Technical models are useful tool to address epistemic uncertainties but often fall short of attending to other types of uncertainty that characterize complex water challenges. It is unclear if and how they might be repositioned as a more deliberative tool to help deal with the many uncertainties related to problem framing, uncertain future conditions, and likely intervention effects at various scales. Through the case of a multi-stakeholder water quality project in East Java, Indonesia, this paper explores how technical systems modeling can be used to support consensus-building regarding the characterization of water pollution problems and adjacent policy goals, both in the use of outputs and in the process of model-making and attendant deliberation. The water quality model combines mapped terrestrial pollution source estimates with rainfall-runoff and pollution transport and fate process models to estimate localized, regional, and basin-wide impacts of various source-reduction scenarios on water quality. By visually identifying pollution source concentrations and illustrating estimated impacts of alternative strategies, the model offers a useful visual tool on which to anchor reframing discussions and scenario-building. In this way, the case demonstrates how modeling can be repositioned as an invitation for planners to simultaneously deliberate alternative problem structures alongside interventions to better deal with uncertainties inherent to water resources management.

Often, individual, communal, regional, or even national conflicts arise when water resources are shared and used. For equitable water-sharing strategies to be implemented, adequate collective action is required to allocate water – not limited to, but specifically in irrigation systems. In this research, we develop an Advanced Irrigation-Related Agent-Based Model (AIRABM) to explore issues of unequal access to water in relation to water use on farm and system levels. By simulating farmer activities and system management decisions within an irrigation system, our research aims to explore farmland dynamics in response to different levels of decision-making according to water availability. We incorporate both individual and collective decision-making processes to explore patterns in farmers’ yields and the dynamics of farmlands. Our results show that (1) within a prevailing trend of increasing yields for higher river discharge and gate capacity, (2) the influence of water availability is characterized by nonlinear changes in yields in response to variations in river discharge and gate capacity, revealing thresholds and tipping points, with (3) strategies for water redistribution partially alleviate inequitable water allocation between upstream and downstream farmers, although considerable variation persists in individual farmers’ and system-wide harvest outcomes. The AIRABM emphasizes individual and collective decision-making processes, encapsulating the uncertainty stemming from water availability and harvests of individual farmers. The modeling framework serves as a valuable tool to explore cooperative approaches in shared (water) resource management. Our findings provide meaningful suggestions to study and promote communication and (conditional) cooperation measures between farmers and management, thereby enhancing the effectiveness of irrigation water distribution.

Early Southern Mesopotamia shows a complex history of expansion of (irrigated) farming in relation to urban developments and changing landscapes. As a first step to study expanding irrigated farming system, an irrigation-related agent-based model was developed to explore farm(land)s and irrigation systems in relation to decision-making processes, both of farms and their farmlands (an agriculture unit) and collective decision-making processes for irrigation system management—especially sharing water between farms. The decision-making processes include options to move farms, expand the system, or start a new system, as these would be options available for Mesopotamian farmers as well. In this text, we report how model parameters contribute to the generation of various patterns of yields and expansion of farms and system. Additionally, the Gini coefficient (based on yields) is applied to estimate levels of inequality among farmers. Our results show how (1) human decision-making determines the level of influence of and benefits for farms, as well as the overall irrigation system; (2) Gini values effectively capture the degree of inequality in yields among farms based on water availability; and (3) our model is a suitable base for further study, by incorporating additional agents into the irrigation system and expanding the spatial–temporal scales of the irrigated landscapes, to reach a more comprehensive understanding of the evolutionary dynamics of irrigation systems in Southern Mesopotamia.

Smallholder farmers (SFs) are cornerstone actors in eradicating poverty and hunger. Companies have recently focused on SFs as potential customers and suppliers. Several hindrances yet prevent SFs to be commercially viable actors. In this respect, sustainable business models (SBMs) bring opportunities for companies to increase profit, improve SFs' livelihoods, and promote environmental sustainability. Recognizing these opportunities, the Dutch company aQysta provides the Barsha pump (BP) as a sustainable irrigation solution for SFs. The challenges for BP adoption that remain for SFs illustrate that there is still limited understanding of how SBMs can support companies in engaging with SFs. To expand this understanding, we conducted a multiple-case analysis of 10 organizations providing SF-tailored products and/or services. Based on this analysis, we have drawn lessons for aQysta (and similar companies) to improve the BP's value proposition and we elaborate on the implications of this study for other organizations engaging commercially with SFs.

Droughts and changing rainfall patterns due to natural climate variability and climate change, threaten the livelihoods of Malawi's smallholder farmers, who constitute 80% of the population. Provision of seasonal climate forecasts (SCFs) is one means to potentially increase the resilience of rainfed farming to drought by informing farmers in their agricultural decisions. Local knowledge can play an important role in improving the value of SCFs, by making the forecast better-suited to the local environment and decision-making. This study explores whether the contextual relevance of the information provided in SCFs can be improved through the integration of farmers’ local knowledge in three districts in central and southern Malawi. A forecast threshold model is established that uses meteorological indicators before the rainy season as predictors of dry conditions during that season. Local knowledge informs our selection of the meteorological indicators as potential predictors. Verification of forecasts made with this model shows that meteorological indicators based on local knowledge have a predictive value for forecasting dry conditions in the rainy season. The forecast skill differs per location, with increased skill in the Southern Highlands climate zone. In addition, the local knowledge indicators show increased predictive value in forecasting locally relevant dry conditions, in comparison to the currently-used El Niño-Southern Oscillation (ENSO) indicators. We argue that the inclusion of local knowledge in the current drought information system of Malawi may improve the SCFs for farmers. We show that it is possible to capture local knowledge using observed station and climate reanalysis data. Our approach could benefit National Meteorological and Hydrological Services in the development of relevant climate services and support drought-risk reduction by humanitarian actors.

Improved water management is an important strategy to support smallholder farming, and thus to foster food security and improved livelihoods. Within this strategy, technologies like water pumps, especially those operating on renewable energies, are key, as they are more environmentally sound and affordable alternatives. Their successful and sustained uptake is a complex process—largely dependent on the adopter and its surrounding context—usually overlooked by traditional linear technology-transfer approaches. By means of Q methodology, we explored cross-cultural discourses around the adoption of the Barsha pump (BP), a self-reliant hydro-mechanical device that does not require any external input than flowing water to operate. We administered the method to 43 (non-)farmer respondents linked to Nepali and Indonesian smallholder farming systems. We identified three relevant discourses, one of them bipolar in nature. These three groups accounted for 39, 36, and 28% of the total explained variance of our study. The first one identified BP's potential early adopters. The second discourse embodied the (stereotypical) highly dependent smallholder. The last one characterized (contrasting) views around the BP as an enabler of potential service-oriented business models to achieve wellbeing. These results reflect the need for a shift of mindset toward new ways of understanding technological change in smallholder settings. On the one side, simplistic one-size-fits-all models cannot connect to the diversity of issues and opinions as we found. On the other side, it is virtually impossible to produce tailored solutions to satisfy each of those individual realities. We propose possible adoption pathways that may lead to the exploration of innovative and adaptable business models that serve the diversity of smallholder farming needs more effectively.

On the basis of a data set from four research sites over the course of three agricultural years (2006/2007, 2012/2013, 2016/2017), this article empirically assesses the relations between land tenure security and smallholder farms’ crop production in Rwanda. We show that the general assumption that secure land tenure improves farm level harvests, is not found for smallholder farms in Rwanda. We defined a farmland tenure security index based on plausible threats as conveyed by smallholder farmers at each research site. Our findings indicate that the harvest of main crops did neither statistically correlate with this index, nor show differences from the mean at all research sites. Instead, factors mainly related to the ongoing crop intensification program, though threatening tenure security, contributed to the increase of small farm harvests. Lower land tenure security did not affect farmers satisfaction of the crop program, most of them claiming that in the end what matters most is that their harvests continue to increase. Therefore, in Rwanda, a new wave of agriculture strategizing contributes to increasing small farms’ harvest of prioritized crops and decreasing farm land tenure security simultaneously.

An Advanced Irrigation-Related Agent-Based Model (AIRABM) of farmers' decision-making mechanism and feedback among farmers is developed. The model explores the interactions among human and non-human agents in the irrigation system. In this paper, we discuss harvest patterns as they result from more equal or unequal water distribution in the system. In a baseline model run, farmers are not restricted in their water use. For those situations that yields are low on the system or farmer level, we allow gate settings to be adjusted to improve poor harvest situations. Our model results show that 1) in the baseline scenario, upstream farmers generally receive more water and gain higher yields compared to downstream farmers; 2) gate capacity adjustments of upstream and middle stream farmers can push more water to downstream farmers, but those specific variations are considerable. We observe unexpected emerging system performance. The AIRABM model offers options for how combinations of individual farmers' decisions on water use and farming create (un)equal yield patterns in irrigation systems.