no differences were noted in Sumter County, potentially due to soil adsorption of the herbicide. Yield differences of up to 800 kg/ha were noted when comparing no herbicide being applied to the full application rate. The recorded injury coincided with large amounts of rainfall at both locations. It was also noted that peanut may be most sensitive to flumioxazin application injury between days seven and ten after planting. Full article

Human activities and climate change increasingly threaten wetlands worldwide, yet their hydrochemical properties and water quality are often inadequately studied. This research focused on the Ghodaghodi Lake Complex (GLC) and associated lakes in Nepal, a Ramsar-listed site known for its biodiversity and ecological significance. The study was conducted to assess seasonal water quality, investigate the factors influencing hydrochemistry, and assess the lakes’ suitability for irrigation. Forty-nine water samples were collected from the GLC in pre-monsoon and post-monsoon periods. Nineteen physicochemical parameters, such as dissolved oxygen (DO), total dissolved solids (TDS), and major ions (calcium ‘Ca²⁺’, magnesium ‘Mg²⁺’, and bicarbonate ‘HCO₃⁻’), were analyzed using standard on-site and laboratory methods. Statistical methods, including analysis of variance (ANOVA), T-tests, and hydrochemical diagrams, e.g., Piper, were adopted to explore spatial and seasonal variations in water quality, revealing significant fluctuations in key hydrochemical indicators. Results showed marked seasonal differences, with pre-monsoon TDS levels averaging 143.1 mg/L compared to 78.9 mg/L post-monsoon, underscoring evaporation and dilution effects. The hydrochemical analysis identified Ca²⁺-HCO₃⁻ as the dominant water type, highlighting the influence of carbonate weathering on GLC’s water composition. Gibbs, mixing, and Piper diagram analysis supported these findings, confirming the predominance of HCO₃⁻, with Ca²⁺ and Mg²⁺ as the main cations. Additionally, sodium adsorption ratio (SAR) values were consistently below 1, confirming excellent irrigation quality. These findings provided critical data for policymakers and stakeholders, supporting sustainable wetland management and aligning with the United Nations’ Sustainable Development Goals relevant to environmental conservation, i.e., clean water and life on land. Full article

The Ramganga River basin, comprising three rivers, the Dhela, Dhandi, and Ramganga, plays a vital role in groundwater recharge, sustaining numerous industries, urban areas, and rural communities reliant on these rivers for daily activities. The study’s primary purpose was to analyze the groundwater quality in the context of potability, irrigation, and health risks to the local inhabitants of the Ramganga River basin. In 2021–2022, 52 samples (26 × 2) were collected from 13 locations in two different seasons, i.e., pre-monsoon and post-monsoon, and 20 physico-chemical and heavy metal and metalloids were analyzed using the standard protocols. The result shows that heavy metal and metalloids and metalloid concentrations of Zn (0.309–1.787 and 0.613–1.633); Fe (0.290–0.965 and 0.253–1.720), Cd (0.001–0.002 and 0.001–0.002); As (0.001–0.002 and 0.001–0.002), Cr (0.009–0.027 and 0.011–0.029), and Pb (−0.001–0.010 and 0.00–0.010) values in mg/L are present in both seasons. The groundwater quality index (GWQI), heavy metal pollution Index (HPI), and heavy metal evaluation index (HEI) were used to assess the water quality and metal pollution in the basin area. As per GWQI values, water quality lies from excellent water quality (41.639 and 43.091) to good water quality (56.326 and 53.902); as per HPI values, it shows good (29.51 and 30.03) to poor quality (60.26 and 59.75) and HEI values show the low-level contamination (1.03–2.57 and 1.13–3.37) of heavy metal and metalloids in both seasons. According to the potential health risk assessment, infants show low risk in pre-monsoon and low risk to medium post-monsoon, while children and adults show low risk to high risk in both seasons. From the health risk perspective, it shows that children and adults have more concerns about non-carcinogenic effects, so adequate remedial measures and treatment are required to avoid the groundwater quality of the Ramganga River basin. Full article

Due to the increase in demand for water, the rapid growth of urbanization and industrialization is the main threat to the source and quality of groundwater. The present study aimed to assess the suitability of groundwater for agricultural purposes in coastal regions using integrated approaches such as the saltwater mixing index (SWMI), the mineral saturation index (MSI), the agriculture suitability index (ASI), and unsupervised machine learning (USML) techniques. The result of the SWMI revealed that 20 and 17 sample locations were highly affected by saltwater intrusion in the study region’s northern and southeastern parts during the pre- and post-monsoon seasons. The detailed analysis of electrical conductivity in groundwater revealed that 19.64% and 14.29% of the samples were unfit for irrigation purposes, especially five sample locations, during both seasons. Regarding the overall suitability of groundwater for irrigation uses, the ASI values divulged that 8.9% of the samples were unsuitable for irrigation purposes. The spatial analysis of the ASI value indicated that 43.19 and 85.33 sq. km of area were unsuitable for irrigation practices. Additionally, the USML techniques identified the most influenced parameters such as Ca²⁺, Mg²⁺, Cl⁻, and SO₄²⁻ during both seasons. The present study results help maintain proper, sustainable water management in the study region. Full article

The growing population and expansion of rural activities, along with changing climatic patterns and the need for water during drought periods, have led to a rise in the water demand worldwide. As a result, the construction of water storage structures such as dams has increased in recent years to meet the water needs. However, dam construction can bring significant alterations to the natural flow regime of rivers, and it is therefore essential to understand the potential effects of human structures on the hydrological regime of rivers to reduce their destructive impacts. This study analyzes the hydrological changes in the Shahrchai River in response to the Shahrchai Dam construction in Urmia, Iran. The study period was from 1950 to 2017 at the Urmia Band station. The Indicators of Hydrological Alteration (IHA) were used to analyze the hydrological changes before and after regulating, accounting for land use changes and climatic factors. The results revealed the adverse effects of the Shahrchai Dam on the hydrological indices. The analysis showed an increase in the average flow rate during the summer season and a decrease in other seasons. However, the combined effects of water transferring for drinking purposes, a decrease in permanent snow cover upstream of the dam, and an increase in water use for irrigation and agricultural purposes resulted in a decrease in the released river flow. Furthermore, the minimum and maximum daily flow rates decreased by approximately 85% and 65%, respectively, after the construction of the Shahrchai Dam. Additionally, the number of days with maximum flow rates increased from 117 days in the pre-dam period to 181 days in the post-dam period. As a concluding remark, the construction of the Shahrchai Dam, land use/cover changes, and a decrease in permanent snow cover had unfavorable effects on the hydrological regime of the river. Therefore, the hydrological indicators should be adjusted to an acceptable level compared to the natural state to preserve the river ecosystem. The findings of this study are expected to guide water resource managers in regulating the sustainable flow regime of permanent rivers. Full article

Perennials are usually pre-cultivated on vegetation mats consisting of coconut fiber (coir), which require weather-dependent irrigation and regular fertilization with fast-acting fertilizer to achieve a saleable condition as quickly as possible. In the pre-cultivation of sheep’s wool–coir–vegetation mats, nitrogen (N) is already sufficiently contained in the vegetation mats due to the natural nitrogen content of the sheep’s wool fibers, so that additional liquid fertilization during pre-cultivation can be dispensed with if necessary. In this study, sheep’s wool–coir–vegetation mats of 4.5 kg/m² were pre-cultivated with 16 perennial plants (8 species) in 2018. Variant 1 (V1) received regular fertilization with mineral liquid fertilizer (total 8.7 g N/m²) during pre-cultivation. Variant 2 (V2) was not fertilized during pre-cultivation. In spring 2019, all pre-cultivated vegetation mats were lifted and laid on an area prepared with topsoil. No additional fertilization was applied after laying. The overall impression, plant height, number of flowering perennials, and plant coverage were examined in the 2018 and 2019 growing seasons, with only minor differences observed between V1 and V2. The number of flowers, biomass, and nitrogen content were determined for the two aster species used. There were differences between V1 and V2 in 2018, but not in 2019. The coverage of perennials of 50%, which is the prerequisite for the saleability of the vegetation mats, was already achieved on both V1 and V2 after 4 months of pre-cultivation. The overall impression of the perennials on both V1 and V2 also did not differ during pre-cultivation nor in the following year. Therefore, liquid fertilization is not necessary during the pre-cultivation of perennials on sheep’s wool–coir–vegetation mats. Full article

Rice is a globally important food crop, and it is crucial to accurately and conveniently obtain information on rice fields, understand their spatial patterns, and grasp their dynamic changes to address food security challenges. In this study, Chongqing’s Yongchuan District was selected as the research area. By utilizing UAVs (Unmanned Aerial Vehicles) to collect multi-spectral remote sensing data during three seasons, the phenological characteristics of rice fields were analyzed using the NDVI (Normalized Difference Vegetation Index). Based on Sentinel data with a resolution of 10 m, the NDVI difference method was used to extract rice fields between 2019 and 2023. Furthermore, the reasons for changes in rice fields over the five years were also analyzed. First, a simulation model of the rice harvesting period was constructed using data from 32 sampling points through multiple regression analysis. Based on the model, the study area was classified into six categories, and the necessary data for each region were identified. Next, the NDVI values for the pre-harvest and post-harvest periods of rice fields, as well as the differences between them, were calculated for various regions. Additionally, every year, 35 samples of rice fields were chosen from high-resolution images provided by Google. The thresholds for extracting rice fields were determined by statistically analyzing the difference in NDVI values within the sample area. By utilizing these thresholds, rice fields corresponding to six harvesting regions were extracted separately. The rice fields extracted from different regions were merged to obtain the rice fields for the study area from 2019 to 2023, and the accuracy of the extraction results was verified. Then, based on five years of rice fields in the study area, we analyzed them from both temporal and spatial perspectives. In the temporal analysis, a transition matrix of rice field changes and the calculation of the rice fields’ dynamic degree were utilized to examine the temporal changes. The spatial changes were analyzed by incorporating DEM (Digital Elevation Model) data. Finally, a logistic regression model was employed to investigate the causes of both temporal and spatial changes in the rice fields. The study results indicated the following: (1) The simulation model of the rice harvesting period can quickly and accurately determine the best period of remote sensing images needed to extract rice fields. (2) The confusion matrix shows the effectiveness of the NDVI difference method in extracting rice fields. (3) The total area of rice fields in the study area did not change much each year, but there were still significant spatial adjustments. Over the five years, the spatial distribution of gained rice fields was relatively uniform, while the lost rice fields showed obvious regional differences. In combination with the analysis of altitude, it tended to grow in lower areas. (4) The logistic regression analysis revealed that gained rice fields tended to be found in regions with convenient irrigation, flat terrain, lower altitude, and proximity to residential areas. Conversely, lost rice fields were typically located in areas with inconvenient irrigation, long distance from residential areas, low population, and negative topography. Full article

Mechanical properties of vegetables or crop materials play a noteworthy part in designing new related implements. These properties can be extracted from force–deformation curves. Several factors, such as soil preparation, irrigation, and pre- and post-harvest treatments influence them. The core objective of this investigation work was to analyze force–deformation curves obtained from compression, penetration, and shear tests of potatoes (Spunta cv.) produced with three tillage implements. The potatoes cv. Spunta were cultivated in loamy sand soil under the center-pivot irrigation system. The tillage implements used were a disc harrow plow, chisel plow, and moldboard plow. The trials were performed at a constant planting depth (15 cm) below the soil and a single plowing speed of 5.4 km/h. All data were expressed as an average of five replicates ± standard deviation. The force–deformation curves analysis showed that the modulus of elasticity for potatoes cv. Spunta ranged from 4.32 to 5.8 N/mm, the bioyield force ranged from 84.25 to 114.12 N, and rupture forces ranged from 100.90 to 139.78 N. Furthermore, the results showed that the average values of the elastic and plastic ranges were 3.0 and 2.1 mm, respectively. The mean value of hardness was 1671.53 N·mm. No significant differences were observed with respect to the two planting seasons, but tillage implements had a significant impact on the characteristics extracted from the compression tests. The mean of the maximum forces required to penetrate the potato during the penetration stage were 41.24 N, 44.86 N, and 47.16 N for potatoes produced with the disc harrow plow, chisel plow, and moldboard plow, respectively. Similarly, the means of the maximum forces required to cut the potato in the shear stage were 724.38 N, 761 N, and 773.43 N for the disc harrow plow, chisel plow, and moldboard plow, respectively. The force–deformation curves showed that additional information might be required to obtain a complete description of the potato quality necessary to harvest potatoes cv. Spunta using harvesting and handling equipment with reduced economic loss. An extensive study of the soil characteristics and the above-mentioned properties is also recommended. The results obtained about the mechanical characteristics of potatoes cv. Spunta can be useful in providing information that aids in designing potato harvesting machines and in potato products factories. Full article