Abstract: Humans have relied on agriculture to feed their communities for thousands of years. Irrigation is practiced in many different forms over the years in countries all over the world. Although modern irrigation systems have been developed, and are in use in many countries, ancient irrigation systems (AISs) have also played a major role in sustaining food production, especially in smallholder farming in least developed and developing countries. The editorial team of Agricultural Systems put out a call for a special issue on restoring AISs for sustainable agro-ecosystems development to capture ancient marvels of traditional irrigation technology across the world. The objectives of this special issue were to: (i) understand and analyse the hydrological and socio-economic networks anchored by AISs; (ii) explain the nature and sustainability of management of these systems in relation to local agro-ecosystems; (iii) analyse the implications of the AISs for land, soil and water quality, and agro-ecosystem services; (iv) qualitative and quantitative analysis of AISs, including bio-physical and bio-economic modelling of these systems; and (v) assess the feasibility of alternative technological, institutional and management strategies to enhance the productivity, profitability, and environmental sustainability of the systems. The overall goal of the special issue was to develop a useful repository for this information as well as to use the journal’s international reach to share this information with the agricultural systems research community and journal readership. This paper provides reflections of papers published in the special issue. The special issue resulted in twelve high quality original research articles and one review article from Asia, Africa and Europe. The findings from various papers revealed that the AISs have been degraded due to human interventions or the anthropogenic activities across the world. Various papers emphasized that as a corrective measure, there is a need for developing and implementing rehabilitation projects in these systems. Authors identified that appropriate policy interventions by the relevant authorities would be a major step towards such rehabilitation process. However, resetting the ecosystem structure of the AISs strictly towards their historical manifestation is neither required nor feasible in the present context as it would contradict the expectations of stakeholders from these systems. The knowledge generated through the special issue provides evidence-based information on various aspects of AISs. It helps aware governments, private sectors and development agencies for improved policy planning and decision making and for prioritizing the restoration, rehabilitation, and management of various AISs around the world.

Abstract: Travel time distributions (TTDs) provide an effective way to describe the transport and mixing processes of water parcels in a subsurface hydrological system. A major challenge in characterizing catchment TTD is quantifying the travel times in deep groundwater and its contribution to the streamflow TTD. Here, we develop and test a novel modeling framework for an integrated assessment of catchment scale TTDs through explicit representation of 3D-groundwater dynamics. The proposed framework is based on the linkage between a flux tracking scheme with the surface hydrologic model (mHM) for the soil-water compartment and a particle tracking scheme with the 3D-groundwater model OpenGeoSys (OGS) for the groundwater compartment. This linkage provides us with the ability to simulate the spatial and temporal dynamics of TTDs in these different hydrological compartments from grid scale to regional scale. We apply this framework in the Nägelstedt catchment in central Germany. Simulation results reveal that both shape and scale of grid-scale groundwater TTDs are spatially heterogeneous, which are strongly dependent on the topography and aquifer structure. The component-wise analysis of catchment TTD shows a time-dependent sensitivity of transport processes in soil zone and groundwater to driving meteorological forcing. Catchment TTD exhibits a power-law shape and fractal behavior. The predictive uncertainty in catchment mean travel time is dominated by the uncertainty in the deep groundwater rather than that in the soil zone. Catchment mean travel time is severely biased by a marginal error in groundwater characterization. Accordingly, we recommend to use multiple summary statistics to minimize the predictive uncertainty introduced by the tailing behavior of catchment TTD.