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Lakes are essential components of the terrestrial water cycle. Their size and quantity reflect natural climate change and anthropogenic activities in time. Lakes on the Inner-Mongolian Plateau (IMP) have experienced significant changes in recent decades, but the current situation remains elusive. In this study, we conducted multi-decadal intensive monitoring of lake area and performed comprehensive variation analysis on the IMP. The study involved pre-processing, lake area extraction, post-processing, and lake area analysis procedures using multi-source satellite images. The results reveal the detailed variation in the lake from various aspects. The temporal analysis indicates that the lake area has undergone two distinct periods of decline followed by subsequent increase, and the variation pattern from January to December was diverse. The spatial analysis suggests that the lake area expanded slightly in the western and southern parts, while the area shrank in the other two. Variations in lakes of different sizes exhibited spatial heterogeneity. To some extent, effective actions have led to lake rehabilitation, but it has not yet reached or surpassed the level of 2000. This study provides a substantial data basis and technological guidance for conducting lacustrine surveys. The results can play important roles in fostering further analyses of the water cycle and the carbon cycle. [ABSTRACT FROM AUTHOR]

Groundwater storage (GWS) in the Haihe River Basin (HRB), which is one of the most densely populated and largest agricultural areas in China, is of great importance for the ecosystem environment and socio-economic development. In recent years, large-scale overexploitation of groundwater in HRB has made it one of the global hotspots of GWS depletion. In this study, monthly GWS variations in HRB from 2003 to 2020 were estimated using the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) data in combination with three land surface models (LSMs) from the Global Land Data Assimilation System (GLDAS). The results show the following: (1) HRB suffered extensive GWS depletion from 2003 to 2020, which has been aggravated since 2014, with a mean rate of 1.88 cm·yr−1, which is equivalent to a volume of 6 billion m3·yr−1. The GWS depletion is more serious in the plain zone (−2.36 cm·yr−1) than in the mountainous zone (−1.63 cm·yr−1). (2) Climate changes are excluded from the reasons for GWS depletion due to annual precipitation and evaporation being close to normal throughout the period. In addition, GWS changes show a low correlation with meteorological factors. (3) The consumption of groundwater for irrigation and land use/cover changes have been confirmed to be the dominant factors for GWS depletion in HRB. (4) The effects of inter-basin water transfer projects cannot be obviously observed using the GRACE and GRACE-FO; more inter-basin water transfers are needed for recovering the GWS in HRB. Therefore, it is imperative to control groundwater exploitation and develop a more economical agricultural irrigation structure for the sustainability of groundwater resources in HRB. [ABSTRACT FROM AUTHOR]

Studying glacier changes is essential for understanding global glacier mass balance, patterns in climate change, and the potential consequences they may have. The glaciers of Geladandong Mountain serve as a crucial water source for the Yangtze River and its downstream regions. Any changes in the glacier at the river source will directly impact the ecological environment and water recycling process downstream. This study presents an approach for monitoring Geladandong Mountain glacier elevation changes using ICESat-2 data combined with a Binned Multilevel Regression Fitting Method (BMRFM). We analysed multi-year ICESat-2 data, considering various topographic features, to understand glaciers’ annual and seasonal elevation changes. Our research reveals significant spatial heterogeneity in glacier elevation changes, influenced by altitude, slope, and aspect factors. It demonstrates the effectiveness of ICESat-2 in glacier monitoring, offering insights into the impacts of climate change on glacier dynamics. Moreover, the results indicate a predominant trend of ongoing melting at lower altitudes, with a small amount of accretion at higher elevations. Over the last two decades, the overall elevation change rate is −0.23 ± 0.12 metres per year. Seasonal analysis shows substantial glacier thickening from April to August, primarily due to increased precipitation offsetting elevated temperatures. This study offers a robust method for monitoring glaciers using satellite data, thereby advancing the precision and reliability of glacier research. [ABSTRACT FROM AUTHOR]

Leaf area index (LAI) is a key parameter in plant growth monitoring. For several decades, vegetation indices-based empirical method has been widely-accepted in LAI retrieval. A growing number of spectral indices have been proposed to tailor LAI estimations, however, saturation effect has long been an obstacle. In this paper, we classify the selected 14 vegetation indices into five groups according to their characteristics. In this study, we proposed a new index for LAI retrieval-transformed triangular vegetation index (TTVI), which replaces NIR and red bands of triangular vegetation index (TVI) into NIR and red-edge bands. All fifteen indices were calculated and analyzed with both hyperspectral and multispectral data. Best-fit models and k-fold cross-validation were conducted. The results showed that TTVI performed the best predictive power of LAI for both hyperspectral and multispectral data, and mitigated the saturation effect. The R2 and RMSE values were 0.60, 1.12; 0.59, 1.15, respectively. Besides, TTVI showed high estimation accuracy for sparse (LAI < 4) and dense canopies (LAI > 4). Our study provided the value of the Red-edge bands of the Sentinel-2 satellite sensors in crop LAI retrieval, and demonstrated that the new index TTVI is applicable to inverse LAI for both low-to-moderate and moderate-to-high vegetation cover. [ABSTRACT FROM AUTHOR]