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Paddy and Water Environment
Journal Prestige (SJR): 0.468
Citation Impact (citeScore): 1
Number of Followers: 9  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1611-2504 - ISSN (Online) 1611-2490
Published by Springer-Verlag Homepage  [2467 journals]
  • Integrated drought evaluation index: considering the ecological feedback
           of the soil moisture and vegetation on wheat

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      Abstract: Abstract With the acceleration of climate instability, drought is causing increasing losses that seriously threaten food security in China. In consideration of the feedback of the ecological environment vulnerability on drought, this study selects the temperature vegetation dryness index to evaluate the boundaries of the regional ecological drought index and integrates many factors, such as precipitation, temperature and human activities, from the four aspects of natural disaster risk management—hazard, vulnerability, exposure and resistance—to establish an integrated drought evaluation index for wheat. The results showed that drought was the main reason for the reduction of wheat yield. Standardized precipitation index (SPI), crop water deficit anomaly index and temperature vegetation dryness index (TVDI) were the most important factors affecting drought. On the monthly scale, precipitation showed seasonal characteristics, and the most severe water shortage period occurred from March to May, which was also the physiological water demand period of wheat; on the annual scale, the precipitation fluctuates more frequently, and the alternate from dry to wet occurs average every 3–4 years, which is basically consistent with the changing trend of yield reduction rate. Spatially, precipitation scarcities were concentrated throughout the north of the study region, where drought was most frequent and severe. There were highly positive spatial correlations between the integrated drought evaluation index and the annual yield reduction rate of wheat in dry years, whose bivariate Moran's I values reached 0.39, 0.42, 0.31 and 0.38 in the 2002, 2005, 2011 and 2016, respectively; further, the yield reduction rate increased with drought aggregation. This study clearly demonstrates that the evaluation accuracy of Integrated drought evaluation index of wheat (IDEIW) with TVDI is 11.8% higher than that of IDEIW without TVDI due to the strong effects of vegetation and soil moisture on drought. Moreover, population density has a strong impact on SPI and TVDI in the long-term time series. Therefore, the IDEIW in the study area is stronger and more stable than TVDI and SPI in terms of availability, precision and sensitivity, which can be used as an important tool to assess and monitor dynamic variations in agricultural drought and provide a new means for the early warning and forecast management of agricultural drought.
      PubDate: 2022-12-05
       
  • Improving fertilization practices to reduce the potential of nutrient loss
           from rice paddy fields

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      Abstract: Abstract Excessive fertilizer or unseasonable fertilization ways are common in rice-cultivated regions over world, and a consequence is an environmental adverse impact resulting from substantial nutrient losses. In order to evaluate the influence of fertilization ways on nutrient losses in flooding paddy field, this work investigated the dynamic of nutrient concentrations via a short-term experiment containing single- and split-application fertilizer during main fertilization period, in the Jiangshan city, Zhejiang, China. The ponded water nutrient concentrations from fertilization plots ranged widely over the experiment: 2.8–80.9 mg L−1 for NH4+-N, 0.2–3.7 mg L−1 for NO3−-N, 1.2–215.0 mg L−1 for TN, 0.02–0.6 mg L−1 for TP, and 0.5 to 48.8 mg L−1 for TK, respectively. Applying mineral fertilizer increased immediately nutrient concentrations in ponded water and followed by a slow drop to a stead levels. The results showed a high-risk period of losses was within 3–5 days for N and 8–11 days for K following fertilization, respectively, if runoff occurred by rainstorm or drainage depending on fertilization ways. The losses risk of ponded water P after basal fertilization was negligible, but within 5 days after first topdressing was a potential pollution risk period. Compared to split fertilization, single fertilization can reduce losses risk via runoff by 66.3–67.5% for N and by 36.9–46.8% for K, respectively. However, in addition to rice yield reduction, the single application as basal fertilizer may enhance losses by NH3 volatilization, which led to a high risk of air pollution, and decrease the pH of ponded water and further soil acidification as well. Hence, the results suggested that the fertilizer split-application containing panicle fertilizer can consider as an ecological fertilization way and is suitable for rice main production region which benefit for both economic and environment despite a little increase of labor costs.
      PubDate: 2022-11-30
       
  • Improving yield and nitrogen use efficiency of hybrid indica rice through
           optimizing nitrogen application strategies in the rice season under
           different rotation patterns

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      Abstract: Abstract Currently, it is difficult to synergistically improve rice yield and nitrogen (N) use efficiency (NUE) resulted from the overuse of N fertilizer under different rotations has become a major issue in China. This study was undertaken to optimize N application and evaluate the feasibility of reducing the amount of N fertilizer in rice crops under different rotations. Three rotations (mustard-rice, rape-rice, and wheat-rice) and different N application strategies (conventional N management and optimum N application strategies according to the Stanford equation) were tested in 2019 and 2020. The relationship between yield or NUE and N accumulation and translocation was, respectively, investigated. Correlation analyses revealed that the yield or NUE was significantly correlated (r = 0.446–0.977, P < 0.05) with the N translocation in stem-sheaths, N translocation contribution rate in blades, and N accumulation from full heading to maturity stage. These results suggest that the N application strategy should be adjusted according to different rotations in order to obtain the highest yield and the best NUE. When the N fertilizer was 105, 125, and 150 kg ha−1, and the N fertilizer ratio all were 30:30:40 base to tiller to panicle fertilizer, rape-rice, mustard-rice, and wheat-rice rotations each achieve a synergistic increased N accumulation and translocation from full heading to maturity stage and hence, attained higher yield and NUE. The results further indicated that it is practicable to reduce the amount of N fertilizer applied in rice crops planted after rape or mustard but not when grown after wheat.
      PubDate: 2022-11-23
       
  • Occurrence of heavy metals in surface water bodies in rice cultivation
           areas in Trincomalee district, Sri Lanka

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      Abstract: Abstract Nonpoint source pollution from agricultural runoff which contains hazardous agrochemicals like pesticides and fertilizers threatens water bodies, posing a serious danger to aquatic ecosystems and drinking water resources. Use of agrochemicals in rice cultivation has rapidly increased in the last few decades in Sri Lanka. It has been reported that many agrochemicals contain toxic trace elements like As, Cd, Pb, Zn, Cu, Ni, Cr, Al, etc. To reduce the harmful effect of heavy metal containing agrochemicals, the Government of Sri Lanka has banned the use of several toxic agrochemicals in recent years. In this context, this study was conducted after posing these restrictions to assess the occurrence of heavy metals in surface water bodies in rice cultivation areas in Trincomalee district, Sri Lanka. Ninety-three (n = 93) sample locations were randomly selected for collection of water, before and after applying agrochemicals to rice fields. This include areas from rural farming communities having endemic (Padavi Sripura DS) and non-endemic (Kanthala DS and Seruvila DS) Chronic Kidney Disease of unknown etiology (CKDu). Mean and standard error of mean of As, Cd, Pb, Cu and Zn concentrations (µg/L) before and after applying agrochemicals were as {0.048 ± 0.038 and 6.220 ± 0.912}, {0.014 ± 0.013 and 0.371 ± 0.192}, {not detected and 4.421 ± 0.712}, {1.583 ± 0.397 and 1.262 ± 0.165} and {not detected and 6.403 ± 0.366}, respectively. Findings revealed that concentrations of As, Cd, Pb and Zn were significantly different (p < 0.001) before and after the application of agrochemicals. However, the observed heavy metal concentrations were far below the permissible levels for irrigation water set by Food and Agriculture Organization and United States Environmental Protection Agency, ambient water quality set by Central Environmental Authority, and drinking water quality set by World Health Organization. In addition, analyzed heavy metal concentrations in surface water samples from CKDu endemic areas were not significantly different from those from non-endemic areas (p <  0.05). To our knowledge, this is the first report of heavy metal analysis after government ban of agrochemicals. Therefore, continuous detailed research is required to fully comprehend the behavior of agrochemicals in surface water bodies in Sri Lanka.
      PubDate: 2022-11-04
       
  • Methane emissions and rice yield in a paddy soil: the effect of biochar
           and polystyrene microplastics interaction

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      Abstract: Abstract Biochar has been suggested as a soil supplement to improve soil fertility and mitigate methane (CH4) emissions from rice farming. On the other side, the world is covered in microplastics (MPs), which are tiny pieces of degraded plastic. Studies have paid little attention to the combined biochar and soil contamination caused by MPs, particularly the mechanism of their interactions with CH4 emissions. In this study, a pot greenhouse experiment with a randomized complete block design (RCBD) was carried out to examine the impact of polystyrene (PS), sugarcane bagasse biochar (SBB), and their interaction (PS*SBB) on the CH4 emission and rice yield in a rice-cultivated paddy calcareous soil. The largest CH4 emission occurred at 30 and 70 days following rice planting, which corresponds to the tillering and heading stages of rice growth. Adding SBB to our paddy soil samples reduced CH4 emissions. Our findings showed that applying PS at different rates greatly increased CH4 emissions in our soil samples under ambient conditions. Our results showed that adding SBB can partially offset the negative effects of PS in the soil. In comparison with when PS was applied alone, the co-application of SBB and PS reduced PS’s stimulation of the global warming potential (GWP) by altering its impacts on the structure and function of the soil’s microbial community and the carbon and nitrogen contents of the microbial biomass. We come to the conclusion that interactions between PS and the use of SBB have an impact on GWP, microbial community activities, and CH4 emissions. Both SBB rates resulted in a considerable increase in height, biomass, and rice grain as compared to control. Our findings indicated that PS negatively impacts rice height, grain yield, and biomass and that the addition of SBB can partially counteract PS’s negative effects on the rice. Further study is needed to understand how various types of MPs interact with soil amendments to affect ecosystem function.
      PubDate: 2022-11-02
       
  • MODWT and wavelet coherence-based analysis of groundwater levels changes
           detection

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      Abstract: Abstract This study used a model to capture trends and dominant periods in groundwater level (GWL), streamflow, and precipitation (GSP) data over the Azarshahr plain, Iran. The trend of GSP was predicted to find dominant time scales affecting the trends observed in the datasets. This study used maximal overlap discrete wavelet transform and Mann–Kendall trend tests to analyze and detect trends in monthly, seasonally based, and annual data from three GWL, one streamflow, and one precipitation gauges in Azarshahr plain during 1968–2015. The present research demonstrated that at the monthly, seasonal, and annual time scales, the trends in stream flow and GW data were significant and downward. Results indicated that this significant negative trend appeared after 1971 in GWL. In addition, the 2-month and 16-month (individual months), 2- and 8-month components were dominant periods at the monthly time scale, and the 6-month, 12-month, and 6- and 12-month components were dominant periods at the seasonal time scale. The 2-year and 4-year components were dominant periods at the annual time scale. Results suggested that climate teleconnections might affect the fluctuations of the GSP process. Wavelet coherency was used to study the correlation and interaction of the variables, where no correlation was detected.
      PubDate: 2022-10-15
       
  • Comparative effects of biochar and compost applications on water holding
           capacity and crop yield of rice under evaporation stress: a two-years
           field study

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      Abstract: Abstract Adding organic amendments to paddies to improve water use efficiency (WUE) could be a potential strategy to improve soil water storage. This research looked at the effects of biochar and compost additions at 20 t ha−1 rates in a rice field for two years, using three irrigation regimes called I100, I75, and I50 which indicate irrigation rates of 100%, 75%, and 50% of evaporation from class A evaporation pan. Changes in soil matric potential curves, as well as rice yield components such as height, grain yield, panicle density, and spikelets per panicle, as well as well water consumption, were measured. Adding biochar to all irrigation regimes resulted in the greatest increase in matric potential points. Biochar enhanced water holding capacity under higher evaporation stress than compost. Biochar treatment under the I50 regime increased grain yield by 35% and 30% in two consecutive years. While in compost-treated soil and I50 regime, the amount of grain yield significantly decreased by 7% and 38% compared to control, respectively, in 2020 and 2021. Using biochar significantly increased WUE in order to decrease irrigation regimes. The two years did not significantly differ from one another. However, using compost, WUE showed a declining trend in response to lower irrigation regimes. When evaporation is excessive and irrigation is insufficient, biochar's higher porosity and surface area, as well as its greater stability to decomposition relative to compost, may improve WUE in rice.
      PubDate: 2022-10-12
       
  • Development of irrigation schedule and management model for sustaining
           optimal crop production under agricultural drought

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      Abstract: Abstract Agriculture is vulnerable to drought indicating that the increasing climate crisis requires the necessity of sustainable crop production. In this study, we developed the Irrigation Schedule and Management (ISM) model based on a simulation–optimization (Soil Water Atmosphere Plant-SWAP model with Genetic Algorithm-GA) framework. The ISM model finds an optimal combination of Irrigation Water Amount (IWA) and Irrigation Interval (II) by adjusting Water Stress (WS) responding to environmental conditions (weather, soils, crops and bottom boundary conditions) throughout growing periods. By conditioning the crop (WS) and water management (IWA and II) variables, ISM improves the sustainability of optimal crop productions under different climatic-land surface conditions. The Regional Agromet Center (RAC) site in Faisalabad (at Punjab, Pakistan) was selected to test the proposed ISM model for the field validation/synthetic numerical experiments with various crops (Wheat, Corn and Potato) and soils. We demonstrated that the ISM model that reflects the relationship between crop and water management variables improved the sustainability of crop productions and Water Productivity (WP) compared to those of the conventional irrigation method at the RAC site under various environment conditions. Additionally, the ISM-based long-term crop productions showed the variations along the yearly precipitation changes indicating that optimal combinations of the crop and water management variables are considerably influenced by environmental conditions. Although uncertainties exist, our proposed ISM model can contribute to the establishment of efficient irrigation schedule/management plans under agricultural drought.
      PubDate: 2022-10-11
       
  • Identifying effective AE parameters for damage evaluation of concrete in
           headwork: a combined cluster and random forest analysis of acoustic
           emission data

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      Abstract: Abstract Agricultural concrete structures are damaged by environmental factors. To maintain such structures, it is necessary to properly determine the mechanical properties and degree of damage suffered by concrete using core tests. In previous studies, the degree of damage has been evaluated by acoustic emissions (AE) detected in compressive stress fields. The process of fracture in damaged concrete has been evaluated by analyzing various AE parameters such as AE hits, energy, and frequency. The usefulness of many AE parameters for evaluating the fracture process is evident, but the most effective AE parameters have not yet been identified. In this study, the relationship between the stress level of concrete under compression and AE parameters was investigated using regression analysis with random forests to identify the most important AE parameters. Whether the accuracy of the regression analysis could be improved by clustering AE waves was also investigated. For this purpose, core samples, severely damaged by frost, were drilled out from a concrete headwork and subjected to compressive strength tests using the AE method. After monitoring the uniaxial compression tests, statistics for seven AE parameters were calculated for every 20 × 10−6 increment of strain. Then, AE waves were classified into three clusters based on three parameters: peak amplitude, peak frequency, and centroid frequency. The accuracy of the regression analysis was compared using non-clustered and clustered data. The peak frequencies of cluster 1 and cluster 3 were significantly higher than that of cluster 2. This result suggests that cluster 1 and cluster 3 can be attributed to macro- or mezzo-scale damage. The regression analysis’ results showed that R2 was higher (0.720 as compared to 0.620), and RMSE and MAE were lower in cluster 1 and cluster 3 (high-peak-frequency clusters) than in non-clustered cases. Therefore, cluster analysis can be expected to improve the accuracy of AE testing. Finally, the importance of AE parameters using random forests was calculated. The most important parameter was determined to be rise time, and the second was the centroid frequency. These results suggest that these two parameters can be used to clarify compressive fracture behavior of damaged concrete.
      PubDate: 2022-10-07
       
  • Evaluation of different irrigation methods based on deep evaluate model
           named IMDEM

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      Abstract: Abstract To reduce the consumption of agricultural irrigation water, which is the most part of the total water consumption, choosing the most efficient irrigation method is the best way to save agriculture water. Different from the former studies, a comprehensive evaluation method named Irrigation Method Deep Evaluation Model (IMDEM) was proposed to evaluate irrigation methods of farmland. IMDEM consists of two parts: indicator screening and Deep Evaluate Model. In the first stage, to screen the preliminary indicators and select final indicators which were used for evaluating different irrigation methods, a method named GApriori consisting of generative adversarial network (GAN) and Apriori algorithm was presented. In the second, to choose the most efficient irrigation method, Deep Evaluate Model, which includes GAN and convolutional neural network (CNN). From 2017 to 2019, field experiments were carried out in the semi-humid area in Heilongjiang Province in China. Irrigation methods during the experiment period were chosen control irrigation, wet irrigation, and flood irrigation. And 14 preliminary indicators were summarized in yield and yield components, agronomic characters, photosynthetic characteristics, and resource use efficiency. IMDEM results show that accuracy, macro-average precision rate, macro-average recall rate, and macro-average F1 value were 79%, 81%, 81%, and 79%, respectively. Additionally, after evaluated by IMDEM, control irrigation is the most suitable irrigation method in the semi-humid area of Heilongjiang Province in China. Different from former studies, IMDEM has three contributions: (1) Due to data acquisition difficulty and less data volume in the field experiment, former studies have used many replicate experiments to obtain data. Therefore, the IMDEM proposed in this paper was used GAN to generate a large amount of real-fake data for training the evaluation model. (2) Different from the traditional indicator screening methods that calculate the contribution of each indicator. The IMDEM screening indicators by counting the frequency and association relationship of indicators appearing in each sample. (3) Different from the traditional evaluation method of farmland irrigation methods that only compares rice growth period data. This paper proposed the IMDEM for comprehensive evaluating irrigation methods. And IMDEM has high accuracy for the level prediction of generated data.
      PubDate: 2022-07-14
      DOI: 10.1007/s10333-022-00908-4
       
  • Variability in meteorological droughts as pivotal mechanism for rice
           production over the middle gangetic plains

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      Abstract: Abstract The meteorological drought dynamics and its impacts on rice productivity has been evaluated for the Indian Summer Monsoon Rainfall (ISMR) season using the standardized precipitation index (SPI) over the middle Gangetic plains (MGP) of Bihar. The meteorological drought over the ISMR period was found to be a recurring phenomenon coinciding with the rice growing season over Bihar. The rice crop has an intensive water requirement; therefore, it is significantly impacted by the meteorological droughts. In the present study, spatiotemporal characteristics viz. intensity, frequency, and probability of meteorological drought has been assessed along with an investigation for significant trends and detection of regime shift points to identify the impact of drought on rice production. For the purpose, SPI-4 derived from high resolution gridded daily rainfall data (0.25° × 0.25°) from India Meteorological Department (IMD) has been considered to analyse the meteorological drought episodes over agro-climatic zones of Bihar from 1961 to 2019. The regime shifts were determined using the Rodionov test for the drought dynamics and production of rice in Bihar. A moderate to severe drought-prone zone was found over the zone BRZ3B; while zone BRZ2 and BRZ3A showed comparatively a greater number of mild drought events persisting with more than 70% probability of occurrence. An inkling of increasing dependency on groundwater is found, which is in turn governing the rice production regime. The present study shows there is a substantial need for climate resilience and food security policies incorporating the subtle linkage between SPI variability and crop production, especially over rice producing regions of the globe.
      PubDate: 2022-07-14
      DOI: 10.1007/s10333-022-00907-5
       
  • Effects of no-tillage practice for late-rice on rice yield and global
           warming potential in double-cropping rice systems

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      Abstract: Abstract Double-cropping rice systems lead to intensive greenhouse gas emissions. No-tillage in late-rice season may be a viable practice to mitigate greenhouse gas emissions without compromising rice yield. A field experiment was conducted with two treatments: tillage for both early-and late-rice (T-T) and tillage for early-rice whereas no-tillage for late-rice (T-NT). The mitigation effect of no-tillage on CH4 was mainly observed in the early vegetative stage. The difference of N2O fluxes between the treatments was mainly observed after fertilization. For the T-T and the T-NT in late-rice season, respectively, seasonal CH4 emissions were 575.1 and 502.9 kg ha−1, seasonal N2O emissions were 0.074 and 0.218 kg ha−1, and rice yields were 5687 and 5169 kg ha−1. CH4 emission was responsible for more than 99% of the global warming potential (GWP). As a result, the T-NT decreased area-scaled GWP by 12.3%, but only decreased yield-scaled GWP by 3.0% due to yield decline by 9.1%. These results reveal that the T-NT is an effective practice in mitigating area-scaled GWP, the risk of yield loss, however, will undermine farmers’ willingness to adopt the practice.
      PubDate: 2022-07-01
      DOI: 10.1007/s10333-022-00894-7
       
  • Identification of optimal level of nitrogen fertilizer and tillage
           practice to reduce nitrous oxide emissions and maximize the nitrogen use
           efficiency and productivity from tropical rice paddy

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      Abstract: Abstract Agricultural tillage practices and fertilizer play an important role in production and consumption of greenhouse gases (GHGs), which contribute to global climate change. Nitrous oxide (N2O) is a major GHG with high global warming potential produced by agricultural systems. This study assessed the yield and N2O emission from rice cropping system under conventional tillage (CT) and reduced tillage (RT) farming systems and four levels of nitrogenous fertilizer i.e. zero nitrogen or fertilizer level 1 (F1), 30 kg-N ha –1 or fertilizer level 2 (F2), 40 kg-N ha–1 or fertilizer level 3 (F3), and 50 kg-N ha–1 or fertilizer level 4 (F4). N2O emission was measured by static chamber technique. Both the tillage practices and fertilizer significantly (p < 0.05) affected the N2O emissions and an average RT practice increased the N2O emission by 9.77% over CT practice. The 25% reduction in fertilizer rate (30 kg N ha–1) over normal rate (40 kg N ha–1) decreased the cumulative emission by 6.90% in CT and 7.59% in RT. The nitrogen use efficiency (NUE) decreased with increasing nitrogen levels and treatmentF2 in both CT and RT with 30 kg N ha–1 increased the NUE and yield, thus leading to the lowest yield-scaled N2O–N emission. The 25% reduction in fertilizer rate or efficient use of applied nitrogen fertilizer in CT plots may be considered an effective and environment-friendly strategy to mitigate climate change through minimizing N2O emissions with optimum productivity.
      PubDate: 2022-06-24
      DOI: 10.1007/s10333-022-00906-6
       
  • Effect of injection on bed shear stress and turbulence characteristics in
           a closed conduit flow

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      Abstract: Abstract Bed shear stress and turbulence quantities are important parameters to understand sediment erosion, transport, and hydraulic processes in most hydraulic studies. An experimental investigation was conducted to understand the effect of injection on the bed shear stress and turbulence characteristics of flows during low sediment transport rate in a closed conduit, which is similar in construction to the erosion function apparatus. In particular, the effect of injection on the bed shear stress, mean velocity profiles, turbulence intensities, Reynolds shear stress, and higher-order moments of the closed conduit flows in the seepage zone as well as at the upstream edge of the seepage zone was examined. The instantaneous velocities were measured using two-dimensional particle image velocimetry (PIV) to evaluate the turbulence structure in both the seepage zone and at the upstream edge of the seepage zone. The bed shear stress estimated by the Reynolds shear stress approach was found to be more appropriate than that estimated by the usual logarithmic law approach. However, a spatial fluctuation in the bed shear stress was noticed as the injection intensity was increased. Injection was found to decrease the velocity near the bed and to increase the velocity near the center of the conduit in comparison to the no-seepage condition in both zones. The injection resulted in more of a decrease in bed stability in the seepage zone in comparison to the upstream edge of the seepage zone as the injection intensities were increased. The introduction of injection increased the magnitudes of the various turbulence parameters in comparison to the no-seepage condition in the seepage zone. The effect of injection was not only visible in the near-bed region, but in both zones as the water depth (measured from top of the sediment surface) increased.
      PubDate: 2022-06-02
      DOI: 10.1007/s10333-022-00905-7
       
  • Recycling deep percolated water in continuously flooding irrigated rice
           fields to mitigate water scarcity

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      Abstract: Abstract Rice is critical to maintaining nutritional demand and food security of many Asian and African nations. The high water demanding rice is traditionally cultivated with continuous flooding (CF) irrigation practices where 60–90% of applied water can be lost as deep percolation. Burgeoning pressures from other sectoral water demands often challenge flooding rice culture. Existing water conserving rice irrigation approaches are not widely accepted at farmers’ level because of compromising yield and/or high operating cost. This study presents the efficacy of a subsurface interceptor system in recycling percolated water for re-irrigating rice fields. The system comprises a pump and filter PVC pipes buried one meter below an experimental rice plot (A) to intercept, store and recycle percolating water. Rice was cultivated in two other adjacent plots (B and C) without an interceptor arrangement where any lateral seepage was restricted in plot B, as did for plot A. There was no such measure for plot C representing a conventional rice field. It was found that plot A produced the highest yield (6.5 t/ha) using the lowest amount of water (650 mm). This could save ~ 50% of water needed for CF irrigated plot C where percolation was the main pathway of water loss (65%). Additional energy requirement for recycling intercepted water was overshadowed by the energy burden of pumping larger amount of water against higher system head for plot C. This led the recycling system to produce the highest irrigation water productivity (3.19 kg/m3) and energy productivity (8.86 kg/kWh).
      PubDate: 2022-06-02
      DOI: 10.1007/s10333-022-00904-8
       
  • Groundwater estimation of Ghayen plain with regression-based and hybrid
           time series models

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      Abstract: Groundwater estimation to be aware of groundwater level and its decline, as well as the well discharge rate in different time periods, is one of the important and practical issues in the field of groundwater level management and abstraction management. Quantitative information on groundwater resources is essential to manage those best and to propose solutions and constraints on aquifer abstraction. Accurate modeling and prediction of this information also helps avoid financial losses and contributes to the protection of natural resources. Regarding the importance of knowing the groundwater level in the region in future periods, in the present study, the time series of groundwater levels in seven wells in the Ghayen plain on a monthly scale in the statistical period 1997–2018 was used. Contemporaneous Autoregressive Moving Average (CARMA) multivariate and time series models, integrated time series model with isotropy (CARMA-ARCH), multivariate regression and support vector regression were used aiming for the aforementioned. Ant colony optimization algorithms, ant-trap optimization strategies, salp swarm methods, dragonfly algorithms and multiverse algorithms were investigated in order to optimize the parameters of the support vector regression model. The results of simulations showed that in terms of the involvement of different optimization algorithms in SVR-based simulations, the accuracy of groundwater estimation in all wells is appropriate and acceptable. The lowest error rate in groundwater estimation of Shir Morgh Road, Pahnai, Firoozabad Road and Sineh-Kooh-Aboozar wells in terms of support vector regression method optimized with dragonfly algorithm–support vector regression, ant colony optimization–support vector regression, antlion optimizer–support vector regression, antlion optimizer–support vector regression algorithms was estimated at 0.192, 0.46, 0.091 and 0.63 m, respectively. Moreover, multivariate regression method in Birjand Ghayen Road, Northern Kalateh Khan and Northern Esfashad wells obtained the lowest error of 0.412, 0.163 and 0.238, respectively. The best efficiency extracted from the Nash–Sutcliffe coefficient in most wells is also related to CARMA method, whose efficiency improvement was over 97%. Since this study aims to provide an optimal method in groundwater quantity studies, the results indicate the proper performance of optimized and hybrid models that include different family models.
      PubDate: 2022-05-25
      DOI: 10.1007/s10333-022-00903-9
       
  • Crop type detection using an object-based classification method and
           multi-temporal Landsat satellite images

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      Abstract: Abstract Crop type detection is of great importance in water resource allocation and planning mostly in arid and semi-arid regions of Iran. Landsat-OLI 16-day inter-annual images are invaluable sources obviating crop monitoring into issues of crop types detection, crop yield prediction, and crop pattern studies. Although many classification methods such as decision tree (DT), support vector machine (SVM), and maximum likelihood (ML) were implied for crop type mapping, recent researches often use an object-based classification approach. In this study, an object-based image analysis (OBIA) classifier based on rule-based decision tree (RBDT) and object-based nearest neighbor (OBNN) used to delineate five common crop types (includes Wheat and Barley together in one class, rice, multiple crop (MC), Alfalfa and Spring crops) in Isfahan city and nearby areas. The classification was applied in five scenarios using different vegetation indexes including normalized difference vegetation index (NDVI), normalized difference water index (NDWI), green normalized difference vegetation index GNDVI and their combination. All scenarios property and accuracy assessed both with by class separation distance matrix and confusion matrix. The overall accuracy of classification with using only one vegetation index was lower than other scenarios. It was the lowest for GNDVI rating 37% whereas combination of Indexes resulted better accuracy. In final map with combination of NDVI, GNDVI and NDWI, overall accuracy and kappa achieved to 88% and 0/83 successively. Comparing individual accuracy of different crops showed that MC crops with 66% has the lowest accuracy and Wheat-Barely crops with 94.8% individual accuracy has the Maximum accuracy. Other crop types accuracy alters between 66 and 94.8%.
      PubDate: 2022-05-14
      DOI: 10.1007/s10333-022-00901-x
       
  • Integration of ridge and furrow rainwater harvesting systems and soil
           amendments improve crop yield under semi-arid conditions

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      Abstract: Abstract Low crop productivity due to prolonged droughts, inappropriate water saving practices, low soil fertility and soil erosion is a major threat to food security in semi-arid areas. In these areas, ridge and furrow rainwater harvesting (RFRH) technique is widely adopted to minimize water deficiency problems. Incorporating mulching in ridge and furrow rainwater harvesting (RFRH + M) is also being promoted to increase water storage and conservation for crop usage. Till date, evidence establishing the efficacy of incorporating mulching and biochar in ridge and furrow system, and modalities for improving crop yield has not been synthesized quantitatively to promote widespread adoption. The objective of this MA was to assess the whether the integration of ridge and furrow rainwater harvesting systems (RFRHs) with soil amendments, namely biochar or mulches affect crop yield and soil properties relative to traditional no-till flat planting. In addition, the MA investigated how factors such as such as precipitation moderate the performance of RFRHs with soil amendments in different regions in China was investigated. A meta-analysis (MA) of data from 42 published articles based on PRISMA guidelines was used to assess the impacts of ridge and furrow tillage with and without mulching on potato (Solanum tuberosum, L.), wheat (Triticum aestivum, L.), and maize (Zea mays, L.) yield relative to traditional no-till flat planting in the Loess Plateau of China. Mulch materials were plastic and straw in addition to biochar amendment. RFRH + M significantly affected crop yield in Gansu, Ningxia, Shanxi and Shaanxi regions of the Loess Plateau. Plastic film mulched ridge-furrow planting compared with flat planting without mulching increased potato yield by 34.01% in Gansu, 32.99% in Ningxia, and 12.78% in Shanxi. Maize yield increased by 33.10% in bare ridge-furrow planting with mean of 10,936.81 kg ha−1 compared with flat planting with a mean of 8217.07 kg ha−1. Conversely, in areas where precipitation was higher than 500 mm, integrated plastic film with straw in ridge-furrow significantly (p < 0.00001) increased wheat yield by 60% compared to flat planting without mulching, which can be attributed to the soil alkalinity (pH > 7–8) of the soils in these areas. The observed differences in crop yield could also be ascribed to the influence of phosphorus availability. Results from the MA showed that the effect of straw mulched-ridge-furrow on crop yield was stronger in soils with higher available phosphorus at 20 mg kg−1 (5.31%; p = 0.0003) than flat planting without mulching. Findings of the MA suggest that the adoption of integrated plastic film mulch with straw in ridge and furrow system can improve soil properties and crop yield under rain-fed conditions. Compared with flat planting without mulching, incorporating plastic film mulch and straw in ridge and furrow systems averts residual plastic film accumulation on farmlands, which could impede plant growth, soil structure, water and nutrient uptake in rain-fed agriculture in semi-arid areas.
      PubDate: 2022-05-09
      DOI: 10.1007/s10333-022-00900-y
       
  • Greenhouse gas emissions from paddy fields in Bangladesh compared to top
           twenty rice producing countries and emission reduction strategies

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      Abstract: Abstract Greenhouse gas (GHG) emissions from agriculture contribute to global warming. Total GHG emissions from paddy fields based on life cycle assessments are limited in developing countries because of data lacking. The amounts of carbon (C) emissions and GHG intensity have been evaluated for top 20 rice producing countries based on measured and review of literature for determining relative position of Bangladesh and delineating reduction strategies of GHG emissions from paddy fields. In 2018, the position of Bangladesh was 7th among top 20 rice producing countries in terms of methane (CH4) emission. Per capita CH4 emission because of rice cultivation was the highest in Cambodia followed by Thailand and 8th position for Bangladesh. The higher per capita GHG emissions were recorded in Thailand (1595.24 kg CO2 eq.) than in Cambodia (1517.21 kg CO2 eq.) and in Bangladesh, it was 706.72 kg CO2 eq. Greenhouse gas intensity (GHGI) was the highest in China (5.87 kg kg−1) than in Thailand (3.91 kg kg−1) and in India (3.44 kg kg−1). Position of Bangladesh was 6th among top 20 rice producing countries in terms of total GHG emission for rice cultivation (9903.03 kg CO2 eq. ha−1). In Bangladesh, irrigation water management contributed about 30% of indirect GHG emission and that of fertilizers by about 6.5%. The balance between C inputs and outputs resulted in net emission by about 179.92 kg C ha−1 because of rice cultivation in Bangladesh. There were comparatively greater total GHG emissions from paddy fields in developed countries than in the least developed and developing countries. The GHG emissions could be minimized by adopting reduced tillage practices, alternate wetting and drying (AWD), fertilizer placement, suitable cropping patterns, high yielding short duration varieties, and integrated nutrient management.
      PubDate: 2022-05-09
      DOI: 10.1007/s10333-022-00899-2
       
  • A field test to investigate spatiotemporal distribution of soil moisture
           under different cropland covers in the semiarid Loess Plateau of China

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      Abstract: Abstract In order to simultaneously describe the spatial and temporal variations of soil moisture and the influence of land cover conditions in the semiarid Loess Plateau in Northwestern China, a field test was performed. In this study, four cover conditions were considered, including bare soil without any cover, non-vegetated soil with plastic mulch (PM), potato field with PM and maize field with PM. The actively heated fiber optics (AHFO) method was used to capture spatial soil moisture distribution, and the frequency domain reflectometry (FDR) sensor with a temporal spatial resolution of 3 min was used to record temporal moisture variation. The experimental results indicate that if the soil moisture remains constant and the cumulative precipitation slowly increases, the in-situ apparent effective soil hydraulic conductivity can be inferred from the precipitation rate. The in-situ measured apparent effective soil hydraulic conductivity has been found to be 7.09 × 10–7 m/s in this study. The estimated evapotranspiration rate was 5.68 mm/d as inferred from linear reduction rate of soil moisture after a rainfall, which agreed well with the reported average value in semiarid regions. The PM can effectively prevent water loss due to field evapotranspiration and result in aggravation of spatially uneven distribution of subsurface soil moisture under the same cover condition and depth. The growth of plant roots facilitates water holding capacity and evapotranspiration rate of soil and reduces its temporal stability.
      PubDate: 2022-04-02
      DOI: 10.1007/s10333-022-00896-5
       
 
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