Pub Date : 2024-09-25DOI: 10.1016/j.agwat.2024.109071
Validating the satellite soil moisture products is always an active research topic for the application of the products and improvement of the retrieval algorithms, attracting extensive attention. Nevertheless, seldom existing validation activities focus on the validation of high-resolution soil moisture products at the fine scale. To this end, an experiment was conducted in the middle stream of the Heihe River Basin in northwestern China in August to October of 2021, aiming to validate high-resolution satellite remote sensing products of soil moisture. The paper introduces the design, composite, and preliminary results of the experiment. A soil moisture observation network was established with two kinds of sensors (CS616 and Stevens Hydra Probe) validated against soil core measurements. Several synchronized campaigns were performed, and data were collected to validate the SMAP/Sentinel-1 L2 Radiometer/Radar 30-Second Scene 3 and 1 km EASE-Grid Soil Moisture (SPL2SMAP_S) products. Besides, an optical trapezoid model (OPTRAM) and collected Sentinel-2 data were applied to estimate soil moisture and to map irrigated area. Preliminary analyses show that: 1) Steven probes perform best, with an RMSE = 0.040 m3m−3 and ubRMSE = 0.034 m3m−3; 2) Both the SPL2SMAP_S products at 3 km and 1 km show large RMSE (0.128 m3m−3 for 3 km and 0.158 m3m−3 for 1 km) and ubRMSE (0.115 m3m−3 for 3 km and 0.158 m3m−3 for 1 km); 3) The OPTRAM retrievals over bare surface present relatively smaller RMSE (0.06 m3m−3) and ubRMSE (0.057 m3m−3), while retrievals over vegetated croplands present a relatively large RMSE/ubRMSE (0.083/0.083 m3m−3), and the retrievals can identify the irrigated area at field scale. Overall, the experiment provides fruitful methodologies and datasets for the validation of high-resolution remote sensing products, benefiting the development and improvement of soil moisture retrieval algorithms and products to support irrigation scheduling and management at a precision agricultural scale in the future.
{"title":"A soil moisture experiment for validating high-resolution satellite products and monitoring irrigation at agricultural field scale","authors":"","doi":"10.1016/j.agwat.2024.109071","DOIUrl":"10.1016/j.agwat.2024.109071","url":null,"abstract":"<div><div>Validating the satellite soil moisture products is always an active research topic for the application of the products and improvement of the retrieval algorithms, attracting extensive attention. Nevertheless, seldom existing validation activities focus on the validation of high-resolution soil moisture products at the fine scale. To this end, an experiment was conducted in the middle stream of the Heihe River Basin in northwestern China in August to October of 2021, aiming to validate high-resolution satellite remote sensing products of soil moisture. The paper introduces the design, composite, and preliminary results of the experiment. A soil moisture observation network was established with two kinds of sensors (CS616 and Stevens Hydra Probe) validated against soil core measurements. Several synchronized campaigns were performed, and data were collected to validate the SMAP/Sentinel-1 L2 Radiometer/Radar 30-Second Scene 3 and 1 km EASE-Grid Soil Moisture (SPL2SMAP_S) products. Besides, an optical trapezoid model (OPTRAM) and collected Sentinel-2 data were applied to estimate soil moisture and to map irrigated area. Preliminary analyses show that: 1) Steven probes perform best, with an RMSE = 0.040 m<sup>3</sup>m<sup>−3</sup> and ubRMSE<!--> <!-->=<!--> <!-->0.034 m<sup>3</sup>m<sup>−3</sup>; 2) Both the SPL2SMAP_S products at 3 km and 1 km show large RMSE (0.128 m<sup>3</sup>m<sup>−3</sup> for 3 km and 0.158 m<sup>3</sup>m<sup>−3</sup> for 1 km) and ubRMSE (0.115 m<sup>3</sup>m<sup>−3</sup> for 3 km and 0.158 m<sup>3</sup>m<sup>−3</sup> for 1 km); 3) The OPTRAM retrievals over bare surface present relatively smaller RMSE (0.06 m<sup>3</sup>m<sup>−3</sup>) and ubRMSE (0.057 m<sup>3</sup>m<sup>−3</sup>), while retrievals over vegetated croplands present a relatively large RMSE/ubRMSE (0.083/0.083 m<sup>3</sup>m<sup>−3</sup>), and the retrievals can identify the irrigated area at field scale. Overall, the experiment provides fruitful methodologies and datasets for the validation of high-resolution remote sensing products, benefiting the development and improvement of soil moisture retrieval algorithms and products to support irrigation scheduling and management at a precision agricultural scale in the future.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142320175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-24DOI: 10.1016/j.agwat.2024.109080
Soil thickness is a useful soil quality indicator. This study aimed to characterize the effects of soil thickness on crop yield and water and nitrogen loss in sloping land. A seven-year experiment was conducted in the purple soil sloping land of Southwest China, which included six soil thickness of 20, 40, 60, 80, 100 and 120 cm. The crop yield, surface runoff, leaching and nitrogen loss were measured. The results showed that the crop yield increased as soil thickness increased from 20 cm to 120 cm. Regression analysis showed that the yield of spring maize and summer maize plateaued when the soil thickness increased to 118 cm, and the yield of winter crops still increased with soil thickness when the soil thickness was more than 120 cm. The total runoff decreased as the soil thickness increased from 20 cm to 120 cm. The surface runoff, leaching and total runoff under 120 cm soil thickness were 50.4 %, 72.3 % and 65.8 % lower than those under 20 cm thickness. The nitrogen loss through leaching accounts for 97.5 % of the total nitrogen loss. The total nitrogen loss decreased with the increase of soil thickness, and the average annual total nitrogen loss in 20, 40, 60, 80, 100, 120 cm soil thickness were 36.6, 25.1, 21.5, 16.9, 10.5 and 7.2 kg ha−1, respectively. Regression analysis showed that the total runoff was efficiently reduced when soil thickness reached 160 cm, and the total nitrogen loss was efficiently reduced when soil thickness reached 140 cm. These critical soil thickness values provided references for the design of high-yield cropping systems and environment benefit evaluation in purple soil sloping land.
{"title":"Effect of soil thickness on crop production and nitrogen loss in sloping land","authors":"","doi":"10.1016/j.agwat.2024.109080","DOIUrl":"10.1016/j.agwat.2024.109080","url":null,"abstract":"<div><div>Soil thickness is a useful soil quality indicator. This study aimed to characterize the effects of soil thickness on crop yield and water and nitrogen loss in sloping land. A seven-year experiment was conducted in the purple soil sloping land of Southwest China, which included six soil thickness of 20, 40, 60, 80, 100 and 120 cm. The crop yield, surface runoff, leaching and nitrogen loss were measured. The results showed that the crop yield increased as soil thickness increased from 20 cm to 120 cm. Regression analysis showed that the yield of spring maize and summer maize plateaued when the soil thickness increased to 118 cm, and the yield of winter crops still increased with soil thickness when the soil thickness was more than 120 cm. The total runoff decreased as the soil thickness increased from 20 cm to 120 cm. The surface runoff, leaching and total runoff under 120 cm soil thickness were 50.4 %, 72.3 % and 65.8 % lower than those under 20 cm thickness. The nitrogen loss through leaching accounts for 97.5 % of the total nitrogen loss. The total nitrogen loss decreased with the increase of soil thickness, and the average annual total nitrogen loss in 20, 40, 60, 80, 100, 120 cm soil thickness were 36.6, 25.1, 21.5, 16.9, 10.5 and 7.2 kg ha<sup>−1</sup>, respectively. Regression analysis showed that the total runoff was efficiently reduced when soil thickness reached 160 cm, and the total nitrogen loss was efficiently reduced when soil thickness reached 140 cm. These critical soil thickness values provided references for the design of high-yield cropping systems and environment benefit evaluation in purple soil sloping land.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424004165/pdfft?md5=ee18bd28886bf6d0dfe3566628c82b63&pid=1-s2.0-S0378377424004165-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142314428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-24DOI: 10.1016/j.agwat.2024.109047
Global water scarcity poses a great challenge to agriculture productivity. Recycled water offers a promising alternative for agricultural irrigation, yet residual pharmaceutical and personal care products (PPCPs) in recycled water can transfer to edible crops during irrigation, and adversely affect food safety. Furthermore, irrigation water quantity can influence the accumulation of PPCPs in edible crops. This study comprehensively investigates the use of recycled water for agricultural irrigation by critically reviewing three key components: PPCPs occurrence in recycled water, their accumulation in edible crops, and the impact of water quantity on PPCPs accumulation. Literature analysis showed that PPCPs were present from 130 to 1400 ng/L in secondary effluent and 25–400 ng/L in tertiary effluent, with sulfamethoxazole being the most prevalent in both effluents. PPCPs uptake and accumulation varied between leafy and fruity vegetables, with diclofenac accumulating highest in leafy vegetables and fluoxetine in fruity vegetables. Furthermore, the water requirement of leafy and fruity crops vary throughout the growing season. In leafy vegetables, PPCPs accumulation in leaves is influenced by transpiration rate, with reduced accumulation occurring under limited water availability due to slower transpiration. In fruity vegetables, osmotic adjustment drives the water transport in fruits, leading to increased PPCPs accumulation under limited water conditions. This study contributes insights into PPCPs occurrence, accumulation, and irrigation water quantity, aiding in the development of effective strategies for recycled water use in agriculture.
{"title":"Pharmaceutical and personal care products in recycled water for edible crop irrigation: Understanding the occurrence, crop uptake, and water quantity effects","authors":"","doi":"10.1016/j.agwat.2024.109047","DOIUrl":"10.1016/j.agwat.2024.109047","url":null,"abstract":"<div><div>Global water scarcity poses a great challenge to agriculture productivity. Recycled water offers a promising alternative for agricultural irrigation, yet residual pharmaceutical and personal care products (PPCPs) in recycled water can transfer to edible crops during irrigation, and adversely affect food safety. Furthermore, irrigation water quantity can influence the accumulation of PPCPs in edible crops. This study comprehensively investigates the use of recycled water for agricultural irrigation by critically reviewing three key components: PPCPs occurrence in recycled water, their accumulation in edible crops, and the impact of water quantity on PPCPs accumulation. Literature analysis showed that PPCPs were present from 130 to 1400 ng/L in secondary effluent and 25–400 ng/L in tertiary effluent, with sulfamethoxazole being the most prevalent in both effluents. PPCPs uptake and accumulation varied between leafy and fruity vegetables, with diclofenac accumulating highest in leafy vegetables and fluoxetine in fruity vegetables. Furthermore, the water requirement of leafy and fruity crops vary throughout the growing season. In leafy vegetables, PPCPs accumulation in leaves is influenced by transpiration rate, with reduced accumulation occurring under limited water availability due to slower transpiration. In fruity vegetables, osmotic adjustment drives the water transport in fruits, leading to increased PPCPs accumulation under limited water conditions. This study contributes insights into PPCPs occurrence, accumulation, and irrigation water quantity, aiding in the development of effective strategies for recycled water use in agriculture.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424003822/pdfft?md5=9bc08e372db7681a18f78ee47cbfd402&pid=1-s2.0-S0378377424003822-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142314427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-24DOI: 10.1016/j.agwat.2024.109074
The supply of water and fertilizer influences the growth and photosynthesis of strawberries, thereby affecting the yield. To determine the optimal combination of irrigation and fertilizer, an experiment was conducted over two years in 2019 and 2020. The experiment included four irrigation levels (I1: 100 % ETc, I2: 85 % ETc, I3: 70 % ETc, I4: 55 % ETc) and three fertilization levels (F1: 120 % F0, F2: 100 % F0, F3: 80 % F0), forming a total of 12 treatments, where F0 represents the exact value determined using the target yield method. Irrigation significantly affected on all growth indicators at flowering and fruit setting (F) and harvesting (H) stages in 2019, and the interaction of irrigation and fertilization was significant on photosynthetic rate (Pn) at seedling (S) stage (S-Pn) and the final fruit dry matter accumulation (FDM) in both study seasons. I1F1 achieved the highest S-Pn, while I2 showed significant promotion on FDM, with its maximum value of I2F1 in 2019 and I2F2 in 2020. F2 exhibited significant advantages on root dry weight (RDW) at H stage (H-RDW), with I3F2 and I4F2 performing the best. Moreover, I1F1 and I2F1 exhibited significantly promotion in stomatal conductance (Gs) at S stage (S-Gs). Based on correlation and path analysis, six indicators affecting yield formation were identified (S-RDW, S-Pn, F-CHll, F-Pn, H-CHll, FDM), with FDM having the greatest direct effect on yield (Y). A comprehensive evaluation system was constructed by considering the growth process and final yield, and Y obtained the highest combined weight (0.432 in 2019 and 0.476 in 2020). I2F2 and I3F1 were consistently ranked the top three in both years based on the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) evaluation model, indicating the combined irrigation and fertilizer of 70–85 % ETc with 100–120 % F0 can achieve optimal yield by promoting photosynthesis and growth of strawberries. This study can provide a theoretical basis for scientific water and fertilizer management of strawberries in arid and semi-arid regions.
{"title":"Appropriate water and fertilizer supply enhanced yield by promoting photosynthesis and growth of strawberries","authors":"","doi":"10.1016/j.agwat.2024.109074","DOIUrl":"10.1016/j.agwat.2024.109074","url":null,"abstract":"<div><div>The supply of water and fertilizer influences the growth and photosynthesis of strawberries, thereby affecting the yield. To determine the optimal combination of irrigation and fertilizer, an experiment was conducted over two years in 2019 and 2020. The experiment included four irrigation levels (I1: 100 % ET<sub>c</sub>, I2: 85 % ET<sub>c</sub>, I3: 70 % ET<sub>c</sub>, I4: 55 % ET<sub>c</sub>) and three fertilization levels (F1: 120 % F<sub>0</sub>, F2: 100 % F<sub>0</sub>, F3: 80 % F<sub>0</sub>), forming a total of 12 treatments, where F<sub>0</sub> represents the exact value determined using the target yield method. Irrigation significantly affected on all growth indicators at flowering and fruit setting (F) and harvesting (H) stages in 2019, and the interaction of irrigation and fertilization was significant on photosynthetic rate (Pn) at seedling (S) stage (S-Pn) and the final fruit dry matter accumulation (FDM) in both study seasons. I1F1 achieved the highest S-Pn, while I2 showed significant promotion on FDM, with its maximum value of I2F1 in 2019 and I2F2 in 2020. F2 exhibited significant advantages on root dry weight (RDW) at H stage (H-RDW), with I3F2 and I4F2 performing the best. Moreover, I1F1 and I2F1 exhibited significantly promotion in stomatal conductance (Gs) at S stage (S-Gs). Based on correlation and path analysis, six indicators affecting yield formation were identified (S-RDW, S-Pn, F-CHll, F-Pn, H-CHll, FDM), with FDM having the greatest direct effect on yield (Y). A comprehensive evaluation system was constructed by considering the growth process and final yield, and Y obtained the highest combined weight (0.432 in 2019 and 0.476 in 2020). I2F2 and I3F1 were consistently ranked the top three in both years based on the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) evaluation model, indicating the combined irrigation and fertilizer of 70–85 % ET<sub>c</sub> with 100–120 % F<sub>0</sub> can achieve optimal yield by promoting photosynthesis and growth of strawberries. This study can provide a theoretical basis for scientific water and fertilizer management of strawberries in arid and semi-arid regions.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424004104/pdfft?md5=38a22bfb13133d624ee4df8c7be15ead&pid=1-s2.0-S0378377424004104-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142314286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-24DOI: 10.1016/j.agwat.2024.109066
Remote sensing-based surface energy balance algorithms have been used to estimate water use of various crops. However, citrus evapotranspiration (ET) estimation is challenging mainly due to evergreen leaves and a clumped canopy structure. In this study, we evaluated the performance of two methods for calculating ET: the ensemble of OpenET models, which are mostly satellite thermal-based models, and the BAITSSS water and energy balance model. Calculated ET was compared with (i.) eddy covariance (EC) ET measurements and (ii.) water received (irrigation plus precipitation) data for two citrus orchards in San Joaquin Valley, California. Polaris-based soil hydraulic properties and measured volumetric water content were used for BAITSSS parameterization and initialization, respectively. Sentinel-2 based NDVI was used for BAITSSS simulation. Results showed that annual ET based on the OpenET ensemble model (1169 mm) was on average 30 % larger (r2 ∼ 0.71, RMSE ∼ 1.16 mm) than both EC ET (908 mm) and water received (886 mm). The disparity mostly occurred in spring. BAITSSS, on the other hand, showed mixed results compared to observations (r2 ∼ 0.77, RMSE ∼ 0.94 mm). Both measured from EC and modeled ET from BAITSSS and ensemble OpenET values were below grass reference ET (ETo) for the majority of the simulation period. Soil moisture and water received data indicated the orchards may have been deficit irrigated. Overall, this study highlights the challenges of ET modeling in citrus orchards and the need for improved estimation of ET for this specialty crop.
{"title":"Intercomparison of citrus evapotranspiration among eddy covariance, OpenET ensemble models, and the Water and Energy Balance Model (BAITSSS)","authors":"","doi":"10.1016/j.agwat.2024.109066","DOIUrl":"10.1016/j.agwat.2024.109066","url":null,"abstract":"<div><div>Remote sensing-based surface energy balance algorithms have been used to estimate water use of various crops. However, citrus evapotranspiration (ET) estimation is challenging mainly due to evergreen leaves and a clumped canopy structure. In this study, we evaluated the performance of two methods for calculating ET: the ensemble of OpenET models, which are mostly satellite thermal-based models, and the BAITSSS water and energy balance model. Calculated ET was compared with (i.) eddy covariance (EC) ET measurements and (ii.) water received (irrigation plus precipitation) data for two citrus orchards in San Joaquin Valley, California. Polaris-based soil hydraulic properties and measured volumetric water content were used for BAITSSS parameterization and initialization, respectively. Sentinel-2 based NDVI was used for BAITSSS simulation. Results showed that annual ET based on the OpenET ensemble model (1169 mm) was on average 30 % larger (r<sup>2</sup> ∼ 0.71, RMSE ∼ 1.16 mm) than both EC ET (908 mm) and water received (886 mm). The disparity mostly occurred in spring. BAITSSS, on the other hand, showed mixed results compared to observations (r<sup>2</sup> ∼ 0.77, RMSE ∼ 0.94 mm). Both measured from EC and modeled ET from BAITSSS and ensemble OpenET values were below grass reference ET (ET<sub>o</sub>) for the majority of the simulation period. Soil moisture and water received data indicated the orchards may have been deficit irrigated. Overall, this study highlights the challenges of ET modeling in citrus orchards and the need for improved estimation of ET for this specialty crop.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424004025/pdfft?md5=b2f3c4f39d2946e60f0af423dd715dcf&pid=1-s2.0-S0378377424004025-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142314426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-24DOI: 10.1016/j.agwat.2024.109081
Waterlogging is one of the major disasters affecting crop yield and food security. The Songliao Plain, located in the mid-latitude region and known as the "Golden Maize Belt," is severely impacted by waterlogging, which significantly affects maize yield. Therefore, it is essential to conduct a detailed assessment of the waterlogging hazard for maize in the Songliao Plain and to apply the results to agricultural meteorological disaster prevention and mitigation measures. In this study, a comprehensive waterlogging hazard assessment index was constructed by combining environmental factors conducive to disaster and disaster-causing factors. Environmental factors included terrain slope, distance from rivers, and soil clay content, while disaster-causing factors included daily SPEI and SMAI during the maize growing season in the Songliao Plain from 1982 to 2020. The results indicate that: (1) The spatial distribution of waterlogging hazard in the Songliao Plain ranges from extremely high to extremely low, showing a gradual decrease from west to east. The western and southern parts of the Songliao Plain, such as Baicheng, Songyuan, Changchun, and Fuxin, are more prone to waterlogging disasters. (2) During different maize growth stages, the spatial distribution of high and extremely high levels of waterlogging hazard exhibited significant heterogeneity. There were notable differences in the duration of waterlogging around the year 2000, with a reduction in the duration of extremely high and high levels of waterlogging after 2000. (3) A Pearson correlation analysis was conducted between the comprehensive waterlogging hazard index and SIF (Solar-Induced Fluorescence) data during different maize growth stages. The results showed a strong correlation between the comprehensive waterlogging hazard index and SIF data, with the highest correlation coefficient reaching −0.9 and a p-value less than 0.05. The comprehensive maize waterlogging hazard index can be used for precise and timely assessment of waterlogging hazard during different growth stages of maize, and it has a positive impact on improving the ability to prevent and mitigate waterlogging risks.
{"title":"Assessment of waterlogging hazard during maize growth stage in the Songliao plain based on daily scale SPEI and SMAI","authors":"","doi":"10.1016/j.agwat.2024.109081","DOIUrl":"10.1016/j.agwat.2024.109081","url":null,"abstract":"<div><div>Waterlogging is one of the major disasters affecting crop yield and food security. The Songliao Plain, located in the mid-latitude region and known as the \"Golden Maize Belt,\" is severely impacted by waterlogging, which significantly affects maize yield. Therefore, it is essential to conduct a detailed assessment of the waterlogging hazard for maize in the Songliao Plain and to apply the results to agricultural meteorological disaster prevention and mitigation measures. In this study, a comprehensive waterlogging hazard assessment index was constructed by combining environmental factors conducive to disaster and disaster-causing factors. Environmental factors included terrain slope, distance from rivers, and soil clay content, while disaster-causing factors included daily SPEI and SMAI during the maize growing season in the Songliao Plain from 1982 to 2020. The results indicate that: (1) The spatial distribution of waterlogging hazard in the Songliao Plain ranges from extremely high to extremely low, showing a gradual decrease from west to east. The western and southern parts of the Songliao Plain, such as Baicheng, Songyuan, Changchun, and Fuxin, are more prone to waterlogging disasters. (2) During different maize growth stages, the spatial distribution of high and extremely high levels of waterlogging hazard exhibited significant heterogeneity. There were notable differences in the duration of waterlogging around the year 2000, with a reduction in the duration of extremely high and high levels of waterlogging after 2000. (3) A Pearson correlation analysis was conducted between the comprehensive waterlogging hazard index and SIF (Solar-Induced Fluorescence) data during different maize growth stages. The results showed a strong correlation between the comprehensive waterlogging hazard index and SIF data, with the highest correlation coefficient reaching −0.9 and a p-value less than 0.05. The comprehensive maize waterlogging hazard index can be used for precise and timely assessment of waterlogging hazard during different growth stages of maize, and it has a positive impact on improving the ability to prevent and mitigate waterlogging risks.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424004177/pdfft?md5=ec8b96edb947a4336220e9bd0291236d&pid=1-s2.0-S0378377424004177-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142314429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-24DOI: 10.1016/j.agwat.2024.109075
Integrating water and nitrogen (N) management is critical to addressing contemporary challenges in agricultural development. This research explored using multispectral sensors mounted on unmanned aerial vehicles (UAVs) to monitor N demand via the normalized difference red-edge (NDRE) vegetation index and consequently schedule fertigation. The experiment included eight treatments with four fertilizer levels under both excessive and full irrigation. The four fertilizer levels comprised: high reference treatment based on commercial lab soil tests, sensor-based treatment triggered by an NDRE saturation threshold of 0.95, deficit treatment with base rate at pre-plant and side-dress, and a control treatment without any N application. The performance of each treatment was evaluated through a comprehensive comparison of yield, water productivity (WP), and nitrogen use efficiency (NUE). The sufficiency index (SI) of sensor-based treatment plots reached a threshold of 0.95, allowing spatially variable adjustment of N application for optimal yield with reduced total N input. Reducing N fertilizer in sensor-based treatments resulted in a substantial reduction of 50 %-60 %, though it led to a yield loss up to 12 %. However, NUE parameters such as partial factor productivity, agronomic efficiency, recovery efficiency, and physiological efficiency improved with sensor-based treatments, alongside reduced N leaching. Combining sensor-based treatment with full irrigation demonstrated the best ecological return, showing relatively lower yield reduction but significant improvements in NUE and WP. Further research into economic returns, saturation threshold algorithms for SI, adaptability to diverse environments, and virtual saturation reference is recommended for the widespread adoption of UAV-based N split management among growers.
{"title":"Estimation of corn nitrogen demand under different irrigation conditions based on UAV multispectral technology","authors":"","doi":"10.1016/j.agwat.2024.109075","DOIUrl":"10.1016/j.agwat.2024.109075","url":null,"abstract":"<div><div>Integrating water and nitrogen (N) management is critical to addressing contemporary challenges in agricultural development. This research explored using multispectral sensors mounted on unmanned aerial vehicles (UAVs) to monitor N demand via the normalized difference red-edge (NDRE) vegetation index and consequently schedule fertigation. The experiment included eight treatments with four fertilizer levels under both excessive and full irrigation. The four fertilizer levels comprised: high reference treatment based on commercial lab soil tests, sensor-based treatment triggered by an NDRE saturation threshold of 0.95, deficit treatment with base rate at pre-plant and side-dress, and a control treatment without any N application. The performance of each treatment was evaluated through a comprehensive comparison of yield, water productivity (WP), and nitrogen use efficiency (NUE). The sufficiency index (SI) of sensor-based treatment plots reached a threshold of 0.95, allowing spatially variable adjustment of N application for optimal yield with reduced total N input. Reducing N fertilizer in sensor-based treatments resulted in a substantial reduction of 50 %-60 %, though it led to a yield loss up to 12 %. However, NUE parameters such as partial factor productivity, agronomic efficiency, recovery efficiency, and physiological efficiency improved with sensor-based treatments, alongside reduced N leaching. Combining sensor-based treatment with full irrigation demonstrated the best ecological return, showing relatively lower yield reduction but significant improvements in NUE and WP. Further research into economic returns, saturation threshold algorithms for SI, adaptability to diverse environments, and virtual saturation reference is recommended for the widespread adoption of UAV-based N split management among growers.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424004116/pdfft?md5=52a20510c8ebcf945d93b84c6d8684de&pid=1-s2.0-S0378377424004116-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142314425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-23DOI: 10.1016/j.agwat.2024.109064
This study investigates the replacement of traditional surface irrigation methods with modern irrigation systems (MIS) including horizontal sprinkler, central pivot, surface drip, and subsurface drip aimed at improving water efficiency in the Nile Delta, Egypt. The primary objectives were to determine the optimal agricultural area for implementing MIS and to assess the effects of these systems on groundwater quantity and quality in the region. To achieve this, the LINDO software was employed to optimize land allocation for each irrigation method. At the same time, the SEAWAT code was utilized to simulate saltwater intrusion (SWI) in the Nile Delta aquifer. The transition from traditional surface irrigation to MIS resulted in significant water savings, reaching 2.15 × 10^9 m³. However, groundwater modeling indicated a decrease in groundwater levels, leading to an 8 % increase in aquifer salinity due to reduced infiltration of recharge water. These findings underscore the urgent need to revise outdated irrigation practices and enhance water management strategies in the Nile Delta to mitigate salinity issues in coastal aquifers. This research's outcomes are crucial for decision-makers and stakeholders in selecting appropriate irrigation methods, particularly in arid and semi-arid regions, to ensure sustainable water use and agricultural productivity.
{"title":"Optimizing Irrigation Systems for Water Efficiency and Groundwater Sustainability in the Coastal Nile Delta","authors":"","doi":"10.1016/j.agwat.2024.109064","DOIUrl":"10.1016/j.agwat.2024.109064","url":null,"abstract":"<div><div>This study investigates the replacement of traditional surface irrigation methods with modern irrigation systems (MIS) including horizontal sprinkler, central pivot, surface drip, and subsurface drip aimed at improving water efficiency in the Nile Delta, Egypt. The primary objectives were to determine the optimal agricultural area for implementing MIS and to assess the effects of these systems on groundwater quantity and quality in the region. To achieve this, the LINDO software was employed to optimize land allocation for each irrigation method. At the same time, the SEAWAT code was utilized to simulate saltwater intrusion (SWI) in the Nile Delta aquifer. The transition from traditional surface irrigation to MIS resulted in significant water savings, reaching 2.15 × 10^9 m³. However, groundwater modeling indicated a decrease in groundwater levels, leading to an 8 % increase in aquifer salinity due to reduced infiltration of recharge water. These findings underscore the urgent need to revise outdated irrigation practices and enhance water management strategies in the Nile Delta to mitigate salinity issues in coastal aquifers. This research's outcomes are crucial for decision-makers and stakeholders in selecting appropriate irrigation methods, particularly in arid and semi-arid regions, to ensure sustainable water use and agricultural productivity.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424003998/pdfft?md5=923785f69dd6e3a5abb1051d56409f8f&pid=1-s2.0-S0378377424003998-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142312752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-23DOI: 10.1016/j.agwat.2024.109070
Small water bodies, such as ponds, are widely distributed in agricultural watersheds. They not only serve agricultural irrigation and drainage but also play a crucial role in reducing nitrogen and phosphorus in agricultural non-point source pollution and improving river water quality. However, the linkage between river water quality and the spatial distribution pattern of small water bodies is still unclear. In this study, an agricultural watershed, consisting of nine sub-watersheds and over 1800 ponds was selected, to evaluate the impact of small water body distribution on river water quality. Despite ponds account for less than 0.6 % of the sub-watershed area, they largely determine water quality variations. Specifically, sub-watersheds with lower connectivity among ponds and shorter distances between ponds and farmland exhibited better water quality. These two indicators alone explain more than 87 % variations of nutrient concentrations among the sub-watersheds. This indicates that dispersed ponds that are located close to farmlands serve as important sinks for pollutants in agricultural watersheds. In this study, we emphasize the importance of location of small water bodies in maintaining river water quality, which can provide crucial information for future agricultural watershed land use planning and the development of optimized strategies for water quality improvement.
{"title":"Small water bodies influence river water quality in agricultural watersheds","authors":"","doi":"10.1016/j.agwat.2024.109070","DOIUrl":"10.1016/j.agwat.2024.109070","url":null,"abstract":"<div><div>Small water bodies, such as ponds, are widely distributed in agricultural watersheds. They not only serve agricultural irrigation and drainage but also play a crucial role in reducing nitrogen and phosphorus in agricultural non-point source pollution and improving river water quality. However, the linkage between river water quality and the spatial distribution pattern of small water bodies is still unclear. In this study, an agricultural watershed, consisting of nine sub-watersheds and over 1800 ponds was selected, to evaluate the impact of small water body distribution on river water quality. Despite ponds account for less than 0.6 % of the sub-watershed area, they largely determine water quality variations. Specifically, sub-watersheds with lower connectivity among ponds and shorter distances between ponds and farmland exhibited better water quality. These two indicators alone explain more than 87 % variations of nutrient concentrations among the sub-watersheds. This indicates that dispersed ponds that are located close to farmlands serve as important sinks for pollutants in agricultural watersheds. In this study, we emphasize the importance of location of small water bodies in maintaining river water quality, which can provide crucial information for future agricultural watershed land use planning and the development of optimized strategies for water quality improvement.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424004062/pdfft?md5=b9eaedacf048fcab80a59f8de637014b&pid=1-s2.0-S0378377424004062-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142312751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-21DOI: 10.1016/j.agwat.2024.109069
<div><p>Soil moisture content (SMC), as a pivotal component in the energy and matter exchange processes within the soil-plant-atmosphere continuum, plays a crucial role in surface water dynamics, energy fluxes, and carbon cycling within ecosystems. The development of remote sensing technology has offered new perspectives for monitoring soil moisture at regional scales. Unmanned aerial vehicles (UAV) equip with multispectral have distinct advantages for vegetation monitoring, including rapidity and cost-effectiveness, which has superior applicability and practicality. Therefore, in a 5a "Daya" late-maturing citrus orchard, the vegetation index (VI) and texture feature (TF) information of citrus canopy based on UAV multi-spectral images were extracted, and soil and plant analyzer development (SPAD) of citrus was collected. These different data sources were integrated into the framework of the random forest algorithm (RF) and genetic algorithm-optimized random forest (GA-RF) to evaluate the accuracy of surface SMC (SSMC) estimation in citrus orchard. The Biswas model was utilized to simulate the root zone SMC (RSMC). The spatiotemporal variations of SMC in citrus orchard were analyzed, and the potential of low-cost sensor-equipped drones in rapidly acquiring spatial and temporal distribution information of SMC at a large regional scale was explored. The results indicated that the GA-RF models outperformed the RF models in estimating citrus orchard SMC (with R<sup>2</sup> ranging from 0.502 to 0.949 and RMSE ranging from 0.552 % to 3.166 % for GA-RF, compared to R<sup>2</sup> ranging from 0.430 to 0.936 and RMSE ranging from 0.587 % to 3.449 % for the RF). The GA-RF models using VI+SPAD as inputs exhibited the best performance for SMC at depths of 5 cm, 10 cm, 20 cm and 40 cm (SMC5, SMC10, SMC20 and SMC40) across citrus growth stages (R<sup>2</sup> ranging from 0.793 to 0.949 at 5 cm, R<sup>2</sup> ranging from 0.702 to 0.938 at 10 cm, R<sup>2</sup> ranging from 0.714 to 0.927 at 20 cm). In bud bust to flowering, young fruit and fruit maturation stages (stage Ⅰ, ⅠⅠ and ⅠⅤ), all models demonstrated good accuracy in estimating SMC at depth of 10 cm (R<sup>2</sup> ranging from 0.567 to 0.908 in stage Ⅰ, with R<sup>2</sup> ranging from 0.681 to 0.916 in stage ⅠⅠ and R<sup>2</sup> ranging from 0.579 to 0.938 in stage ⅠⅤ). In fruit expansion stage (stage III), the models performed best in predicting SMC5 (R<sup>2</sup> ranging from 0.698 to 0.861). The Biswas model was constructed to simulate SMC40 by utilizing the inverted SMC10 and SMC20, thereby generating spatiotemporal distribution maps of SMC at different depths in citrus orchard. The SSMC was susceptible to environmental factors, exhibiting significant spatiotemporal heterogeneity. In summary, this study illustrated that the integration of multiple data sources into GA-RF enhanced the estimation performance of SMC at different growth stages of late-maturing citrus orchard in the Southwest China. Add
{"title":"Soil moisture content estimation of drip-irrigated citrus orchard based on UAV images and machine learning algorithm in Southwest China","authors":"","doi":"10.1016/j.agwat.2024.109069","DOIUrl":"10.1016/j.agwat.2024.109069","url":null,"abstract":"<div><p>Soil moisture content (SMC), as a pivotal component in the energy and matter exchange processes within the soil-plant-atmosphere continuum, plays a crucial role in surface water dynamics, energy fluxes, and carbon cycling within ecosystems. The development of remote sensing technology has offered new perspectives for monitoring soil moisture at regional scales. Unmanned aerial vehicles (UAV) equip with multispectral have distinct advantages for vegetation monitoring, including rapidity and cost-effectiveness, which has superior applicability and practicality. Therefore, in a 5a \"Daya\" late-maturing citrus orchard, the vegetation index (VI) and texture feature (TF) information of citrus canopy based on UAV multi-spectral images were extracted, and soil and plant analyzer development (SPAD) of citrus was collected. These different data sources were integrated into the framework of the random forest algorithm (RF) and genetic algorithm-optimized random forest (GA-RF) to evaluate the accuracy of surface SMC (SSMC) estimation in citrus orchard. The Biswas model was utilized to simulate the root zone SMC (RSMC). The spatiotemporal variations of SMC in citrus orchard were analyzed, and the potential of low-cost sensor-equipped drones in rapidly acquiring spatial and temporal distribution information of SMC at a large regional scale was explored. The results indicated that the GA-RF models outperformed the RF models in estimating citrus orchard SMC (with R<sup>2</sup> ranging from 0.502 to 0.949 and RMSE ranging from 0.552 % to 3.166 % for GA-RF, compared to R<sup>2</sup> ranging from 0.430 to 0.936 and RMSE ranging from 0.587 % to 3.449 % for the RF). The GA-RF models using VI+SPAD as inputs exhibited the best performance for SMC at depths of 5 cm, 10 cm, 20 cm and 40 cm (SMC5, SMC10, SMC20 and SMC40) across citrus growth stages (R<sup>2</sup> ranging from 0.793 to 0.949 at 5 cm, R<sup>2</sup> ranging from 0.702 to 0.938 at 10 cm, R<sup>2</sup> ranging from 0.714 to 0.927 at 20 cm). In bud bust to flowering, young fruit and fruit maturation stages (stage Ⅰ, ⅠⅠ and ⅠⅤ), all models demonstrated good accuracy in estimating SMC at depth of 10 cm (R<sup>2</sup> ranging from 0.567 to 0.908 in stage Ⅰ, with R<sup>2</sup> ranging from 0.681 to 0.916 in stage ⅠⅠ and R<sup>2</sup> ranging from 0.579 to 0.938 in stage ⅠⅤ). In fruit expansion stage (stage III), the models performed best in predicting SMC5 (R<sup>2</sup> ranging from 0.698 to 0.861). The Biswas model was constructed to simulate SMC40 by utilizing the inverted SMC10 and SMC20, thereby generating spatiotemporal distribution maps of SMC at different depths in citrus orchard. The SSMC was susceptible to environmental factors, exhibiting significant spatiotemporal heterogeneity. In summary, this study illustrated that the integration of multiple data sources into GA-RF enhanced the estimation performance of SMC at different growth stages of late-maturing citrus orchard in the Southwest China. Add","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424004050/pdfft?md5=db2c2299e15804c87635309e6c534499&pid=1-s2.0-S0378377424004050-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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