Explore the vast range of titles available.

Vegetation‐related processes, such as evapotranspiration (ET), irrigation water withdrawal, and groundwater recharge, are influencing surface water (SW)—groundwater (GW) interaction in irrigation districts. Meanwhile, conventional numerical models of SW‐GW interaction are not developed based on satellite‐based observations of vegetation indices. In this paper, we propose a novel methodology for multivariate assimilation of Sentinel‐based leaf area index (LAI) as well as in‐situ records of streamflow. Moreover, the GW model is initially calibrated based on water table observations. These observations are assimilated into the SWAT‐MODFLOW model to accurately analyze the advantage of considering high‐resolution LAI data for SW‐GW modeling. We develop a data assimilation (DA) framework for SWAT‐MODFLOW model using the particle filter based on the sampling importance resampling (PF‐SIR). Parameters of MODFLOW are calibrated using the parameter estimation (PEST) algorithm and based on in‐situ observation of the GW table. The methodology is implemented over the Mahabad Irrigation Plain, located in the Urmia Lake Basin in Iran. Some DA scenarios are closely examined, including univariate LAI assimilation (L‐DA), univariate streamflow assimilation (S‐DA), and multivariate streamflow‐LAI assimilation (SL‐DA). Results show that the SL‐DA scenario results in the best estimations of streamflow, LAI, and GW level, compared to other DA scenarios. The streamflow DA does not improve the accuracy of LAI estimation, while the LAI assimilation scenario results in significant improvements in streamflow simulation, where, compared to the open loop run, the (absolute) bias decreases from 75% to 6%. Moreover, S‐DA, compared to L‐DA, underestimates irrigation water use and demand as well as potential and actual crop yield. Key Points Using source code modification, SWAT‐MODFLOW is connected to sequential DA Multivariate assimilation of streamflow, GW‐level and leaf area index (LAI) shows the best results Streamflow data assimilation does not improve LAI simulation, while LAI data assimilation improves streamflow simulation

Land degradation significantly impacts regional economic development and food security, particularly in arid river basins where soil and water conservation is crucial. Understanding the extent and causes of land degradation is pivotal for effectively prevention and management. This study employs the soil adjusted vegetation index (SAVI), the temperature vegetation dryness index (TVDI), and the salinization detection index (SDI), combined with the analytic hierarchy process and the entropy weight method, to construct a comprehensive land degradation index (LDI). Sen’s slope trend analysis and the Mann-Kendall significance test were used to analyze land degradation trends in the Ebinur Lake watershed from 2002 to 2022. Additionally, the optimal parameters-based geographical detector was used to examine the underlying mechanisms of land degradation. The results indicate the following: (1) From 2002 to 2012, the degree of land degradation in the Ebinur Lake watershed worsened, particularly in the eastern and southeastern parts, as well as in the southern region of Toli County. From 2012 to 2022, land degradation significantly improved, with a notable reduction in degraded land area. (2) Over the period of 2002-2022, 93.08 % of the land in the research region exhibited a declining LDI trend, 3.95 % showed no change, and only 2.96 % showed an increasing LDI trend. (3) Moderate, severe, and very severe degradation mainly occurred on grassland and unused land, while light degradation and non-degradation primarily occurred on forest land and cultivated land. (4) Unreasonable land use and overgrazing were identified as the primary factors influencing land degradation, with elevation being a secondary factor. The interaction between land use and other factors was found to be most significant, followed by the synergistic effects of grazing quantity with elevation, annual average temperature, gross domestic product, soil moisture, and elevation with annual average precipitation, and temperature. The results of this study offer an empirical basis and taking decisions assistance for land degradation control in the Ebinur Lake Basin, as well as examples and references for assessing land degradation in other places.

Human activities have increased with urbanisation in the Erhai Lake Basin, considerably impacting its eco-environmental quality (EEQ). This study aims to reveal the evolution and driving forces of the EEQ using water benefit–based ecological index (WBEI) in response to human activities and policy variations in the Erhai Lake Basin from 1990 to 2020. Results show that (1) the EEQ exhibited a pattern of initial degradation, subsequent improvement, further degradation and a rebound from 1990 to 2020, and the areas with poor and fair EEQ levels mainly concentrated around the Erhai Lake Basin with a high level of urbanisation and relatively flat terrain; (2) the EEQ levels were not optimistic in 1990, 1995 and 2015, and areas with poor and fair EEQ levels accounted for 43.41%, 47.01% and 40.05% of the total area, respectively; and (3) an overall improvement in the EEQ was observed in 1995–2000, 2000–2005, 2005–2009 and 2015–2020, and the improvement was most significant in 1995–2000, covering an area of 823.95 km 2 and accounting for 31.79% of the total area. Results also confirmed that the EEQ changes in the Erhai Lake Basin were primarily influenced by human activities and policy variations. Moreover, these results can provide a scientific basis for the formulation and planning of sustainable development policy in the Erhai Lake Basin.

The GIS-multicriteria decision analysis (GIS-MCDA) technique is increasingly used for landslide hazard mapping and zonation. It enables the integration of different data layers with different levels of uncertainty. In this study, three different GIS-MCDA methods were applied to landslide susceptibility mapping for the Urmia lake basin in northwest Iran. Nine landslide causal factors were used, whereby parameters were extracted from an associated spatial database. These factors were evaluated, and then, the respective factor weight and class weight were assigned to each of the associated factors. The landslide susceptibility maps were produced based on weighted overly techniques including analytic hierarchy process (AHP), weighted linear combination (WLC) and ordered weighted average (OWA). An existing inventory of known landslides within the case study area was compared with the resulting susceptibility maps. Respectively, Dempster-Shafer Theory was used to carry out uncertainty analysis of GIS-MCDA results. Result of research indicated the AHP performed best in the landslide susceptibility mapping closely followed by the OWA method while the WLC method delivered significantly poorer results. The resulting figures are generally very high for this area, but it could be proved that the choice of method significantly influences the results.

Context Decades of intensifying human activities have led to drastic changes in land use and land cover (LULC) in the Poyang Lake Basin (PLB), resulting in significant changes in landscape pattern and ecosystem service value (ESV), thereby affecting regional sustainability. Objectives We focused on understanding the impact of LULC changes on the landscape pattern and ESV of the PLB and used the Patch-generating Land Use Simulation model (PLUS) to predict LULC changes in 2050. Methods We evaluated landscape patterns using landscape metrics and calculated ESV using the ecosystem service equivalent factor method. The Pearson correlation coefficient was used to analyze the correlation between landscape patterns and ESV from 1990 to 2020. Then, we combined the PLUS model and the ecosystem service equivalent factor method to calculate the ESV under multiple scenarios from 2020 to 2050. Results From 1990 to 2020, the LULC of the PLB changed to varying degrees. The PLB has undergone a rapid process of landscape fragmentation, and the total ESV of the PLB has decreased. The total ESV was positively correlated with the CONTAG index and negatively correlated with the SHDI index. Between 2020 and 2050, the ESV of the PLB is projected to decrease under the NDS (nature development scenario) and EDS (economic development scenario) and increase under the EPS (ecological protection scenario). Conclusions ESV responded to changes in landscape pattern. We recommend that the PLB should increase patch connectivity. Additionally, future development in the PLB should prioritize ecological protection to prevent further declines in ESV.

The five major plateau lake basins in central Yunnan are densely populated areas with high land use intensity. The spatiotemporal changes in land use significantly affect the ecological environment quality of the entire basin. This research utilized land use data from 1990 to 2020, and the InVEST model to analyze land use change and its impact on habitat quality in the basin. The results indicated that cropland has been the predominant land use type during this period but has steadily decreased, while the areas of forest land and impervious surfaces increased. Additionally, the intensity of conversion between different land types was significant, primarily involving the transformation of cropland into other land types. The overall habitat quality improved, predominantly characterized by high and relatively low grades of habitat quality. Regions experiencing improved habitat quality outnumber those degradation, and the spatial distribution of habitat quality showed \"high at the edges, low in the lakeside areas\" around each lake. Land use change was the most dominant factor influencing the distribution of habitat quality within the lake basin, with 91.89% of the contribution rate to habitat quality improvement attributed to transitions from cropland to forest and grassland, while 94.12% of the contribution rate to habitat quality degradation was due to the expansion of impervious surfaces and the encroachment of cropland into other ecological land uses. Therefore, the findings of this study provide important reference for future land use planning and ecological environmental protection in the lake basin of central Yunnan.

Given the escalating issue of global climate change, it is imperative to comprehend and quantify the effects of land use change on carbon storage (CS), which pertains not only to the preservation of ecosystem functions but also directly influences the equilibrium and stability of the global carbon cycle. This study examines the correlation between CS and land use change, forecasts the future spatial distribution of CS, and offers a reference for the rational planning of watershed space. Focusing on the Bosten Lake Basin of Xinjiang in China, employing the land use simulation (PLUS) model and the integrated valuation of ecosystem services and trade-offs (InVEST) model to forecast the spatial distribution of carbon stocks across three developmental scenarios, while also examining the shift in the center of gravity of CS and the autocorrelation of their spatial distribution. The findings derived from the study are as follows: (1) From 1990 to 2020, the predominant land use type in the Bosten Lake Basin was grassland, while there was an upward trend in the areas of cropland, forest land, built-up land, and wetland, alongside a downward trend in the areas of grassland, water, and unused land. (2) In the long term, the regional CS exhibits an upward trend, with the most significant increase anticipated in the EPS scenario. Grassland constitutes the most extensive carbon reservoir in the Bosten Lake Basin, while wetlands exhibit the highest carbon sequestration potential. (3) The alteration in the center of gravity of CS is associated with the expansion or reduction of the major regional carbon reservoirs and types characterized by significant carbon sequestration potential. (4) In the long term, the spatial correlation of CS in the Bosten Lake Basin exhibits a consistent upward trend, with the most pronounced spatial correlation observed under EPS.

Understanding past and present hydrosystem feedbacks to global ocean–atmospheric interactions represents one of the main challenges to preventing droughts, extreme events, and related human catastrophes in the face of global warming, especially in arid and semiarid environments. In eastern Africa, the El Niño–Southern Oscillation (ENSO) was identified as one of the primary drivers of precipitation variability affecting water availability. However, the northern East African Rift System (EARS) still suffers from the underrepresentation of predictive and ENSO teleconnection models because of the scarcity of local to regional historical or palaeo-data. In this paper, we provide a 50-year seasonal flood and drought chronicle of the Awash River catchment from the study of laminated sediment from Gemeri and Afambo lakes (central Afar region, Ethiopia) with the aim of reconstructing the magnitude of regional hydroclimatic events. Pluricentimetric micro-laminated lithogenic facies alternating with plurimillimetric carbonate-enriched facies are investigated in both lakes. We couple dating methods including radiocarbon, short-lived radionuclides, palaeomagnetic field variations, and varve counting on both lake deposits to build a high-resolution age model and to discuss the regional hydrosedimentary dynamics of the Awash River over the last ∼ 700 years with a focus on the last 50 years. Using a multiproxy approach, we observe that following a multicentennial enhanced hydrological period, the two lakes have experienced a gradual decrease in river load inflow since 1979 CE, attaining extreme drought and high evaporative conditions between 1991 and 1997 CE. In 2014, the construction of a dam and increased agricultural water management in the lower Awash River plain impacted the erodibility of local soils and the hydrosedimentary balance of the lake basins, as evidenced by a disproportionate sediment accumulation rate. Comparison of our quantitative reconstruction with (i) lake water surface evolution, (ii) the interannual Awash River flow rates, and (iii) the El Niño 3.4 model highlights the intermittent connections between ENSO sea surface temperature anomalies, regional droughts, and hydrological conditions in the northern EARS.

In the face of the increasingly severe water environment, establishing an effective water environment management mechanism is a major concern of governments around the world. The River Chief System attempts to match water environment management to the performance of the main leaders of the local party and government and represents an institutional innovation to solve the problem of river and lake management in China. However, there is still a lack of systematic research on the performance of the River Chief System and how to promote its overall effectiveness. This paper took Chaohu Lake Basin, with a concentrated and complicated water environment, as the research object and divided it into eastern and western halves. The water ecological security before and after the implementation of the River Chief System was comprehensively evaluated, and the obstacles to ecological security were diagnosed. The implementation effect of the River Chief System and the weak links of the corresponding river chiefs’ work performance were analyzed. The results show the following: (1) Since the implementation of the River Chief System in 2013, the overall water ecological security of Chaohu Lake Basin has been raised from the lower limit to the upper limit of the generally healthy category, initially reflecting the effect of the River Chief System. (2) For the eastern half of the lake, the threat to water ecological security mainly comes from the development of industry. Industrial water use intensity is the primary obstacle to the ecological security of the eastern half of the lake in recent years. (3) For the western half of the lake, the threat to water ecological security mainly comes from the process of urbanization. The wetland area, urban domestic water use intensity, and artificial afforestation area are the main factors hindering the ecological security of the western half of the lake. The above analysis results can be used as the basis for future work to improve the performance of the relevant river chiefs in Chaohu Lake Basin.

Climate change (CC) is likely to have a negative effect on water balance components thereby increasing global water scarcity. These effects, particularly in arid and semi-arid areas, have not been fully understood, in part because green water was not adequately represented in the relevant assessments. This study analyzes the spatiotemporal variations of blue and green water resources under baseline and future climate conditions by applying the Soil and Water Assessment Tool plus (SWAT+) model to the Meki River, located in Central Rift Valley (CRV) Lake Basins of Ethiopia. Based on sensitive parameters, identified from sensitivity analysis, we calibrated and validated the SWAT + model for the period from 1993 to 2000 and 1987 to 1992, respectively. During both the calibration and validation period, the model showed reasonable performance with a Nash-Sutcliffe efficiency of greater than 0.65. The model was then used to assess the effects of CC (representative concentrations pathways, RCP, 4.5 and 8.5) on the blue and green water components of the Meki River. We found that blue water is expected to decrease under both RCPs (4.5 and 8.5) scenarios, but anticipated to show a more decline of up to 56% under the RCP 8.5 scenario. Oppositely, green water is expected to increase under both scenarios, but RCP8.5 is projected to cause a larger increase (24%) when compared to the baseline. Overall, the integrated blue and green water modeling and assessment can be used as a tool to develop efficient strategies for water resources management of the Meki River.