Sociohydrology aims to deliver user-inspired solutions to water challenges, often through model-based understanding and simulation of local realities. However, sociohydrological modeling methodologies used to understand such complex human-water systems remain difficult to apply to many real-world case studies. Sociohydrological model predictions at daily to annual time scales of decision- making remain a challenge due to often difficult-to-acquire social sciences data, and missing or unknown feedbacks that lead to model structural errors, among other issues. This paper assesses and reduces model structural deficiencies of a smallholder sociohydrological (SH) model when applied to a case study of small-scale agricultural production in India, where variables from a farmer survey help alleviate structural deficiencies. A structural error model is proposed based on a regression model of nonlinear projection of the these variables to a Kernel space, called Kernel Principal Component Analysis (KPCA) based model. Based on this, a hybrid model that is a sum of the SH model and the structural error model is proposed. It offers significantly better yield predictions on ‘unseen’ (to the model) survey data than the SH only model. The hybrid model also performs better on yield prediction than a KPCA model alone, which predicts yields without any SH dynamics. This is because the hybrid model combines the structural error model that learns from the spatial pattern of observed yields with the temporal dynamics explained by the SH model alone. The results indicate that the structure of the SH model can be improved by further incorporation of irrigation and adaptive behaviour of farmers.

Background: There is increasing recognition of the complexity underlying WASH conditions in developing countries. This article explores the complexity by assessing the vulnerability of a specific area to poor WASH conditions using a qualitative approach. Methods: We present our findings for the district of East Sumba in Indonesia. This area is known as one of the poorest regions in Indonesia with inadequate WASH services, indigenous belief that hinder the practice of WASH-related behaviours, and has a high rate of children malnutrition. All the factors that contribute to poor WASH conditions were discussed through the lens of the Financial, Institutional, Environmental, Technological, and Social (FIETS) framework. We then summarised the factors and visualized the “system” using a mind map which shows how factors are interconnected and helps to find the root causes of poor WASH conditions. Results: There are three main challenges that inhibit the improvement of WASH conditions in this area: inadequate institutional capacity, water scarcity, and poor socio-economic conditions. We found that a village leader is the most important actor who influences the sustainability of WASH services in this area and healthcare workers are influential WASH promoters. This study also shows how culture shapes people’s daily lives and institution performance, and influences the current WASH conditions in East Sumba. The mind map shows there is an overlap and interconnection between FIEST aspects and WASH conditions in the study area. Conclusion: WASH conditions are influenced by many factors and are often interconnected with each other. Understanding this complexity is necessary to improve WASH conditions and sustain adequate WASH services in developing countries. Finally, WASH interventions have to be considerate of the prevailing cultural practices and should involve multidisciplinary stakeholders.

It is argued that there are interconnected and dynamic factors that influence the sustainability of water, sanitation, and hygiene (WASH) services in developing countries. Five sustainability factors are often mentioned by literature: financial, institutional, environmental, technical, and social (FIETS) factors. This article aims to understand the interaction of those five sustainability factors in the context of WASH services in Indonesia. A system approach, in the form of a “modified” causal loop diagram, was utilized to analyze this interaction. The strength of influence from one factor to others were obtained from small surveys of 16 WASH practitioners and experts from international and national non-governmental organizations (NGOs) based in Indonesia and national government institutions related to WASH. It was found that institutional factor is the “leverage” factor, i.e., the most influential and least dependent, in the WASH services system in Indonesia. It means that WASH institutional strengthening is necessary to sustain WASH services in Indonesia. Furthermore, the most important feedback loop is social–WASH services. This depicts the importance of the bi-directional effect of WASH services and the social conditions of the community, i.e., the more supportive the community is, the higher the likelihood of the sustainability of WASH services, and then positively influence back the social conditions of the community. Moreover, the relationship between factors varies across context or location. Finally, this paper shows that the sustainability of WASH services involves complex interactions of the sustainability factors and understanding these interactions is critical to sustaining the WASH services or program in rural Indonesia.