Surface Water Distribution Research Articles

Modeling of Soil Water Distribution in a Small Mid-Latitude Watershed on the British Isle for Short Term Landslide and Flood Risk Assessment

The R-TopModel hydrological model coupled with two landslide and flood probability distribution models was applied to simulate the daily hydrological conditions of a small catchment in the Midlands of the British Isles, throughout 2017. Originally, the methodology was applied to a risk area in the tropical region. In this work, the application was extended to mid-latitude watersheds. The hydrographic basin around the Carsington Water dam (located in the Midlands of the Great Britain) is chosen because it presents risks. The model Nash-Sutcliffe Efficiency for the upstream discharge from the Carsington Water dam reached 50% with a correlation coefficient of the order of 70%, an acceptable value considering the seasonal effects of the dam on evapotranspiration and higher soil permeability. Modeling the distribution of soil moisture and excess surface water allowed obtaining the spatial distribution of the maximum conditional probability of landslides and floods in the Carsington Water catchment. These probability maps obtained are consistent with long-term susceptibility maps for Great Britain.

Microplastics abundance, distribution and composition in surface waters, sediments and fish species from Amir-Kalayeh Wetland, Northern Iran.

Microplastics (MPs) pollution is considered as a globally pervasive threat to aquatic ecosystems and many studies reported this pollution in different aquatic ecosystems. However, studies on MPs pollution in wetlands are still scarce. Therefore, the aim of present study was to investigate the presence of MPs in the surface water, sediment and different fish species of Amir-Kalayeh wetland, Northern Ian. Surface water and sediment samples were collected from six stations during June to July 2022. Moreover, the gills and gastrointestinal tract (GIT) of 54 fish specimens belonging to four species including Cyprinus carpio, Tinca tinca, Esox lucius and Silurus glanis were analysed. MPs were detected in all samples with an average of 2.15 ± 1.98 items/m3 for surface water, 51.66 ± 32.20 items/kg dry weight for sediments, 0.17 ± 0.17 items/individual for fish GIT and 0.12 ± 0.12 items/individual for fish gills. There was no significant relationship between MPs abundance in surface waters and sediments as well as between MPs abundance in environmental matrices and fish (P > 0.0.5). In terms of feeding habit, no significant differences were observed between the number of MPs found in omnivorous and carnivorous fish species (P > 0.05). Moreover, no significant relationship was detected between the MPs abundance in fish tissues and body size (P > 0.05). MPs were mainly fibers, mostly transparent, and in a range size of 70-5000 µm. The dominant MPs type was nylon in all samples. This study will help increase our knowledge about MPs pollution in inland freshwater systems and suggests that management policies take essential steps to reduce this insidious problem in freshwater ecosystems.

Late Miocene drainage reorganization on the NE Tibetan Plateau linked to growth of the Qilian Shan revealed by coupled carbonate Sr-silicate Nd isotopic tracers

The tectonically active NE Tibetan Plateau, which is located at the confluent area of the humid Asian monsoon region and dry Asian inlands, provides excellent archives of drainage pattern evolution in response to regional changes in topography and climate. However, the uplift of the NE Tibetan Plateau and formation of modern drainage patterns are still disputed. In this study, based on the SrNd isotopic distribution in modern surface water and sediments, we present integrated records of 87Sr/86Sr ratios in carbonate and 87Sr/86Sr-εNd(0) values in silicate of the Huaitoutala section in the northern Qaidam Basin to reveal the source-to-sink history of particulate and dissolved loads since ∼15 Ma. Our results show that changes in SrNd isotopes at ca. 10 Ma and ca. 5 Ma are indicative of two stages of source alteration and reorganization of the drainage system. Specifically, a remarkable increase in 87Sr/86Sr ratios in carbonate and silicate together with a decrease in εNd(0) values since ca. 10 Ma suggests a tectonic denudation event of Qilian Shan at ∼10 Ma. The subsequent declines in 87Sr/86Sr ratios in carbonate and silicate together with an increase in εNd(0) values since ca. 5 Ma, which approach the modern 87Sr/86Sr ratios near the study section site, suggest that a modern-like drainage pattern in the northern Qaidam Basin might have formed in response to tectonic uplift of Qilian Shan at ca. 5 Ma. Using coupled carbonate Sr-silicate SrNd isotopes, we provide reliable provenance tracers of drainage reorganization and the evolution of source-to-sink systems caused by tectonic deformation.

Reducing Carbon Emission, Groundwater Over-Exploitation and Energy Consumption on Agricultural Lands by Off-Farm Water Management Practices: Modernization of Surface Water Distribution Systems

A wide range of endeavors has been made to propose various approaches to reduce Greenhouse gas emissions in the agricultural sector. The present study investigates the impacts of Surface Water Distribution Systems (SWDS) modernization in reducing groundwater overexploitation, energy consumption, and carbon emission in the agriculture sector. Four modernization alternatives, including an improved manual-based system (A1, A2), off-line, and real-time automatic control systems (A3, A4), are developed and tested on a real test case in Central Iran, which is confronted with severe water shortages. The results reveal that SWDS’s operating system modernization improves 4 ~ 21% surface water distribution through the alternatives A1 ~ A4. This surface water distribution enhancement led to groundwater over-extraction reduction. Spatial analysis reveals that 0.075, 0.100, 0.281, and 0.470 of the irrigation district’s cultivated area was thoroughly fulfilled by the delivered surface water and no need for groundwater extraction due to alternatives A1 ~ A4, respectively. Closure of several active tubewells up to 1,668 semi-deep and 497 deep tube-well were verified. SWDS’ modernization led to 5, 7, 20, and 30% of energy consumption and consequently 1,864.90, 2,714.33, 8,427.19, and 12,674.32 tC ha-1 carbon emission reduction in alternatives A1 ~ A4, respectively. This study’s results show that modernization of off-farm operating systems - responsible for surface water conveyance and distribution from a dam reservoir to farms - resulted in significant environmental benefits through improving the reliability of systems supplied by surface water and reducing the tendency of the farmers to groundwater resources.

Modifying physical supply and use tables (PSUTs) in the system of environmental-economic accounting (SEEA) for off-farm irrigation water management

A reliable water accounting framework is crucial for understanding the contribution of water resources in meeting agricultural demands and selecting appropriate operating systems for off-farm water systems, including hydraulic conveyance and distribution structures. This ensures fair, adequate, and dependable irrigation water distribution, especially under water scarcity operational scenarios. This study presents a novel and effective method for modifying PSU tables in the SEEA water accounting framework that is specifically designed for small-scale agricultural water management study areas. The proposed approach entails a comprehensive analysis of the surface water distribution within the water holders using a hydraulic simulation model and a spatial analysis of the groundwater extraction for meeting on-farm water demands. This approach was implemented on Iran's Central Plateau and revealed notable variations in water rights and distribution effectiveness among stakeholders so that, surface water contributed 27–40% less than the legal water rights, leading to aquifer overexploitation. The evaluation indicated that changing crop patterns and upgrading to pressurized irrigation systems led to 4–7.5% overexploitation of groundwater and 3.5–6% water conservation on farm scales. Besides, the spatial assessment verified a considerable overlap of 59% between the farms with modern irrigation systems and those with cultivated area expansion, resulting in sustained overexploitation pressure on the aquifer. The present study has two significant practical implications. Firstly, it specifies the contribution of surface- and groundwater resources in fulfilling the water demands of individual water-holders. Secondly, it provides reliable information to decision-makers about the incentives for modernization, rehabilitation, and renovation projects in an irrigation district.

Influence of Climate, Topography, and Hydrology on Vegetation Distribution Patterns—Oasis in the Taklamakan Desert Hinterland

Vegetation in natural desert hinterland oases is an important component of terrestrial ecosystems. Determining how desert vegetation responds to natural variability is critical for a better understanding of desertification processes and their future development. The aim of this study is to characterize the spatial distribution of vegetation in the natural desert hinterland and to reveal how different environmental factors affect vegetation changes. Taking a Taklamakan Desert hinterland oasis as our research object, we analyzed the effects of different environmental factors on desert vegetation using a time-series normalized difference vegetation index (NDVI) combined with meteorological, topographic, and hydrological data, including surface water and groundwater data. Vegetation was distributed in areas with high surface water frequency, shallow groundwater levels, relatively flat terrain, and dune basins. NDVI datasets show greening trends in oasis areas over the past 20 years. The frequency of surface water distribution influences water accessibility and effectiveness and shapes topography, thus affecting the spatial distribution pattern of vegetation. In this study, areas of high surface water frequency corresponded with vegetation distribution. The spatial distribution of groundwater depth supports the growth and development of vegetation, impacting the pattern of vegetation growth conditions. Vegetation is most widely distributed in areas where the groundwater burial depth is 3.5–4.5 m. This study provides data for restoring riparian vegetation, ecological water transfer, and sustainable development.

Impacts of artificial dams on terrestrial water storage changes and the Earth's elastic load response during 1950–2016: A case study of medium and large reservoirs in Chinese mainland

The construction of dams for intercepting and storing water has altered surface water distributions, land-sea water exchanges, and the load response of the solid Earth. The lack of accurate estimation of reservoir properties through the land surface and hydrological models can lead to water storage simulation and extraction errors. This impact is particularly evident in many artificial reservoirs in China. The study aims to comprehensively assess the spatiotemporal distribution and trends of water storage in medium and large reservoirs (MLRs) in Chinese mainland during 1950–2016, and to investigate the gravity, displacement, and strain effects induced by the reservoir mass concentration using the load elasticity theory. In addition, the impoundment contributions of MLRs to the relative sea level changes were assessed using a sea-level equation. The results show impoundment increases in the MLRs during 1950–2016, particularly in the Yangtze River (Changjiang) and southern basins, causing significant elastic load effects in the surrounding areas of the reservoirs and increasing the relative sea level in China's offshore. However, long-term groundwater estimation trends are overestimated and underestimated in the Yangtze River and southwestern basins, respectively, due to the neglect of the MLRs impacts or the uncertainty of the hydrological model's output (e.g., soil moisture, etc.). The construction of MLRs may reduce the water mass input from land to the ocean, thus slowing global sea level rise. The results of the impact of human activities on the regional water cycle provide important references and data support for improving the integration of hydrological models, evaluating Earth's viscoelastic responses under long-term reservoir storage, enhancing in-situ and satellite geodetic measurements, and identifying the main factors driving sea level changes.

Drought Risk Assessment for Surface Water Distribution Systems in Irrigation Districts

Drought Risk Assessment for Surface Water Distribution Systems in Irrigation Districts

Microplastic distribution in Surface Water and Sediments of Way Belau River, Lampung, Indonesia

Microplastic research in Lampung water body is becoming concern because of its strategic location towards the Sunda Strait. The Way Belau River in surface water and sediments are one of the places to identify the potential for microplastic deposition, and to estimate the distribution of microplastics from upstream to downstream. In the surface water, the abundance of microplastics are found about 36.76 ± 21,81 particles/500 ml, and in the sediments of the Way Belau River, it showed the abundance of microplastics are about 21.03 ± 11.92 particles/100 g of dry sediment. The dominant microplastic morphologies are fragments and fibers with a size range of 20-250 µm. The results of identification of polymer types using Raman spectroscopy showed the presence of polyethylene and polypropylene plastic types.

Study on hydrological response of runoff to land use change in the Jing River Basin, China.

Land use change greatly affects the runoff characteristics of the basin, which in turn affects the distribution of surface water and groundwater in the region. Quantitative analyses of the hydrological response of watershed runoff to land use change are conducive to the formulation of sustainable water resource strategies. In this paper, the impact of land use change on runoff characteristics in the Jing River Basin was evaluated using the SWAT model, the land use pattern of the Jing River Basin in 2040 was predicted using CA-Markov model, and five land use change scenarios were set up in combination with the trend of land use transfer, and the response relationship between land use change and runoff hydrological characteristics in the basin was studied. The results show that the land use changes reduce runoff and change the hydrological cycle process of the basin. The hydrological response of different land use types varies significantly, but only has a less impact on annual runoff. Farmland has a promoting effect on production flow; woodland and grassland are not conducive to the formation of surface runoff and will increase underground runoff and evapotranspiration in the basin. The increase in vegetation coverage after returning farmland to woodlands and grasslands has reduced surface runoff, increased the recharge of groundwater, and played a positive role in ecological restoration in the river basin. The research results are of great significance for understanding the hydrological consequences of land use change and the rational planning of land use patterns in river basins.

Pan-Greenland mapping of supraglacial rivers, lakes, and water-filled crevasses in a cool summer (2018) and a warm summer (2019)

The spatiotemporal distribution and variability of surface water remained poorly known at the pan-Greenland scale, and its dominant features (supraglacial rivers, lakes, and water-filled crevasses) were rarely studied collectively. We present pan-GrIS surface water extent and volume for a relatively cool (2018) and a relatively warm (2019) summer, using 10 m resolution Sentinel-2 imagery, a semi-automated multi-scale water extraction algorithm, and the Regional Atmospheric Climate Model (RACMO). While the 10 m resolution of Sentinel-2 imagery prevents inclusion of all water-filled crevasses and narrow rivers, our findings include: (1) strong interannual differences are observed in total surface water area (4903km2 vs. 9988 km2), volume (3.5 km3 vs. 6.8 km3), and mean elevation limit (1407 m a.s.l. vs. 1545 m a.s.l.) in response to a low (cool) (265 Gt/yr) and high (warm) (510 Gt/yr) runoff year; (2) large spatial contrasts in surface water extent, volume, elevation limit, and drainage pattern among the eight major GrIS basins; (3) supraglacial rivers dominate GrIS surface water appearance, accounting for 57%/48% of total surface water area/volume, respectively, over the two years (in contrast, water-filled crevasses and supraglacial lakes account for 33%/32% and 10%/20%, respectively); (4) ratio of remotely sensed water volume to RACMO-simulated cumulative surface runoff declines during the cool (2.6%) vs. the warm (1.8%) year; and from north (4.5%) to south (1.1%) Greenland. In summary, this study reveals strong temporal and spatial differences in GrIS surface water extent, volume, and drainage pattern and raises prospects for improved understanding of pan-Greenland Ice Sheet surface hydrology.

Monitoring of Surface Water bodies in Mainpuri District Using Remote Sensing and GIS Technology

Abstract: These days, a range of analytical tasks are carried out using popular, computer-dependent, time-oriented methodologies such as remote sensing and GIS (Geographic Information System) technology. Remote sensing technology provides a synoptic perspective that aids in mapping the dynamics of surface water bodies at regional and global scales. With this study, we can gather information on seasonal changes over time in the Mainpuri District because variations in the distribution of surface water have an impact on the hydrogeology and physical surroundings of the area. Mainpuri District has a Ramsar site named Saman Bird Sanctuary, which is home to a significant number of migratory and local migratory birds, primarily Sarus cranes. The research demonstrated that the area's abundance of waterbodies benefits biodiversity by giving migratory birds enough food and shelter. Shrinkage and expansion in surface water bodies are useful for determining the ecology of the region. In the current work, pre-monsoon and post-monsoon multi-temporal Landsat satellite images have been used to monitor spatiotemporal changes in the water bodies’ surface area in the Mainpuri District of Uttar Pradesh, India. In the north-west to southeast of the district, waterbodies' temporal changes show a 60% sharp decline in the number of waterbodies from 1992 to 2022.

Accurate estimation of surface water volume in tufa lake group using UAV-captured imagery and ANNs

Quantitative acquisition of surface water volume of tufa lake group is significant for protecting the tufa landscapes. Limited by low spatial resolution, satellite remote sensing failed to extract the surface water distribution of small and scattered tufa lakes. In recent years, Unmanned Aerial Vehicle (UAV) remote sensing has been increasingly applied to survey aquatic resources and environments, posing great potential for accurately measuring surface water volume of tufa lake group. In this paper, taking the Shuzheng Lakes in Jiuzhai Valley of China as the study site, we used UAV-captured images and Artificial Neural Network (ANN) models to precisely estimate the surface water volume of the tufa lake group. Digital Surface Model (DSM) and orthomosaic were first generated using aerial triangulation. Next, the two classification networks were trained to separate water from vegetation, and then the water extents of individual tufa lakes were extracted. Subsequently, the water depth map of each tufa lake was retrieved using the transferred shallow and deep bathymetry networks. Lastly, the total surface water volume of tufa lake group was achieved by summing the products of pixel unit area and the water depth of each pixel. As results, the surface water volume of tufa lake group estimated by the optimum model combination was approximately 181,360 m3, and the corresponding R-squared was 0.92. These demonstrated the effectiveness of utilizing UAV-based remote sensing and integrated ANN models to accurately estimate surface water volume of tufa lakes.

Distributed model predictive control based on the alternating direction method of multipliers for branching open canal irrigation systems

Most studies of open canal automation concentrated on the control of single canal pool or cascaded multiple canal pools, neglecting the hydraulic coupling effects between the main canal and lateral canals. Low transmission efficiency and poor equity of agriculture water delivery may be caused in the practical application of large-scale irrigation networks. Considering the high computation and communication requirements for large-scale operating systems, a distributed model predictive control (DMPC) algorithm based on the alternating direction method of multipliers (ADMM) is developed for the branching open canal irrigation systems (BOCISs). A simplified BOCIS example, originating from Test case 2 proposed by the American Society of Civil Engineers, is used for control tests. Moreover, for control performance comparisons and evaluations, centralized model predictive control (CMPC) is employed by modifying the state space of the integrator delay (ID) model. The results show that the control performance of the proposed DMPC converges to the global optimal solution of the CMPC under the normal scenario, and the degradation is less than 0.35 %. The communication and coordination process of DMPC contributes to more powerful robustness and interference immunity than CMPC. Furthermore, in case of sudden accidents occurring in some subsystems, the proposed DMPC is more convenient and timely to execute fault isolation. The improvements on water level oscillations and overshoots can reach 20.3 % and 52.1 % in the other subsystems which need normal water delivery, respectively. Equipped with outstanding control characteristics, the proposed ADMM-based DMPC framework enables the water authorities of large-scale BOCISs to promote surface water distribution in a practicable, flexible, and secure way, showing great potential in developing intelligent irrigation districts.

A dataset of land surface water with a spatial resolution of 30 meters on the Qinghai-Tibet Plateau in 2022

The Tibetan Plateau is known as the Asian Water Tower. The distribution of surface water and its changes are closely related to global change, biodiversity and water-related ecosystems. Based on the collection of high-precision land surface water samples, we used the random forest classification algorithm in machine learning to extract land surface water information from Landsat series satellite images and produced a dataset of land surface water with a spatial resolution of 30 meters on the Qinghai-Tibet Plateau based on satellite remote sensing images in 2022. According to data quality assessment, the overall accuracy of the dataset is 92.9%, and the Kappa coefficient is 0.84. This dataset can provide foundational data support for water resource monitoring, ecosystem services, and global change research on the Qinghai-Tibet Plateau.

Groundwater–Surface Water Exchange and Spatial Distribution of Arsenic in Arid and Semi-Arid Regions: The Case of Aksu River in Xinjiang, Northwestern China

The Aksu River, a quintessential inland river, exhibits elevated arsenic (As) concentrations in certain sections of its natural waters. Further investigation is necessary to determine the role of surface water and groundwater (SW-GW) exchanges in contributing to these high As concentrations. Both surface water and groundwater constitute crucial components of the basin water cycle, and the interaction between the two has been a central focus in basin water cycle research. In this study, a total of 59 groundwater samples and 41 surface water samples were collected along the river’s course within the basin. Among the groundwater samples, 18.64% exceeded the permissible drinking limit for As concentrations (10 μg/L), while 39.02% of the surface water samples exceeded this threshold. The water bodies in the Aksu River Basin are mildly alkaline, with total dissolved solids (TDSs) in surface water significantly surpassing those in groundwater. The chemical compositions of surface water and groundwater are strikingly similar, with the predominant anions being chloride (Cl−) and sulfate (SO42−) and the principal cations being sodium (Na+). The dissolution of silicate and carbonate minerals primarily influences the water chemistry characteristics of surface water and groundwater in the Aksu River Basin, followed by the dissolution of salt rocks. Human activities also play a major role in affecting the river’s water quality. The distribution of groundwater with elevated As content is entirely encompassed within the spatial distribution of surface water. Groundwater–surface water exchange plays a vital role in As enrichment in surface water.

Spatial investigation of water quality and estimation of groundwater pollution along the main stream in the Geum River Basin, Korea

This study aims to identify spatially water quality distribution of groundwater and surface water in reservoirs, and comprehensively to address possible influencing factors. The concentration of NO3 in the reservoirs along the main stream of the Geum River was generally lower than that in groundwater. The pollution level of the reservoir, especially the particulate pollutant SS, clearly showed seasonal variations and increased significantly downstream. The H-3 concentration of the groundwater was high in the plains and low in the mountain areas, indicating a difference in residence time between the two regions. The hydrochemical properties and factor loading values of the principal components indicated that the major factors were water‒rock interactions and residence time, but a positive correlation of K-NO3 and Mg-Cl showed the influence of agricultural activities. The main groundwater pollutants were likely to be contributed by agricultural activities at upstream and seawater intrusion at downstream. The sensitive redox species uranium in the groundwater of this region existed as the uranyl ion, and it showed a positive correlation with HCO3, pH, and Ca. The results emphasize the importance of monitoring both tributaries and groundwater together in order to effectively manage the water quality of the Geum River basin.

Imaging VOC distribution and tracing emission sources in surface water by a mobile shipborne spray inlet proton transfer reaction mass spectrometry

Volatile organic compound (VOC) pollution in surface water can affect the growth of microorganisms and even cause damage to human health. Quickly obtaining VOC distribution and tracing emission sources are of great significance to ensure the security of water quality. In this study, we developed a mobile shipborne spray inlet proton transfer reaction mass spectrometry (S-SI-PTR-MS) instrument for rapid and on-line detection of volatile organic compounds (VOCs) in surface water. It mainly consists of a shipborne platform, a spray inlet system, a proton transfer reaction mass spectrometer, and geographic information software (GIS). During the navigation, VOCs in water can be quickly extracted to gaseous state by the SI system and transferred into the proton transfer reaction mass spectrometry (PTR-MS) for detection. The GIS can receive VOC and longitude-latitude data at the same time. And then the identification and concentration information can be shown on an electronic map in real time. The limit of detection and response time were 1.32 μg/L∼9.43 μg/L and 56 s∼114 s, respectively. The spatial resolution is 0.14 m in a common navigation experiment (5 km/h, dwell time=0.1 s), allowing for high-resolution monitoring of VOCs in water. Finally, field experiments were performed on the lower Nanfeihe River and some surfaces of Chaohu Lake in China. During tracing pollution in Nanfeihe River, two VOC emission sources in the downstream were located, nearing a sewage outlet and a wharf, respectively. During imaging VOC distribution in the Chaohu Lake, we found the areas with high-concentration VOCs were mainly along the ship channel. The newly developed S-SI-PTR-MS can monitor water quality in surface water in real time and has the potential to assist environmental protection enforcement.

Sub-Pixel Surface Water Mapping for Heterogeneous Areas from Sentinel-2 Images: A Case Study in the Jinshui Basin, China

Mapping high-spatial-resolution surface water bodies in urban and suburban areas is crucial in understanding the spatial distribution of surface water. Although Sentinel-2 images are popular in mapping water bodies, they are impacted by the mixed-pixel problem. Sub-pixel mapping can predict finer-spatial-resolution maps from the input remote sensing image and reduce the mixed-pixel problem to a great extent. This study proposes a sub-pixel surface water mapping method based on morphological dilation and erosion operations and the Markov random field (DE_MRF) to predict a 2 m resolution surface water map for heterogeneous regions from Sentinel-2 imagery. DE_MRF first segments the normalized difference water index image to extract water pixels and then detects the mixed pixels by using combined morphological dilation and erosion operations. For the mixed pixels, DE_MRF considers the intra-pixel spectral variability by extracting multiple water endmembers and multiple land endmembers within a local window to generate the water fraction images through spectral unmixing. DE_MRF was evaluated in the Jinshui Basin, China. The results suggested that DE_MRF generated a lower commission error rate for water pixels compared to the comparison methods. Because DE_MRF considers the intra-class spectral variabilities in the unmixing, it is better in mapping sub-pixel water distribution in heterogeneous regions where different water bodies with distinct spectral reflectance are present.

A dataset of annual surface water distribution in the growing season on the Mongolia Plateau from 2013 to 2022

Mongolia Plateau is located in arid and semi-arid areas, and hydrology and water resources are important constraints for the development of its resources and environment. Grasping the temporal and spatial distribution of water bodies on the Mongolian Plateau is of great significance for indicating the temporal and spatial characteristics of water resources and the water environment and their impacts on and responses to regional climate change as well as disaster prevention and reduction. However, as the vast Plateau spans both China and Mongolia, it is a great challenge to accurately and automatically obtain large-scale and long time series water bodies at the basin scale. In this research, we adopted the method of combining local deep learning training and Google Earth Engine (GEE) distributed computing to endow GEE with deep learning computing capabilities so that GEE could rapidly and automatically deploy deep learning models. Based on this, we obtained the distribution of surface water in the growing season of the Mongolia Plateau from 2013 to 2022 with a spatial resolution of 30 meters. 5,000 verification points were manually selected, and the overall verification rate was 88.0%. The dataset is in the form of TIFF grid, containing 28 tile images of with 5°×5°×10 years, with a data volume of 339 MB (88.1 MB compressed, 189 GB in RAW). The data volume in the raw format is 189 GB. With the method used in this dataset, users can automatically and efficiently map water bodies in the cloud platform, which makes it possible to automatically and efficiently process large-scale and long-time series water bodies in arid and semi-arid regions. This is a valuable dataset for application and promotion.