Irrigated Fields Research Articles

Chapter 5. Finding and understanding ancient irrigated agricultural fields in southern Arizona

AbstractFor over a century, archaeologists have investigated the vast network of prehistoric Hohokam canal irrigation systems in the lower Salt River and middle Gila River valleys, as well as in other areas of southern Arizona. However, documentation of the agricultural fields in which prehistoric farmers irrigated their crops generally was lacking until the last 25 years. This is largely a result of the difficulty in identifying ancient fields, since they are not visible on the surface and have been obscured or destroyed by natural landscape processes as well as historic and modern disturbances. More recent archaeological investigations have revealed ancient irrigated fields through innovative methods and excavation techniques. The fields were constructed both by Hohokam irrigators (450–1450 CE) as well as by farmers from preceding cultural traditions during the Early Agricultural period (2100 BCE–50 CE). These discoveries occurred during projects conducted in compliance with the National Historic Preservation Act. In this chapter, I highlight these important studies that have expanded the view of ancient agricultural landscapes in southern Arizona.

Agronomic performance of Ciherang near-isogenic lines for nitrogen use efficiency trait in irrigated lowland paddy field

Abstract Nitrogen (N) is an essential nutrient that affects plant growth and productivity. The consumption of N fertilizer is continuously increasing with the rapid demand for agricultural production. However, the rise in N fertilizer utilization causes higher production costs and leads to a negative impact on the environment. Improvement in nitrogen use efficiency (NUE) of rice plants is therefore important for sustainable rice production to reduce N fertilizer consumption while maintaining high grain yield. To improve the NUE of Indonesian elite cultivars, near-isogenic lines (NILs) with Ciherang genetic background have been developed by introducing genes related to N use efficiency, qRL6.1, and actpk1 through backcross breeding. Preliminary yield trials were conducted to evaluate the agronomic performance of CiherangNILqRL6.1 and CiherangNILactpk1 rice lines under optimum N fertilizer conditions in irrigated lowland fields for two seasons, wet season 2021/2022 and dry season 2022. Observations were performed on flowering time, biomass, yield, and yield component of NILs and Ciherang. The result from this preliminary observation indicated that under optimum N fertilizer, the agronomic performance of the NILs was comparable to Ciherang as the genetic background. Some NILs showed higher grain yield compared to Ciherang and were selected for further experiments to evaluate their performance under different N fertilizer conditions.

Smart irrigation system using node microcontroller unit ESP8266 and Ubidots cloud platform

The agricultural irrigation system is extremely important. For optimal harvest yields, farmers must manage rice plant quality by monitoring water, soil, and temperature on agricultural fields. If market demand rises, traditional rice field irrigation in Indonesia will make things harder for farmers. This modern era requires a system that lets farmers monitor and regulate agricultural fields anywhere, anytime. We need a solution that can control the irrigation system remotely using an internet of things (IoT) device and a smartphone. This study employed the Ubidots IoT cloud platform. In addition, the study uses soil moisture and temperature sensors to monitor conditions in agricultural regions, while pumps function as irrigation systems. The test results indicate the proper design of the system. Each trial collected data. The pump will turn on and off automatically based on soil moisture criteria, with the pump active while the soil moisture is less than 20% and deactivated when the soil moisture exceeds 20%. In simulation mode, the pump operates for an average of 0–5 seconds of watering. The monitoring system shows the current soil temperature and moisture levels. Temperature sensors respond in 1-3 seconds, whereas soil moisture sensors respond in 0–4 seconds.

Smart irrigation system using node microcontroller unit ESP8266 and Ubidots cloud platform

The agricultural irrigation system is extremely important. For optimal harvest yields, farmers must manage rice plant quality by monitoring water, soil, and temperature on agricultural fields. If market demand rises, traditional rice field irrigation in Indonesia will make things harder for farmers. This modern era requires a system that lets farmers monitor and regulate agricultural fields anywhere, anytime. We need a solution that can control the irrigation system remotely using an internet of things (IoT) device and a smartphone. This study employed the Ubidots IoT cloud platform. In addition, the study uses soil moisture and temperature sensors to monitor conditions in agricultural regions, while pumps function as irrigation systems. The test results indicate the proper design of the system. Each trial collected data. The pump will turn on and off automatically based on soil moisture criteria, with the pump active while the soil moisture is less than 20% and deactivated when the soil moisture exceeds 20%. In simulation mode, the pump operates for an average of 0–5 seconds of watering. The monitoring system shows the current soil temperature and moisture levels. Temperature sensors respond in 1-3 seconds, whereas soil moisture sensors respond in 0–4 seconds.

Assessing irrigation water demand and pumping operations for rice farming in the Bengawan Solo River, Indonesia

Owing to population growth, the rice demand in Indonesia has been increasing, which has led to an increase in rice consumption. One way to boost rice production is to enhance pump irrigation in rainfed fields. The aim of this study is to evaluate irrigation water usage and water pumping practices in the Bengawan Solo River, focusing on enhancing rice production. Data were sourced from governmental entities, which include the Indonesian Bureau of Meteorology, Climatology, and Geophysics and the Ministry of Public Works and Housing. Water requirement was calculated using the FAO Penman–Monteith equation. The study highlights that throughout the three distinct growing seasons (GS), the water requirements for irrigating rainfed rice fields vary, with the most substantial demand observed during the first growing season (GS I), followed by the third growing season (GS III), and the second growing season (GS II). In dry years, a consistent pattern of low water balances occurs, which persists below 500 mm across all months. Compared with the other two scenarios, the dry year shows higher variability in rainfall, as evidenced by its higher coefficient of variation of 0.620 compared with 0.347 and 0.416 for the wet and normal years, respectively. The electricity cost rate peaks in GS I, trailed by GS II and GS III, with rates of IDR 2,400, 1,180, and 1,028 per kilowatt-hour, respectively. The findings play a pivotal role in shaping regional planning decisions regarding the utilization and necessity of river water resources and the development of cropping calendars.

Warming effect of the desert regulates spatio-temporal distribution of cotton Verticillium wilt for the oasis agriculture ecosystem

Verticillium wilt (VW) is threatening global cotton yield and quality. However, the accurate spatio-temporal dynamics of cotton VW in large regions remain unclear, especially in the complicated oasis agriculture ecosystem. We explored the spatio-temporal distribution of VW in the cotton-dominated region of Northern Xinjiang characterized by a typical desert-oasis irrigation agriculture ecosystem, utilizing reconstructed high-resolution time series remote sensing data from 2019 to 2021. Results revealed that the area of VW-infected cotton remained consistently around 20 % each year. However, there were significant seasonal variations, with outbreaks peaking in August. Regarding the spatial pattern of cotton VW, the mean temperature (TMP) difference in irrigated cotton fields along the Gurbantunggut Desert-oasis gradient reaches a maximum of approximately 1 ℃ caused by warming effect of the desert on the oasis (WEDO) during the cotton growing period. This TMP difference drives the spatial pattern of cotton VW incidence characterized by a low-to-high-to-moderate trend. WEDO significantly suppresses the cotton VW incidence due to relatively higher TMP, forming the low-risk zone for cotton VW within 16 km near the Gurbantunggut Desert. Our study significantly enhances the understanding of the spatio-temporal dynamics of cotton VW in the distinctive oasis irrigation agricultural ecosystem and advances the accurate monitoring and assessment of cotton VW across large regions.

Downscaling the MODIS land surface temperature using a trapezial concept applied to the MODIS and sentinel 2 images.

Downscaling methods are crucial for accessing high-resolution thermal data simultaneously. The DisTRAD model is commonly used for downscaling thermal images, but changes in soil moisture, such as those caused by irrigation operations, can lead to errors in the process. This study investigated the potential use of TOTRAM and OPTRAM models to reduce errors in LST downscaling in irrigated fields. Sentinel satellite imagery was utilised to enhance the resolution of MODIS Land Surface Temperature (LST) from 1000 to 20 m in the fields of Megsal and Hezarjolfa agro-industrial company in Qazvin province. Soil moisture was estimated using the OPTRAM model, and the results were compared with observational data. The findings indicated that on days with NDVI greater than 0.6, the R2 value exceeded 0.88 and the RMSE value was less than 0.06 cm3/cm3. Then, MODIS LST images were downscaled to 20 m using codes in Google Earth Engine (GEE). Evaluation was conducted using observational data from collected land surface temperature data for 36 points. Comparison of the downscaled LST data with observational data on days with irrigation revealed a decrease in MAE and RMSE error indices by approximately 0.4 and 1.2 degrees Celsius, respectively, in the OPTRAM-TPTRAM model compared to the DisTRAD model. Consequently, the OPTRAM-TOTRAM model generally outperforms the DisTRAD model in LST downscaling. Lastly, it is recommended to assess the TOTARM and OPTRAM models for downscaling MODIS sensor LST in other irrigated fields.

Monitoring small-scale irrigation performance using remote sensing in the Upper Blue Nile Basin, Ethiopia

Temporal and spatial irrigation performance indicators are crucial in informing decisions for improving the efficiency and sustainability of water and land resources. However, evaluating these indicators requires reliable and cost-effective data, which is challenging to obtain, particularly for small-scale irrigation schemes. This study aimed to assess the performance of a small-scale irrigation scheme using remote sensing and ground truth data for the 2021/22 and 2022/2023 irrigation seasons employing the Shimburit irrigation scheme in Northwestern Ethiopia, predominantly cultivated with wheat, as a case study. The performance indicators, including equity, adequacy, overall consumed ratio (OCR), and productivity, were assessed. The actual evapotranspiration (ET), the main input for performance assessment, was estimated using the surface energy balance for land – improved (SEBALI) model in the Google Earth Engine (GEE) platform. The results revealed good equity within the scheme, with a coefficient of variation of ETa value per field inside the scheme are 1.90 and 1.63 for the respective seasons. The water use adequacy across the fields was assessed to be very good in the two seasons. The scheme's overall consumed ratio (OCR) was 0.54 and 0.43 during the two subsequent seasons. Water productivity of wheat is 3.03 kg/m3 and 3.06 kg/m3 in the two seasons. However, due to untimely rainfall during harvest, land productivity declined from 3.25 tons/ha in the first season to 2.08 tons/ha in the second season. The study demonstrates the potential of using remote sensing to evaluate irrigation performance indicators and water productivity in smallholder irrigated fields.

A Pathway Analysis of Evapotranspiration Variation Characteristics and Influencing Factors of Summer Maize in the Haihe Plain

The Haihe Plain in China is situated in the world’s largest groundwater funnel area, with per capita water resources far below the internationally recognized “extremely water-scarce” standard. To address the issue of water shortage in summer maize-planting areas of the Haihe Plain, we conducted research on the variation of summer maize evapotranspiration using a medium-sized lysimeter. This study aims to provide technical support for water-saving irrigation in summer maize fields. Through path analysis, direct and indirect influencing factors affecting the evapotranspiration of summer maize fields were determined. The results showed that the cumulative evapotranspiration of bare ground and farmland during the entire growth period of summer maize was 173.57 mm and 382.97 mm, respectively, with evapotranspiration intensities of 1.52 mm/d and 3.36 mm/d, respectively. Evapotranspiration during the maturity stage of summer maize was the least, accounting for only 1.82% of total evapotranspiration during the entire growth period. The period from the jointing to milk-ripening stage is when evapotranspiration in maize fields is at its highest. During this period, evapotranspiration in maize fields amounted to 265.58 mm, accounting for 69.35% of total evapotranspiration. The evapotranspiration intensity was 3.59 mm/day, which is 1.34 times higher than that of bare soil. The evapotranspiration intensities during each growth stage were ranked as jointing stage > tasseling-silking stage > seedling stage > milk maturity stage > maturity stage. The daily evapotranspiration of summer maize fields showed a “unimodal” curve with low values in the morning and evening, and high values at noon. Path analysis indicated that daily radiation and maximum daily temperature had the greatest impact on the evapotranspiration of maize fields, with the direct effect of maximum daily temperature being restrictive and the indirect effect being promotive, resulting in an overall promotive effect.

Carbon dioxide fluxes over irrigated and rainfed alfalfa in the Southern Great Plains, USA

The annual dynamics of carbon dioxide (CO2) fluxes for irrigated and rainfed alfalfa (Medicago sativa L.) in the Southern Great Plains of the United States of America (USA) under different watering regimes are not yet fully understood. The main objective of this study was to examine the dynamics of eddy covariance (EC) measured CO2 fluxes in relation to various biophysical factors and hay harvests for irrigated and rainfed alfalfa in central Oklahoma, USA. The study also aimed to investigate the relationship between CO2 fluxes and satellite-derived enhanced vegetation index (EVI) at different spatiotemporal scales and to assess the temporal variability in CO2 fluxes and EVI to variable growing conditions and hay harvests. The cumulative hay yields were 7.15 t ha−1 (two harvests in 2019) in the rainfed field and ∼9 t ha−1 (4–5 harvests in 2020 and 2021) in the irrigated field. Having sufficient rainfall during April and May was crucial to achieve economically feasible yields of alfalfa during the first harvest in May. The availability of water strongly regulated the potential for regrowth and carbon uptake of alfalfa following harvesting. The alfalfa fields were near carbon neutral or a small carbon source from January to mid-March and carbon sink after the initiation of vegetative growth in mid-March. The alfalfa fields were strong carbon sinks (cumulative annual net ecosystem CO2 exchange, NEE, up to −578 g C m−2 in irrigated field) on an annual scale. When accounting for the loss of carbon due to the removal of hay from the fields, the carbon balance of the alfalfa fields varied from small carbon sinks to small carbon sources, depending on the amount of hay harvested annually and the growing conditions. In general, the temporal patterns of CO2 fluxes and EVI were similar in relation to growing conditions and hay harvests. However, some discrepancies and time lags were observed due to the coarse spatiotemporal resolution of the EVI products. Thus, it is essential to integrate two or more satellite products with different temporal and spatial resolutions to accurately monitor the frequent and varying sizes of hay harvests and vegetation regrowth after harvesting, and to simulate continuous time-series CO2 fluxes.

Observations of electrical resistivity tomography and groundwater level under an irrigated terraced paddy field in northern Taiwan

Observations of electrical resistivity tomography and groundwater level under an irrigated terraced paddy field in northern Taiwan

Implementasi Pemanfaatan Pembangkit Listrik Tenaga Surya (PLTS) untuk Peningkatan Produktivitas Budidaya Ikan dan Pertanian di Kalurahan Sumbersari

Kalurahan Sumbersari, a border village in Sleman Regency, possesses significant potential in natural resources, particularly in agriculture and fisheries. However, the village faces substantial challenges, including inadequate aeration systems for fishponds and irrigation difficulties for rice fields. This community service initiative aims to address these issues by implementing solar energy-based solutions. The activities involved the design of an optimized aeration system for fishponds, the strategic installation of water pumps to facilitate rice field irrigation, and the construction of a Solar Power Plant (PLTS). The adoption of solar energy not only aims to meet the electricity needs but also contributes to Indonesia's achievement of the Sustainable Development Goals (SDGs), particularly Goal 7, which focuses on Affordable and Clean Energy. The success of this project hinged on the active participation of the local community. Socialization and training sessions were conducted to ensure understanding of the aeration systems, water pump operations, and PLTS maintenance. It is anticipated that the implementation of these activities will resolve the fish health issues and irrigation difficulties, thereby enhancing fish and agricultural production in Kalurahan Sumbersari. In addition to these direct benefits, the use of renewable energy is also expected to mitigate the negative environmental impacts associated with fossil fuel energy consumption.

Deep vertical rotary tillage reduced soil salinity and improved seed cotton yield and water productivity under limited irrigation in saline-alkaline fields

Water scarcity and soil salinization severely limit cotton production in arid areas on the globe. A two-season (2020 and 2021) field experiment was performed on cotton under film-mulched drip irrigation in south Xinjiang of China to explore the responses of soil moisture, soil salinity, root growth, seed cotton yield and water productivity to deep vertical rotary tillage (DVRT) depth (T20: 20 cm, T40: 40 cm, T60: 60 cm, Tck: 20 cm, traditional rotary tillage) in saline-alkaline fields under two irrigation amounts (W1:360 mm, W2: 480 mm, local irrigation amount). It was found that the soil moisture storage (0–120 cm) increased with as irrigation amount increased and decreased with increasing DVRT depth. Soil electrical conductivity in the root zone (0–60 cm) and 0–120 cm soil layer declined as irrigation amount and DVRT depth increased. Irrigation amount and DVRT depth had significant effects on root length density, root mass density, root/shoot ratio, and seed cotton yield, all of which increased with increasing irrigation amount and DVRT depth. Under W2, T20, T40 and T60 increased seed cotton yield by 23.3 %, 45.3 %, 65.6 % in 2020, and by 38.9 %, 62.0 % and 84.1 % in 2021 compared with TCK, respectively. Both water productivity and irrigation water productivity increased with increasing DVRT depth. There were significant positive correlations among seed cotton yield and leaf area index, dry matter accumulation, harvest index, root length density, root mass density, root/shoot ratio, water productivity and irrigation water productivity. W1T60 was suggested for cotton production in the saline regions of southern Xinjiang. The DVRT offset the decrease in seed cotton yield under limited irrigation, which indicates that DVRT is promising to reduce soil salinity and improve seed cotton yield and water productivity in saline-alkaline fields for coping with water scarcity and soil salinization.

High‐Resolution Forensic Evaluation of Nitrate‐Contaminated Groundwater

AbstractDetermining the source(s) of nitrate contamination in agricultural areas is complicated; doing this as a forensic evaluation for litigation in one field week is especially challenging. The objective of this 2021 investigation, conducted for an agricultural producer who began applying animal waste in 2007, was to determine whether animal waste was the source of nitrate reported at downgradient residential wells. The test Site was a 180 acre, irrigated field that overlies a thick sand aquifer with the water table at about 20 ft below ground level (fbgl). We used multiple lines of evidence to resolve the source(s) of nitrate at three test locations at the Site using continuous vertical testing for hydraulic conductivity and high‐resolution vertical testing of selected chemical and isotopic parameters in water at 5‐ft depth intervals between 5 and 80 fbgl. We found that beneath the Site at the depth interval of most of the impacted residential wells: (1) groundwater travel time indicates nitrate at the impacted residential wells could not have originated from the Site, (2) the groundwater age based on tritium (3H) pre‐dates the establishment of manure spreading, and (3) the nitrogen‐15 concentrations (δ15N) in nitrate indicate the nitrate is not all, if in any part, due to animal waste. This high‐resolution investigation clearly indicated that the agricultural producer was not responsible for the impacted residential wells and was completed in only 1 week.

Assessment of Increasing Rice Plant Index 400 with the Application of Environmentally Friendly Rice Cultivation Technology in Irrigation Land, Banjar City, West Java

Abstract Achieving rice self-sufficiency is the main target of the Ministry of Agriculture in order to meet the demand for rice consumption which continues to increase every year. Various efforts have been made, including through a program to increase the Rice Planting Index (PI) from 300 to 400 or from three times to four times in one year. The research aim was to determine the technical and financial feasibility of increasing PI Paddy 400 by applying Environmentally Friendly Rice Cultivation (EFRC) technology to irrigated paddy fields. The study was carried out in an irrigated paddy field in Pataruman Village, Pataruman District, Banjar City, West Java Province, Indonesia. The study used an adaptive research approach on 2.0 ha of farmers’ land involving 12 implementing farmers (cooperators). The assessment will be carried out in 2021, starting from the 2nd Planting Season (PS) to the 4th PS, while the 1st PS activities have been carried out by farmers. The technology adapted is the early maturing New Superior Varieties (NSV) Cakrabuana and M70D as well as setting cropping patterns and implementing EFRC technology packages. The results of the study show that the use of NSV Cakrabuana and M70D can speed up harvest time, so that they can harvest four times in one year. EFRC technology can increase rice production for one year by 24.24% from 16.5 to 20.5 tons of dry harvested grain (DHG). Farmers are still hesitant to develop PI 400 rice technology even though it is financially profitable and feasible with an RC Ratio of 1.84.

Erosion characteristics of a centrifugal pump based on rosin-rammler distribution of particles

Abstract Centrifugal pumps are widely used in water conservancy, agricultural irrigation and petrochemical fields, but the transferred fluid usually contains solid particles. With prolonged operation in a solid-liquid flow, the components of centrifugal pump are easily eroded, resulting in damaged components, shortened life and reduced efficiency. It is crucial to study the erosion characteristics on centrifugal pump in solid-liquid flow. In this work, based on the particles with Rosin-Rammler distribution in a pump station, the transient operation and erosion process of the centrifugal pump under sandy flow are simulated by using the Eulerian-Lagrangian method and Oka model. Results show that the erosion of R-R distribution is characterized by both large and small particle sizes, but it is closer to the latter condition due to the higher proportion of small particle sizes. The distribution ratio of average erosion rate on hub, blade and shroud is 1.18: 1.68: 1.00, and the most eroded areas are in the leading edge of blade and the trailing edge of the blade suction surface.

Customizing pyfao56 for evapotranspiration estimation and irrigation scheduling at the Limited Irrigation Research Farm (LIRF), Greeley, Colorado

Estimation of evapotranspiration (ET, the water used by soil evaporation and plant transpiration) and soil water depletion (Dr, the amount of water to bring the soil water in the root zone to field capacity) are critical in irrigation water management. The open-source Python-based crop ET and water balance modeling package named “pyfao56” was originally developed based on the dual crop coefficient approach as described in the Food and Agricultural Organization of the United Nations, Irrigation and Drainage Paper No. 56 (FAO-56). The package later expanded on the seminal FAO-56 document to consider various options relevant to ET and water balance modeling, including both short (grass) and tall (alfalfa) reference crops, optional discretization of variable soil layers based on field capacity, and interpretation of readily available water (RAW) and Dr based on both a dynamic (growing) root zone and maximum root zone. The package requires two input data objects; the “Parameters” class defines variables affecting soil water balance and ET and the “Weather” class specifies relevant meteorological data. Other optional input data objects include the “Irrigation” class for irrigation events, the “Soil_Profile: class for defining stratified soil layer data, and the “Update” class for assimilation of measured data. Additional tools are available for estimating and forecasting standardized reference ET (ETref), providing seasonal water balance summaries, computing goodness-of-fit statistics between measured and modeled values, and visualizing time series plots of daily Dr, ET, and crop coefficients. The current pyfao56 release (v1.2.1) was incorporated into a customized workflow for specific use at the USDA-ARS Limited Irrigation Research Farm (LIRF) in Greeley, Colorado, and named the LIRF Implementation of Pyfao56 (LIRFIP). Field data from 2023 full and limited irrigation field trials were used to demonstrate the functionality of LIRFIP and its customizations and integration of pyfao56 into the LIRF workflow. Specific customizations included use of pyfao56 “customload” functions to input data from various sources, including weather from an on-site micrometerological station (using the application programming interface (API) developed by the maintainers of the Colorado Agricultural Meteorological (CoAgMet) weather station network), irrigation events (via a shared Google docs sheet), field capacity values by plot and soil layer (via an Excel spreadsheet), and measured soil water content as well as basal crop coefficient (Kcb) calculated from fractional canopy cover (fc) (via an SQLite database). To evaluate multiple research plots, LIRFIP was designed to iterate simulations from multiple instances of pyfao56 and to produce customized output summary files and interactive hypertext markup language (html) graphs as an aid for irrigation management decisions for LIRF field trials. This study demonstrated pyfao56 as a useful, flexible, customizable, and repeatable ET-based water balance model by showcasing its integration within a specific computational workflow for irrigation management field research at LIRF. The approach serves as an example for pyfao56 integration in other water management tools as conceived by water managers, researchers, and practitioners worldwide.

Effects of heat exposure from late sowing on agronomic traits and the technological quality of hexaploid wheat

Heat stress reduces wheat grain yield and affects quality traits relevant to trading and end use. In this study, 98 landraces and 152 elite hexaploid wheat varieties and breeding lines were trialled at two irrigated field sites in southern NSW to better understand heat stress responses and identify promising genotypes for heat tolerance breeding. Potential heat tolerance was defined using performance in heat-exposed late-sown (LS) plots relative to normal-sown (NS) plots, using a regression approach to calculate response indices uncorrelated with awn emergence time and performance per se in NS. The best individual responders for grain yield included genotypes from both Australia and Mexico. On average, lines selected in CIMMYT's High Temperature Wheat Yield Trials (HTWYT) performed well for yield per se in NS as well as for yield response to LS. CIMMYT lines previously selected for large grains under heat stress conditions performed well for grain size in NS and for LS responses of grain size and test weight. Dough peak resistance and time to peak resistance in a mixograph were increased by LS and these traits were positively correlated with grain protein and the occurrence of the Glu-D1d high molecular weight glutenin locus allele, respectively.

Assessment of Water Resources Potential of Ogun River for Irrigation Purposes at Middle Ogun Irrigation Project

The Middle Ogun Irrigation Project (MOIP) was conceived by the Federal Government of Nigeria to boost agricultural food production in the southwestern part of the country using modern irrigation facilities. However, water supply from the Ikere Gorge dam has been intermittent, particularly at the intake weir of this project, despite the enormous water resources on the dam. Therefore, this project assessed the water resources potential at the Odo Ogun intake weir guage station of the Middle Ogun Irrigation Project and evaluated the seasonal irrigation requirements on irrigation fields. The Flow Duration Curve (FDC) was derived at the gauge site for streamflow discharge from four quartiles and percentage reliability of Q95%, Q75%, Q50% and Q25%, which gave 32.40, 55.01, 60.00 and 90.00 m3/s, respectively. Hydrological modelling of the catchment was carried out using the MapWindow Soil and Water Assessment Tool (MWSWAT) for ten delineated sub-basins on the catchment and the average annual yield from the catchment was 10,094.00 mm/year. The net seasonal irrigation requirement of crops grown was evaluated using CROPWAT 8.0 and gave 428.46 mm per planting season.

Compensation of cotton yield by nitrogen fertilizer in non-mulched fields with deficit drip irrigation

Irrigation and fertilization are the main measures used by farmers to maintain crop yield and quality, especially in arid and semi-arid regions. To investigate the compensation of cotton yield loss due to deficit drip irrigation in non-mulched fields by increasing nitrogen (N) fertilizer application, a split-plot experiment with irrigation amount as the main plot and N application as the subplot was carried out in southern Xinjiang, China. The experiment included two irrigation amounts of 450 mm (deficit irrigation, W1) and 540 mm (full irrigation, W2) and three N application rates of 150 kg ha−1 (F1), 225 kg ha−1 (F2), and 300 kg ha−1 (F3). From the cotton seedling stage, ET0 (reference evapotranspiration) was calculated from daily meteorological data and irrigation was applied when the cumulative ET0-P reached 45 ± 3 mm. The results showed that irrigation and fertilization significantly affected soil moisture and total N, which in turn affected cotton growth, biomass formation, and yield (P<0.05). Soil water storage (SWS) increased by 15.9% on average under W2 compared to W1. F2 and F3 decreased SWS by 5.0%-5.1% and 7.7%-10.9% respectively, compared to F1. Total soil nitrogen in W2 was on average 13.3% lower than W1, and F2 and F3 were 4.4%-11.1% and 11.3%-16.5% lower than F1, respectively. Aboveground biomass increased significantly with increasing irrigation and N amounts and was 47.9% higher in W2F3 than in W1F1. However, the increased biomass was not translated into yield and excessive accumulation of root and stem biomass reduced cotton yield. Under full irrigation (W2), cotton yield increased and then decreased with increasing N application. Cotton yield in F2 increased by 3.4% and 8.6% compared to F1 and F3, respectively. Under deficit irrigation (W1), N fertilizer compensation increased with increasing N application, and cotton yield in F3 increased by 10.3% and 15.0% compared to F1 and F2, respectively (P<0.05). TOPSIS analysis showed that W1F3 had the highest rank, followed by W1F2. The results indicated that W1F3, irrigation amount of 450 mm and N application rate of 300 kg ha−1, could be proposed for cotton fields under non-mulched drip irrigation in southern Xinjiang, China.