Determination of long-term volume change in lakes by integration of UAV and satellite data: the case of Lake Burdur in Türkiye

Kaya, Yunus; Sanli, Fusun Balik; Abdikan, Saygin

doi:10.1007/s11356-023-30369-z

Cited by 9 publications

(4 citation statements)

References 84 publications

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“…Moreover, drought propagation is closely related to the water cycle. Satellites enable more comprehensive estimation of multiple aspects of the water cycle, such as lake level and volume changes [56,57]. More factors in the water environment should be considered in drought chain processes.…”

Section: The Drought Chain Methods For Estimating Precipitation Accuracymentioning

confidence: 99%

Can the Accuracy of Fine-Resolution Precipitation Products Be Assessed from the Surrounding Water Balance and Drought Chain (WBDC) in the Qinghai–Tibetan Plateau?

Li,

Shi,

Pan

et al. 2023

Remote Sensing

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The Qinghai–Tibetan Plateau (QTP), which has a unique and severe environment, suffers from the absence of rainfall gauges in western arid land. Using different precipitation products in this region would easily lead to contradictory results. To evaluate nine fine-resolution precipitation products in the QTP, we propose a “down to top” methodology, based on water balance and drought chain, by forecasting two accuracy assessment indices—multi-year precipitation bias and precipitation correlation. We assessed the biases of all products in the Jinsha–Yalong, Yellow, Heihe, Yangtze, Yarlung Zangbo catchments and interior drainage areas. And we assessed gauge-based correlation of precipitation products, based on the correlations between precipitation product-based effective drought index (EDI), Soil Moisture Active Passive (SMAP)-based soil moisture anomaly, and the moderate-resolution imaging spectroradiometer (MODIS)-based normalized difference vegetation index (NDVI) anomaly (R = 0.712, R = 0.36, and R = 0.785, respectively) for cross-sectional rainfall observations on the Tibetan Plateau in 2018. The results showed that ERA5-Land and IMERG merged precipitation dataset (EIMD) can efficiently close the water budget at the catchment scale. Moreover, the EIMD-based EDI exhibited the best performance in correlation with both the SMAP-based soil moisture anomaly and MODIS-based NDVI anomaly for the three main herbaceous species areas—Kobresia pygmaea meadow, Stipa purpurea steppe, and Carex moorcroftii steppe. Overall, we find that EIMD is the most accurate among the nine products. The annual average precipitation (2001–2018) was determined to be 568.16 mm in the QTP. Our assessment methodology has a remote sensing basis with low cost and can be used for other arid lands in the future.

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Section: The Drought Chain Methods For Estimating Precipitation Accuracymentioning

confidence: 99%

Can the Accuracy of Fine-Resolution Precipitation Products Be Assessed from the Surrounding Water Balance and Drought Chain (WBDC) in the Qinghai–Tibetan Plateau?

Li,

Shi,

Pan

et al. 2023

Remote Sensing

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“…Water resources are essential for the survival of humans, plants, and animals [1]. The growing global population and economic growth have resulted in an elevated need for water supplies.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Groundwater Potential Zones by Integrating Hydrogeological Data, Geographic Information Systems, Remote Sensing, and Analytical Hierarchical Process Techniques in the Jinan Karst Spring Basin of China

Opoku,

Shu,

Amoako-Nimako

2024

Water

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Groundwater management in the Jinan Spring basin is hampered by its complex topography, overexploitation, and excessive urbanisation. This has led to springs drying up during dry seasons and a decrease in discharge in recent years. GIS and the AHP were employed to delineate groundwater potential zones using eight thematic layers: slope, geology, lineament density, topographic wetness index (TWI), rainfall, soil, drainage density, and land use/land cover (LULC). The model’s accuracy was assessed by comparing the findings to basin groundwater observation well data. We found that 74% of the observations matched the projected zoning. Further validation utilising the receiver operating characteristic (ROC) curve gave an AUC of 0.736. According to the study, 67.31% of the land has a good GWPZ, 5.60% has a very good one, 27.07% is medium, and 0.03% is low. Heavy rains throughout the rainy season raise water levels. Dry weather lowers water levels. This study’s conclusions will protect groundwater from climate change. Integrating hydrogeological data, GIS, remote sensing, and AHP approaches maximises data use, improves groundwater potential zone delineation, and promotes sustainable groundwater resource management decision making. This integrated method can help land use planners, hydrologists, and policymakers find optimal locations for water supply projects, establish groundwater management techniques, and reduce groundwater risks.

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“…For instance, it is less sensitive to water quality parameters such as COD [21]. Moreover, water transparency is affected by various factors, including climate, season, and substrate [22][23][24][25]. The specific relationship between transparency and the water quality parameters it reflects remains unclear.…”

Section: Introductionmentioning

confidence: 99%

A Qualitative Study of Water Quality Using Landsat 8 and Station Water Quality-Monitoring Data to Support SDG 6.3.2 Evaluations: A Case Study of Deqing, China

Chen,

Tan,

Peng

et al. 2024

Water

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Facing the challenge of the degradation of global water quality, it is urgent to realize the Sustainable Development Goal 6.3.2 (SDG 6.3.2), which focuses on improving global water quality. Currently, remote sensing technology is widely used for water quality monitoring. Existing water quality-monitoring studies have been conducted based on quantitative water quality inversion. It requires a high degree of the synchronization of the time and location of the collection of station monitoring data and remote sensing data (air–ground spatiotemporal synchronization), which can be resource intensive and time consuming. However, policymakers and the public are more interested in the quality of water (good or poor) than in the specific values of the water quality parameters, as evidenced by the emergence of SDG 6.3.2. In this study, we change the traditional idea of quantitative water quality research, focus on water quality qualitative research combined with the characteristics of water pollution, propose a remote sensing water quality sample enhancement method under the condition of “air–ground spatiotemporal asynchrony”, and construct a remote sensing water quality sample library. On the basis of this sample library, a random forest water quality classification model was constructed to classify water quality qualitatively. We obtained the distribution of good water bodies in Deqing County, China, for example, from 2013 to 2022. The results show that the model has high accuracy (Kappa = 0.6004, OA = 0.8387), and we found that the water quality in Deqing County improved in the order of “major rivers, lakes, and tributaries” during the period from 2013 to 2015. This also verifies the feasibility of using this sample enhancement method to conduct qualitative research on water quality. Based on this water quality classification model, a set of spatial-type evaluation processes of SDG 6.3.2 based on image elements was designed. The evaluation results show that the water quality situation in Deqing County can be divided into two stages: there is a trend of substantial improvement from 2013 (evaluated value of SDG 6.3.2 = 63.25) to 2015 (evaluated value of SDG 6.3.2 = 83.16); and it has remained stable and fluctuating after reaching the good environmental water quality since 2015. This study proposes a simple method for rapidly evaluating SDG 6.3.2 via utilizing easily accessible Landsat 8 and water quality-monitoring data to classify water quality. The method can directly obtain water quality category information without the need for additional sampling, thus saving costs. It is a very simple process that is easy to implement, while also providing a high level of accuracy. This significantly reduces the barriers to evaluating SDG 6.3.2, supports the realization of the sustainable management of water resources globally, and is highly generalizable.

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Determination of long-term volume change in lakes by integration of UAV and satellite data: the case of Lake Burdur in Türkiye

Cited by 9 publications

References 84 publications

Can the Accuracy of Fine-Resolution Precipitation Products Be Assessed from the Surrounding Water Balance and Drought Chain (WBDC) in the Qinghai–Tibetan Plateau?

Can the Accuracy of Fine-Resolution Precipitation Products Be Assessed from the Surrounding Water Balance and Drought Chain (WBDC) in the Qinghai–Tibetan Plateau?

Assessment of Groundwater Potential Zones by Integrating Hydrogeological Data, Geographic Information Systems, Remote Sensing, and Analytical Hierarchical Process Techniques in the Jinan Karst Spring Basin of China

A Qualitative Study of Water Quality Using Landsat 8 and Station Water Quality-Monitoring Data to Support SDG 6.3.2 Evaluations: A Case Study of Deqing, China

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