Long-term monitoring of soil salinity in a semi-arid environment of Turkey

Akça, Erhan; Aydin, Mehmet; Kapur, Selım; Kume, Takashi; Nagano, Takanori; Watanabe, Teiji; Çilek, Ahmet; Zorlu, Kemal

doi:10.1016/j.catena.2020.104614

Cited by 41 publications

(22 citation statements)

References 17 publications

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“…Drip irrigation under mulch is small-scale irrigation, which can effectively maintain soil moisture and evenly drive out salt ( Akça et al, 2020 ). In the process of drip irrigation, the salt in the soil has a directional distribution ( Wang et al, 2014b ).…”

Section: Discussionmentioning

confidence: 99%

“…In our study, the soil moisture of the 0-60 cm layer in T2 was higher than that in T3, indicating that the water holding capacity of the middle and upper plow layer in T2 was better than that in T3. Drip irrigation under mulch is small-scale irrigation, which can effectively maintain soil moisture and evenly drive out salt (Akça et al, 2020). In the process of drip irrigation, the salt in the soil has a directional distribution (Wang et al, 2014b).…”

Section: Discussionmentioning

confidence: 99%

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Effects of drip tape modes on soil hydrothermal conditions and cotton yield (Gossypium hirsutumL.) under machine-harvest patterns

Wang

et al. 2021

PeerJ

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Background The layout of drip tapes under mulch has changed in Xinjiang, China, with the development of machine-harvest cotton (Gossypium hirsutum L.) planting technology. This study aims to demonstrate the effects of drip tape modes on soil hydrothermal conditions, cotton yield, and water use efficiency (WUE) of machine-harvest cotton under mulch in Xinjiang. Methods A field experiment was conducted to set up two machine-harvest cotton planting patterns (T1: the cotton planting model with one film, two drip tapes and six rows; T2: the cotton planting model with one film, three drip tapes and six rows), and a conventional planting mode (T3: the cotton planting model with one film, two drip tapes and four rows) as a control. Results Our results showed that the heat preservation and warming effects of the cotton planting model with one film, two drip tapes and six rows and the cotton planting model with one film, three drip tapes and six rows were better than that of the conventional planting mode. Soil temperature under the mulching film quickly increased and slowly decreased, which was beneficial to the early growth and development of cotton. The mean soil moisture content of the 0–60 cm soil layer in the cotton planting model with one film, three drip tapes and six rows was significantly higher than the other two treatments at the middle and late stage of cotton growth (90 days after sowing (DAS) and 135 DAS). Moreover, the water holding capacity of the middle and upper part of the tillage layer in the cotton planting model with one film, three drip tapes and six rows was the best. At the medium cotton growth stage, the main root layer in the cotton planting model with one film, three drip tapes and six rows formed a desalination zone. At the late cotton growth stage, the soil salinity content of the 0–60 cm soil layer showed that the cotton planting model with one film, three drip tapes and six rows was the lowest, the cotton planting model with one film, two drip tapes and six rows was the highest, and the conventional planting pattern was in the middle. Among these three modes, the cotton planting model with one film, three drip tapes and six rows was more efficient in controlling soil salt accumulation. The agronomic traits and cotton quality in the cotton planting model with one film, three drip tapes and six rows were better than that for the other two treatments. Compared with the other treatments, the cotton yield in the cotton planting model with one film, three drip tapes and six rows increased by 6.15% and 11.0% and 8.1% and 12.3%, in 2017 and 2018, respectively, and WUE increased by 17.4% and 22.7% and 20.9% and 22.8%, in 2017 and 2018 respectively. In conclusion, the cotton planting model with one film, three drip tapes and six rows can be recommended for machine-harvest cotton planting for arid areas in Xinjiang, considering water conservation and improving cotton yield.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Effects of drip tape modes on soil hydrothermal conditions and cotton yield (Gossypium hirsutumL.) under machine-harvest patterns

Wang

et al. 2021

PeerJ

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“…As a form of soil degradation, soil salinization not only destroys resources and reduces agricultural production, but also poses a severe threat to the biosphere and ecological environment, thus becoming an environmental problem worldwide [1,2]. Soil salinization is a process during which soluble salt accumulates on the soil surface, and it is one of the main forms of land desertification and degradation [3].…”

Section: Introductionmentioning

confidence: 99%

Monitoring of Soil Salinization in the Keriya Oasis Based on Deep Learning with PALSAR-2 and Landsat-8 Datasets

et al. 2022

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Currently, soil salinization is one of the main forms of land degradation and desertification. Soil salinization not only seriously restricts the development of agriculture and the economy, but also poses a threat to the ecological environment. The main purpose of this study is to map soil salinity in Keriya Oasis, northwestern China using the PALSAR-2 fully polarized synthetic aperture radar (PolSAR) L-band data and Landsat8-OLI (OLI) optical data combined with deep learning (DL) methods. A field survey is conducted, and soil samples are collected from 20 April 2015 to 1 May 2015. To mine the hidden information in the PALSAR-2 data, multiple polarimetric decomposition methods are implemented, and a wide range of polarimetric parameters and synthetic aperture radar discriminators are derived. The radar vegetation index (RVI) is calculated using PALSAR-2 data, while the normalized difference vegetation index (NDVI) and salinity index (SI) are calculated using OLI data. The random forest (RF)-integrated learning algorithm is used to select the optimal feature subset composed of eight polarimetric elements. The RF, support vector machine, and DL methods are used to extract different degrees of salinized soil. The results show that the OLI+PALSAR-2 image classification result of the DL classification was relatively good, having the highest overall accuracy of 91.86% and a kappa coefficient of 0.90. This method is helpful to understand and monitor the spatial distribution of soil salinity more effectively to achieve sustainable agricultural development and ecological stability.

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“…Jin et al (2019) reported that alluvial farmland is located in gullies with a shallow groundwater table. High evapotranspiration rate and shallow groundwater table are the main causes of soil salinization in arid and semi-arid areas (Akça et al, 2020;Wang et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

On the importance of monsoon rainstorm impact period in soil salinization

Liu

et al. 2021

Preprint

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Long-term soil salt accumulation could lead to salinization. Aimed to prevent soil salinization, we investigated soil salt dynamics, its interface with the groundwater table, rainfalls duration and the impact periods when salt is mostly accumulated. Total soil salt accumulation and dynamic distribution were monitored in the 0–80 cm layer in alluvial farmland from 2018 to 2020. We found soil salt contents increased by 0.15 g kg–1 and 0.07 g kg–1 in the 0–40 and 40–80 cm soil layers, respectively, which indicated that soil salinization occurred. We defined the rainstorm impact period (RIP) as period when soil salt dynamic distribution was affected by rainstorm event. The salinity time-trend during RIP was sequentially characterized by a first salt leaching, followed by a rapid and then slow salt accumulation, which took the first 4 days, from day 4 to 10, and then beyond, respectively. In the first leaching stage, salt migration content was determined by rainfall (P < 0.05) which could leach 41.5% of salt on average in the whole soil layer. In the rapid accumulation stage, lots of salt accumulated due to high evapotranspiration and shallow groundwater table. In the slow accumulation stage, salt accumulation rate was inhibited by deeper groundwater table. In addition, the total accumulated soil salt in the whole soil layer increased by 0.14 g kg–1 in the RIPs, which comprised only 14.5% of the overall study period, but the value accounted for 63.6% of the salt accumulation, thereby indicating that RIPs were the main periods when salt accumulated during the soil salinization process. Our results provided insights into soil salt dynamic distribution during RIPs, thereby facilitating the effective prevention and control of soil salinization.

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Long-term monitoring of soil salinity in a semi-arid environment of Turkey

Cited by 41 publications

References 17 publications

Effects of drip tape modes on soil hydrothermal conditions and cotton yield (Gossypium hirsutumL.) under machine-harvest patterns

Effects of drip tape modes on soil hydrothermal conditions and cotton yield (Gossypium hirsutumL.) under machine-harvest patterns

Monitoring of Soil Salinization in the Keriya Oasis Based on Deep Learning with PALSAR-2 and Landsat-8 Datasets

On the importance of monsoon rainstorm impact period in soil salinization

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