Process based model sheds light on climate sensitivity of Mediterranean tree-ring width

We use the process-based VS (Vaganov-Shashkin) model to investigate whether a regional <i>Pinus halepensis</i> tree-ring chronology from Tunisia can be simulated as a function of climate alone by employing a biological model linking day length and daily temperature and precipitation (AD 1959–2004) from a climate station to ring-width variations. We check performance of the model on independent data by a validation exercise in which the model's parameters are tuned using data for 1982–2004 and the model is applied to generate tree-ring indices for 1959–1981. The validation exercise yields a highly significant positive correlation between the residual chronology and estimated growth curve (<i>r</i>=0.76 <i>p</i><0.0001, <i>n</i>=23). The model shows that the average duration of the growing season is 191 days, with considerable variation from year to year. On average, soil moisture limits tree-ring growth for 128 days and temperature for 63 days. Model results depend on chosen values of parameters, in particular a parameter specifying a balance ratio between soil moisture and precipitation. Future work in the Mediterranean region should include multi-year natural experiments to verify patterns of cambial-growth variation suggested by the VS model

Research trends in combinatorial optimization

Acknowledgments This work has been partially funded by the Spanish Ministry of Science, Innovation, and Universities through the project COGDRIVE (DPI2017-86915-C3-3-R). In this context, we would also like to thank the Karlsruhe Institute of Technology. Open access funding enabled and organized by Projekt DEAL.Peer reviewedPublisher PD

Use of the Genetic Algorithm for the Optimal Operation of Multi-Reservoirs on Demand Irrigation System

This study presents the application of a Genetic Algorithm (GA) model developed for computation of the optimal supply hydrographs in on demand irrigation systems aimed at the optimal regulation of the upstream storage reservoirs. The model was applied to an Italian irrigation scheme whe re the optimal inflows to five reservoirs were computed. The obtained result is characteris ed by two inflow values. In addition, the maximum discharge supplied by the upstream dam was redu ced by 10.65 %, and the maximum violation of reservoirs water levels was reduced to acceptable values. The optimal solution guarantees to satisfy the daily demand requirements, to minimize the maximum discharge delivered by the upstream dam, and to avoi d the reservoirs emptiness. In addition, the on- demand delivery schedule according to the actual demand hydrograph recorded downstream the reservoirs may be applied also during the peak periodCette \uc8tude pr\uc8sente l\uedapplication d\uedun Algorithme G\uc8n\uc8 tique (AG) d\uc8velopp\uc8 pour le calcul des hydrogrammes d'approvisionnement optimaux dans les syst\ucbmes d\uedirrigation \u2021 la demande vis\uc8 pour la r\uc8gulation optimale des r\uc8servoirs de stockage. Le mod\ucble a \uc8t\uc8 appliqu\uc8 pour un r\uc8seau d\uedirrigation italien o \u306 les apports optimaux \u2021 cinq r\uc8servoirs ont \uc8t\uc8 calcul\uc8s. Le r\uc8sultat obtenu est caract\uc8ris \uc8 par deux valeurs d\uedapports. En addition, le d\uc8bit maximal fourni par le barrage en amont a \uc8t\uc8 r\uc8duit par 10.65 %, et les violations maximales des niveaux d'eau de r\uc8servoirs ont \uc8t\uc8 r\uc8duites \u2021 des valeurs accepta bles. La solution optimale garantit de satisfaire les besoins jou rnaliers, de minimiser le d\uc8bit maximal de barrage en amont et d\ued\uc8viter la vidange des r\uc8se rvoirs. En outre, la livraison \u2021 la demande selon l'hydrogramme de la demande actuelle enregistr\uc8e en aval des r\uc8servoirs peut-\ucdtre \uc8galement appliqu\uc8s pendant la p\uc8riode de pointe

The genetic algorithm approach for identifying the optimal operation of a multi-reservoirs on-demand irrigation system

A stochastic methodology, based on real-coded genetic algorithms for optimising the operation of reservoirs in an on-demand irrigation system, is presented. The methodology analyzes the adequacy of the difference between supply and demand taking into account the storage capacity of the reservoirs. It determines adequate inflow hydrographs to ensure the optimal regulation of reservoirs during the peak demand period. To take into account the variability of farmers' requirements, demand hydrographs were randomly generated within a pre-determined confidence interval. A weighted objective function, including violations of the admissible reservoir water levels (maximum, minimum and target water levels), is proposed. To solve the optimisation problem, a computer program was developed. The model was applied and tested on the Sinistra Ofanto irrigation scheme (Foggia, Italy), comprising five reservoirs fed with water from an upstream dam, each of them serving different irrigation districts. Results show that the model is efficient and robust

OPTIWAM : an intelligent tool for optimizing irrigation water management in coupled reservoir-groundwater systems

An approach based on a real coded Genetic Algorithm (GA) model was used to optimize water allocation from a coupled reservoir-groundwater system. The GA model considered five objectives: satisfying irrigation water demand, safeguarding water storage for the environment and fisheries, maximizing crop water productivity, protecting the downstream ecosystem against elevated soil salinity and hydromorphic issues, and reducing the unit cost of water. The model constraints are based on hydraulic and storage continuity requirements. The objectives and constraints were combined into a fitness function using a weighting factor and the penalty approaches. The decision variable was water allocation for irrigation demand from reservoir and groundwater. The irrigation water demands around the reservoir were estimated using the Food and Agriculture Organization (FAO) Penman-Monteith method in the water evaluation and planning (WEAP) software. The deterministic GA model was coded using Visual Basic 6 and a new tool for irrigation water management optimization (OPTIWAM) was developed. To validate the applicability of the deterministic model for the operation of coupled reservoir-groundwater systems, the Boura reservoir (in the center-west region of Burkina Faso) and the downstream irrigation area were used as a case study. Results show that the proposed methodology and the developed tool are effective and useful for determining optimal allocation of irrigation water. Furthermore, the methodology and tool can improve water resources management of coupled reservoir-groundwater systems