A two-stage approach for assessment of distributional impacts in model-based delta planning: exploration of plausible inequality patterns and justice-based evaluation of policies

Author(s):  
Bramka Arga Jafino ◽  
Jan Kwakkel

<p>Climate-related inequality can arise from the implementation of adaptation policies. As an example, the dike expansion policy for protecting rice farmers in the Vietnam Mekong Delta in the long run backfires to the small-scale farmers. The prevention of annual flooding reduces the supply of natural sediments, forcing farmers to apply more and more fertilizers to achieve the same yield. While large-scale farmers can afford this, small-scale farmers do not possess the required economics of scale and are thus harmed eventually. Together with climatic and socioeconomic uncertainties, the implementation of new policies can not only exacerbate existing inequalities, but also induce new inequalities. Hence, distributional impacts to affected stakeholders should be assessed in climate change adaptation planning.</p><p>In this study, we propose a two-stage approach to assess the distributional impacts of policies in model-based support for adaptation planning. The first stage is intended to explore potential inequality patterns that may emerge due to combination of new policies and the realization of exogenous scenarios. This stage comprises four steps: (i) disaggregation of performance indicators in the model in order to observe distributional impacts, (ii) performance of large-scale simulation experimentation to account for deep uncertainties, (iii) clustering of simulation results to identify distinctive inequality patterns, and (iv) application of scenario discovery tools, in particular classification and regression trees, to identify combinations of policies and uncertainties that lead to a specific inequality pattern.</p><p>In the second stage we attempt to asses which policies are morally preferable with respect to the inequality patterns they generate, rather than only descriptively explore the patterns which is the case in the previous stage. To perform a normative evaluation of the distributional impacts, we operationalize five alternative principles of justice: improvement of total welfare (utilitarianism), prioritization of worse-off actors (prioritarianism), reduction of welfare differences across actors (two derivations: absolute inequality and envy measure), and improvement of worst-off actor (Rawlsian difference). The different operationalization of each of these principles forms the so-called social welfare function with which the distributional impacts can be aggregated.</p><p>To test this approach, we use an agricultural planning case study in the upper Vietnam Mekong Delta. Specifically, we assess the distributional impacts of alternative adaptation policies in the upper Vietnam Mekong Delta by using an integrated assessment model. We consider six alternative policies as well as uncertainties related to upstream discharge, sediment supply, and land-use change. Through the first stage, we identify six potential inequality patterns among the 23 districts in the study area, as well as the combinations of policies and uncertainties that result in these types of patterns. From applying the second stage we obtain complete rankings of alternative policies, based on their performance with respect to distributional impacts, under different realizations of scenarios. The explorative stage allows policy-makers to identify potential actions to compensate worse-off actors while the normative stage helps them to easily rank alternative policies based on a preferred moral principle.</p>

Author(s):  
Lu Chen ◽  
Handing Wang ◽  
Wenping Ma

AbstractReal-world optimization applications in complex systems always contain multiple factors to be optimized, which can be formulated as multi-objective optimization problems. These problems have been solved by many evolutionary algorithms like MOEA/D, NSGA-III, and KnEA. However, when the numbers of decision variables and objectives increase, the computation costs of those mentioned algorithms will be unaffordable. To reduce such high computation cost on large-scale many-objective optimization problems, we proposed a two-stage framework. The first stage of the proposed algorithm combines with a multi-tasking optimization strategy and a bi-directional search strategy, where the original problem is reformulated as a multi-tasking optimization problem in the decision space to enhance the convergence. To improve the diversity, in the second stage, the proposed algorithm applies multi-tasking optimization to a number of sub-problems based on reference points in the objective space. In this paper, to show the effectiveness of the proposed algorithm, we test the algorithm on the DTLZ and LSMOP problems and compare it with existing algorithms, and it outperforms other compared algorithms in most cases and shows disadvantage on both convergence and diversity.


2021 ◽  
Vol 17 (1) ◽  
pp. 342-357
Author(s):  
Julie Gwendolin Zaehringer ◽  
Peter Messerli ◽  
Markus Giger ◽  
Boniface Kiteme ◽  
Ali Atumane ◽  
...  

Land ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 111
Author(s):  
Haixia Wu ◽  
Hantao Hao ◽  
Hongzhen Lei ◽  
Yan Ge ◽  
Hengtong Shi ◽  
...  

The excessive use of fertilizer has resulted in serious environmental degradation and a high health cost in China. Understanding the reasons for the overuse of fertilizer is critical to the sustainable development of Chinese agriculture, and large-scale operation is considered as one of the measures to deal with the excessive fertilizer use. Under the premise of fully considering the resource endowment and heterogeneity of large-scale farmers and small-scale farmers in production and management, different production decision-making frameworks were constructed. Based on the 300 large-scale farmers and 480 small-scale farmers in eight provinces of northern China wheat region, we analyzed the optimal fertilizer use amount and its deviation as well as the influencing factors of small-scale and large-scale farmers, then further clarified whether the development of scale management could solve the problem of excessive fertilizer use. The empirical results show that: (1) both small-scale farmers and large-scale farmers deviated from the optimal fertilizer application amount, where the deviation degree of optimal fertilizer application of small-scale farmers is significantly higher than that of large-scale farmers, with a deviation degree of 35.43% and 23.69% for small and large scale farmers, respectively; (2) not all wheat growers in North China had the problem of excessive use of chemical fertilizer, as the optimal level of chemical fertilizer application in Heilongjiang and Inner Mongolia are 346.5 kgha−1 and 335.25 kgha−1, while the actual fertilizer use amount was 337.2 kgha−1 and 324.6 kgha−1, respectively; and (3) the higher the risk aversion level, farmers tended to apply more fertilizer to ensure grain output. Therefore, increasing farm size should be integrated into actions such as improving technological innovation and providing better information transfer to achieve the goal of zero-increase in Chinese fertilizer use.


Author(s):  
Rui Qiu ◽  
Yongtu Liang

Abstract Currently, unmanned aerial vehicle (UAV) provides the possibility of comprehensive coverage and multi-dimensional visualization of pipeline monitoring. Encouraged by industry policy, research on UAV path planning in pipeline network inspection has emerged. The difficulties of this issue lie in strict operational requirements, variable flight missions, as well as unified optimization for UAV deployment and real-time path planning. Meanwhile, the intricate structure and large scale of the pipeline network further complicate this issue. At present, there is still room to improve the practicality and applicability of the mathematical model and solution strategy. Aiming at this problem, this paper proposes a novel two-stage optimization approach for UAV path planning in pipeline network inspection. The first stage is conventional pre-flight planning, where the requirement for optimality is higher than calculation time. Therefore, a mixed integer linear programming (MILP) model is established and solved by the commercial solver to obtain the optimal UAV number, take-off location and detailed flight path. The second stage is re-planning during the flight, taking into account frequent pipeline accidents (e.g. leaks and cracks). In this stage, the flight path must be timely rescheduled to identify specific hazardous locations. Thus, the requirement for calculation time is higher than optimality and the genetic algorithm is used for solution to satisfy the timeliness of decision-making. Finally, the proposed method is applied to the UAV inspection of a branched oil and gas transmission pipeline network with 36 nodes and the results are analyzed in detail in terms of computational performance. In the first stage, compared to manpower inspection, the total cost and time of UAV inspection is decreased by 54% and 56% respectively. In the second stage, it takes less than 1 minute to obtain a suboptimal solution, verifying the applicability and superiority of the method.


Author(s):  
Chelsea Klinke ◽  
Gertrude Korkor Samar

The contemporary global agrarian regime has altered the patterns of food production, circulation, and consumption. Its efforts towards food security vis-á-vis capitalist modes of mechanized cultivation have produced large-scale climatic and socioeconomic ramifications, including the dispossession of small-scale farmers from their lands and positions in market value-chains. In an effort to improve the dynamics of contemporary agro-food systems, food practitioners and scholars are engaging in critical analyses of land-grabbing, the feminization of agriculture, extractive-led development, and more. However, we argue that there is a gap between Food Studies scholarship and community-based transformative engagement. To support social justice frameworks, our paper calls for an academic paradigm shift wherein learner-centered experiential classrooms bridge academic-public divides and enhance student learning. Through a case-study of urban farming in Calgary, we also explore topics in place-based learning and participatory approaches that acknowledge and integrate Indigenous ways of knowing, doing, being, and connecting. Our paper provides strategies for supporting local food systems through activist scholarship, capacity building of leadership and technical skills in advanced urban farming, and intercultural relationship building. We conclude by evaluating the success of our approach, presenting potential benefits and challenges, and providing recommendations for best practices in food scholarship to support transformative change.


Author(s):  
Abiodun E. Obayelu

Agriculture is in critical state in Nigeria with domestic food production being less than the growing population. The chapter analyzes the ongoing transformation of subsistence agriculture to commercial in Nigeria and the attendant effects of large-scale land acquisition on small-scale farmers. It uses both theoretical and empirical research designs with direct interviews of relevant stakeholders and case studies. It reviews past and present policies and programs aimed at transforming agriculture from subsistence to commercial in Nigeria. The results reveal that large-scale land acquisition and farming is not new in Nigeria. Acquisitions of land by foreigners has always been with the help and consent of government, unlike the case when it involves indigenous investors. Acquisitions have in most cases been characterized by conflicts between the landowners or tillers and investors. To transition successfully from subsistence to commercial agriculture, there is a need for strong collective actions between the depraved land owners, government, and investors.


2019 ◽  
Vol 31 (3) ◽  
pp. 290-298 ◽  
Author(s):  
Gunilla Hallenberg Ström ◽  
Hanna Björklund ◽  
Andrew C. Barnes ◽  
Chau Thi Da ◽  
Nguyen Huu Yen Nhi ◽  
...  

In India Coconut is the major plantation crop in the states of Tamilnadu, kerala, Karnataka, Kongan region of Maharastra and Andaman and Nicobar Islands for entire seasons. Copra is the major product from the coconut cultivation earning higher income of small and medium livelihoods. The approval of copra quality is mainly based on how well the copra got dried. Open drying or other conventional methods is the major process of making copra. In adverse weather condition, rainy season the drying process will be very challenging. Many dryers are made and used currently was affordable to medium and large scale copra producers. Those dryers also having limitations in size, high initial cost and nature dependency. There is very few attempt made for Small and individual household copra producers. This paper mainly focuses on how to dry-up the copra in all climate conditions. An electric handy dryer is designed to dry up the coconut copra and other grains. It mainly helps the small scale farmers as a handy dryer unit to dry-up the copra, those who are using coconut as a way of income. Based on the experiments conducted the electric dryer removed high moisture content than forced convection and direct sun dryers.


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