Characterizing the spatiotemporal distribution of dissolved organic matter (DOM) in the Yongding River Basin: Insights from flow regulation

Bai, Yijuan; Zhang, Shurong; Mu, Enlin; Zhao, Yinjun; Cheng, Long; Zhu, Yi; Yuan, Yumin; Wang, Yingying; Ding, Aizhong

doi:10.1016/j.jenvman.2022.116476

Cited by 17 publications

(3 citation statements)

References 113 publications

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“…Accurate determination of SOC is of immense importance in formulating effective land management tactics, environmental regulations, climate change mitigation plans, and conservation methodologies aimed at increasing soil carbon sequestration [5,6]. It provides vital information for understanding and monitoring soil health, carbon sequestration potential, and sustainable land use practices [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Using Various Models for Predicting Soil Organic Carbon Based on DRIFT-FTIR and Chemical Analysis

Thabit,

Negim,

AbdelRahman

et al. 2024

Soil Systems

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Soil organic carbon (SOC) is a crucial factor influencing soil quality and fertility. In this particular investigation, we aimed to explore the possibility of using diffuse reflectance infrared fourier transform spectroscopy (DRIFT-FTIR) in conjunction with machine-learning models, such as partial least squares regression (PLSR), artificial neural networks (ANN), support vector regression (SVR) and random forest (RF), to estimate SOC in Sohag, Egypt. To achieve this, we collected a total of ninety surface soil samples from various locations in Sohag and estimated the total organic carbon content using both the Walkley-Black method and DRIFT-FTIR spectroscopy. Subsequently, we used the spectral data to develop regression models using PLSR, ANN, SVR, and RF. To evaluate the performance of these models, we used several evaluation parameters, including root mean square error (RMSE), coefficient of determination (R2), and ratio of performance deviation (RPD). Our survey results revealed that the PLSR model had the most favorable performance, yielding an R2 value of 0.82 and an RMSE of 0.006%. In contrast, the ANN, SVR, and RF models demonstrated moderate to poor performance, with R2 values of 0.53, 0.27, and 0.18, respectively. Overall, our study highlights the potential of combining DRIFT-FTIR spectroscopy with multivariate analysis techniques to predict SOC in Sohag, Egypt. However, additional studies and research are needed to improve the accuracy or predictability of machine-learning models incorporated into DRIFT-FTIR analysis and to compare DRIFT-FTIR analysis techniques with conventional soil chemical measurements.

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Section: Introductionmentioning

confidence: 99%

Using Various Models for Predicting Soil Organic Carbon Based on DRIFT-FTIR and Chemical Analysis

Thabit,

Negim,

AbdelRahman

et al. 2024

Soil Systems

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“…The most important function of interrelations of ecosystem components (biotic and abiotic) having genetic, historical and functional relationships, manifesting themselves in continuous exchange of substances, energy and information, is performed at a basin level (Bai et al, 2023;Montes et al, 2023). A river basin acts as an integral system with established ecological, social and economic relationships (Li et al, 2022;Jiang et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Agricultural Dependence of the Formation of Water Balance Stability of the Sluch River Basin Under Conditions of Climate Change

Pichura,

Potravka,

Barulina

2023

Ecol. Eng. Environ. Technol.

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The purpose of the research was to calculate water footprint in growing the basic field crops and establish the volumes of additional water accumulation to provide the hydro-functioning of the Sluch river basin in the territory of Ukraine under conditions of climate change. The research was based on the data of climate change analysis in 1901-2022, decoding of the actual satellite imagery of the spacecraft Sentinel 2 and statistical data on crop rotation structure in the agro-landscapes of the water catchment area in the research region. The volumes of water footprint were calculated for the vegetation periods of the basic field winter and spring crops in 2018-2021: 2018-2019 -a semi-wet year grows into a dry year; 2019-2020 -a dry year grows into a semi-wet year; 2020-2021 -a semi-wet year grows into a wet year. Spatio-temporal regularities of the formation of water footprint and the ratio of green and blue water use in growing different agricultural crops were determined. The total volume of water footprint in growing the field crops of a certain crop rotation equaled:

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“…The Yongding River basin receives scarce precipitation [20,21] and is a typical waterscarce basin in northern China [22][23][24]; thus, the severe water shortages have received considerable attention from researchers [25][26][27]. The agricultural economy is an important economic source in the Yongding River basin, and water for agricultural irrigation is an important factor contributing to water scarcity in the Yongding River [28,29].…”

Section: Introductionmentioning

confidence: 99%

Evolution of Hydrological Conditions and Driving Factors Analysis of the Yongding River in a Changing Environment: A Case Study of the Xiangshuipu Section

Yang,

Cai,

Wang

et al. 2023

Agronomy

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Hydrological conditions are key factors in the evaluation of water resources and ecosystems. The Yongding River Basin has many irrigated areas, and excessive agricultural water consumption has led to serious water shortages and ecosystem damage. To investigate the evolution of ecohydrological conditions and their driving factors in the Yongding River basin in a changing environment, this study combines indicators of hydrologic alteration with the range of variability approach (IHA-RVA) to identify the most ecologically relevant hydrological indicators (ERHIs) and to determine the periods of hydrological variability in the basin, using the Xiangshuipu section on the Yang River as the study area. By calculating the degree of hydrological alteration, the evolutionary pattern of ecohydrological conditions in the basin was analyzed, and the WetSpa model was used to quantitatively identify the contributions of climate change, reservoir storage, and irrigation water withdrawal to the alteration of hydrological conditions. The results showed that the rise and fall rate; maximum and minimum 1 day flows; dates of maximum flow; and July flows were the most ecologically relevant hydrological indicators for the Xiangshuipu section. Variability of this section occurred between 1982 and 1988; except for the annual maximum 1 day flows and fall rate, which underwent moderate changes; all other indicators exhibited small changes and the overall hydrological alteration of the Xiangshuipu section was low. The most influential change in the hydrological conditions was irrigation water withdrawal (from specific irrigation); followed by climate change and reservoir storage. The results of this study provide an important basis for water resources utilization and ecological management in the Yongding River basin.

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Characterizing the spatiotemporal distribution of dissolved organic matter (DOM) in the Yongding River Basin: Insights from flow regulation

Cited by 17 publications

References 113 publications

Using Various Models for Predicting Soil Organic Carbon Based on DRIFT-FTIR and Chemical Analysis

Using Various Models for Predicting Soil Organic Carbon Based on DRIFT-FTIR and Chemical Analysis

Agricultural Dependence of the Formation of Water Balance Stability of the Sluch River Basin Under Conditions of Climate Change

Evolution of Hydrological Conditions and Driving Factors Analysis of the Yongding River in a Changing Environment: A Case Study of the Xiangshuipu Section

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