Emergence of Cooperation in a Model for Agricultural Production

The emergence of cooperation in a model for an artificial farming society is studied here by the use of an agent-based model. The system is composed of an ensemble of N agents assumed to have equal access to water, whose availability fluctuates randomly in time. Each agent makes two decisions every sowing season regarding: (1) the type of crop mix to plant and (2) whether s/he joins, or not, a cooperative group that allocates water amongst farmers to maximize the production and share revenues equally. Results show that the degree to which farmers choose to cooperate has a strong dependency on the mean water availability. Cooperation seems to emerge as a way of adaptation to uncertain environments by which individual risk is minimized

Improving Operational Short- to Medium-Range (SR2MR) Streamflow Forecasts in the Upper Zambezi Basin and Its Sub-Basins Using Variational Ensemble Forecasting

The combination of Hydrological Models and high-resolution Satellite Precipitation Products (SPPs) or regional Climatological Models (RCMs), has provided the means to establish baselines for the quantification, propagation, and reduction in hydrological uncertainty when generating streamflow forecasts. This study aimed to improve operational real-time streamflow forecasts for the Upper Zambezi River Basin (UZRB), in Africa, utilizing the novel Variational Ensemble Forecasting (VEF) approach. In this regard, we describe and discuss the main steps required to implement, calibrate, and validate an operational hydrologic forecasting system (HFS) using VEF and Hydrologic Processing Strategies (HPS). The operational HFS was constructed to monitor daily streamflow and forecast them up to eight days in the future. The forecasting process called short- to medium-range (SR2MR) streamflow forecasting was implemented using real-time rainfall data from three Satellite Precipitation Products or SPPs (The real-time TRMM Multisatellite Precipitation Analysis TMPA-RT, the NOAA CPC Morphing Technique CMORPH, and the Precipitation Estimation from Remotely Sensed data using Artificial Neural Networks, PERSIANN) and rainfall forecasts from the Global Forecasting System (GFS). The hydrologic preprocessing (HPR) strategy considered using all raw and bias corrected rainfall estimates to calibrate three distributed hydrological models (HYMOD_DS, HBV_DS, and VIC 4.2.b). The hydrologic processing (HP) strategy considered using all optimal parameter sets estimated during the calibration process to increase the number of ensembles available for operational forecasting. Finally, inference-based approaches were evaluated during the application of a hydrological postprocessing (HPP) strategy. The final evaluation and reduction in uncertainty from multiple sources, i.e., multiple precipitation products, hydrologic models, and optimal parameter sets, was significantly achieved through a fully operational implementation of VEF combined with several HPS. Finally, the main challenges and opportunities associated with operational SR2MR streamflow forecasting using VEF are evaluated and discussed

Modeling vadose zone hydrological processes in naturally-occurring piezometric depressions. The Chari-Baguirmi region, southeastern of the Lake Chad Basin, Republic of Chad

The Chari-Baguirmi region, southeastern of the Lake Chad (Africa), has a wide naturally occurring piezometric depression with values deeper than the expected regional groundwater level. To date, the most widely accepted hypotheses to explain its origin and dynamics are based on lack of rainwater infiltration and exfiltration processes. The code HYDRUS-1D is applied to numerically simulate the hydrological flow processes along the unsaturated zone in two soil profiles located in the central part and on the boundary of this piezometric depression under bare and vegetated soil coverage. The simulated time period is 2004–2015 with 715 mm annual rainfall average. The computed recharge with respect to total precipitation accounts for 21% on the boundary and 12% in the central part, which is limited by thick silty low permeability layer on the top surface. Considering modelling uncertainty and limitations under the simulated climatic conditions, the rainfall effect is observed only at upper soil layers, which leads to low aquifer recharge, while the upward water flux causing water table evaporation is very low. Past climate conditions, capable of developing a drying front to reach the water table after thousands of years of drying and geological structural constraints, may explain the current depressed area.Peer ReviewedPostprint (published version

Hydrology and its role in water engineering

[ES] La Hidrología es una ciencia esencial en Ingeniería del Agua, la cual abarca un amplio abanico de temas de investigación que engloban los diversos estadios del agua en el ciclo Hidrológico, tanto en atmósfera, superficie y suelo. Con motivo del relanzamiento de la revista Ingeniería del Agua se presenta un breve artículo de carácter introductorio en el que se muestran algunas de la líneas de investigación actuales en Hidrología, dedicadas a lluvia, interceptación de agua por la vegetación, sensores en Hidrología, agua subterránea, entre otras. Dicha revisión no pretende ser exhaustiva, dado el tamaño limitado de este formato de publicación, sino motivar la publicación en Ingeniería del Agua de artículos dentro de la temática Hidrología.[EN] Hydrology is the basic science for water engineering, including a wide list of research topics ranging from atmospheric water and surface hydrology to groundwater hydraulics. To initiate the new publication period of the journal Ingeniería del Agua, we present here a brief review paper where the current state of research in many hydrologic fields is discussed. The aim of the paper is not to present a complete picture of current state-of-the-art research topics, but rather to provide a broad overview and stimulate new and innovative publication of Hydrology papers in the journal Ingeniería del Agua.García-Marín, A.; Roldán-Cañas, J.; Estévez, J.; Moreno-Pérez, F.; Serrat-Capdevila, A.; González, J.; Francés García, FR.... (2014). La hidrología y su papel en ingeniería del agua. Ingeniería del agua. 18(1):1-14. https://doi.org/10.4995/ia.2014.3048OJS11418

Data collection for cooperative water resources modeling in the Lower Rio Grande Basin, Fort Quitman to the Gulf of Mexico.

Water resource scarcity around the world is driving the need for the development of simulation models that can assist in water resources management. Transboundary water resources are receiving special attention because of the potential for conflict over scarce shared water resources. The Rio Grande/Rio Bravo along the U.S./Mexican border is an example of a scarce, transboundary water resource over which conflict has already begun. The data collection and modeling effort described in this report aims at developing methods for international collaboration, data collection, data integration and modeling for simulating geographically large and diverse international watersheds, with a special focus on the Rio Grande/Rio Bravo. This report describes the basin, and the data collected. This data collection effort was spatially aggregated across five reaches consisting of Fort Quitman to Presidio, the Rio Conchos, Presidio to Amistad Dam, Amistad Dam to Falcon Dam, and Falcon Dam to the Gulf of Mexico. This report represents a nine-month effort made in FY04, during which time the model was not completed

Climate Change Impacts in Hydrology: Quantification and Societal Adaptation

The research presented here attempts to bridge science and policy through the quantification of climate change impacts and the analysis of a science-fed participatory process to face a sustainability challenge in the San Pedro Basin (Arizona). Paper 1 presents an assessment of a collaborative development process of a decision support system model between academia and a multi-stakeholder consortium created to solve water sustainability problems in a local watershed. This study analyzes how science-fed multi-stakeholder participatory processes lead to sustainability learning promoting resilience and adaptation. Paper 2 presents an approach to link an ensemble of global climate model outputs with a hydrological model to quantify climate change impacts in the hydrology of a basin, providing a range of uncertainty in the results. Precipitation projections for the current century from different climate models and IPCC scenarios are used to obtain recharge estimates as inputs to a groundwater model. Quantifying changes in the basin's water budget due to changes in recharge, evapotranspiration (ET) rates are assumed to depend only on groundwater levels. Picking on such assumption, Paper 3 explores the effects of a changing climate on ET. Using experimental eddy covariance data from three riparian sites, it analyzes seasonal controls on ET. An approach to quantify evapotranspiration rates and growing season length under warmer climates is proposed. Results indicate that although atmospheric demand will be greater, increasing pan and reference crop evaporation, ET rates at the studied field sites will remain unchanged due to stomatal regulation. However, the length of the growing season will increase, mainly with an earlier leaf-out and at a lesser level by a delayed growing season end. These findings - implying decreased aquifer recharge, increased riparian water use and a lesser water balance - are very relevant for water management in semi-arid regions. Paper 4, in which I am second author, explores the theory relating changes in area-average and pan evaporation. Using the same experimental data as Paper 3, it corroborates a previous theoretical relationship and discusses the validity of Bouchet's hypothesis

An Alternative Approach to the Operation of Multinational Reservoir Systems: Application to the Amistad & Falcon Reservoir System (Lower Rio Grande/Rio Bravo)

An optimization approach for the operation of international multi-reservoir systems is presented. The approach uses Stochastic Dynamic Programming (SDP) algorithms — both steady-state and real-time. — to develop two models. In the first model, the reservoirs and flows of the system were aggregated to yield an equivalent reservoir, and the obtained operating policies were disaggregated using a non-linear optimization procedure for each reservoir and for each nation's water balance. In the second model a multi-reservoir approach was followed, disaggregating the releases for each country's water share in each reservoir. The non-linear disaggregation algorithm uses the SDP derived operating policies as boundary conditions for a local time-step optimization. These models were applied to the Amistad-Falcon International Reservoir System as part of a dynamic modeling project between the US and Mexico for a better management of the water resources in the Lower Rio Grande Basin, currently enduring a severe drought.hydrology collectio

Evaluation of the Performance of Three Satellite Precipitation Products over Africa

We present an evaluation of daily estimates from three near real-time quasi-global Satellite Precipitation Products-Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Climate Prediction Center (CPC) Morphing Technique (CMORPH)-over the African continent, using the Global Precipitation Climatology Project one Degree Day (GPCP-1dd) as a reference dataset for years 2001 to 2013. Different types of errors are characterized for each season as a function of spatial classifications (latitudinal bands, climatic zones and topography) and in relationship with the main rain-producing mechanisms in the continent: the Intertropical Convergence Zone (ITCZ) and the East African Monsoon. A bias correction of the satellite estimates is applied using a probability density function (pdf) matching approach, with a bias analysis as a function of rain intensity, season and latitude. The effects of bias correction on different error terms are analyzed, showing an almost elimination of the mean and variance terms in most of the cases. While raw estimates of TMPA show higher efficiency, all products have similar efficiencies after bias correction. PERSIANN consistently shows the smallest median errors when it correctly detects precipitation events. The areas with smallest relative errors and other performance measures follow the position of the ITCZ oscillating seasonally over the equator, illustrating the close relationship between satellite estimates and rainfall regime.Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT); GeoAguas Consultores (Chile); NASA SERVIR Program [11-SERVIR11-0058]; International Center for Integrated Water Resources Management (ICIWaRM) a Category II UNESCO CenterThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

A platform for probabilistic Multimodel and Multiproduct Streamflow Forecasting

We develop and test a probabilistic real-time streamflow-forecasting platform, Multimodel and Multiproduct Streamflow Forecasting (MMSF), that uses information provided by a suite of hydrologic models and satellite precipitation products (SPPs). The SPPs are bias-corrected before being used as inputs to the hydrologic models, and model calibration is carried out independently for each of the model-product combinations (MPCs). Forecasts generated from the calibrated models are further bias-corrected to compensate for the deficiencies within the models, and then probabilistically merged using a variety of model averaging techniques. Use of bias-corrected SPPs in streamflow forecasting applications can overcome several issues associated with sparsely gauged basins and enable robust forecasting capabilities. Bias correction of streamflow significantly improves the forecasts in terms of accuracy and precision for all different cases considered. Results show that the merging of individual forecasts from different MPCs provides additional improvements. All the merging techniques applied in this study produce similar results, however, the Inverse Weighted Averaging (IVA) proves to be slightly superior in most cases. We demonstrate the implementation of the MMSF platform for real-time streamflow monitoring and forecasting in the Mara River basin of Africa (Kenya & Tanzania) in order to provide improved monitoring and forecasting tools to inform water management decisions.NASA-USAID [11-SERVIR11-58]; International Center for Integrated Water Resources Management (ICIWaRM-UNESCO); Australian Research Council through the Centre of Excellence for Climate System Science [CE110001028]; EU [INCO-20011-7.6, 294947]6 month embargo; First published: 17 January 2017This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]