Predicted changes in future precipitation and air temperature across Bangladesh using CMIP6 GCMs.

Understanding spatiotemporal variability in precipitation and temperature and their future projections is critical for assessing environmental hazards and planning long-term mitigation and adaptation. In this study, 18 Global Climate Models (GCMs) from the most recent Coupled Model Intercomparison Project phase 6 (CMIP6) were employed to project the mean annual, seasonal, and monthly precipitation, maximum air temperature (Tmax), and minimum air temperature (Tmin) in Bangladesh. The GCM projections were bias-corrected using the Simple Quantile Mapping (SQM) technique. Using the Multi-Model Ensemble (MME) mean of the bias-corrected dataset, the expected changes for the four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) were evaluated for the near (2015-2044), mid (2045-2074), and far (2075-2100) futures in comparison to the historical period (1985-2014). In the far future, the anticipated average annual precipitation increased by 9.48%, 13.63%, 21.07%, and 30.90%, while the average Tmax (Tmin) rose by 1.09 (1.17), 1.60 (1.91), 2.12 (2.80), and 2.99 (3.69) °C for SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. According to predictions for the SSP5-8.5 scenario in the distant future, there is expected to be a substantial rise in precipitation (41.98%) during the post-monsoon season. In contrast, winter precipitation was predicted to decrease most (11.12%) in the mid-future for SSP3-7.0, while to increase most (15.62%) in the far-future for SSP1-2.6. Tmax (Tmin) was predicted to rise most in the winter and least in the monsoon for all periods and scenarios. Tmin increased more rapidly than Tmax in all seasons for all SSPs. The projected changes could lead to more frequent and severe flooding, landslides, and negative impacts on human health, agriculture, and ecosystems. The study highlights the need for localized and context-specific adaptation strategies as different regions of Bangladesh will be affected differently by these changes.

The impact of climate change, population growth and development on sustainable water security in Bangladesh to 2100.

There are concerns that groundwater use for irrigation and for urban water supply is unsustainable in some parts of Bangladesh, particularly in the agriculturally productive northwest region. We use an integrated population - GDP - food - water model to examine water demand to 2100 in Bangladesh in development scenarios relevant to food and water security. The results indicate that irrigation water demand is projected to increase in coming decades, but later in the century it may decrease due to increasing crop yields and a falling population. The increased demand is greatest in the northwest region and, if unchecked, would increase concerns there about the unsustainable use of groundwater. The growth in demand is determined particularly by growth in crop yields, population growth and the fraction of food demand satisfied by imports. An extreme hot-dry climate change scenario has a lesser impact. This suggests that, in principle, Bangladesh can offset the impacts of climate change on irrigation water demand through its domestic policies. Urban water use currently also leads to concerns over unsustainable groundwater use. Our results suggest that urban water demand is likely to grow proportionately significantly more than irrigation water demand. Alternative sources for urban water are therefore urgently required.

Numerical groundwater modelling for studying surface water-groundwater interaction and impact of reduced draft on groundwater resources in central Ganga basin.

Water resources in India's Indo-Gangetic plains are over-exploited and vulnerable to impacts of climate change. The unequal spatial and temporal variation of meteorological, hydrological and hydrogeological parameters has created additional challenges for field engineers and policy planners. The groundwater and surface water are extensively utilized in the middle Gangetic plain for agriculture. The primary purpose of this study is to understand the discharge and recharge processes of groundwater system using trend analysis, and surface water and groundwater interaction using groundwater modelling. A comprehensive hydrological, and hydrogeological data analysis was carried out and a numerical groundwater model was developed for Bhojpur district, Bihar, India covering 2395 km2 geographical area, located in central Ganga basin. The groundwater level data analyses for the year 2018 revealed that depth to water level varies from 3.0 to 9.0 meter below ground level (m bgl) in the study area. The M-K test showed no significant declining trend in the groundwater level in the study area. The groundwater modelling results revealed that groundwater head is higher in the southern part of the district and the groundwater flow direction is from south-west to north-east. The groundwater head fluctuation between the monsoon and the summer seasons was observed to be 2 m, it is also witnessed that groundwater is contributing more to rivers in the monsoon season in comparison with other seasons. Impact of reduction in pumping on groundwater heads was also investigated, considering a 10% reduction in groundwater withdrawal. The results indicated an overall head rise of 2 m in the southern part and 0.2-0.5 m in the middle and northern part of the district.

Future rice farming threatened by drought in the Lower Mekong Basin.

The Lower Mekong River basin (LMB) has experienced droughts in recent decades, causing detrimental economic losses and food security conundrums. This study quantified the impact of climate change on drought, and rainfed rice production in the LMB. The Soil and Water Assessment Tool (SWAT) and AquaCrop models were used to evaluate long-term drought indices and rainfed rice yields under historical and future climate conditions (1954-2099) with four climate models and two emission scenarios (RCP 4.5 and RCP8.5) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). We found that rice yield might increase (24-43%) due to the elevated levels of atmospheric CO2 concentration (+ 34.3 to + 121.9%) and increases in precipitation. Contrastingly, considerable decreases in rice yield up to 1.5 ton/ha in the Vietnam Central High Plain (VCHP) region could be expected resulting from reduced precipitation by about 34% during drought years. To avert any major food crisis, an expansion of irrigation areas could be required to compensate for the expected reduction in rice yields. We conclude that a framework combining hydrology and crop models to assess climate change impacts on food production is key to develop adaptation strategies in the future.

Multi-faceted impact and outcome of COVID-19 on smallholder agricultural systems: Integrating qualitative research and fuzzy cognitive mapping to explore resilient strategies.

The shock of Coronavirus Disease 2019 (COVID-19) has disrupted food systems worldwide. Such disruption, affecting multiple systems interfaces in smallholder agriculture, is unprecedented and needs to be understood from multi-stakeholder perspectives. The multiple loops of causality in the pathways of impact renders the system outcomes unpredictable. Understanding the nature of such unpredictable pathways is critical to identify present and future systems intervention strategies. Our study aims to explore the multiple pathways of present and future impact created by the pandemic and "Amphan" cyclonic storm on smallholder agricultural systems. Also, we anticipate the behaviour of the systems elements under different realistic scenarios of intervention. We explored the severity and multi-faceted impacts of the pandemic on vulnerable smallholder agricultural production systems through in-depth interactions with key players at the micro-level. It provided contextual information, and revealed critical insights to understand the cascading effect of the pandemic and the cyclone on farm households. We employed thematic analysis of in-depth interviews with multiple stakeholders in Sundarbans areas in eastern India, to identify the present and future systems outcomes caused by the pandemic, and later compounded by "Amphan". The immediate adaptation strategies of the farmers were engaging family labors, exchanging labors with neighbouring farmers, borrowing money from relatives, accessing free food rations, replacing dead livestock, early harvesting, and reclamation of waterbodies. The thematic analysis identified several systems elements, such as harvesting, marketing, labor accessibility, among others, through which the impacts of the pandemic were expressed. Drawing on these outputs, we employed Mental Modeler, a Fuzzy-Logic Cognitive Mapping tool, to develop multi-stakeholder mental models for the smallholder agricultural systems of the region. Analysis of the mental models indicated the centrality of "Kharif" (monsoon) rice production, current farm income, and investment for the next crop cycle to determine the pathways and degree of the dual impact on farm households. Current household expenditure, livestock, and soil fertility were other central elements in the shared mental model. Scenario analysis with multiple stakeholders suggested enhanced market access and current household income, sustained investment in farming, rapid improvement in affected soil, irrigation water and livestock as the most effective strategies to enhance the resilience of farm families during and after the pandemic. This study may help in formulating short and long-term intervention strategies in the post-pandemic communities, and the methodological approach can be used elsewhere to understand perturbed socioecological systems to formulate anticipatory intervention strategies based on collective wisdom of stakeholders.

Yield, profitability, and prospects of irrigated Boro rice cultivation in the North-West region of Bangladesh.

The North-West (NW) region of Bangladesh is pivotal for the country's agricultural development, mainly in producing irrigated Boro rice. However, increasing cost of irrigation water, fertilizers, labour and other inputs, and the spatio-temporal variation in actual yield, market price and profitability of rice, have added uncertainty to the sustainability of Boro rice cultivation. In this study, we evaluated the productivity, profitability, and prospect of Boro rice production using comprehensive field data collected directly from 420 farmers' fields over two consecutive seasons (2015-16 and 2016-17), across seven geographically distributed locations in the NW region. We also analyzed the risk and return trade of popular Boro rice cultivars using Monte-Carlo simulation. The results show that there were significant (p≤0.05) variations in rice yield between sites, irrigation pump-types, and rice varieties, with Hybrid rice and BRRI dhan29 producing highest yields (6.0-7.5 t/ha). Due to different pricing systems, the cost of irrigation water varied from site to site and from year to year, but always comprised the highest input cost (20-25% of total production). The total paid-out cost, gross benefit, and gross income of rice significantly (p≤0.05) differed between sites, type of irrigation pumps, rice varieties, transplanting dates, and two cropping years. The variations in observed yield and profitability reveal considerable scope to improve rice production systems. Market variation in the price of rice affected overall profitability significantly. Probability and risk analysis results show that Minikit and BRRI dhan29 are the most stable varieties for yield and profitability. Hybrid rice, which has the maximum attainable yield among the cultivated rice varieties, also has the risk of negative net income. Based on the analysis, we discussed ways to improve yield and profitability and the prospect of Boro rice cultivation in the region. The study provides valuable information for policy-makers to sustain irrigated rice cultivation in both the NW region and nationally.

Impact of climate change and management strategies on water and salt balance of the polders and islands in the Ganges delta.

Enhancing crop production, particularly by growing a crop in the typically-fallow dry season is a key strategy for alleviating poverty in the Ganges delta region. We used a polder water and salt balance model to examine the impact of several crop management, salt management and climate change scenarios on salinity and crop evapotranspiration at Dacope and Amtali in Bangladesh and Gosaba in India. A key (and unsurprising) finding is that salt management is very important, particularly at the two drier sites, Dacope and Gosaba. Good salt management lowers salinity in the shallow groundwater, soil and water storage ponds, and leads to more irrigation. Climate change is projected to alter rainfall, and this in turn leads to modelled increases or decreases in runoff from the polders, and thence affect salt concentrations in the soil and ponds and canals. Thus, the main impacts of climate change are through the indirect impacts on salt concentrations, rather than the direct impacts of the amount of water supplied as rainfall. Management practices to remove salt from polders are therefore likely to be effective in combatting the impacts of projected climate change particularly at Dacope and Gosaba.

COVID-19 induced economic loss and ensuring food security for vulnerable groups: Policy implications from Bangladesh.

At present nearly half of the world's population is under some form of government restriction to curb the spread of COVID-19, an extremely contagious disease. In Bangladesh, in the wake of five deaths and 48 infections from COVID-19, between March 24 and May 30, 2020, the government imposed a nationwide lockdown. While this lockdown restricted the spread of COVID-19, in the absence of effective support, it can generate severe food and nutrition insecurity for daily wage-based workers. Of the 61 million employed labor force in Bangladesh, nearly 35% of them are paid on a daily basis. This study examines the food security and welfare impacts of the COVID-19 induced lockdown on daily wage workers both in the farm and nonfarm sectors in Bangladesh. Using information from more than 50,000 respondents complied with the 2016-17 Household Income and Expenditure Survey (HIES) in Bangladesh, this study estimates daily wage rates as Bangladesh Taka (BDT) 272.2 in the farm sector and BDT 361.5 in the nonfarm sector. Using the estimated daily wage earnings, this study estimates that a one-day complete lockdown generates a US$64.2 million equivalent economic loss only considering the wage loss of the daily wage workers. After estimating the daily per capita food expenditure separately for farm and nonfarm households, this study estimates a minimum compensation package for the daily wage-based farm and nonfarm households around the US $ 1 per day per household to ensure minimum food security for the daily wage-based worker households.

Profitability, energetics and GHGs emission estimation from rice-based cropping systems in the coastal saline zone of West Bengal, India.

This study compares thirteen rice-based cropping systems in the coastal part of West Bengal, India in terms of productivity, profitability, energetics, and emissions. Information on the crop management practices of these systems was collected on 60 farms through a questionnaire survey. Rice-bitter gourd system was observed to have the highest system yield (49.88 ± 4.34 tha-1yr-1) followed by rice-potato-ridge gourd (37.78 ± 2.77 tha-1yr-1) and rice-potato-pumpkin (36.84 ± 2.04 tha-1yr-1) systems. The rice-bitter gourd system also recorded the highest benefit:cost ratio (3.92 ± 0.061). The lowest system yield and economics were recorded in the rice-fallow-fallow system. Rice-sunflower system recorded highest specific energy (2.54 ± 0.102 MJkg-1), followed by rice-rice (2.14 ± 0.174 MJkg-1) and rice-fallow-fallow (1.91 ± 0.327 MJkg-1) systems, lowest being observed in the rice-bitter gourd (0.52 ± 0.290 MJkg-1) and rice-pointed gourd (0.52 ± 0.373 MJkg-1) systems. Yield-scaled GHGs (YSGHG) emission was highest (1.265 ± 0.29 t CO2eqt-1 system yield) for rice-fallow-fallow system and was lowest for rice-vegetable systems. To estimate the uncertainty of the YSGHG across different systems under study, Monte-Carlo Simulation was performed. It was observed that there was a 5% probability of recording YSGHG emission > 1.15 t CO2eqt-1 system yield from different cropping systems in the present experiment. Multiple system properties such as productivity, economics, energy, and emission from all rice-based systems taken together, the rice-vegetable system performed consistently well across parameters and may be practised for higher economic returns with judicious and sustainable utilization of resources in the coastal saline tracts of the region.

Assessing irrigated agriculture's surface water and groundwater consumption by combining satellite remote sensing and hydrologic modelling.

Globally, irrigation accounts for more than two thirds of freshwater demand. Recent regional and global assessments indicate that groundwater extraction (GWE) for irrigation has increased more rapidly than surface water extraction (SWE), potentially resulting in groundwater depletion. Irrigated agriculture in semi-arid and arid regions is usually from a combination of stored surface water and groundwater. This paper assesses the usefulness of remotely-sensed (RS) derived information on both irrigation dynamics and rates of actual evapotranspiration which are both input to a river-reach water balance model in order to quantify irrigation water use and water provenance (either surface water or groundwater). The assessment is implemented for the water-years 2004/05-2010/11 in five reaches of the Murray-Darling Basin (Australia); a heavily regulated basin with large irrigated areas and periodic droughts and floods. Irrigated area and water use are identified each water-year (from July to June) through a Random Forest model which uses RS vegetation phenology and actual evapotranspiration as predicting variables. Both irrigated areas and actual evapotranspiration from irrigated areas were compared against published estimates of irrigated areas and total water extraction (SWE+GWE).The river-reach model determines the irrigated area that can be serviced with stored surface water (SWE), and the remainder area (as determined by the Random Forest Model) is assumed to be supplemented by groundwater (GWE). Model results were evaluated against observed SWE and GWE. The modelled SWE generally captures the observed interannual patterns and to some extent the magnitudes, with Pearson's correlation coefficients >0.8 and normalised root-mean-square-error<30%. In terms of magnitude, the results were as accurate as or better than those of more traditional (i.e., using areas that fluctuate based on water resource availability and prescribed crop factors) irrigation modelling. The RS irrigated areas and actual evapotranspiration can be used to: (i) understand irrigation dynamics, (ii) constrain irrigation models in data scarce regions, as well as (iii) pinpointing areas that require better ground-based monitoring.