Browsing by Author "Haro Monteagudo, David"
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Item Open Access Assessing future drought risks and wheat yield losses in England(Elsevier, 2020-11-24) Clarke, D.; Hess, Tim M.; Haro Monteagudo, David; Semenov, Mikhail M.; Knox, Jerry W.Droughts pose a major risk to agricultural production. By comparing the outputs from an ecophysiological crop model (Sirius) with four drought severity indicators (DSI), a comparative assessment of the impacts of drought risk on wheat yield losses has been evaluated under current (baseline) and two future climate scenarios. The rationale was to better understand the relative merits and limitations of each approach from the perspective of quantifying agricultural drought impacts on crop productivity. Modelled yield losses were regressed against the highest correlated variant for each DSI. A cumulative distribution function of yield loss for each scenario (baseline, near and far future) was calculated as a function of the best fitting DSI (SPEI-5July) and with the equivalent outputs from the Sirius model. Comparative analysis between the two approaches highlighted large differences in estimated yield loss attributed to drought, both in terms of magnitude and direction of change, for both the baseline and future scenario. For the baseline, the average year differences were large (0.25 t ha−1 and 1.4 t ha−1 for the DSI and Sirius approaches, respectively). However, for the dry year, baseline differences were substantial (0.7 t ha−1 and 2.7 t ha−1). For the DSI approach, future yield losses increased up to 1.25 t ha−1 and 2.8 t ha−1 (for average and dry years, respectively). In contrast, the Sirius modelling showed a reduction in future average yield loss, down from a baseline 1.4 t ha−1 to 1.0 t ha−1, and a marginal reduction for a future dry year from a baseline of 2.7 t ha−1 down to 2.6 t ha−1. The comparison highlighted the risks in adopting a DSI response function approach, particularly for estimating future drought related yield losses, where changing crop calendars and the impacts of CO2 fertilisation on yield are not incorporated. The challenge lies in integrating knowledge from DSIs to understand the onset, extent and severity of an agricultural drought with ecophysiological crop modelling to understand the yield responses and water use relations with respect to changing soil moisture conditions.Item Open Access D-Risk: a decision-support webtool for improving drought risk management in irrigated agriculture(Elsevier, 2019-05-22) Haro Monteagudo, David; Knox, Jerry W.; Holman, Ian P.Drought constitutes a significant production and business risk in agriculture, particularly for those enterprises dependent on irrigation to deliver high quality continuous supplies of fresh produce to the retail sector. Whilst most farmers are well attuned to managing short term weather-related crop risks, they lack access to tools that can support medium-term decision-making and risk management strategies under conditions of increasing water scarcity and climate uncertainty. This paper describes D-Risk, an intuitive online webtool designed to help farming enterprises easily understand their existing and emergent drought and irrigation abstraction risks and thereby support more robust decision-making regarding future changes in crop planning and water resources infrastructure investment.Item Open Access Drought early warning based on optimal risk forecasts in regulated river systems: Application to the Jucar River Basin (Spain)(Elsevier, 2016-11-14) Haro Monteagudo, David; Solera, Abel; Andreu, JoaquínDroughts are a major threat to water resources systems management. Timely anticipation results crucial to defining strategies and measures to minimise their effects. Water managers make use of monitoring systems in order to characterise and assess drought risk by means of indices and indicators. However, there are few systems currently in operation that are capable of providing early warning with regard to the occurrence of a drought episode. This paper proposes a novel methodology to support and complement drought monitoring and early warning in regulated water resources systems. It is based in the combined use of two models, a water resources optimization model and a stochastic streamflow generation model, to generate a series of results that allow evaluating the future state of the system. The results for the period 1998–2009 in the Jucar River Basin (Spain) show that accounting for scenario change risk can be beneficial for basin managers by providing them with information on the current and future drought situation at any given moment. Our results show that the combination of scenario change probabilities with the current drought monitoring system can represent a major advance towards improved drought management in the future, and add a significant value to the existing national State Index (SI) approach for early warning purposes.Item Open Access Exploring the utility of drought and water scarcity indicators to assess climate risks to agricultural productivity in a humid climate(IWA Publishing, 2017-08-21) Haro Monteagudo, David; Daccache, Andre; Knox, Jerry W.Drought indices have been extensively used by the hydrological research community for understanding drought risks to water resources systems. In a humid climate, such as in England, most agricultural production is rainfed and dependent on summer rainfall, but knowledge of drought risks in terms of their occurrence and potential agronomic impacts on crop productivity remains limited. This paper evaluated the utility of integrating data from three well-established drought indices, including the standardised precipitation index (SPI), standardised precipitation evapotranspiration index (SPEI) and the Palmer drought severity index (PDSI), with simulated yield outputs from a biophysical crop model for potato, a drought-sensitive and high-value crop. The relationships between drought onset and yield response were statistically evaluated. The SPEI-3 drought indicator was found to be most suited to monitoring water availability and hence drought conditions for both rainfed and irrigated production. ‘Heat maps’ were produced to illustrate the strength of the correlation between the modelled SUBSTOR-Potato yields and SPEI for different aggregation periods and monthly lags. Finally, the outputs were used to assess alternative ways in which decision-making could be improved regarding adaptation strategies to reduce agricultural system vulnerability to future drought events.Item Open Access A generic approach for live prediction of the risk of agricultural field runoff and delivery to watercourses: linking parsimonious soil-water-connectivity models with live weather data APIs in decision tools(Frontiers, 2019-06-04) Comber, Alexis; Collins, Adrian L.; Haro Monteagudo, David; Hess, Tim; Zhang, Yusheng; Smith, Andrew; Turner, AndrewThis paper describes the development and application of a novel and generic framework for parsimonious soil-water interaction models to predict the risk of agro-chemical runoff. The underpinning models represent two scales to predict runoff risk in fields and the delivery of mobilized pesticides to river channel networks. Parsimonious field and landscape scale runoff risk models were constructed using a number of pre-computed parameters in combination with live rainfall data. The precomputed parameters included spatially-distributed historical rainfall data to determine long term average soil water content and the sensitivity of land use and soil type combinations to runoff. These were combined with real-time live rainfall data, freely available through open data portals and APIs, to determine runoff risk using SCS Curve Numbers. The rainfall data was stored to provide antecedent, current and future rainfall inputs. For the landscape scale model, the delivery risk of mobilized pesticides to the river network included intrinsic landscape factors. The application of the framework is illustrated for two case studies at field and catchment scales, covering acid herbicide at field scale and metaldehyde at landscape scale. Web tools were developed and the outputs provide spatially and temporally explicit predictions of runoff and pesticide delivery risk at 1 km2 resolution. The model parsimony reflects the driving nature of rainfall and soil saturation for runoff risk and the critical influence of both surface and drain flow connectivity for the risk of mobilized pesticide being delivered to watercourses. The novelty of this research lies in the coupling of live spatially-distributed weather data with precomputed runoff and delivery risk parameters for crop and soil types and historical rainfall trends. The generic nature of the framework supports the ability to model the runoff and field-to-channel delivery risk associated with any in-field agricultural application assuming application rate data are available.Item Open Access Identifying trade-offs and reconciling competing demands for water - integrating agriculture into a robust decision-making framework(Wiley, 2018-02-26) Knox, Jerry W.; Haro Monteagudo, David; Hess, Tim M.; Morris, JoeIncreasing demands for water, driven by population growth and socio‐economic development, environmental regulations and future climate uncertainty, are highlighting limitations on water supplies. This water‐energy‐food‐environment nexus is not confined to semi‐arid regions but is emerging as a key business, societal and economic risk in humid and temperate countries, where abundant water supplies and regulation have historically coped with fluctuating demands between industry, power generation, agriculture, domestic supply and the environment. In the UK, irrigation is supplemental to rainfall, consumptive in use and concentrated in the driest years and most resource‐stressed catchments. This paper describes an empirical application of a mixed methods approach to integrate agriculture into a robust decision‐making framework, focusing on a water‐stressed region in England. The approach shows that competing demands between sectors can be reconciled and that potential options or portfolios compatible with multi‐sectoral collaboration and investment can be identified. By combining model outputs to forecast the impacts of climate and socio‐economic change on agricultural demand within a regional water resource simulator, future spatial estimates of demand were derived. A set of search and tracked metrics were used to drive multi‐criteria searches to identify preferred supply and demand management orientated portfolios. The methodological challenges in forecasting agricultural demand, defining acceptable ‘trade‐offs’, managing scale and uncertainty issues and the importance of engendering open dialogue between stakeholders is described. The study provides valuable insights for countries where similar emergent issues regarding conflicts over water demand exist.Item Open Access Meta-analysis of climate impacts and uncertainty on crop yields in Europe(IOP, 2016-11-11) Knox, Jerry W.; Daccache, Andre; Hess, Tim M.; Haro Monteagudo, DavidFuture changes in temperature, rainfall and soil moisture could threaten agricultural land use and crop productivity in Europe, with major consequences for food security. We assessed the projected impacts of climate change on the yield of seven major crop types (viz wheat, barley, maize, potato, sugar beet, rice and rye) grown in Europe using a systematic review (SR) and meta-analysis of data reported in 41 original publications from an initial screening of 1748 studies. Our approach adopted an established SR procedure developed by the Centre for Evidence Based Conservation constrained by inclusion criteria and defined methods for literature searches, data extraction, meta-analysis and synthesis. Whilst similar studies exist to assess climate impacts on crop yield in Africa and South Asia, surprisingly, no comparable synthesis has been undertaken for Europe. Based on the reported results (n = 729) we show that the projected change in average yield in Europe for the seven crops by the 2050s is +8%. For wheat and sugar beet, average yield changes of +14% and +15% are projected, respectively. There were strong regional differences with crop impacts in northern Europe being higher (+14%) and more variable compared to central (+6%) and southern (+5) Europe. Maize is projected to suffer the largest negative mean change in southern Europe (−11%). Evidence of climate impacts on yield was extensive for wheat, maize, sugar beet and potato, but very limited for barley, rice and rye. The implications for supporting climate adaptation policy and informing climate impacts crop science research in Europe are discussed.Item Open Access Optimal management of the Jucar River and Turia River basins under uncertain drought conditions(Elsevier, 2014-12-17) Haro Monteagudo, David; Solera, A.; Pedro-Monzonís, M.; Andreu, JoaquínThis paper presents a methodology to assess the best behavior achievable for a water resources system, and we apply it to the joint system of the Jucar River and Turia River basins in Spain. The resources of the two rivers are used jointly to meet the different water uses within the region, especially urban demands and environmental requirements. The climate change effects in this area are predicted to be particularly severe in this area with great variability in drought patterns. The results are particularly suitable for evaluating the best performance of the system under uncertain conditions.Item Open Access A sweet deal? Sugarcane, water and agricultural transformation in Sub-Saharan Africa(Elsevier, 2016-06-06) Hess, Tim M.; Sumberg, J.; Biggs, T.; Georgescu, M.; Haro Monteagudo, David; Jewitt, G.; Ozdogan, M.; Thenkabail, P.; Daccache, Andre; Marin, F.; Knox, Jerry W.Globally, the area of sugarcane is rising rapidly in response to growing demands for bioethanol and increased sugar demand for human consumption. Despite considerable diversity in production systems and contexts, sugarcane is a particularly “high impact” crop with significant positive and negative environmental and socio-economic impacts. Our analysis is focused on Sub-Saharan Africa (SSA), which is a critical region for continued expansion, due to its high production potential, low cost of production and proximity, and access, to European markets. Drawing on a systematic review of scientific evidence, combined with information from key informants, stakeholders and a research-industry workshop, we critically assess the impacts of sugarcane development on water, soil and air quality, employment, food security and human health. Our analysis shows that sugarcane production is, in general, neither explicitly good nor bad, sustainable nor unsustainable. The impacts of expansion of sugarcane production on the environment and society depend on the global political economy of sugar, local context, quality of scheme, nature of the production system and farm management. Despite threats from climate change and forthcoming changes in the trade relationship with the European Union, agricultural development policies are driving national and international interest and investment in sugarcane in SSA, with expansion likely to play an important role in sustainable development in the region. Our findings will help guide researchers and policy makers with new insights in understanding the situated environmental and social impacts associated with alternative sugar economy models, production technologies and qualities of management.