Imperial College London


Faculty of EngineeringDepartment of Civil and Environmental Engineering

Research Associate







411Skempton BuildingSouth Kensington Campus





Publication Type

12 results found

Moulds S, Buytaert W, Templeton MR, Kanu Iet al., 2021, Modeling the impacts of urban flood risk management on social inequality, Water Resources Research, Vol: 57, ISSN: 0043-1397

The exposure of urban populations to flooding is highly heterogeneous, with the negative impacts of flooding experienced disproportionately by the poor. In developing countries experiencing rapid urbanization and population growth a key distinction in the urban landscape is between planned development and unplanned, informal development, which often occurs on marginal, flood-prone land. Flood risk management in the context of informality is challenging, and may exacerbate existing social inequalities and entrench poverty. Here, we adapt an existing socio-hydrological model of human-flood interactions to account for a stratified urban society consisting of planned and informal settlements. In the first instance, we use the model to construct four system archetypes based on idealized scenarios of risk reduction and disaster recovery. We then perform a sensitivity analysis to examine the relative importance of the differential values of vulnerability, risk-aversion, and flood awareness in determining the relationship between flood risk management and social inequality. The model results suggest that reducing the vulnerability of informal communities to flooding plays an important role in reducing social inequality and enabling sustainable economic growth, even when the exposure to the flood hazard remains high. Conversely, our model shows that increasing risk aversion may accelerate the decline of informal communities by suppressing economic growth. On this basis, we argue for urban flood risk management which is rooted in pro-poor urban governance and planning agendas which recognize the legitimacy and permanence of informal communities in cities.

Journal article

Zogheib C, Ochoa-Tocachi BF, Moulds S, Ossa-Moreno J, Villacis M, Verano C, Buytaert Wet al., 2021, A methodology to downscale water demand data with application to the Andean region (Ecuador, Peru, Bolivia, Chile), Hydrological Sciences Journal, Vol: 66, Pages: 630-639, ISSN: 0262-6667

Mountainous regions are a hotspot for water scarcity and anthropogenic pressure on water resources. Substantial uncertainty surrounds projections of future climate and water availability. Furthermore, quantitative and distributed data on water demand are generally scarce, dispersed, and highly heterogeneous. This forms a major bottleneck to studying water resources issues and developing strategies to improve water resource management. Here we present a methodology to produce and evaluate high-resolution gridded maps of anthropogenic surface water demand with application to the Andean region. These data are disaggregated according to the major types of water demand: domestic users, irrigated area, and hydropower. This dataset was built by homogenizing, integrating, and interpolating data obtained from various national institutions in charge of water resource management as well as relevant global datasets. The maps can be used to research anthropogenic impacts on water resources, and to guide regional decision-making in regions such as the Andes.

Journal article

O'Keeffe J, Moulds S, Scheidegger JM, Jackson CR, Nair T, Mijic Aet al., 2020, Isolating the impacts of anthropogenic water use within the hydrological regime of north India, Earth Surface Processes and Landforms, Vol: 45, Pages: 1217-1228, ISSN: 0197-9337

The effects of anthropogenic water use play a significant role in determining the hydrological cycle of north India. This paper explores anthropogenic impacts within the regions’ hydrological regime by explicitly including observed human water use behaviour, irrigation infrastructure and the natural environment in the CHANSE (Coupled Human And Natural Systems Environment) socio‐hydrological modelling framework. The model is constrained by observed qualitative and quantitative information collected in the study area, along with climate and socio‐economic variables from additional sources. Four separate scenarios, including business as usual (BAU, representing observed irrigation practices), groundwater irrigation only (where the influence of the canal network is removed), canal irrigation only (where all irrigation water is supplied by diverted surface water) and rainfed only (where all human interventions are removed) are used. Under BAU conditions the modelling framework closely matched observed groundwater levels. Following the removal of the canal network, which forces farmers to rely completely on groundwater for irrigation, water levels decrease, while under a canal only scenario flooding occurs. Under the rainfed only scenario, groundwater levels similar to current business as usual conditions are observed, despite much larger volumes of recharge and discharge entering and leaving the system under BAU practices. While groundwater abstraction alone may lead to aquifer depletion, the conjunctive use of surface and groundwater resources, which includes unintended contributions of canal leakage, create conditions similar to those where no human interventions are present. Here, the importance of suitable water management practices, in maintaining sustainable water resources, are shown. This may include augmenting groundwater resources through managed aquifer recharge and reducing the impacts on aquifer resources through occasional canal water use where possib

Journal article

Agrawal S, Chakraborty A, Karmakar N, Moulds S, Mijic A, Buytaert Wet al., 2019, Effects of winter and summer-time irrigation over Gangetic Plain on the mean and intra-seasonal variability of Indian summer monsoon (correction to vol 53, pg 3147, 2019), Climate Dynamics, Vol: 53, Pages: 6519-6519, ISSN: 0930-7575

Journal article

Agrawal S, Chakraborty A, Karmakar N, Moulds S, Mijic A, Buytaert Wet al., 2019, Effects of winter and summer-time irrigation over Gangetic Plain on the mean and intra-seasonal variability of Indian summer monsoon, Climate Dynamics, Vol: 53, Pages: 3147-3166, ISSN: 0930-7575

The decreasing trend in rainfall in the last few decades over the Indo-Gangetic Plains of northern India as observed in ground-based observations puts increasing stress on groundwater because irrigation uses up to 70% of freshwater resources. In this work, we have analyzed the effects of extensive irrigation over the Gangetic Plains on the seasonal mean and intra-seasonal variability of the Indian summer monsoon, using a general circulation model and a very high-resolution soil moisture dataset created using extensive field observations in a state-of-the-art hydrological model. We find that the winter-time (November–March) irrigation has a positive feedback on the Indian summer monsoon through large scale circulation changes. These changes are analogous to a positive North Atlantic Oscillation (NAO) phase during winter months. The effects of the positive NAO phase persist from winter to spring through widespread changes in surface conditions over western and central Asia, which makes the pre-monsoon conditions suitable for a subsequent good monsoon over India. Winter-time irrigation also resulted in a reduction of low frequency intra-seasonal variability over the Indian region during the monsoon season. However, when irrigation is practiced throughout the year, a decrease in June–September precipitation over the Gangetic Plains, significant at 95% level, is noted as compared to the no-irrigation scenario. This decrease is attributed to the increase in local soil moisture due to irrigation, which results in a southward shift of the moisture convergence zone during the active phase of monsoon, decreasing its mean and intraseasonal variability. Interestingly, these changes show a remarkable similarity to the long-term trend in observed rainfall spatial pattern and low-frequency variability. Our results suggest that with a decline in the mean summer precipitation and stressed groundwater resources in the Gangetic Plains, the water crisis could exacerbate, wi

Journal article

Moulds S, Buytaert W, Mijic A, 2018, A spatio-temporal land use and land cover reconstruction for India from 1960-2010, Scientific Data, Vol: 5, ISSN: 2052-4463

In recent decades India has undergone substantial land use/land cover change as a result of population growth and economic development. Historical land use/land cover maps are necessary to quantify the impact of change at global and regional scales, improve predictions about the quantity and location of future change and support planning decisions. Here, a regional land use change model driven by district-level inventory data is used to generate an annual time series of high-resolution gridded land use/land cover maps for the Indian subcontinent between 1960-2010. The allocation procedure is based on statistical analysis of the relationship between contemporary land use/land cover and various spatially explicit covariates. A comparison of the simulated map for 1985 against remotely-sensed land use/land cover maps for 1985 and 2005 reveals considerable discrepancy between the simulated and remote sensing maps, much of which arises due to differences in the amount of land use/land cover change between the inventory data and the remote sensing maps.

Journal article

O'Keeffe J, Moulds S, Bergin E, Brozovic N, Mijic A, Buytaert Wet al., 2018, Including farmer irrigation behavior in a sociohydrological modeling framework with application in north India, Water Resources Research, Vol: 54, Pages: 4849-4866, ISSN: 0043-1397

Understanding water user behavior and its potential outcomes is important for the development of suitable water resource management options. Computational models are commonly used to assist water resource management decision making; however, while natural processes are increasingly well modeled, the inclusion of human behavior has lagged behind. Improved representation of irrigation water user behavior within models can provide more accurate and relevant information for irrigation management in the agricultural sector. This paper outlines a model that conceptualizes and proceduralizes observed farmer irrigation practices, highlighting impacts and interactions between the environment and behavior. It is developed using a bottom‐up approach, informed through field experience and farmer interaction in the state of Uttar Pradesh, northern India. Observed processes and dynamics were translated into parsimonious algorithms, which represent field conditions and provide a tool for policy analysis and water management. The modeling framework is applied to four districts in Uttar Pradesh and used to evaluate the potential impact of changes in climate and irrigation behavior on water resources and farmer livelihood. Results suggest changes in water user behavior could have a greater impact on water resources, crop yields, and farmer income than changes in future climate. In addition, increased abstraction may be sustainable but its viability varies across the study region. By simulating the feedbacks and interactions between the behavior of water users, irrigation officials and agricultural practices, this work highlights the importance of directly including water user behavior in policy making and operational tools to achieve water and livelihood security.

Journal article

Bradley AV, Rosa IMD, Brandao A, Crema S, Dobler C, Moulds S, Ahmed SE, Carneiro T, Smith MJ, Ewers RMet al., 2017, An ensemble of spatially explicit land-cover model projections: prospects and challenges to retrospectively evaluate deforestation policy, MODELING EARTH SYSTEMS AND ENVIRONMENT, Vol: 3, Pages: 1215-1228, ISSN: 2363-6203

Journal article

Buytaert W, Moulds S, Acosta L, De Bièvre B, Olmos C, Villacis M, Tovar C, Verbist KMJet al., 2017, Glacier melt content of water use in the tropical Andes, Environmental Research Letters, Vol: 12, ISSN: 1748-9326

Accelerated glaciers melt is expected to affect negatively the water resources of mountain regions and their adjacent lowlands, with tropical mountain regions being among the most vulnerable. In order to quantify those impacts, it is necessary to understand the changing dynamics of glacier melting, but also to map how glacier melt water contributes to current and future water use, which often occurs at considerable distance downstream of the glacier terminus. While the dynamics of tropical glacier melt are increasingly well understood and documented, major uncertainty remains on how tropical glacier meltwater contribution propagates through the hydrological system, and hence how it contributes to various types of human water use in downstream regions. Therefore, in this paper we present a detailed regional mapping of current water demand in regions downstream of the major tropical glaciers. We combine these maps with a regional water balance model to determine the dominant spatiotemporal patterns of glacier meltwater contribution to human water use at unprecedented scale and resolution. We find that the number of users relying continuously on water resources with a high (>25%) long-term average glacier melt contribution is low (391 000 domestic users, 398 km2 of irrigated land, and 11 MW of hydropower production). But this reliance increases sharply during drought conditions (up to 3.92 million domestic users, 2096 km2 of irrigated land, and 732 MW of hydropower production in the driest month of a drought year). A large share of domestic and agricultural users is located in rural regions where climate adaptation capacity tends to be low. Therefore, we suggest that adaptation strategies should focus on increasing the natural and artificial water storage and regulation capacity to bridge dry periods.

Journal article

Moulds S, Buytaert W, Mijic A, 2015, An open and extensible framework for spatially explicit land use change modelling: the lulcc R package, Geoscientific Model Development, Vol: 8, Pages: 3215-3229, ISSN: 1991-9603

We present the lulcc software package, an object-oriented framework for land use change modelling written in the R programming language. The contribution of the work is to resolve the following limitations associated with the current land use change modelling paradigm: (1) the source code for model implementations is frequently unavailable, severely compromising the reproducibility of scientific results and making it impossible for members of the community to improve or adapt models for their own purposes; (2) ensemble experiments to capture model structural uncertainty are difficult because of fundamental differences between implementations of alternative models; and (3) additional software is required because existing applications frequently perform only the spatial allocation of change. The package includes a stochastic ordered allocation procedure as well as an implementation of the CLUE-S algorithm. We demonstrate its functionality by simulating land use change at the Plum Island Ecosystems site, using a data set included with the package. It is envisaged that lulcc will enable future model development and comparison within an open environment.

Journal article

Moulds SC, Buytaert W, Mijic A, 2015, An open and extensible framework for spatially explicit land use change modelling in R: the lulccR package (0.1.0), Geoscientific Model Development, Vol: 8, Pages: 3359-3402, ISSN: 1991-9603

Journal article

Tsarouchi GM, Mijic A, Moulds S, Buytaert Wet al., 2014, Historical and future land-cover changes in the Upper Ganges basin of India, International Journal of Remote Sensing, Vol: 35, Pages: 3150-3176

The green revolution represents one of the greatest environmental changes in India over the last century. The Upper Ganges (UG) basin is experiencing rapid rates of change of land cover and irrigation practices. In this study, we investigated the historical rate of change and created future scenario projections by means of 30 m-resolution multi-temporal Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper Plus data of the UG basin. Post-classification change analysis methods were applied to Landsat images in order to detect and quantify land-cover changes in the UG basin. Subsequently, Markov chain analysis was applied to project future scenarios of land-cover change. Fifteen different scenarios were generated based on historic land-cover change. These scenarios diverged in terms of future projections, highlighting the dynamic nature of the changes. This study has shown that between the years 1984 and 2010 the main land-cover change trends are conversion from shrubs to forest (+4.7%), urbanization (+5.8%), agricultural expansion (+1.3%), and loss of barren land (–9.5%). The land-cover change patterns in the UG basin were mapped and quantified, showing the capability of Landsat data in providing accurate land-cover maps. These results, in combination with those derived from the Markov model, provide the necessary evidence base to support regional land-use planning and develop future-proof water resource management strategies.

Journal article

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