Irrigation and Drainage最新文献

{"title":"Restructuring the Knowledge Platforms of ICID","authors":"Ashwin B. Pandya","doi":"10.1002/ird.2935","DOIUrl":"https://doi.org/10.1002/ird.2935","url":null,"abstract":"","PeriodicalId":14848,"journal":{"name":"Irrigation and Drainage","volume":"73 1","pages":"378-380"},"PeriodicalIF":1.9,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139744901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Guest editors and referees 2023","authors":"","doi":"10.1002/ird.2936","DOIUrl":"https://doi.org/10.1002/ird.2936","url":null,"abstract":"","PeriodicalId":14848,"journal":{"name":"Irrigation and Drainage","volume":"73 1","pages":"381-384"},"PeriodicalIF":1.9,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139744902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reply to commentary by Offer Rozenstein on ‘Is the crop evapotranspiration rate a good surrogate for the recommended irrigation rate?’","authors":"Shmulik P. Friedman","doi":"10.1002/ird.2865","DOIUrl":"https://doi.org/10.1002/ird.2865","url":null,"abstract":"<p>I thank Offer Rozenstein for his commentary, and I agree with most of the things he wrote, those that refer to the original article (Friedman, <span>2023</span>) and those that are not directly related to its main idea. The main idea of that short article was that optimal irrigation (from an agronomic or economic point of view) is usually at a rate higher or lower than the actual evapotranspiration (ET<sub>c act</sub>) rate of the crop (Rozenstein agrees with this main idea).</p><p>For example, Figure 1 displays the water consumption (ET<sub>c act</sub>) of cotton (cv. <i>Pima</i>) that Rozenstein et al. (<span>2018</span>) estimated by remote sensing of plant indices, in very good agreement with ground measurements using the eddy covariance method. Also displayed in this figure are the daily irrigation dose recommendations (in terms of <i>K</i><sub>c</sub> to be multiplied by ET<sub>0</sub>) of the Israeli Extension Service (IES) for that region, which were higher during most of the irrigation season and amounted to seasonal irrigation that was about 10% higher than the evaluated estimated crop evapotranspiration (until day of year [DOY] 227). The question arises: Are the recommendations of the IES higher than the (agronomical or economical) optimal irrigation rate? The answer is probably: No. Irrigation according to the IES recommendations which are at a multi-annual average rate of about 490 mm per season results in a yield of about 5300 kg ha<sup>−1</sup> and an income of about $15,900 ha<sup>−1</sup> (current cotton market price is about $3 kg<sup>−1</sup>). According to the cotton yield–irrigation production functions under various conditions (Dağdelen et al., <span>2009</span>; Shalhevet et al., <span>1979</span>; Wanjura et al., <span>2002</span>), it seems that reducing the seasonal irrigation amount by about 10% would have reduced the yield by about 5% and the grower's profit by 4%, $650 ha<sup>−1</sup> (accounting for only the cotton market price and irrigation water price of ~ $0.3 m<sup>−3</sup>). And what about the seasonal course of the irrigation dose recommended by the IES concerning the seasonal course of the crop's water consumption? Does it make sense to irrigate at rates higher than the actual ET at earlier stages and lower than the ET towards the end of the growing season (until eventually stopping irrigation at 30%–40% open bolls)? Yes, that makes sense. In the first growth stages, the root systems are small and cannot take up most of the water supplied from the point sources in drip irrigation, so it is necessary to irrigate in excess. It is also necessary to prevent the accumulation of harmful salinity. On the other hand, towards the end of the growing season, the available water in the soil profile can be utilized and it can be dried. In the case of cotton, in addition to water saving, the activation of water stress may improve fibre quality and promote natural defoliation resulting in a more efficient and effective h","PeriodicalId":14848,"journal":{"name":"Irrigation and Drainage","volume":"73 1","pages":"375-377"},"PeriodicalIF":1.9,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird.2865","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139744900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of soil moisture using machine learning techniques: A case study of an IoT-based irrigation system in a naturally ventilated polyhouse","authors":"Lakshmi Poojitha Challa,&nbsp;Chandra Deep Singh,&nbsp;Kondapalli Venkata Ramana Rao,&nbsp;Anakkallan Subeesh,&nbsp;Mandru Srilakshmi","doi":"10.1002/ird.2933","DOIUrl":"10.1002/ird.2933","url":null,"abstract":"<p>The agricultural sector faces a massive challenge in enhancing food production for the growing population with limited water resources. For effective and optimum utilization of fresh water, developing smart irrigation systems based on the internet of things (IoT) is essential for scheduling irrigation based on crop water requirements. In this study, an IoT-based irrigation system was developed and evaluated inside a greenhouse located in the experimental fields of Indian Council of Agricultural Research-Central Institute of Agricultural Engineering (ICAR-CIAE), Bhopal, India. Data on microenvironmental parameters such as temperature, relative humidity, light intensity, soil temperature and soil moisture were collected from the sensors developed inside the greenhouse. Soil moisture was predicted based on the field data collected via different machine learning techniques, such as the decision tree (DT), random forest (RF), multiple linear regression (MLR), extreme gradient boosting (XGB), K-nearest neighbour (KNN) and artificial neural network (ANN) methods, with three input combinations. The ANN (coefficient of determination [<i>R</i>²] = 0.942, 0.939) models performed well but were found to be less effective than the RF (<i>R</i>² = 0.991, 0.951) and XGB (<i>R</i>² = 0.997, 0.941) models in the training and testing phases, respectively. The RF and XGB models outperformed the other models, while the MLR (<i>R</i>² = 0.955, 0.875) technique underperformed. With respect to both the testing and training datasets, the models trained with all four inputs outperformed the models trained with two or three inputs.</p>","PeriodicalId":14848,"journal":{"name":"Irrigation and Drainage","volume":"73 3","pages":"1138-1150"},"PeriodicalIF":1.6,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139791644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing zero-till direct seeding at variable water stress levels compared to traditional puddled transplanting of rice under groundwater-fed irrigation systems in north-west India","authors":"Satyendra Kumar,&nbsp;Bhaskar Narjary,&nbsp;Kalpana Paudyal,&nbsp;Rajender Kumar Yadav,&nbsp;Sushil Kumar Kamra","doi":"10.1002/ird.2930","DOIUrl":"10.1002/ird.2930","url":null,"abstract":"<p>Irrigation of rice using groundwater is considered one of the main contributors to north-west India's declining water level. The present study hypothesizes that zero-till direct seeding of rice (ZTDSR) with the optimum irrigation schedule may reduce irrigation compared to puddled transplanted rice (PTR). Crop growth stage-dependent predefined soil matric potential (SMP), that is, −15, −30 and −45 kPa based irrigation schedules either during the entire growing period or their combinations during the vegetative phase in ZTDSR, were compared with PTR for two consecutive seasons. The results showed that irrigation in ZTDSR at lower SMP at any growth stage caused adverse effects on yield. Irrigation at −15 kPa during the entire crop season with straw mulch was found to be the best schedule for ZTDSR. ZTDSR with −15 kPa irrigation, however, saved 36.2 cm of water and recorded higher water productivity but produced 20% less grain yield over the prevailing PTR. A higher groundwater system loss (GWSL) was found in the PTR (29.2 cm) than in the best ZTDSR (23.6 cm) schedule, which indicates better groundwater management in the ZTDSR than in the PTR. Hence, the ZTDSR has the potential to save irrigation, achieve higher water productivity and manage the depletion of groundwater resources in rice–wheat dominant north-west India.</p>","PeriodicalId":14848,"journal":{"name":"Irrigation and Drainage","volume":"73 3","pages":"928-943"},"PeriodicalIF":1.6,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139799895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimation of loss in arable land and irrigation requirements using high-resolution imagery and Google Earth Engine","authors":"Majid Farooq,&nbsp;Fayma Mushtaq,&nbsp;Ubaid Yousuf","doi":"10.1002/ird.2931","DOIUrl":"10.1002/ird.2931","url":null,"abstract":"<p>Water resources planning and management are critical in intricate basins such as the Indus Basin, shared by India and Pakistan under the Indus Water Treaty (IWT) for food security, conserving the environment, sustainable economic development and supporting livelihoods. The present study assesses arable land loss within the Padshahi and Sindh Extension (SE) canal catchments over 54 years, utilizing high-resolution satellite imagery and Google Earth Engine's normalized difference vegetation index (NDVI) derivations for strategizing irrigation efficiency, minimizing water loss and ensuring sustainable utilization of limited water resources under the IWT. Results revealed that irrigated land has decreased from 5127 ha (1966) to 3501 ha (2020) in both canals. The Padshahi canal sees substantial loss (1278 ha), primarily due to the highest transitions from agricultural land/crop land (−69%) to built-up areas. The SE canal, experiencing shifts to horticulture and plantation, records relatively fewer changes in built-up areas (348 ha). The monthly variation in the NDVI clearly depicted the high demand for irrigation to cater to agricultural lands with the onset of the sowing season for paddy in the Padshahi (1900 ha) and SE (2600 ha) canals in May.</p>","PeriodicalId":14848,"journal":{"name":"Irrigation and Drainage","volume":"73 3","pages":"1151-1167"},"PeriodicalIF":1.6,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140478779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling land suitability and development potential options for irrigable and rainfed agricultural scenarios in Ethiopia","authors":"Hailu Shiferaw Desta","doi":"10.1002/ird.2929","DOIUrl":"10.1002/ird.2929","url":null,"abstract":"<p>Despite being a significant sector in Ethiopia, agriculture is mainly run in rainfed system. However, it is imperative to look for irrigation systems and their suitability to the country's agriculture. The study's objectives were to (1) map areas appropriate for irrigable and rainfed agriculture and examine gaps with current active areas, (2) model possible development for irrigation and rainfed scenarios, and (3) offer evidence-based decision support for agricultural investment. Land features, agroecology, population density, market accessibility and length of growing seasons were considered as important indicators when determining land suitability for each scenario. Geographically weighted regression was used to model these indicators. The results show that approximately 359,360 (34%) and 13,802 km² (1.6%) are highly suitable areas for irrigation and rainfed agriculture, respectively. However, Ethiopia's production depends on areas moderately suitable for rainfed agriculture, but these areas are highly suitable for irrigation rather, indicating that it is unfortunate that the areas suitable for irrigation are used for rainfed agriculture so far. In terms of development potential, areas of approximately 71,317 (7%) and 347,435 km² (33%) had the highest and a high irrigation potential, respectively, while areas with rainfed agriculture had approximately 33,821 (3%) and 105,013 km² (10%) with the highest and a high development potential, respectively. These analyses suggest that the country has untapped potential for agricultural development in both scenarios, but this remains within the scope identified in this study.</p>","PeriodicalId":14848,"journal":{"name":"Irrigation and Drainage","volume":"73 3","pages":"1168-1191"},"PeriodicalIF":1.6,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140480286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Farmers on the front line: Perceptions, practices and discrepancies from the Aral Sea's Karakalpakstan and Khorezm regions","authors":"Kakhramon Djumaboev,&nbsp;Iroda Amirova,&nbsp;Abdulla Primov,&nbsp;Javlonbek Ishchanov","doi":"10.1002/ird.2922","DOIUrl":"10.1002/ird.2922","url":null,"abstract":"<p>Undesirable changes in surface water and groundwater resources and land quality for biophysical and institutional reasons will further endanger the livelihoods of people in Central Asia. The farmers' understanding of these problems and the adaptation and solution strategies they opt for are the critical variables in devising relevant policies. Our findings captured significant disparities between farmer-perceived water shortages and officially documented water availability, as well as soil salinity discrepancies. Farmers' coping strategies, including crop alterations and water-saving measures, often lead to trade-offs, such as reduced crop yields. The study highlights the need to consider farmer perceptions and practices along with official data when designing policies. Effective policymaking must consider this dynamic interplay and the multifaceted challenges faced by farmers in these vulnerable Aral Sea regions.</p>","PeriodicalId":14848,"journal":{"name":"Irrigation and Drainage","volume":"73 3","pages":"1102-1118"},"PeriodicalIF":1.6,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139598743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The effect of soil texture, layering and water head on the infiltration rate and infiltration model accuracy","authors":"Azizeh Alizadeh Berdouki,&nbsp;Sina Besharat,&nbsp;Kamran Zeinalzadeh,&nbsp;Cristina Cruz","doi":"10.1002/ird.2918","DOIUrl":"10.1002/ird.2918","url":null,"abstract":"<p>Infiltration is one of the most important physical characteristics of soil and depends on various factors. This study investigated the influence of soil texture, layering and water head on the soil water infiltration rate. It also selected the most accurate infiltration models to determine the water infiltration rate in homogeneous and heterogeneous soil profiles. Experiments were carried out in four soil containers with a length, width and height of 20 × 20 × 70 cm. Treatments consisted of two soil textures (sandy loam, SL; clay loam, CL), four soil profiles (homogeneous texture, SL and CL; and heterogeneous texture, lighter texture on the top, SL/CL, and heavier texture on the top CL/SL) and three water head sizes (4, 7 and 10 cm). Several models were used to determine the water infiltration rate under homogeneous (Kostiakov, modified Kostiakov, Philip, Horton, traditional Green–Ampt, modified Green–Ampt and HYDRUS-1D) and heterogeneous soils (traditional Green–Ampt, modified Green–Ampt and HYDRUS-1D). According to the results, the infiltration rate decreased over time and along the soil profile. Nevertheless, it jumped at the interface of two-layered soils when the heavier soil was in the bottom layer (SC treatments) due to the high potential of the second layer, and then it decreased. In the reverse layering, the infiltration rate in the interface was lowest (CS treatments) because of the higher hydraulic conductivity of the second layer. Additionally, the infiltration rate increased with increasing water head, but the rate of this increase was higher by changing the water head from 7 to 10 cm. The results of infiltration models showed that the accuracy of these models was higher in clay loam texture than in sandy loam texture. The modified Green–Ampt was the most accurate model in homogeneous and layered soils, with average RMSE of 0.0204 and 0.019, respectively. The Horton model had the weakest simulation in homogeneous soils, with an average RMSE of 0.1299. Additionally, the accuracy of HYDRUS-1D in layered soils was less than that in homogeneous soils (NS of 0.95 and 0.85, respectively), and its accuracy decreased with increasing water head in most treatments.</p>","PeriodicalId":14848,"journal":{"name":"Irrigation and Drainage","volume":"73 3","pages":"846-865"},"PeriodicalIF":1.6,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139603227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing multi-sensor hourly maize evapotranspiration estimation using a one-source surface energy balance approach","authors":"Edson Costa-Filho,&nbsp;José L. Chávez,&nbsp;Huihui Zhang","doi":"10.1002/ird.2923","DOIUrl":"10.1002/ird.2923","url":null,"abstract":"<p>In this study, the performance of a one-source surface energy balance (OSEB) remote sensing (RS) of actual crop evapotranspiration (ET_a), incorporating data from different spaceborne, airborne and proximal multispectral data, was evaluated. The RS platforms in this study included Landsat-8 (30 m pixel size), Sentinel-2 (10 m), Planet CubeSat (3 m), a handheld (proximal) multispectral radiometer (MSR) (1 m) and an unmanned aerial system (UAS) (0.03 m). A 2-year data set (2020 and 2021) from two maize research sites in Greeley and Fort Collins, Colorado, USA, provided ground-based data for estimating and evaluating hourly ET_a from the OSEB algorithm. The accuracy of OSEB hourly maize ET_a estimates was evaluated using calculated hourly maize ET_a using high-frequency data collected with an eddy covariance energy balance system installed at each research site. The results indicated that the Planet CubeSat multispectral sensor (3 m), combined with on-site surface temperature data, yielded the least errors when predicting maize ET_a. The hourly ET_a estimation errors for the Planet CubeSat were MBE ± RMSE of −0.02 (−3%) ± 0.07 (13%) mm h⁻¹. These results suggest the urgent need for a specific approach to improve RS multispectral and thermal radiometric data (quality) to better support sustainable irrigation water management practices.</p>","PeriodicalId":14848,"journal":{"name":"Irrigation and Drainage","volume":"73 3","pages":"988-1009"},"PeriodicalIF":1.6,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird.2923","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139605495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}