Assessing drought vulnerability using geospatial techniques in northwestern part of Bangladesh

Interaction of drought-influencing factors for drought mitigation strategies in Lam Ta Kong Watershed, Khorat Plateau

Generally, drought is influenced by both spatial characteristics and anthropogenic activities within an area. Drought vulnerability assessment is a critical tool that can be effectively used to develop proper drought mitigation strategies to prevent avoidable losses. To develop suitable drought mitigation strategies, the overall drought vulnerability must be assessed, and the interaction among drought-influencing factors in the area should be considered. Consequently, this study aimed to investigate the interactions among critical drought-influencing factors and drought vulnerability in the Lam Ta Kong Watershed via spatial analysis with the analytical hierarchy process (AHP) and geographical information system (GIS) technology. Ten drought-influencing factors were considered in the vulnerability assessment: slope, elevation, soil texture, soil fertility, stream density, precipitation, temperature, precipitation days, evaporation, and land use. The results indicated that the critical drought-influencing factors were precipitation, precipitation days, and land use, resulting in most of the watershed experiencing high drought vulnerability (35.1% of the watershed or 1810.83 km2). Moreover, this research highlighted the interactions among the critical drought-influencing factors. Precipitation interacted with precipitation days to cause drought vulnerability across the watershed, with a p-value <0.05. Similarly, the interactions between precipitation and land use and between precipitation days and land use, with p-values <0.05, showed that they were associated with and influenced by drought in the Lam Ta Kong Watershed. This study further indicated that appropriate drought mitigation strategies for this watershed must consider the interactions among these drought-influencing factors, as well as their specific interactions across the watershed.

Assessment of the combined vulnerability to droughts and heatwaves in Shandong Province in summer from 2000 to 2018

Droughts and heat waves exhibit synergistic effects and are among the world's most costly disasters. To explore the spatiotemporal differences and formation mechanisms of the combined vulnerability to droughts and heat waves in Shandong Province over the past 20 years, a vulnerability scoping diagram (VSD) model with three dimensions-exposure, sensitivity, and adaptability-was constructed to assess and compare the combined vulnerability to high-temperature and drought events, considering economic and social conditions. The results showed that (1) over the past 20 years, heat waves and droughts have increased in Shandong Province. The number of high-temperature events significantly increased in the west and decreased along the eastern coast, and drought change was characterized by an increase in the south and a decrease in the north. (2) The combined exposure to summer droughts and heat waves in Shandong Province showed a significant increasing trend (P < 0.05) at a rate of approximately 0.072/10a; the combined sensitivity significantly decreased (P < 0.05) at a rate of approximately 0.137/10a, and the combined adaptability continued to increase at a rate of approximately 0.481/10a. (3) The combined vulnerability to summer droughts and heat waves in the western inland area of Shandong Province was high and gradually decreased toward the southeastern coast. The overall decrease trend was nonsignificant with a decrease of approximately 0.126/10a, and the decline rate decreased from northwest to southeast, in which Laiwu, Yantai, Jinan, and Zibo cities exhibited a significant decreasing trend (P < 0.05). Although the compound vulnerability of Shandong Province has decreased insignificantly, the frequency of combined drought and heat wave events has increased, and the combined vulnerability will increase in the future.

Drought risk assessment on the eastern part of Indian peninsula-a study on Purulia district, West Bengal

This study focuses on measuring the spatial nature of drought risk which is conceived as the product of drought severity, drought vulnerability, and drought exposure in the Purulia district, located in the eastern part of the Indian peninsula. Drought severity is measured using the Standard Precipitation Index and drought vulnerability is calculated as the average condition of meteorological, hydrological, agricultural, and socio-economic drought. The drought types and drought exposure conditions are the outcome of multi-criteria analysis where the Fuzzy Analytical Hierarchy Process is used for assigning weights to the respective parameters and the Analytical Hierarchy Process is used for determining the class ranks. 31.46% of the total district area has registered moderate to high and high vulnerability to drought situations, while 16.57% of the entire district area has been found moderate to high and highly exposed to drought situations. Similarly, 39.39% of the district's total area is under a significant drought risk. Blocks like Barabazar (75.49%), Jhalda-I (71.85%), and Purulia-II (52.66%) have the majority of their area under extreme drought risk conditions. The modeled outcome of drought vulnerability was found significant while being tested with phenomena highly correlated to drought events, land surface temperature, and aridity index. The computed spatial profile of the districts' drought risk condition is of substantial help for the policymakers in preparing effective drought mitigation measures to restrict drought impacts reasonably.

Flood risk mapping and analysis using an integrated framework of machine learning models and analytic hierarchy process

In this study, a new approach of machine learning (ML) models integrated with the analytic hierarchy process (AHP) method was proposed to develop a holistic flood risk assessment map. Flood susceptibility maps were created using ML techniques. AHP was utilized to combine flood vulnerability and exposure criteria. We selected Quang Binh province of Vietnam as a case study and collected available data, including 696 flooding locations of historical flooding events in 2007, 2010, 2016, and 2020; and flood influencing factors of elevation, slope, curvature, flow direction, flow accumulation, distance from river, river density, land cover, geology, and rainfall. These data were used to construct training and testing datasets. The susceptibility models were validated and compared using statistical techniques. An integrated flood risk assessment framework was proposed to incorporate flood hazard (flood susceptibility), flood exposure (distance from river, land use, population density, and rainfall), and flood vulnerability (poverty rate, number of freshwater stations, road density, number of schools, and healthcare facilities). Model validation suggested that deep learning has the best performance of AUC = 0.984 compared with other ensemble models of MultiBoostAB Ensemble (0.958), Random SubSpace Ensemble (0.962), and credal decision tree (AUC = 0.918). The final flood risk map shows 5075 ha (0.63%) in extremely high risk, 47,955 ha (5.95%) in high-risk, 40,460 ha (5.02%) in medium risk, 431,908 ha (53.55%) in low risk areas, and 281,127 ha (34.86%) in very low risk. The present study highlights that the integration of ML models and AHP is a promising framework for mapping flood risks in flood-prone areas.

Land subsidence susceptibility mapping: comparative assessment of the efficacy of the five models

Land subsidence (LS) as a major geological and hydrological hazard poses a major threat to safety and security. The various triggers of LS include intense extraction of aquifer bodies. In this study, we present an LS inventory map of the Daumeghan plain of Iran using 123 LS and 123 non-LS locations which were identified through field survey. Fourteen LS causative factors related to topography, geology, hydrology, and anthropogenic characteristics were selected based on multi-collinearity test. Based on the results, five susceptibility maps were generated employing models and input data. The LS susceptibility models were evaluated and validated using the receiver operating characteristic (ROC) curve and statistical indices. The results indicate that the LS susceptibility maps produced have good accuracy in predicting the spatial distribution of LS in the study area. The result showed that the optimization models BA and GWO were better than the other machine learning algorithm (MLA). In addition, The BA model has 96.6% area under of ROC (AUROC) followed by GWO (95.8%), BART (94.5%), BRT (93.1%), and SVR (92.7%). The LS susceptibility maps formulated in our study can serve as a useful tool for formulating mitigation strategies and for better land-use planning.

Assessment of remote sensing-based indices for drought monitoring in the north-western region of Bangladesh

Drought is a widespread hazard that can tremendously affect the biodiversity, habitat of wild species, and ecosystem functioning and stability, especially in the dry region. Due to its geographic location, the north-western region of Bangladesh has a comparatively arid climate which is very much susceptible to drought occurrence and is marked as a red zone. Despite the growing evidence of the impact of drought on food security and ecosystem functioning, little effort has been paid to mitigate the drought in this region. The present study aimed to assess the drought condition of the north-western region of Bangladesh using earth observation techniques. For this purpose, Landsat data from 1990 to 2020 was used to determine various vegetation indices such as Normalized Difference Vegetation Index (NDVI), Water Index (NDWI), Moisture Index (NDMI) and Soil Adjusted Vegetation Index (SAVI), along with Land Surface Temperature (LST). Results show that the depletion of forests (2832 km2) and water bodies (6773 km2) resulted from the expansion of settlement (6563 km2) and agricultural land (1802 km2) for the period 1990-2020. Examination of the temporal changes of vegetation indices and LST showed that the values of all indices decreased while the LST increased. The negative correlation between NDVI value and LST indicates that the vegetation in our study was subject to drought-induced shocks. This study reveals the current situation of the vegetation health in the north-western region of Bangladesh in relation to the drought conditions. The findings of this study have practical implications for the policymakers in implementing necessary measures for agriculture, forests, water development, and economic zone planning.

Evaluating the climatic and socio-economic influences on the agricultural drought vulnerability in Jharkhand

Environmental hazards like drought lead to degrading food production and adversely impact the agro-economy. This study investigates the contributions of different climatic and socio-economic variables to agricultural drought in Jharkhand. The three primary criteria, i.e., exposure (E), sensitivity (S), and adaptive capacity (AC), responsible for agricultural drought vulnerability, were examined to identify the drought-prone areas. Long-term (1958-2020) gridded climatic datasets obtained from the Terra-climate global dataset, MODIS vegetation index dataset (MOD13Q1) for the years 2001-2020, different soil parameters obtained from the ISRIC global soil database and state agricultural portal of Jharkhand, and different socio-economic datasets obtained from census data (2011) provided by Govt. of India, were utilized for this study. Analytic Hierarchy Process (AHP) was used to estimate the weighted contribution of the indicator variables falling under each criterion (E, S, and AC), and three criteria index maps were generated. These separate maps were further integrated to generate the final vulnerability index map. Finally, the study area was categorized into different zones based on the drought vulnerability index value ranging from 0 to 1, according to the severity of the drought. It was observed that about 4.05%, 28.12%, and 37.07% of the total geographical area is very highly, highly, and moderately vulnerable to agricultural drought, respectively. Amongst the three primary criteria, exposure showed a significant positive correlation (R = 0.61), and sensitivity showed a strong positive correlation (R = 0.55) with vulnerability. The adaptive capacity was negatively correlated (R =  -0.75) with the vulnerability. However, putting equal weights to the variables to calculate the vulnerability, the exposure and sensitivity indicators showed a significant positive correlation with the vulnerability, with an R-value of 0.82 and 0.79, respectively. In contrast, the adaptive capacity showed a negative correlation with the vulnerability with R =  -0.75.

Site selection of check dams using geospatial techniques in Debre Berhan region, Ethiopia - water management perspective

Remote sensing and GIS technology were very helpful to determine an appropriate location of freshwater storage in Amhara, Ethiopia. The techniques were used to investigate the impact of lithology, surface geomorphology, slope parameters, drainage flow, drainage density, lineament density, land cover parameters on relief, and aerial and linear features and to understand their interrelationships. Morphometric parameters such as mean stream length (Lsm), stream length ratio (RL), bifurcation ratio (Rb), mean bifurcation ratio (Rbm), relief ratio (Rh), drainage density (Dd), stream frequency (Fs), drainage texture (Rt), form factor (Rf), circularity ratio (Rc), and elongation ratio (Re) were calculated. Spatial maps of morphometric parameters were produced by using AHP (analytical hierarchy process) of ArcGIS 10.3. Final priority map was generated by the overlay of those parameters with five categories of poor (16.6%), low (41.63%), moderate (29.61%), high (8.88%), and very high (3.28%) storage locations. The map showed that this study area belonged to the low to moderate storage location. The results exhibit precision-based assessment of the suitability for the dam construction sites of 6, 7, and 9 sub-basin zones. The outcome of this study strengthens the knowledge of geospatial analysis for water resources vulnerability and also allows policymakers in this drought-prone area to sustainably manage water supplies.

Evaluation of Drought Vulnerability of Maize and Influencing Factors in Songliao Plain Based on the SE-DEA-Tobit Model

Rain-fed agriculture is easily affected by meteorological disasters, especially drought. As an important factor of risk formation, actively carrying out agricultural drought vulnerability assessments is conducive to improving food security and reducing economic losses. In this study, an SE-DEA model with regional exposure and drought risk as input factors and the maize yield reduction rate and drought-affected area as output factors is established. The aim is to evaluate and zone the drought vulnerability of the maize belt in the Songliao Plain. The results show the following: (1) From 2000 to 2019, the drought vulnerability of maize showed a fluctuating increasing trend. The vulnerability in Harbin and central Jilin Province is high, which is extremely unfavorable for maize production. (2) Comparing the historical disaster data with the drought vulnerability map generated using the SE-DEA model, it could be found that the results obtained using the SE-DEA model are reliable. (3) The Tobit model shows that the proportion of the effective irrigated area is more important to alleviate vulnerability. For drought vulnerability zoning using a cluster analysis, we suggest that regulated deficit irrigation should be actively developed in high-vulnerability areas to ensure maize yield while improving water efficiency. The results of this study can provide a basis for the development of drought mitigation and loss reduction strategies, and they provide new ideas for future research.

Drought vulnerability and risk assessment in India: Sensitivity analysis and comparison of aggregation techniques

Long term drought management requires proper assessment and characterization of drought hazard, vulnerability and risk. This is particularly important for an agriculture-dependent, highly-populated, developing country such as India. However, the regulation of drought vulnerability and drought risk assessment in the country is mostly region-specific and ad-hoc, considering only a limited number of vulnerability indicators. In this study, a comprehensive, fine-resolution, country-wide drought risk assessment is carried out considering drought hazard in a multivariate framework, and using reliable drought vulnerability indicators that account for exposure, sensitivity and adaptive capacity. Further, multiple aggregation techniques including subjective, objective and comprehensive methods are employed for vulnerability assessment, and their performance assessed and compared. The Analytic Hierarchy Process (AHP)+Entropy and TOPSIS methods, which are comprehensive aggregation techniques are found to be better performing, TOPSIS being the most robust method. A bivariate choropleth map based on the TOPSIS-derived drought vulnerability shows regions of Punjab, Haryana, Uttar Pradesh and Tamil Nadu subjected to drought hazard-driven risk, while risk in other regions such as Rajasthan, parts of Central India, Orissa and parts of Maharashtra are driven more by drought vulnerability. Parts of Western Rajasthan, Vidharbha, North-East India, Chattisgarh, Tamil Nadu and Karnataka are under severe drought risk resulting from an interplay of hazard and vulnerability. Irrigation index, water body fraction, and groundwater availability are found to be the most significant indicators for assessing drought vulnerability in India. The above findings can aid decision makers and government bodies to plan region-specific line of action for building drought resilience.

Spatiotemporal evaluation of drought trend during 1979-2019 in seven climatic zones of Bangladesh

Evaluation of drought is essential and useful to eradicate climate change impact. Therefore, this study aims to explore the spatiotemporal drought intensity trend in seven climatic zones of Bangladesh during 1979–2019. Mann-Kendall trend test and Standardized Precipitation Evapotranspiration Index (SPEI) are employed to identify drought trend and status, whereas spatial visualization is checked through Inverse Distance Weighting Interpolation. The study's findings emphasize the decreasing rate of SPEI in all climatic zones except the south-eastern zone, which is > 0.0065, >0.007, >0.0128, and >-0.0001 for SPEI 09 12, 24, and 06, respectively. Furthermore, the northern region has the highest value in SPEI in some periods with the highest decrease rate in SPEI 06, SPEI 09, SPEI 12 demonstrates greater drought responsibilities. The Barisal (.>-3.75), Rangpur (>-3.65), Dinajpur ((>-3.00), Rajshahi (>-4.35), Bogra (>-4.50), Ishurdi (>-3.45), Faridpur (>-4.30) and Madaripur (>-2.10) found under extreme drought-prone climatic zone. Thus, the study recommends taking initiatives and management for water resources to adopt mitigation planning for drought-prone climatic zones.

Drought Vulnerability Assessment Using Geospatial Techniques in Southern Queensland, Australia

In Australia, droughts are recurring events that tremendously affect environmental, agricultural and socio-economic activities. Southern Queensland is one of the most drought-prone regions in Australia. Consequently, a comprehensive drought vulnerability mapping is essential to generate a drought vulnerability map that can help develop and implement drought mitigation strategies. The study aimed to prepare a comprehensive drought vulnerability map that combines drought categories using geospatial techniques and to assess the spatial extent of the vulnerability of droughts in southern Queensland. A total of 14 drought-influencing criteria were selected for three drought categories, specifically, meteorological, hydrological and agricultural. The specific criteria spatial layers were prepared and weighted using the fuzzy analytical hierarchy process. Individual categories of drought vulnerability maps were prepared from their specific indices. Finally, the overall drought vulnerability map was generated by combining the indices using spatial analysis. Results revealed that approximately 79.60% of the southern Queensland region is moderately to extremely vulnerable to drought. The findings of this study were validated successfully through the receiver operating characteristics curve (ROC) and the area under the curve (AUC) approach using previous historical drought records. Results can be helpful for decision makers to develop and apply proactive drought mitigation strategies.

A Novel Hybrid Model for Developing Groundwater Potentiality Model Using High Resolution Digital Elevation Model (DEM) Derived Factors

The present work aims to build a unique hybrid model by combining six fuzzy operator feature selection-based techniques with logistic regression (LR) for producing groundwater potential models (GPMs) utilising high resolution DEM-derived parameters in Saudi Arabia’s Bisha area. The current work focuses exclusively on the influence of DEM-derived parameters on GPMs modelling, without considering other variables. AND, OR, GAMMA 0.75, GAMMA 0.8, GAMMA 0.85, and GAMMA 0.9 are six hybrid models based on fuzzy feature selection. The GPMs were validated by using empirical and binormal receiver operating characteristic curves (ROC). An RF-based sensitivity analysis was performed in order to examine the influence of GPM settings. Six hybrid algorithms and one unique hybrid model have predicted 1835–2149 km2 as very high and 3235–4585 km2 as high groundwater potential regions. The AND model (ROCe-AUC: 0.81; ROCb-AUC: 0.804) outperformed the other models based on ROC’s area under curve (AUC). A novel hybrid model was constructed by combining six GPMs (considering as variables) with the LR model. The AUC of ROCe and ROCb revealed that the novel hybrid model outperformed existing fuzzy-based GPMs (ROCe: 0.866; ROCb: 0.892). With DEM-derived parameters, the present work will help to improve the effectiveness of GPMs for developing sustainable groundwater management plans.

Analysis of Smallholders’ Livelihood Vulnerability to Drought across Agroecology and Farm Typology in the Upper Awash Sub-Basin, Ethiopia

Assessing the magnitude of smallholder farmers’ livelihood vulnerability to drought is an initial step in identifying the causal factors and proposing interventions that mitigate the impacts of drought. This study aimed to assess smallholders’ livelihood vulnerability to the drought in the upper Awash sub-basin, Ethiopia. Household (HH) and climate data were used for indicators related to sensitivity, exposure, and adaptive capacity that define vulnerability to drought. The vulnerability of farmers’ livelihood to drought was compared among the studies agroecological zone (AEZ) and farm typologies. The result illustrated a diverse magnitude of vulnerability index (VI) ranging from −1.956 to −4.253 for AEZ. The highest magnitude of VI was estimated for livelihood in the lowland AEZ, while the lowest magnitude of VI was estimated in midland AEZ. This could be accounted for by the fact that lowland farmers shown the highest exposure (0.432) and sensitivity (0.420) and the lowest adaptive capacity (0.288). A closer look at farmers’ livelihood typology, in each of the AEZ, showed substantial diversity of farmers’ livelihood vulnerability to drought, implying potential aggregations at AEZ. Accordingly, the vulnerability index for livestock and on-farm-income-based livelihood and marginal and off-farm-income-based livelihood typologies were higher than the intensive-irrigation-farming-based smallholders’ livelihood typology. Based on the result, we concluded that procedures for smallholders’ livelihood resilience-building efforts should better target AEZ to prioritize the focus region and farmers’ livelihood typology to tailor technologies to farms. Although the result emphasizes the importance of irrigation-based livelihood strategy, the overall enhancement of farmers adaptive capacity needs to focus on action areas such as reducing the sensitivity and exposure of the households, improving farmers usage of technologies, diversify farmers’ livelihood options, and, hence, long-term wealth accumulation to strengthen farmers’ adaptive capacity toward drought impacts.

Gendered Perspectives on Climate Change Adaptation: A Quest for Social Sustainability in Badlagaree Village, Bangladesh

Climate change effects cause major socioeconomic challenges for marginalized groups, particularly women, in Bangladesh. Specifically, drought increases resource scarcity, causing social problems that impact women, which can be described as the gendered sociocultural construction of vulnerabilities. Given this constructed dimension of gender-based vulnerability, this paper explores the effects of drought on marginalized women in one local case study, namely Badlagaree village in Gaibandha district, Bangladesh. To examine this linkage, we collected qualitative primary data using ethnographic research methods, primarily focus group discussions. Findings show that gender-based vulnerability is increasing due to growing drought effects, including agricultural production loss. Marginalized women, because of their gender identity, encounter these drought effects through unemployment, food insecurity, illiteracy, early marriage, dowry costs and violence. While further national-scale research is required, this paper argues that in order to overcome such gender-based vulnerability, current development policies, social programs, and adaptation strategies should better recognize such social dynamics. Further, a gender-specific understanding requires incorporation into adaptation policies through greater collaborative governance as an important prerequisite for sustainability.

Agricultural drought risk assessment of Northern New South Wales, Australia using geospatial techniques

Droughts are recurring events in Australia and cause a severe effect on agricultural and water resources. However, the studies about agricultural drought risk mapping are very limited in Australia. Therefore, a comprehensive agricultural drought risk assessment approach that incorporates all the risk components with their influencing criteria is essential to generate detailed drought risk information for operational drought management. A comprehensive agricultural drought risk assessment approach was prepared in this work incorporating all components of risk (hazard, vulnerability, exposure, and mitigation capacity) with their relevant criteria using geospatial techniques. The prepared approach is then applied to identify the spatial pattern of agricultural drought risk for Northern New South Wales region of Australia. A total of 16 relevant criteria under each risk component were considered, and fuzzy logic aided geospatial techniques were used to prepare vulnerability, exposure, hazard, and mitigation capacity indices. These indices were then incorporated to quantify agricultural drought risk comprehensively in the study area. The outputs depicted that about 19.2% and 41.7% areas are under very-high and moderate to high risk to agricultural droughts, respectively. The efficiency of the results is successfully evaluated using a drought inventory map. The generated spatial drought risk information produced by this study can assist relevant authorities in formulating proactive agricultural drought mitigation strategies.

Assessment of Vulnerability to Drought Disaster in Agricultural Reservoirs in South Korea

Drought is a natural disaster affecting agriculture worldwide. Drought mitigation and proactive response require a comprehensive vulnerability mapping approach considering various factors. This study investigates the vulnerability to agricultural drought in South Korea based on exposure, sensitivity, and adaptability. The evaluation of agricultural drought factors yielded 14 items, which are categorized into meteorological, agricultural reservoir, social, and adaptability factors. Each item is assigned a weight using the analytical hierarchy process (AHP). We analyzed vulnerability to drought disaster in agricultural reservoirs, and generated vulnerability maps by applying the vulnerability framework for climate change. The generated map was divided into four categories based on drought vulnerability: A (Very high), B (High), C (Moderate), and D (Low). The weights for the meteorological (0.498), agricultural reservoir (0.286), social (0.166), and adaptability (0.05) factors were obtained using AHP. The rating frequencies were 41.91%, 19.76%, 9.58%, and 5.39% for A, B, C, and D, respectively. The western region is extremely vulnerable to meteorological and agricultural reservoir factors, whereas the eastern region is more vulnerable to adaptability. The results of this study visually represent agricultural drought and can be used for evaluating regional drought vulnerability for assisting preemptive drought responses to identify and support drought-prone areas.

An inverted U-shaped curve relating farmland vulnerability to biological disasters: Implications for sustainable intensification in China

Sustainable farmland intensification is necessary in order to harmonize relationships between food security, socioeconomic development, and ecological civilization. However, the degradation of farmland sustainability because of biological disasters represents a major challenge if we are to achieve this intensification. Our understanding of farmland vulnerability to biological disasters (FVBD) remains relatively rudimentary and subjective, limiting its effectiveness as a tool for farmland sustainability analysis. Limited research has also been carried out on FVBD changes taking into account human decisions on farmland use. The aim of this study is to achieve a novel understanding of FVBD change and its implications for sustainable intensification using evidence from Chinese farmland use. A theoretical framework based on an inverted U-shaped curve that depicts FVBD as well as an assessment framework for FVBD were established using induced substitution of agricultural production. Across China and considering 15 provincial districts with scarce farmland, the relationship between FVBD and socio-economic development was identified as consistent with an inverted U-shaped curve at both national and provincial levels. FVBD values in 2016 across Southern China, on the Huang-Huai-Hai Plain, and on the middle-lower Yangtze Plain were 45.44, 40.58, and 37.22, respectively. These values also decreased in provinces on the middle-lower Yangtze Plain between 1995 and 2016, but increased markedly across provinces in Southern China and on the Huang-Huai-Hai Plain. Contributions to FVBD changes during stages of growth and decline were also analyzed between 1995 and 2016. An inverted U-shaped curve was effective in investigating the responses of farmland sustainability to a range of alternative future socioeconomic development pathways. Thus, in the Chinese settings, a typical country with scarce farmland, policies on FVBD control are essential if we are to promote sustainable farmland intensification. The findings of this work are important and present us with a new way to understand FVBD from a human perspective.

Drought Stress and Livelihood Response Based on Evidence from the Koshi River Basin in Nepal: Modeling and Applications

Drought vulnerability analysis at the household level can help people identify livelihood constrains and potential mitigation and adaptation strategies. This study used meteorological and household level data which were collected from three different districts (Kavrepalanchowk, Sindhuli, and Saptari) in the Koshi River Basin of Nepal to conduct a drought vulnerability analysis. We developed a model for assessing drought vulnerability of rural households based on three critical components, i.e., exposure, sensitivity, and adaptive capacity. The results revealed that Saptari (drought vulnerability index, 0.053) showed greater vulnerability to drought disasters than Kavrepalanchowk (0.014) and Sindhuli (0.007). The most vulnerable district (Saptari) showed the highest exposure, the highest sensitivity, and the highest adaptive capacity. Kavrepalanchowk had the middle drought vulnerability index with middle exposure, low sensitivity, and middle adaptive capacity. Sindhuli had the lowest vulnerability with the lowest exposure, the lowest sensitivity, and the lowest adaptive capacity. On the basis of the results of the vulnerability assessment, this paper constructed livelihood adaptation strategies from the perspectives of households, communities, and the government. Many households in Kavrepalanchowk and Sindhuli significantly depend on agriculture as their main source of income. They need to implement some strategies to diversify their sources of income. In addition, the most important livelihood adaptation strategy for Saptari is improving water conservancy facilities to facilitate the allocation of water.