An exact solution for transient Forchheimer flow to a well does not currently exist. However, this paper presents a set of approximate solutions, which can be used as a framework for verifying future numerical models that incorporate Forchheimer flow to wells. These include: a large time approximation derived using the method of matched asymptotic expansion; a Laplace transform approximation of the well-bore response, designed to work well when there is significant well-bore storage and flow is very turbulent; and a simple heuristic function for when flow is very turbulent and the well radius can be assumed infinitesimally small. All the approximations are compared to equivalent finite-difference solutions.

Cities are complex systems characterised by interdependencies among infrastructural, economic, social, ecological, and human elements. Urban surface water flooding poses a significant challenge due to climate change, population growth, and ageing infrastructure, often resulting in substantial economic losses and social disruption. Traditional hydrological modelling approaches for flood risk management, while providing invaluable support in the analysis of hydrological dynamics of floods, lack an understanding of the complex interplay between hydrological and non-hydrological (i.e., social, environmental, economic) aspects in an urban system, hindering effective flood risk management strategies. In this context, socio-hydrological modelling methods offer a complementary perspective to traditional hydrological models by integrating hydrological and social processes, thereby enhancing the understanding of the complex interactions driving flood resilience.

Water logging is one of the most detrimental phenomena continuing to burden Dhaka dwellers. This study aims to spatio-temporarily identify the water logging hazard zones within Dhaka Metropolitan area and assess the extent of their water logging susceptibility based on informal settlements, built-up areas, and demographical characteristics. The study utilizes integrated geographic information system (GIS)-remote sensing (RS) methods, using the Normalized Difference Vegetation Water and Moisture Index, distance buffer zone from drainage streams, and built-up distributions to identify waterlogged zones with a temporal extent, incorporating social and infrastructural attributes to evaluate water logging effects. These indicators were integrated into an overlay GIS method to measure the vulnerability level across Dhaka city areas. The findings reveal that south and south-western parts of Dhaka were more susceptible to water logging hazards. Almost 35% of Dhaka belongs to the high/very highly vulnerable zone. Greater number of slum households were found within high to very high water logging vulnerable zones and approximately 70% of them are poorly structured. The built-up areas were observed to be increased toward the northern part of Dhaka and were exposed to severe water logging issues. The overall findings reveal the spatio-temporal distribution of the water logging vulnerabilities across the city as well as its impact on the social indicators. An integrated approach is necessary for future development plans to mitigate the risk of water logging.

Worldwide, there is growing recognition of the need to reduce agricultural groundwater use in response to rapid rates of aquifer depletion. To date, however, few studies have evaluated how benefits of conservation vary along an aquifer's depletion pathway. To address this question, we develop an integrated modeling framework that couples an agro‐economic model of farmers' field‐level irrigation decision‐making with a borehole‐scale groundwater flow model. Unique to this framework is the explicit consideration of the dynamic reductions in well yields that occur as an aquifer is depleted, and how these changes in intraseasonal groundwater supply affect farmers' ability to manage production risks caused by climate variability and, in particular, drought. For an illustrative case study in the High Plains region of the U.S., we apply our model to analyze the value of groundwater conservation activities for different initial aquifer conditions. Our results demonstrate that there is a range of initial conditions for which reducing pumping will have long‐term economic benefits for farmers by slowing reductions in well yields and prolonging the usable lifetime of an aquifer for high‐value irrigated agriculture. In contrast, restrictions on pumping that are applied too early or too late will provide limited welfare benefits. We suggest, therefore, that there are “windows of opportunity” to implement groundwater conservation, which will depend on complex feedbacks between local hydrology, climate, crop growth, and economics.

Several modeling tools commonly used for supporting flood risk assessment and management are highly effective in representing physical phenomena, but provide a rather limited understanding of the multiple implications that flood risk and flood risk reduction measures have on highly complex systems such as urban areas. In fact, most of the available modeling tools do not fully account for this complexity—and related uncertainty—which heavily affects the interconnections between urban systems evolution and flood risk, ultimately resulting in an ineffective flood risk management. The present research proposes an innovative methodological framework to support decision‐makers involved in an urban regeneration process at a planning/strategic level, accounting for the multi‐dimensional implications of flood risk and of different flood risk management strategies. The adopted approach is based on the use of System Thinking principles and participatory System Dynamics modeling techniques, and pursues an integration between scientific and stakeholder knowledge. Reference is made to one of the case studies of the CUSSH and CAMELLIA projects, namely Thamesmead (London), a formerly inhospitable marshland currently undergoing a process of urban regeneration, and perceived as being increasingly vulnerable to flooding. It represents an interesting opportunity for building a replicable modeling approach to integrate urban development dynamics with flood risk, ultimately supporting policy and decision‐makers in identifying mitigation/prevention measures and understanding how they could help achieve multi‐dimensional benefits (e.g., environmental, social and economic).

Land surface models (LSMs) are prospective starting points to develop a global hyper-resolution model of the terrestrial water, energy, and biogeochemical cycles. However, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. A diagnostic approach to model evaluation and improvement is taken here that exploits hydrological expert knowledge to detect LSM inadequacies through consideration of the major behavioural functions of a hydrological system: overall water balance, vertical water redistribution in the unsaturated zone, temporal water redistribution, and spatial water redistribution over the catchment's groundwater and surface-water systems. Three types of information are utilized to improve the model's hydrology: (a) observations, (b) information about expected response from regionalized data, and (c) information from an independent physics-based model. The study considers the JULES (Joint UK Land Environmental Simulator) LSM applied to a deep-groundwater chalk catchment in the UK. The diagnosed hydrological limitations and the proposed ways to address them are indicative of the challenges faced while transitioning to a global high resolution model of the water cycle.