Adapting agriculture to climate change

We evaluate the potential impacts and measure the potential limits of adaptation of agriculture to climate change. Pressures on land and water resources are expected to intensify existing risks in low latitude areas – e.g., South-East Asia deltas – and in regions with current water scarcity – e.g. Mediterranean, and create new opportunities in some northern temperate areas – e.g., Northern Russia, Northern Europe. The need to respond to these risks and opportunities is addressed by evaluating the costs and benefits of a number of technical and policy actions. The discussion aims to assist stakeholders facing the adaptation challenge and develop measures to reduce the vulnerability of the sector to climate change.Adaptation, climatic change, global production, mitigation, Agricultural and Food Policy, Crop Production/Industries, Land Economics/Use, Resource /Energy Economics and Policy, C51, C53, Q17, Q18,

Drought risk and vulnerability in water supply systems.

This paper provides an overview of the challenges presented to the managers of water supply systems by drought and water scarcity. Risk assessment is an essential tool for the diagnostic of water scarcity in this type of systems. The evaluation of the risk of water shortage is performed with the use of complex mathematical models. Different alternatives to address the problem are presented, covering a range of methodological approaches. The actions adopted to prevent or mitigate the effects of water scarcity should be properly organized in drought management plan. The process of development and implementation of drought management plans is briefly described presenting several examples taken from the Mediterranean region

Impacts of Climate Change in Agriculture in Europe. PESETA-Agriculture Study

The objective of the study is to provide a European assessment of the potential effects of climate change on agricultural crop production and monetary estimates of these impacts for the European agricultural sector. The future scenarios incorporate socio economic projections derived from several SRES scenarios and climate projections obtained from global climate models and regional climate models. The work links biophysical and statistical models in a rigorous and testable methodology, based on current understanding of processes of crop growth and development, to quantify crop responses to changing climate conditions. European crop yield changes were modeled under the HadCM3/HIRHAM A2 and B2 scenarios for the period 2071 - 2100 and for the ECHAM4/RCA3 A2 scenario for the period 2011 - 2040. The yield changes include the direct positive effects of CO2 on the crops, the rainfed and irrigated simulations in each district. Although each scenario projects different results, all three scenarios are consistent in the spatial distribution of effects. Crop suitability and productivity increases in Northern Europe are caused by lengthened growing season, decreasing cold effects on growth, and extension of the frost-free period. Crop productivity decreases in Southern Europe are caused by shortening of the growing period, with subsequent negative effects on grain filling. It is very important to notice that the simulations considered no restrictions in water availability for irrigation due to changes in policy. In all cases, the simulations did not include restrictions in the application of nitrogen fertilizer. Therefore the results should be considered optimistic from the production point and pessimistic from the environmental point of view.JRC.J.2-The economics of climate change, energy and transpor

Real-time modeling of river basin response using radar-generated rainfall maps and a distributed hydrologic database

Thesis (Civ. E)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1992.Includes bibliographical references (p. 315-324).by Luis Garrote.Civ.

Análisis de los posibles hidrogramas producidos por la rotura de la presa de puentes

En la ponencia se presenta un análisis de los posibles hidrogramas originados por la rotura de la presa de Puentes. Se ha elaborado un modelo simplificado de vaciado del embalse, al que se han aplicado distintas condiciones de contorno. Se ha estudiado el posible sifonamiento de la cimentación y su posterior tubificación, obteniendo las leyes de caudales en función del tiempo a medida que progresa el proceso. Una vez formado el orificio, se ha analizado la ley de vaciado del embalse. Como resultado se han obtenido conclusiones respecto al proceso de rotura de la presa, a partir de la descripción de su vaciad

Design flood hydrographs from the relationship between flood peak and volume

Hydrological frequency analyses are usually focused on flood peaks. Flood volumes and durations have not been studied as extensively, although there are many practical situations, such as when designing a dam, in which the full hydrograph is of interest. A flood hydrograph may be described by a multivariate function of the peak, volume and duration. Most standard bivariate and trivariate functions do not produce univariate three-parameter functions as marginal distributions, however, three-parameter functions are required to fit highly skewed data, such as flood peak and flood volume series. In this paper, the relationship between flood peak and hydrograph volume is analysed to overcome this problem. A Monte Carlo experiment was conducted to generate an ensemble of hydrographs that maintain the statistical properties of marginal distributions of the peaks, volumes and durations. This ensemble can be applied to determine the Design Flood Hydrograph (DFH) for a reservoir, which is not a unique hydrograph, but rather a curve in the peak-volume space. All hydrographs on that curve have the same return period, which can be understood as the inverse of the probability to exceed a certain water level in the reservoir in any given year. The procedure can also be applied to design the length of the spillway crest in terms of the risk of exceeding a given water level in the reservoi

A bivariate return period based on copulas for hydrologic dam design: accounting for reservoir routing in risk estimation

A multivariate analysis on flood variables is needed to design some hydraulic structures like dams, as the complexity of the routing process in a reservoir requires a representation of the full hydrograph. In this work, a bivariate copula model was used to obtain the bivariate joint distribution of flood peak and volume, in order to know the probability of occurrence of a given inflow hydrograph. However, the risk of dam overtopping is given by the maximum water elevation reached during the routing process, which depends on the hydrograph variables, the reservoir volume and the spillway crest length. Consequently, an additional bivariate return period, the so-called routed return period, was defined in terms of risk of dam overtopping based on this maximum water elevation obtained after routing the inflow hydrographs. The theoretical return periods, which give the probability of occurrence of a hydrograph prior to accounting for the reservoir routing, were compared with the routed return period, as in both cases hydrographs with the same probability will draw a curve in the peak-volume space. The procedure was applied to the case study of the Santillana reservoir in Spain. Different reservoir volumes and spillway lengths were considered to investigate the influence of the dam and reservoir characteristics on the results. The methodology improves the estimation of the Design Flood Hydrograph and can be applied to assess the risk of dam overtoppin

Improving probabilistic flood forecasting through a data assimilation scheme based on genetic programming

Opportunities offered by high performance computing provide a significant degree of promise in the enhancement of the performance of real-time flood forecasting systems. In this paper, a real-time framework for probabilistic flood forecasting through data assimilation is presented. The distributed rainfall-runoff real-time interactive basin simulator (RIBS) model is selected to simulate the hydrological process in the basin. Although the RIBS model is deterministic, it is run in a probabilistic way through the results of calibration developed in a previous work performed by the authors that identifies the probability distribution functions that best characterise the most relevant model parameters. Adaptive techniques improve the result of flood forecasts because the model can be adapted to observations in real time as new information is available. The new adaptive forecast model based on genetic programming as a data assimilation technique is compared with the previously developed flood forecast model based on the calibration results. Both models are probabilistic as they generate an ensemble of hydrographs, taking the different uncertainties inherent in any forecast process into account. The Manzanares River basin was selected as a case study, with the process being computationally intensive as it requires simulation of many replicas of the ensemble in real time

Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

The performance of distributed hydrological models depends on the resolution, both spatial and temporal, of the rainfall surface data introduced. The estimation of quantitative precipitation from meteorological radar or satellite can improve hydrological model results, thanks to an indirect estimation at higher spatial and temporal resolution. In this work, composed radar data from a network of three C-band radars, with 6-minutal temporal and 2 × 2 km2 spatial resolution, provided by the Catalan Meteorological Service, is used to feed the RIBS distributed hydrological model. A Window Probability Matching Method (gage-adjustment method) is applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation in both convective and stratiform Z/R relations used over Catalonia. Once the rainfall field has been adequately obtained, an advection correction, based on cross-correlation between two consecutive images, was introduced to get several time resolutions from 1 min to 30 min. Each different resolution is treated as an independent event, resulting in a probable range of input rainfall data. This ensemble of rainfall data is used, together with other sources of uncertainty, such as the initial basin state or the accuracy of discharge measurements, to calibrate the RIBS model using probabilistic methodology. A sensitivity analysis of time resolutions was implemented by comparing the various results with real values from stream-flow measurement stations