Measuring dam induced alteration in water richness and eco-hydrological deficit in flood plain wetland

Assessment of wetland ecosystem health in Rarh Region, India through P-S-R (pressure-state-response) model

The current study attempted to assess wetland ecosystem health (EH) in the Murshidabad district's Rarh tract using the P-S-R (Pressure-State-Response) model and machine learning (ML) algorithms and validated it with a field-based validation approach as well as conventional validation approaches. To assess the ecosystem's health, 27 metrics were used to monitor the wetlands' pressure, state, and response. All of the models found that 46.1 % of wetlands in strong EH zones have transformed to 11.41 % in relatively fragile EH zones during the previous thirty years, demonstrating a progressive loss of EH quality throughout larger wetland areas. All of the applied models were deemed to be acceptable based on the results of the model validation process, however, the Random Forest (RF) model performed exceptionally well. The deterioration of EH in the wetlands happened due to the rapid expansion of settlement areas and agricultural land. So, the findings of the study deepen our knowledge about EH in the Rarh tract's wetlands, assisting decision-makers in creating sustainable wetland management strategies.

Inundation dynamics of the natural and manmade wetlands in the Mayurakshi River basin, Eastern India

The present study aimed to measure wetland inundation inconsistency level (IIL) at a spatial scale to appraise the potential serviceability in the Mayurakshi river basin of Eastern India. Inconsistency was used for measuring both wetland water presence area and proxy water depth based on historical satellite images from 1988 to 2022. Applying inconsistency assessment, it was tried to assess how water appearance at a pixel is inconsistent and how average proxy water depth is inconsistent to attain. Four manmade and natural floodplain wetland complexes were taken for this. The study revealed about 51-53% and 59-86% manmade and natural wetland losses respectively and the IIL was also found significantly higher (30-50%) in the cases of natural wetlands in pre and post-monsoon seasons. The scenario is worse in pre-monsoon season in the natural wetlands. Inconsistency of water depth anomaly (IWDA) was also significantly increased almost in the same trend. Discharge control through hydro-engineering structures like dams, barrages, and embankments; river and wetland connecting tie channel loss; and loss of groundwater support are some crucial reasons behind the hydrological inconsistency of wetlands. Growing loss and IIL are caused for concerned economic and ecological adversity. So, the findings would be very useful for taking necessary planning for wetland management and restoration.

Measuring anthropogenic impact of the ox-bow lakes in moribund Ganges deltaic India

Measuring the anthropogenic impact score (AIS) of the ox-bow lakes in order to explore the present situation and future ways of restoration is very necessary, particularly in highly populated areas. The present work targeted to do this considering 68 contributing parameters under eight AIS constituting components like pollution impact score (PIS), habitat alteration impact score (HAIS), hydrological alteration impact score (HYAIS), landscape alteration impact score (LAIS), etc. and tried to explore the major determinants behind. Machine learning (ML) algorithms were applied for computing component level and overall, AIS. A supervised correlation attribute evaluator (CAE) was applied for detecting major determinants. The result revealed out of total 44 major ox-bow lakes 40.90 % to 59.09 % (9.97 km2 to 14.69 km2) were identified as highly impacted both at the component level and overall scale as per the best predicted Random Forest (RF) model. Hydrologically connected lakes were less impacted than isolated ones. Genetically main river (Bhagirathi-Hooghly) left ox-bow lakes are less affected than those of the off-shoot channel. Larger size lakes witnessed less impact than medium and smaller lakes. Pollution, habitat, and hydrological components were found as the most dominant components of AIS. Reclamation, pollution, and eutrophication factors were identified as the dominant factors. AIS is negatively associated with fish yield and positively associated with the livelihood vulnerability of the dependent fishermen community. Since hydrological connectivity is a big issue; maintenance of it could be a good approach to its sustainability.

Dynamic landscapes and the influence of human activities in the Yellow River Delta wetland region

The Yellow River Delta (YRD) wetland is one of the largest and youngest wetland ecosystems in the world. It plays an important role in regulating climate and maintaining ecological balance in the region. This study analyzes the spatiotemporal changes in land use, wetland migration, and landscape pattern from 2013 to 2022 using Landsat-8 and Sentinel-1 data in YRD. Then wetland landscape changes and the impact of human activities are determined by analyzing correlation between landscape and socio-economic indicators including nighttime light centroid, total light intensity, cultivated land area and centroid, building area and centroid, economic and population. The results show that the total wetland area increased 1426 km2 during this decade. However, the wetland landscape pattern tended to be fragmented from 2013 to 2022, with wetlands of different types interlacing and connectivity decreasing, and distribution becoming more concentrated. Different types of human activities had influences on different aspects of wetland landscape, with the expansion of cultivated land mainly compressing the core area of wetlands from the edge, the expansion of buildings mainly disrupting wetland connectivity, and socio-economic indicators such as total light intensity and the centroid mainly causing wetland fragmentation. The results show the changes of the YRD wetland and provide an explanation of how human activities effect the change of its landscape, which provides available data to achieve sustainable development goals 6.6 and may give an access to measure the change of wetland using human-activity data, which could help to adject behaviors to protect wetlands.

Wetland transformation and its impact on the livelihood of the fishing community in a flood plain river basin of India

Discretely wetland transformations and livelihood vulnerability related works are profoundly found worldwide, but their linkage is not investigated often. The present study aimed to explore the after damming transformation of wetland's eco-hydrological status and water quality and assessed its effects on livelihood vulnerability state of the fishermen community in the lower part of the Tangon river basin. Based on 15 field and satellite image-driven indicators of transformation, multiple machine learning (ML) algorithms were used to model the eco-hydrological state (EHS) of the wetland. Livelihood Vulnerability Index (LVI) of 45 fishing-dominated villages was computed using a balanced weighted LVI score. The result revealed that 60.55 % wetland area was obliterated between the pre- dam and post-dam periods, and the existing wetland area (21.06 km²) witnessed noticeable eco-hydrological and water quality degradation. Correlation and kernel density estimation (KDE) plot clearly revealed that rate of EHS degradation and water quality changes was negatively associated (at ≤0.01 level of significance) and both controlled LVI. So, such changes not only pose pressure on the aquatic species like fishes but also hampered the well-being of the fishermen communities evolving. The findings of the work would be useful in this transition while deciding the alternative strategies to build a resilient community. Moreover, since the eco-hydrological state were explored this would be effective for wetland restoration planning.

Socio-ecological well-being perspectives of wetland loss scenario: A review

Previous original research focused on wetland loss and finding out its drivers across different regional units of the world. A few reports also tried to account world's condition on wetland loss. A couple of review articles articulated the causes of wetland loss and services. The present study intended to explore the linkage between wetland loss rate and processes concerning socio-ecological well-being parameters to highlight alternative ways to adopt wetland conservation policies. A total of 132 pieces of Scopus index literature were taken analysing loss rate and drivers of loss from 22 sample countries where publication frequency is relatively high. Meta-analysis was done to explain the publication trend and spatial change in publication polarity. Results distinctly revealed that the rate of wetland loss varies from 0.06% to 4.81% annually, with substantially low in developed countries (DC) than in developing (DeV) and least developed countries (LDC). Six drivers, such as agricultural land expansion, the built-up area, the conversion to grassland area, construction of the dam, climate change and tourism, were the primary drivers. But all these are not equally active across the DC, DeV and LDC. Climate change, tourism development in DC, agriculture and built-up expansions in the Dev and LDC appeared as the major causes behind wetland loss. Socio-ecological well-being parameters like human development, environmental performance, social progression, and economic status were found to be significantly negatively (-0.48 to -0.57), and the poverty rate was positively (0.27) associated with the rates of wetland loss. Drivers also varied with respect to the socio-ecological conditions. These findings are not merely added knowledge to the state-of-arts but are also helpful in re-directing global policies toward wetland conservation.

Linking river flow modification with wetland hydrological instability, habitat condition, and ecological responses

Flow modification pursuing dams is widely found. Some works also focused on its impact on floodplain wetland hydrology. However, how this change can pose an impact on habitat conditions, ecological conditions, and trophic state is also a matter of investigation. The very least attention has been paid to this so far. Therefore, the present study focused on these, taking the dam-induced Lower Tangon river basin of India and Bangladesh as a case. The degree of flow alteration in the river was presented in a heat map. Multi-parametric machine learning (ML) approaches were applied to model hydrological instability and habitat condition. The ecological consequences like evaluating eco-deficit using flow duration curve (FDC) approach, trophic state using trophic state index (TSI), fish habitat zone using image-based hydrological parameters, etc. were measured. The study exhibited that after damming, the degree of river flow modification was about 41%. Consequently, the wetland hydrological instability and habitat conditions were degraded. In the post-dam period, > 50% of wetland area was lost, and hydrological instability was enhanced considerably over wider parts of the wetland. Habitat conditions of the existing wetland also witnessed fragility (poor and very poor areas increased by about 22.23 and 9.34%). As a result of this, adverse ecological responses were found. For instance, the eco-deficit area was increased by 36.19%, a good proportion (100%) of wetlands was witnessed the transformation of TSI from oligotrophic to mesotrophic state, and optimum fish habitat area was declined. The ecological strength map integrating all the cause-effect model parameters showed that good ecological strength was reduced from 49 to 2% in the post-dam. The result of the study would be very useful for wetland restoration for ecological and human well-being.

Predicting wetland area and water depth in Barind plain of India

The present study attempts to delineate wetlands in the lower Tangon river basin in the Barind flood plain region using spectral water body extraction indices. The main objectives of this present study are simulating and predicting wetland areas using the advanced artificial neural network-based cellular automata (ANN-CA) model and water depth using statistical (adaptive exponential smoothing) as well as advanced machine learning algorithms such as Bagging, Random Subspace, Random Forest, Support vector machine, etc. The result shows that RmNDWI and NDWI are the representative wetland delineating indices. NDWI map was used for water depth prediction. Regarding the prediction of wetland areas, a remarkable decline is likely to be identified in the upcoming two decades. The small wetland patches away from the master stream are expected to dry out during the predicted period, where the major wetland patches nearer to the master stream with greater water depth are rather sustainable, but their depth of water is predicted to be reduced in the next decades. All models show satisfactory performance for wetland depth mapping, but the random subspace model was identified as the best-suited water depth predicting method with an acceptable prediction accuracy (root mean square error <0.34 in all the years) and the machine learning models explored better result than adaptive exponential smoothing. This recent study will be very helpful for the policymakers for managing wetland landscape as well as the natural environment.

Impact of river flow modification on wetland hydrological and morphological characters

A good number of researchers investigated the impact of flow modification on hydrological, ecological, and geomorphological conditions in a river. A few works also focused on hydrological modification on wetland with some parameters but as far the knowledge is concerned, linking river flow modification to wetland hydrological and morphological transformation following an integrated modeling approach is often lacking. The current study aimed to explore the degree of hydrological alteration in the river and its effect on downstream riparian wetlands by adopting advanced modeling approaches. After damming, maximally 67 to 95% hydrological alteration was recorded for maximum, minimum, and average discharges. Wavelet transformation analysis figured out a strong power spectrum after 2012 (damming year). Due to attenuation of flow, the active inundation area was reduced by 66.2%. After damming, 524.03 km2 (48.9% of total pre-dam wetland) was completely obliterated. Hydrological strength (HS) modeling also reported areas under high HS declined by 14% after post-dam condition. Wetland hydrological security state (WSS) and HS matrix, a new approach, are used to explore wetland characteristics of inundation connectivity and hydrological security state. WSS was defined based on lateral hydrological connectivity. HS under critical and stress WWS zones deteriorated in the post-dam period. The morphological transformation was also well recognized showing an increase in area under the patch, edge, and a decrease in the area under the large core area. All these findings established a clear linkage between river flow modification and wetland transformation, and they provided a good clue for managing wetlands.

Image-driven hydrological parameter coupled identification of flood plain wetland conservation and restoration sites

A good many works focus on wetland vulnerability; some works also explore restoration sites at a very limited spatial extent. But the satellite image-driven hydrological data-based approach adopted in this work is absolutely new. Moreover, existing work only focused on identifying restoration sites in the present context, but for devising long-term sustainable planning, predicted hydrological parameters based on possible restoration sites may be an effective tool. Considering this, the present work focused on exploring hydrological data (water presence frequency (WPF), hydro-period (HP) and water depth (WD)) from time-series satellite images. This exploration may resolve the hydrological data scarcity of wetland over the wider geographical areas. Using these parameters, we developed wetland restoration and conservation sites for different historical years (2008, 2018) and predicted years (2028) using ensemble machine learning (EML) models. From the analysis, it was found that water depth, hydro-period and WPF became poorer over the period, and the trend may seem to continue in predicted years. Among the applied EML models, Random Subspace (RS) predicted wetland restoration and conservation sites precisely over others. The predicted area under high-priority restoration sites is 34% in 2018, which was 14% in 2008. In 2028, 12% more areas may fall in this priority level. Wetland away from main streams (mainly ortho-fluvial wetland) and fringe wetland parts should be given more priority for restoration. These present and predicted information will effectively help to frame sustainable wetland restoration planning.

Assessing the Impact of the Farakka Barrage on Hydrological Alteration in the Padma River with Future Insight

Climate change and human interventions (e.g., massive barrages, dams, sand mining, and sluice gates) in the Ganga–Padma River (India and Bangladesh) have escalated in recent decades, disrupting the natural flow regime and habitat. This study employed innovative trend analysis (ITA), range of variability approach (RVA), and continuous wavelet analysis (CWA) to quantify the past to future hydrological change in the river because of the building of the Farakka Barrage (FB). We also forecast flow regimes using unique hybrid machine learning techniques based on particle swarm optimization (PSO). The ITA findings revealed that the average discharge trended substantially negatively throughout the dry season (January–May). However, the RVA analysis showed that average discharge was lower than environmental flows. The CWA indicated that the FB has a significant influence on the periodicity of the streamflow regime. PSO-Reduced Error Pruning Tree (REPTree) was the best fit for average discharge prediction (RMSE = 0.14), PSO-random forest (RF) was the best match for maximum discharge (RMSE = 0.3), and PSO-M5P (RMSE = 0.18) was better for the lowest discharge prediction. Furthermore, the basin’s discharge has reduced over time, concerning the riparian environment. This research describes the measurement of hydrological change and forecasts the discharge for upcoming days, which might be valuable in developing sustainable water resource management plans in this location.

Integration of satellite image-derived temperature and water depth for assessing fish habitability in dam controlled flood plain wetland

The present study attempted to investigate the changes in temperature conducive to fish habitability during the summer months in a hydrologically modified wetland following damming over a river. Satellite image-driven temperature and depth data calibrated with field data were used to analyse fish habitability and the presence of thermally optimum habitable zones in some fishes, such as labeo rohita, cirrhinus mrigala, tilapia fish, small shrimp, and catfish. The study was conducted both at the water's surface and at the optimum depth of survival. It is very obvious from the analysis that a larger part of the wetland has become an area that destroyed aquatic habitat during the post-dam period, and existing wetlands have suffered significant shallowing of water depth. This has resulted in a shrinking of the thermally optimum area of fish survival in relation to surface water temperature (from 100.09 to 74.24 km² before the dam to 93.97 to 0 km² after the dam) and an improvement in the optimum habitable condition in the comfortable depth niche of survival. In the post-dam period, it increased from 75.49 to 99.76%. Since the damming effect causes a 30.53 to 100% depletion of the optimum depth niche, improving the thermal environment has no effect on fish habitability. More water must be released from dams for restoration. Image-driven depth and temperature data calibrated with field information has been successfully applied in data sparse conditions, and it is further recommended in future work.

Tackling water security: A global need of cross-cutting approaches

The Virtual Special Issue entitled "Tackling Water Security" is mainly focused on water availability, water quality, management, governance, biotic or abiotic emerging contaminants and policy development in the Anthropocene. The issue is further dedicated to highlight the new opportunities and approaches to elevate the efficiency of water treatment and wastewater reuse. It has undergone an open call for papers and rigorous peer-review process, where each submission has been evaluated by the panel of experts. 43 articles have been selected from 85 submissions that represents the ongoing research and development activities. The message that emerged explicitly from nearly a hundred submissions to this special issue is that there is an urgent global need for cross-cutting approaches for the rational, quick, cost-effective and sustainable solutions for tackling water-security in the Anthropocene.

A legendary landscape in peril: Land use and land cover change and environmental impacts in the Wulagai River Basin, Inner Mongolia

The Mongolian Plateau, home to the world's largest contiguous temperate grasslands, has been known for its vast steppe landscapes and legendary history of the Mongol Empire. However, like temperate grasslands elsewhere around the world, the Mongolian steppe landscapes have been severely degraded by increasing human activities during the past several decades. The main objective of this study was to assess the landscape and ecosystem changes in the Wulagai River Basin (WRB) in Inner Mongolia, where China's last intact steppe ecosystem reportedly resides. Using remote sensing data and landscape metrics, we found that, during 1979-2016, WRB lost about 55 % of wetlands, 76 % of shrublands, and 46 % of sandy-land vegetation, with its most dominant vegetation type shifting from meadow steppe to dry steppe for the first time in history. Human land uses continued to intensify: cropland expanded by about 40 %; impervious surface area increased by almost 34 times; and surface coal mining rampaged through the heartland, tearing up vegetation and sucking up water near and far. The WRB landscape became more diverse compositionally (increasing land cover types), more fragmented ecologically (habitat loss and isolation), and more complex geometrically (anthropogenic and natural landscape elements entangled). Damming, mining, and overgrazing were the major direct drivers for the observed environmental changes. Government-sponsored restoration programs have had positive ecological changes across China, but landscape destruction and fragmentation in the Wulagai River Basin have continued. This dire situation demands urgent government policy intervention and stakeholder-involved governance actions to promote the sustainability of this legendary landscape.

Impact of wetland fragmentation due to damming on the linkages between water richness and ecosystem services

Evaluation of the importance of ecosystem services (ES) of various wetlands is well reported with global and regional level research, but the degree to which spatial-temporal variations in water richness (availability of water) have had an effect on ES has not yet been examined. The present work is intended to investigate the influence of wetland fragmentation due to damming on wetland water richness and the impact of changes in water richness on the ecosystem service value (ESV) of the wetland-dominated rivers of the lower Punarbhaba Basin, India, and Bangladesh, as the case. Water richness models of pre- and post-dam periods have been constructed based on four hydro-ecological parameters (hydro-period, depth of water, consistency of water appearance, and wetland size) following the semi-quantitative analytic hierarchy process (AHP). ESV of different wetland types, with and without considering water richness effect, has been computed. The result indicates that the overall wetland area decreased from 73,563 to 52,123 km² during the post-dam period. Approximately 53.8% of the high water-rich region is decreased. Total wetland ESV has been lowered by 63.4% from 1989 to 2019, with an average reduction rate of 2%. This is mainly due to the squeezing of the wetland area during the post-dam period. If the impact of water richness on ESV is considered, the scenario is found to be very distinct. Total ESV of various ESV areas amounted to $33 million during the pre-dam period and is reduced to $19.71 million during the post-dam period. If compared to the total ESV of the wetland without considering the effect of water richness, the calculated ESV gap was $105 million in pre-dam and $38 million in post-dam period indicating a widening of the gap. Maintaining the ES of wetland hydrological management, specifically the flow maintenance of river and riparian wetlands, is essential.