SOCIO-ECONOMIC AND ECOLOGICAL ADAPTABILITY ACROSS SOUTH ASIAN FLOODPLAINS

. Flood Risk Potential across South Asian Floodplains corresponding to 2010 economic exposures had been re-ported to be about 11 billion US2012$ and contributing more than 10% of Global values. Ecosystem approaches, based on Integrated Flood Management strategy of World Meteorological Organization, have been explored for balanced socio-economic and ecological adaptability enhancement, considering degradation of ecosystem services as fundamental issues and adaptation as optional solution. Adaptive Management methods have been explored for Flood Risk Minimization. General benefits of balanced socio-economic and ecological adaptation have been reviewed. Distributions of flood hazards, Gross Domestic Product, flood risk, Net Primary Productivity, carbon dioxide emissions and landscapes heterogeneity have been presented and analyzed for its influences over socio-economic and ecological adaptability. Distributions of Expected Annual Exposed socio-economic resources across 500 Years floodplains have been presented. Projected results corresponding to various two dimensional socio-environmental scenarios have been presented. Low Adaptable regions have been delineated.


Introduction
Synergy had been defined as the interaction and cooperation capacities of two or more individual elements with the objectives of achieving benefits of combined effects which are expected to be higher than the sum of benefits of separate individual effects (Cambridge University Press, 2021). To deal with uncertain events like Flood Hazard, Adaptive Management (AM) Strategy have been recommended by many literatures including Allen and Garmestani (2015) for achieving the objectives under uncertain Scenario, and also has been accommodated in the levels as per Sustainable Development standards of United Nations (UN, 2015). South Asian Economy is consistently increasing in par with that of USA, China and European Countries (World Bank, 2021). Anyhow, Flood Risk Potential across South Asian Floodplains corresponding to 2010 Economic Exposures had been reported to be about 11 billion US2012$ and contributing more than 10% of Global Values (United Nations Office for Disaster Risk Reduction [UNISDR], 2015). Historical growths of Global Population, Global Gross Domestic Product (GDP) and corresponding carbon dioxide (CO 2 ) emissions have been compared using Figure 1a. The possible reason for the change of Trend and sharp increase in growth rate of Population and GDP after 1950 as in Figure 1 is attributed to the invention of Semiconductor Transistor by 1948. Based on the principles of miniaturization, the Vacuum Tube had got replaced by Transistor after the invention of this Semiconductor device by Bell Telephone Laboratories, Murray Hill, New Jersey, USA (Bardeen & Brattain, 1948). Anyhow this had caused for the further development of VLSI System across 1970s and become the foundation for the development and existence of current Computer based System of Internet Communications. In the name of Adaptation, it becomes the work of Cement to bind the coarse and fine Aggregates in order to develop a stronger Construction Materials having Strength higher than that of component Materials. Similarly the Synergy or Adaptation Level across Global Social Systems (GSS) had got increased or stimulated or excited by the development of Virtual Adaptor in the form of Semiconductor Devices based Global Electronics Communication System binding the Aggregate GSS into Concrete GSS towards Globalized Economy. Keeping the radiative forcing at constant high level, projected socio-economic developments corresponding to Globalised and Localized Economy have been compared as in Figure 1b in order to delineate the benefits of high socio-economic adaptable Globalised solutions with respect to low socio-economic adaptable localized solutions. The possible benefits of Socio-Economic Adaptation across the floodplains are expected to be similar to the sharp increase in Socio-Economic Development what had happened after 1950 as in Figure 1a. Irrespective of Globalised or Localized Economy, Fossil Fuelled (FF) development represented by high radiative forcing had caused for high CO 2 Emissions and has been presented in Figure 1 for emphasizing the need of balanced SE-EA developments. This article explores strategies to enhance Economic Development, using AM based FRM. Based on the principles of IFM, SE-EA analysis at floodplain level has been compared with corresponding parameters at basins level and Global level.

Study area
For the purpose of SE-EA Analysis, the Study Area of South Asian Floodplains has been delineated based on the Criteria proposed by USGS Hydrologic Derivatives for Modeling and Applications (HDMA) database (Verdin, 2017) into three Units of Groups of River Basins such as GBMS (Ganga, Brahmaputra, Meghna and Supernarekha) Basins, SLSS (Sindhu, Luni, Saraswathi and Sabarmati) Basins, and GKSI (Godavari, Krishna and other South India) Basins and Floodplains of only Peninsular River Basins have been analyzed without considering South Asian islands including Sri Lanka. The Location and Boundaries of the 500 Years Floodplains along with that of Peninsular River Basins and corresponding National administration of South Asia across the Basins are presented in Figure 2. Based on the Criteria of Critical Action Floodplains that had been recommended by FEMA (1986), 500 Years Floodplains have been considered as reference Floodplain and referred simply as "Floodplains" for Adaptability Analysis. Global 500 Year 30s gridded Flood Hazard Maps provided by United Nations Environment Programme and Global Resources Information Database (UNEP-GRID, 2015) and European Commission and Joint Research Centre (EC-JRC, 2016) have been combined as Union using the "OR" Logic, to get 500 Years Floodplains including the water bodies as in Figure 2. Indo-Gangetic Floodplains of GBMS and SLSS unit had been distributed over the alluvial soil deposits at the foot of Himalayan Range of mountains. More than 55% of 500 Years Floodplain are located at an elevation less than 100 m and across Indo-Gangetic plains and the delta regions of all three units of river basins (Lehner et al., 2008).

Socio-economic and socio-ecological adaptability
Based on the Principles of Adaptation (Chapin et al., 2011) and ( where: AC1 = Socio-Economic Adaptability of floodplains for the specified year; AC2 = Socio-Ecological Adaptability of floodplains for the specified year.

Principles of two-phase adaptation across floodplains
Using the objectives of Multi-Benefit Floodplain Management (MB-FPM), all the Benefits of MB-FPM have been grouped into benefits to society and that to ecosystems, while MB-FPM have been recommended to achieve new levels of synergies where there will be balanced distribution of benefits across social and ecological systems. Conventional Flood control methods, based on Structural measures have produced social benefits at the cost of adverse environmental consequences (Serra-Llobet et al., 2022). Using the principles of Sustainable Flood Risk Management, synergies between different policy fields including floodplain restoration, ecosystem services, and other nature based solutions representing the ecological dimensions have been emphasized along with minimization of economic losses (European Environment Agency, 2016). It has been recommended by Congressional Research Service (2020) to maximize the contribution of Flood Risk Reduction capacities of Natural and Nature-Based Features (NNBFs) along with the use of traditional structural and non-structural methods in order to balance the benefits across social and ecological systems. Even though Globalised Economy representing high level of Socio-Economic Adaptability across GSS, GDP development process has caused for sharp increase in CO 2 emissions during last 6 decades as in Figure 1a and corresponding degradation of Socio-Ecological Adaptability representing imbalance over the distribution of benefits across social and ecological systems. This indicates unbalanced Socio-Economic (Phase-1) Adaptation over Socio-Ecological (Phase-2) Adaptation. Both Climate Change Adaptation (CCA) and Climate Change Mitigation (CCM) had been recommended by IPCC (2007), to reduce the losses or impacts of Climate Change Issues. Socio-Economic Adaptation across Floodplains has been accommodated as component of CCA (United States Government Accountability Office, 2016). In the name of Socio-Ecological Adaptation, any of the attempts to reduce CO 2 emissions (including SDG 15.1 and SDG 7.2) have been considered as component of CCM. Benefits can be maximized by the optimum combination or Trade-off between Mitigation and Adaptation (IPCC, 2007). Hence balanced implementation of CCA and CCM has been referred as two-phase system of managing the climate change issues including flood issues. Accordingly, the procedures of gradual conversion of single phase floodplain adaptation measures into twophase adaptation has been adopted in this article and analysis has been aimed towards balanced development of both socio-economic and socio-ecological adaptability across South Asian Floodplains and has been referred as two-phase system of floodplain adaptation. Assuming Mitigation as Technical (Hardware) Solution and Adaptation as Managerial (Software) Solution for IFM, only Adaptation has been focused. In this article no attempt has been made to present any of the Floodplain adaptation practices or floodplain management practices. Floodplain socio-economic adaptability level has been analyzed and presented to be considered as an input parameter to determine best or optimum mix of flood management strategies as recommended by WMO (2009) towards efficient distribution of limited flood control investment across the floodplains. Low adaptable regions have been presented with the expectation that more priority will given to those regions towards allocation of flood control investment and/or implementation of flood regulated developments. Multi-criteria based Cost-Benefit Analyses (CBAs) as recommended by IPCC (2007), has been proposed for deciding the operating point representing balanced benefits between social and ecosystems across the selected local regions, where the results presented in this article such as socio-economic and socio-ecological adaptability levels are expected to be used as limiting values of the constraint equations along with objective functions of Multi-Criteria Decision Making (MCDM) model. Based on the principles of Socio-Ecological Stewardship as defined by Chapin et al. (2011), socio-ecological adaptability analysis is expected to be useful for motivating the human community and to remind the responsibility of Social System to improve Ecosystem Resilience and thereby enhancing life supporting capacity of Planet Earth. Accordingly, similar to Cost-Benefit Ratio (CBR) of a Project, Adaptability results has been considered as an exciting or stimulating agent, to act as catalyst towards further developments.

Projections based on Two-Phase Scenarios
Scenarios are being used by IPCC to drive Global Circulation Model (GCM) in order to generate future projected results. Based on the level of radiative forcing values by the year 2100, ranging between 8.5 W/m 2 and 2.6 W/m 2 , Representative Concentration Pathways (RCPs) scenarios having only Environmental dimensions had been used by IPCC AR5 towards the projection of future socio-economic and environmental parameters (IPCC, 2013). Such one dimensional Scenarios based projections of IPCC AR5 has got improved by two dimensional Scenarios based projections of IPCC AR6 where, social value or social dimension denoted as Shared Socioeconomic Pathways (SSPs) have also been accommodated and represented by combined RCPs and SSPs (IPCC, 2021). The mapping of SSPs and RCPs based Scenarios matrix over Social and Environmental dimensions has been presented in the Figure 3 using the narratives of Riahi et al. (2017). The projections of future Population, GDP, Expected Annual Damage (EAD), CO 2 Emissions used in this article are corresponding to the two-dimensional reference scenarios as mentioned against the projected results.

Analysis of Expected Annual Exposed (EAE) resources
Area of 500 Years Floodplains and corresponding Basins has been presented in Table 1 using the same accuracy level of 30s resolution as that of Flood Hazard database. Based on the Submergence Areas corresponding to Floods of Return Period ranging from 5 to 500 Years, EAE Floodplain Area have been estimated using the methods reported by many literatures including Apel et al. (2016), and also presented in Table 1. The Probable Maximum Loss (PML) contributed by the Flood of 2 Years Return Period, have been reported by WRI (2015) to be Zero and hence not considered in EAE Analysis. Accordingly 10% of 500 Years Floodplains of South Asian River Basins is expected to be annually exposed to Flood. The % EAE Floodplain Area of GBMS Basins is relatively higher with respect to that of other two units of Basins such as SLSS and GKSI.
Flood Frequency Distribution across a Grid converts the Grid Resources into EAE Resources, while the loss depends on Vulnerability Function or Damage Model used (Apel et al., 2016). Irrespective of the Vulnerability, only EAE Floodplain, EAE 2010 Population and EAE 2010 GDP have been analyzed for its distribution across the study area using Figure 4 and

Analyses of socio-economic and socioecological adaptability
The Economic and Ecological Performances across the Study Area have been presented using Figure 5 and Figure 6 respectively. The grid wise distributions of 2010 Economic performance across South Asian Floodplains in terms of GDP gain, Expected Annual Loss and the Gain-Loss ratio representing Economic Adaptability estimated using Equation (1) have been shown in Figure 5. Low socio-economic adaptable floodplain regions have also been delineated in Figure 5. Similarly the grid wise distributions of 2010 Ecological performance across South Asian Rivers Basins in terms of CO 2 Absorption, CO 2 Emission and the ratio of CO 2 Absorption to CO 2 Emission representing the Ecological Adaptability estimated using Equation (2) have been shown in Figure 6. Low socio-ecological adaptable regions have also been delineated in Figure 6. The distributions of Flood Risk Potential in terms of Expected Annual Damage (EAD) corresponding to 2010 GDP Exposures provided by UNEP-GRID (2015) dataset were used. Based on the NASA Earth Observations (2018) NPP dataset, the distribution of 2010 annual NPP representing CO 2 Absorption has been estimated. Using the International Energy Agency (2021) dataset representing the Nation wise CO 2 Emission Equivalent of each unit of corresponding national GDP of specified Year, the distribution of 2010 GDP provided by UNEP-GRID (2015) has been converted to distribution of equivalent CO 2 Emission. While the Flood Loss is applicable only for Floodplains, the parameters NPP, CO 2 Emission, Socio-Ecological Adaptability are applicable for entire Basin and hence the grid wise distribution of these three parameters has been presented across entire Basins including Floodplains.
Higher the Socio-Ecological Adaptability represents higher the Ecosystem Resilience to absorb the anthropogenic impact of high CO 2 Emission and corresponding Climate Change Adaptation (CCA) Capacity. Hence irrespective of the Ecosystem Threshold, the distribution of Socio-Ecological Adaptability also represents the corresponding distribution of Ecosystem Resilience to absorb CO 2 Emission. Higher the GDP can cause for the increase in Floodplain Economic Adaptability while, the corresponding increase in CO 2 Emission can cause for the decrease in Ecological Adaptability. It represents the existence of possible trade-off between Economic Adaptability and Ecological Adaptability. As an element of AM Strategy, Adaptability Assessment is a continuous process and need to be updated periodically towards the design and implementation of Control actions to improve the Adaptability Level as well as maintaining optimum combination of Economic and Ecological Adaptability Levels to achieve the final quantitative objectives in collaboration with Sustainable Development Goals (SDGs).

Contributions of United Nations, World Bank and Local Governments towards SE-EA enhancement
All the efforts of UN, starting from 1945, towards successful developments of SDGs framework and up to date implementations of SDGs across the world in collaboration with national Governments are the contributions of UN, towards balanced SE-EA development both across basin and floodplain levels. SDG 7.2 has the potential to reduce CO 2 Emission contribution of GDP. SDG 15.1 has the Potential to increase CO 2 Absorption Capacity. SDG 17 demands for the participation and partnership of all local

investment against Flood Control
Infrastructure in India has potential to reduce the EAD by $238 (WRI, 2020). The basic aim of this Paper is to explore efficient use of such flood control investment towards FRM and balanced development of SE-EA levels.

Analysis of Projected Future Flood Damages based on 2010 base year values
Basin level lumped values of projected GDP and EAD have been compared using Table 4, for selected scenarios represented as SSP2-4.5, SSP2-8.5 and SSP3-8.5. Increase in radiative forcing level from 4.5 to 8.5 W/m 2 for same SSP2 scenario have caused for corresponding increase in EAD. This is interpreted as the impact of low socioecological adaptability causing for increased EAD. Similarly keeping the radiative forcing at constant 8.5 W/m 2 level, SSP2 having high socio-economic adaptability with respect to SSP3 as in Figure 3, have caused for increased GDP development over SSP3 scenario. Hence, balanced increase in socio-economic adaptability and socio-ecological adaptability is expected to cause for minimizing EAD.
Comparing the projected performances of three units of basins, GBMS unit is reported to have highest Climate sensitive EAD while, SLSS unit is reported to have lowest Climate sensitive EAD.

Analysis of Landscape Heterogeneity
When the Economic Adaptability of Floodplains is highly influenced by the Flood hazard and vulnerability of the Floodplain Exposures, the Ecological Adaptability is highly influenced by Ecosystem Performance which is being controlled by spatial heterogeneity of Landscape as the Floodplain Ecosystem does not exist as isolated unit on the Floodplain Landscape (Chapin et al., 2011). Land Use and Land Cover (LULC) data set of EC-JRC (2004) and (  Accordingly the Landscape Composition of the entire basins of the Study Area has been compared for the year 2000 and 2020 using Figure 7 and Table 5. The distribution of Landscape composition is in Figure 7 while the lumped values of areas of individual types of Landscape pattern across the three units of basins and corresponding Floodplains units are in Table 5. Distributions of Wetlands with respect to other landscapes, approximately represents that of floodplains. It is interpreted that there is sharp increase in bare land of more than 3,50,000 sq. km and corresponding decrease in Agricultural and Forest Area during this 20 years from 2000 to 2020 across SLSS unit. Reduction in NPP capacity across SLSS unit is attributed to such inappropriate change in Landscape composition. It is also interpreted that Wetland Area across all the three units of basins is consistently getting decreased from 2000 to 2020 and also being occupied by Urban Area and causing for corresponding increase in Urban Area. Any anthropogenic disturbance to Wetland can bring down the Ecosystem NPP performance Chapin et al. (2011). Hence protection and restoration of Wetland Ecosystem, is expected to enhance the Ecological Adaptability Level.

Conclusions
Temporal smoothing of Flood loss using regular AAL investment had been recommended by UNISDR (2015) as one on the Adaptation Strategy towards Flood Adaptation by balancing the Flood Loss for exploiting the Productive Capacities of Floodplains. In a Social System, to solve a family problem within the family has been considered to be somewhat better than moving towards a third party including public court system. Even though the Flood discharge is contributed by entire River Basins, the Flood Loss is concentrated only across Floodplains. Board of Floodplain Adaptation needs to be organized to work in collaboration with existing Disaster Emergency Management Agencies so that AM based pre flood management operations will get synchronized with the post flood management operations from low level village to high level national administration towards the purpose of enhancing Socio-Economic Adaptability. Similarly successful implementation of both SDGs 7.2 and 15.1 has the potential to enhance the level of Socio-Ecological Adaptability and thereby to maintain balanced socio-economic and ecological performance across the floodplains. The localized elevated land regions surrounded by flood inundation is expected to suffer from at least low vulnerable indirect losses produced by surrounded flood inundation. Anyhow such localized elevated Regions surrounded by flood inundation have not been accommodated as Floodplains and assumed to be not influenced by flood inundation. The NPP performance of regions of Wetland Ecosystem surrounded by flood inundation and adjacent to flood inundation is highly influenced by frequency and intensity of flood inundation (Chapin et al., 2011). Anyhow such indirect influences of flood inundation over the NPP Performance of adjacent elevated regions of Wetland Ecosystem have not been considered in this Socio-Ecological Adaptability analysis. Based on Area Elevation topography of the 500 Years Floodplains, more than 15% of South Asian Floodplains are located over Low Elevation Coastal Zones (LECZ). The Flood Risk across LECZ is being developed by a scenario of compound coastal flooding having different possible combinations of Riverine flood, tidal waves, tsunami waves, storm surges coupled with cyclonic rain, wave run-up, climate change induced sea level rise trend (McGranahan et al., 2007). Anyhow Economic losses due to such Compound Coastal Flooding over the Floodplains of Coastal Delta Regions of all River basins of the Study Area have also not been considered in this Adaptability Analysis. The Flood Hazard Maps provided by UNEP-GRID (2015) and EC-JRC (2016) are applicable only for fluvial Flood and not accommodating both pluvial and coastal flood hazard. These Global fluvial flood hazards had been estimated using derived River networks at 30 sec accuracy and 3 sec SRTM DEM data (Trigg et al., 2016). Hence the Flood Protection capacity of existing Flood Embankment having width less than 90 m has not been accommodated in the Flood hazard Map. Current Socio-Economic and Ecological Adaptability analysis is applicable for 2010 Scenario of Flood Hazard and Exposures distributions. Hence Projected Adaptability needs to be analyzed corresponding to various socio-environmental SSP-RCP scenarios.