Transforming climate information into usable knowledge to enhance decision-making in water resources management of the Río Salado

del Norte Basin, Argentina

A proposal submitted to the

Sectors Applications Research Program (SARP)of the

National Oceanic and Atmospheric Administration, Office of Global Programs

Total project cost: $ 402,930 Project performance period: 1 January 2006 – 30 June 2008 (2.5 years)

Participating Investigators

Guillermo Podestá(Co-Lead Investigator)

Rosenstiel School of Marine and Atmospheric Science, Univ. of Miami, USATelephone: 1.305.361.4142; FAX 1.305.361.4675E-mail: gpodesta@rsmas.miami.edu

Rajagopalan Balaji(Co-Lead Investigator)

Department of Civil, Environmental and Architectural Engineering, University of Colorado, Boulder, CO, USA Telephone: 1.303.492.5968; FAX 1.303.492.7317E-mail: balajir@colorado.edu

Edith Zagona CADSWES, Dept. of Civil, Environmental and Architectural Engineering, University of Colorado, Boulder, CO, USA

Leticia Rodríguez Universidad Nacional del Litoral, Argentina

Carlos Vionnet Universidad Nacional del Litoral, Argentina

Angel Menéndez Facultad de Ingeniería, Universidad de Buenos Aires, Argentina

Budget Summary:

Institution Year 1 Year 2 Year 3 TotalUniv. Of Miami $75,682 $78,037 $42,730 $196,449

Univ. Of Colorado

$ 79,742 $ 74,194 $ 52,545 $ 206,481

$ 402,930

NOTE: This proposal is being simultaneously submitted by the University of Miami (Dr. Guillermo Podesta, PI and Co-PIs from Argentina). Although the text describes the entire set of tasks proposed by both universities, the budget figures given here only include the University of Colorado component.

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A. AbstractTransforming climate information into usable knowledge to enhance

decision-making in water resources management of the Río Salado del Norte Basin, Argentina

NOTE: This proposal is being simultaneously submitted by the University of Miami (Dr. Guillermo Podesta, PI and Co-PIs from Argentina). Although the text describes the entire set of tasks proposed by both universities, the budget figures given here only include the University of Colorado component.

Lead Investigator at Boulder, CO: Rajagopalan BalajiCo-PI, CO: Edith Zagona

Department of Civil Environmental and Architectural Engineering, Univ. of Colorado, Boulder, USATelephone: 1.303.492.5968; FAX 1.303.492.7317, E-mail: balajir@colorado.edu

Total project cost: $ 402,930 - Total University of Colorado budget: $ 206,481 Project performance period: 1 January 2006 – 30 June 2008 (2.5 years)

We propose to explore conditions for the effective use of climate information to enhance decision-making and address water resource management challenges in the Río Salado del Norte Basin in central Argentina, a component of the Río de la Plata Basin that drains a large portion of South America. Floods and droughts are the main issues in this basin and currently, management practices and decisions are largely ‘emergency-response’ in nature. Advances in climate information availability have not been fully utilized in resource management and decision making, often due to the potential mismatch between the capabilities of information producers and the needs and expectations of users. To address this, we propose an integrated framework with two broad prongs. The first prong will adapt and combine existing tools and approaches (e.g., hydrologic models, downscaling procedures) in order to “translate” raw climate information into products or indices of decision variables useful to support adaptive management responses to climatic risk factors. There is abundant evidence that the effective use of climate information is not simply the transmission of salient technical facts, but also involves a process of understanding and melding political, social, institutional, and other contextual interests that often may conflict. The second prong of the project, therefore, will involve close collaboration with relevant stakeholders to identify and address issues that could impede or facilitate use of climate information. We will map the decision landscape, characterizing decision problems and identifying ‘entry points’ for relevant climate information. Given the prominent role of governmental institutions (at national, provincial and municipal levels) in water management and emergency drought/flood relief provisioning, we will characterize existing institutional frameworks and their role in providing credible and salient information. Nevertheless, we also will work with individual stakeholders and NGOs (e.g., agricultural producers, farmers’ groups). The framework to be developed in this proposed research will enable the development of an ‘early warning’ and monitoring system for flood and drought. The framework will help in developing decision strategies for resources planning and management at the short (1-2 week) and long (season to inter-annual) time scales in the face of climate risks.

The component of the research coordinated by the University of Miami (UM) is being conducted within the institutional framework of the Cooperative Institute for Marine and Atmospheric Science (CIMAS, the UM-NOAA Joint Institute). The work proposed supports CIMAS Theme 1 (Climate Variability). The research addresses two of the mission goals identified in NOAA’s 2005-2010 Strategic Plan: (a) Understand Climate Variability and Change to Enhance Society’s Ability to Plan and Respond (the project will link seasonal climate predictions and other kinds of climate information with likely impacts on water resources, and will include a preliminary decision support system); and (b)  Serve Society’s Needs for Weather and Water Information (the project will test and implement relevant hydroclimatic products to support decisions in water resources management).

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B. Results from Prior NOAA Support• Regional Application of ENSO-based Climate Forecasts to Agriculture in the Americas, Aug 1997-Sept 1999 and Use of climate prediction to support decision making in Argentine agriculture, Nov 2001- Oct 2003. G. Podestá (PI), D. Letson and K. Broad (Co-PIs), NOAA OGP.

The goal of these projects was a multidisciplinary assessment of the consequences of seasonal-to-interannual climate variability linked to the El Niño-Southern Oscillation (ENSO) phenomenon on Argentine agriculture. Statistical analyses of historical data showed ENSO impacts on crop yields in the Pampas. These analyses were complemented by modeling to quantify the range of outcomes (yields and economic returns) and their likelihood under different ENSO phases and current management. To assess perceptions of ENSO and climate forecasts, we conducted extended interviews with farmers, focus groups, and a field survey of about 200 farmers in Pergamino, the top agricultural production region of Argentina. We estimated value of ENSO forecasts in the face of variability in commodity prices.

Publications. Seven peer-reviewed papers were published to date (Llovet and Letson, 1999; Podestá et al., 1999; Grondona et al., 2000; Ferreyra et al., 2001; Letson et al., 2001; Podestá et al., 2002; Letson et al., 2005). Seven non-peer reviewed articles were published. Thirteen abstracts were presented at AMS meetings and climate outlook fora in southeastern South America, and NOAA and IAI meetings. An MS thesis (Messina, 1999) was based on this project.

• Building capacity to use climate information and forecasts to enhance decision-making in agriculture: An application to the Argentine Pampas. G. Podestá (PI), K. Broad and H. Herzer, NOAA-OGP Environment, Science and Development, May 2004.

The goal of this project is to enhance the match of informational climate messages to the characteristics and decision contexts of Argentine farmers and their technical advisors. The project is about half-way through planned activities because of initial delays in the funding and a major illness of the collaborator originally trained to conduct farmers’ interviews. The project involves a two-pronged approach. First, we are assessing the missions, functions, capabilities and products of relevant boundary institutions (institutions with missions involving both producers and users of climate information) to assess flows of information. In a second strand of the project, we have conducted about 60 interviews with farmers in two regions of Argentina (one climatically optimal, the other more marginal) to assess what farmers already know and believe about climate, and what knowledge they lack. The mental model interviews have helped to identify misconceptions and erroneous beliefs that need to be addressed in subsequent communication efforts. A few results include: The National Meteorological Service lacks some functions required by a boundary organization.

For instance, there are no formal mechanisms to receive user feedback on its various climate products. Provision of climate services often takes a backseat to the production of daily weather forecasts

A promising approach involves strategic partnerships between the Met Service and other organizations (governmental or private) with a clear boundary role in climate-sensitive sectors. For example, we are facilitating and monitoring the process of collaboration between the Met Service and a non-profit group of farmers (AACREA) whose mission is technology dissemination.

Location A may have better crop yields than location B because of better soils or better agronomic management. Nevertheless, farmers often assume that “climate in location A is more favorable than in B”, assigning to climate any advantages in other environmental or technological factors. That is, the causes of good agricultural results frequently are confounded.

If a given season is unusually dry (wet), farmers assume that a La Niña (an El Niño) event is happening, even if these extreme ENSO phases, usually associated with rainfall anomalies in spring/summer, are not occurring. This reverse assignation of causality may affect the perceived salience of truly ENSO-related climate anomalies.

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Publications: Two manuscripts are in preparation describing each project component. One abstract describing a new climate product for the Pampas (the Standardized Precipitation Index) was submitted to the Latin American Congress of Meteorology (Buenos Aires, October 2005).

• Decision-making in agricultural production in the Argentine Pampas: Alternative choice process formulations and the value of climate information. E. Weber, D. Letson and G. Podestá. NOAA OGP Human Dimensions of Climate Change. May 2004.

A specific objective of the project is the empirical identification of objective functions of a sample of Pampas farmers (as well as their technical advisors) and an assessment of the prevalence of decision objectives outside the subjective expected utility model that is conventional in economics. The identification of alternative goals will be helpful to provide meaningful estimates of value of information, and to tailor agronomic technical advice. We have implemented four alternative objective functions: (a) subjective expected utility, (b) prospect theory’s value function, and (c-d) utility and values corrected according to regret theory. We used crop simulation models to find optimal land allocations for each function. Preliminary results show differences in optimal actions identified by each tested objective function. We have explored the parameter space for each of the implemented functions, and found regimes

where the results change quickly in response to small variations in parameter values. These results will help plan subsequent field studies.

A discontinuity in the original formulation of the prospect theory value function makes it difficult to optimize this function using widely available software packages (e.g., GAMS). We have developed an alternative formulation that does not have the discontinuity problem and is otherwise equivalent to the original.

Publications: A paper by C. Laciana and E. Weber has been submitted on the implementation of an alternative formulation for prospect theory’s value function.

• Understanding the Spatio-Temporal Variability of the North American Monsoon: Implication to Water Resources Management in the South Western US. R. Balaji (PI), E. Zagona, M. Clark, S. Gangopadhyay (Co-PIs), NOAA Office of Global Programs.

This is an ongoing project to (a) understand the space-time variability of North American summer monsoon; (b) develop forecast tools and; (c) demonstrate the utility of incorporating the variability information into water resources management. So far we find the following interesting aspects: (i) There seems to be a significant shift in the timing of the monsoon– i.e., monsoon occurring later in recent decades; (ii) consequently, the July-August rainfall is now pushed into September, which shows a strong increasing rainfall trend; (iii) Land conditions in the pre-monsoon (late winter, early spring) seems to be a key player in the monsoon timing and strength; (iv) The pre-monsoon land conditions are strongly modulated by ENSO, thus preceding winter ENSO might have a substantial influence on the following summer monsoon, than previously thought and; (v)This raises hopes for long-lead forecast of the summer monsoon that can be of great importance to resources management.

Publications. We anticipate 3~4 peer-reviewed papers, the first of which, describing the space-time variability of the North American monsoon is being written up for submission to a special issue of the Journal of Climate on the North America Monsoon. In addition, we have presented these results at the Spring 2005 AGU in a special session on North American Monsoon organized by the PI.

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C. Statement of Work

1. INTRODUCTION1.1 Statement of the ProblemCurrent use of climate information to support decision-making in climate-sensitive sectors of society is evolving rapidly. Improved scientific and technological capabilities, a growing appreciation for the importance of climate on human endeavors (including sustainable development and poverty mitigation), and an increasing demand for information to support decisions are all providing strong incentives for the production and delivery of useful climate data, information, and knowledge to decision-makers (National Research Council, 2001; Dutton, 2002). The ability to provide timely climate information offers an exciting opportunity to learn how important and prevalent climate-sensitive sectors such as flood control activities or water resources management may respond.

Several empirical studies have identified theoretical and practical obstacles to the use of climate information and forecasts (Mjelde, 1998; Pulwarty and Redmond, 1997; Finan, 1998; Stern and Easterling, 1999; Roncoli et al., 2001; Broad and Agrawala, 2000; Broad et al., 2002; Lemos et al., 2002; Patt and Gwata, 2002; Ziervogel, 2004). The obstacles are diverse, ranging from limitations inherent to the climate system’s complexities (seasonal forecasts have coarse spatial and temporal resolution, not all relevant variables can be predicted, the skill of forecasts is not well characterized or understood, contradictory predictions may coexist), to procedural, institutional, and cognitive difficulties in receiving or understanding the information, or in the ability and willingness of decision-makers to modify their actions.

We argue that at the root of most barriers or impediments to the use of climate information lies a fundamental misfit between the capabilities and communication abilities of producers of climate information, and the expectations, needs and beliefs of potential users of such information. To overcome this misfit, the informational message must be matched to the characteristics and situation of the target group (Stern and Easterling, 1999). For example, Orlove and Tosteson (1999) stress that climate forecasts must be well matched to the problem frame, decision-making processes, and capacity for adaptive response of the users. Nevertheless, the fit between information and needs is not simply the combination of a predetermined set of users’ potential decisions and the climate information. Rather, the fit develops from the interaction over time of information producers and users, in which users learn to expand their choice set in response to the availability of new information, and producers adapt their information products to the evolving capacity of users (Patt, 2000; Pulwarty and Melis, 2001).

1.2 Brief Project OverviewWe propose to explore conditions for the effective use of climate information to enhance decision-making and address resource management challenges in the Río Salado del Norte Basin (hereafter, Salado Basin) in central Argentina, a component of the Río de la Plata Basin that drains a large portion of South America. The Salado Basin is part of the flat plains of central Argentina known as the Pampas, one of the major agricultural areas of the world, and is the site of considerable crop, beef and milk production. Dry conditions can have considerable impacts on the prevalently rainfed agricultural production systems of the region. Precipitation and streamflow in the Salado watershed show marked interannual climate variability associated with extreme phases of the El Niño-Southern Oscillation (ENSO) phenomenon. Also, decadal trends in precipitation have had significant impacts on streamflows of major rivers and regional land use patterns (see “Background” section). There are few structural works and no managed reservoirs in the Salado Basin. The major climate-related management issues in the Salado basin, therefore, are associated with flood prevention and mitigation, and drought monitoring and mitigation.

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To address the potential mismatch between capabilities of climate information producers and the needs and expectations of users, we plan a two-pronged approach. As part of the first prong, we propose to adapt and combine existing tools and approaches (e.g., hydrologic models, downscaling procedures) in order to “translate” raw climate information into products or indices of decision variables useful to support adaptive management responses to climatic risk factors.

There is abundant evidence that the effective use of climate information is not simply the transmission of salient technical facts, but also involves a process of understanding and melding political, social, institutional, and other contextual interests that often may conflict (Pulwarty and Melis, 2001; Wernstedt and Hersh, 2002; Lemos et al., 2002; Varis et al., 2004). The second prong of the project, therefore, will involve close collaboration with relevant stakeholders to identify and address issues that could impede or facilitate use of climate information. We will map the decision landscape, characterizing decision problems and identifying entry points for relevant climate information (Jones et al., 1999; Pulwarty and Melis, 2001).We will characterize existing institutional frameworks and their role in providing credible and salient information, targeting both governmental and non-governmental organizations (e.g., agricultural producers, farmers’ groups). Many of the proposed hydroclimatic products will be available for the first time in the study area: this offers unique opportunities to document the iterative, collaborative development of products in collaboration with stakeholders, and to monitor the adoption of these innovations.

2. BACKGROUND2.1 The Study AreaThe Río Salado del Norte Basin is a component of the Río de la Plata Basin, the fifth largest in the world and second only to the Amazon Basin in South America. The Plata Basin encompasses parts of five countries (Argentina, Bolivia, Brazil, Paraguay and Uruguay), is home to about 50% of the combined population of these countries, and generates about 70% of their total GNP (VAMOS Scientific Study Group, 2001).

The Salado River originates in the Argentine Northwest, fed by both snowmelt and rainfall. However, the upper and middle basins’ contribution to streamflow is relatively minor. The lower Salado Basin is a flat hydrologic system composed of two different reaches. The upper reach, which has a low conduction capacity points in a NW-SE direction from the city of Tostado to the confluence with the Calchaquí River. The Calchaquí drains large lowlands (Bajos Submeridionales) in the northern part of the Province of Santa Fe. The lower reach develops in a N-S direction, down to the discharge into the Paraná River, between the cities of Santa Fe and Santo Tomé. The lower basin of the Salado encompasses about 32,000 km2 in the central portion of the province of Santa Fe, not including the Bajos Submeridionales drainage area.

The basin has a subtropical climate, with a mean annual temperature of 19°C. Precipitations are characterized by high temporal and spatial heterogeneities. About 70-75% of the total annual precipitation falls from September to April (southern spring/summer). There is a smooth east-west gradient in total precipitation on the direction, with annual means of 1200-1000 mm in the east of the lower basin, and 1000-800 mm in the west. The main losses from the system are through evapotranspiration, reaching between 900 and 975 mm per year.

The major climate-related management issues in the Salado basin are associated with flood prevention and mitigation, and drought monitoring and mitigation. Flooding is a major concern in the Salado Basin. Most floods in the lower Salado basin tend to occur when protracted high streamflows from the northern Santa Fe lowlands coincide with short high-streamflow pulses from local rainfalls in the lower basin (Giampieri et al., 2004). The Salado is a meandering river with an average channel width of 150 m, bounded by eroded banks, and flowing within a floodplain belt between 1500 and 2000 m wide that has

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been cultivated and inhabited. Over a considerable period (1950-73), annual floods were not extensive. This encouraged the belief that settlements could be built in locations that were subsequently shown to be at severe risk of flooding. Currently, an increasing portion of the population of the City of Santa Fe inhabits the floodplains of both the Salado and Paraná rivers. The increase in the numbers of this vulnerable population is associated with recent economic troubles in Argentina and with the failure of provincial authorities to enforce state law that explicitly prohibits settlements in flood-prone lowlands.

In April-May of 2003, the region suffered the most devastating flood on record for the Salado River, triggered by heavy rains in its lower basin. The west side of Santa Fe City, located at the mouth of the Salado River, was suddenly flooded when a protective levee failed. People living in the floodplains near the city, used to coping with slowly rising floods, faced a sudden increase of up to 4 m of water in a matter of hours. During the flooding of one third of the city, nearly 120,000 people were displaced from their homes, 23 people died as a direct result of the flood, and other 43 are believed to have died from post-traumatic distress (Vionnet et al., 2005).

The Salado Basin is an important agricultural area, where considerable grain, beef and milk production takes place. Production systems in the basin are almost entirely dependent on rainfall, as irrigation is not very common. For this reason, flood and drought monitoring and mitigation are very relevant in this region. A marked increase since the 1970s in spring-summer precipitation in central-eastern Argentina (see following section) has contributed to significant changes in land use patterns (Castañeda & Barros 1994; Viglizzo et al 1995, 1997; Satorre 2001). Continuous cropping has replaced agriculture-pasture rotations in many places, including the Salado basin.

Currently, the management system is largely ‘emergency response’ in nature. The framework to be developed in this proposed research will contribute significantly to the development of an ‘early warning’ and monitoring system for flood and drought, planned by the Province of Santa Fe. The framework will help in developing decision strategies for resource planning and management at short (1-2 week) and long (seasonal to inter-annual) time scales in the face of climate risks.

2.2 Climate and Streamflow VariabilityENSO is the major single source of climate variability on seasonal-to-interannual scales in southeastern South America (Ropelewski and Halpert, 1987, 1989; Grimm et al., 2000; Montecinos et al., 2000). In the target region, during November-December, El Niño events are associated with higher median precipitation and likelihood of high rainfall anomalies than other phases, whereas La Niña events show markedly lower median rainfall and a narrower range of anomalies (Podestá et al., 1999; Vargas et al., 1999; Rusticucci and Vargas, 2002). Predictions of rainfall over southeastern South America during October–December exhibit one of the highest skill levels anywhere (Goddard et al. 2002).

Several studies have addressed the interannual variability of streamflows in the Plata Basin (e.g. Aceituno, 1988; Mechoso and Perez-Iribarren, 1992; Marengo, 1995; García and Vargas, 1998; Genta et al., 1998; Robertson and Mechoso, 1998; Bischoff et al., 2000; Camilloni and Barros, 2000; Robertson et al., 2001; Berbery and Barros, 2002; Berri et al., 2002; Krepper et al., 2003). In addition to the interannual signal, the region’s climate shows marked decadal-scale variability. A steady increase in annual precipitation has been observed since the 1950s over most of central-eastern Argentina (Krepper at al. 1989; Castañeda and Barros 1994; Rusticucci and Penalba 2000). Streamflows for the Paraná, Paraguay, Uruguay, and Negro rivers show a decrease during the first half of the 20th century followed by an increase in the second half, most marked since about 1970 (García and Vargas, 1998; Genta et al., 1998; Robertson and Mechoso, 1998). Robertson et al. (2001) analyzed the interannual to decadal predictability of the Paraná River extracting near-cycling components of the summer river streamflow. They found that the ENSO oscillatory component was associated to changes in the probability distribution of monthly flows and that the decadal modulation of ENSO may be important. More details on the variability of the Río de la Plata basin climate and hydrology can be found in a recent report by the VAMOS Scientific Study Group (2001) and the references therein.

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The mean annual streamflow of the Salado River (at State Route No. 70, between the cities of Esperanza and Recreo) is about 150 m3 s-1, with lows in December of the order of 20 m3 s-1, and highs in February of about 1800 m3 s-1. There is considerable interannual variability in streamflow: the three major discharges recorded in the period 1952-2005 were (a) 2600 m3 s-1 in 1972/73, (b) 2450 m3 s-1 in 1997/98, and (c) 4000 m3 s-1 in 2002/03; all these events coincided with the occurrence of El Niño events. During the same period, minimum streamflow was 7 m3 s-1 in January 1995 (a neutral ENSO year). The low-frequency signal is also reflected on Río Salado streamflows: the annual mean average discharge for the period 1954-2002 is about 135 m3 s-1. If only the period 1954-1970 is considered, the mean annual streamflow is about 71 m3 s-1. If the period 1971-2002 is considered instead, the mean annual streamflow increases to 176 m3 s-1 (Figure 1).

3. PROPOSED APPROACH3.1 OverviewThe overall goal of this project is to develop a framework for the effective use of climate information to enhance decision-making and address resource management and decision-making in the Río Salado Basin in central Argentina. Three main design considerations will guide the project: (a)  to draw as much as possible on existing insights, methods and tools, (b) to integrate seamlessly approaches from the natural and social sciences, and (c) to work closely with stakeholders to foster a quasi-operational implementation of the approaches and products developed. The work proposed involves two major components or strands. The framework is presented in Figure 2.

The first strand of the project will focus on the production and assessment of usable climate information and products (sensu Lemos and Moorehead, 2004). The rationale for this strand is that information on sector-relevant variables or indices (e.g., flood risk maps, drought indices) is more important to stakeholders than climate information by itself. The first project strand will include two distinct components: Production of relevant prognostic hydroclimate information and products derived from seasonal

forecasts and plausible decadal scenarios; and Production of relevant diagnostic hydroclimate information (“What has happened in the recent

past?”) that provides context for forecast interpretation and decision-making.

The second project strand will center primarily on the “demand side” of climate information. The goals are to develop better matches among what is needed, what is asked for, what is provided and, what actions can be taken (Pulwarty and Melis, 2001). These processes must be embedded within an understanding of the decision contexts within which trade-offs take place. This strand will include components involving: Mapping the decision landscape; Characterizing the institutional structures that facilitate/impede the flow of climate information, and Monitoring the process of diffusion of new hydroclimate information products, including an

assessment of the relevance and usefulness of this information by appropriate stakeholders.

3.2 Specific Tasks Proposed3.2.1 Data CompilationHistorical Climate Data : The Argentine Meteorological Service will compile quality-controlled historical climate series (maximum and minimum daily temperature, daily precipitation) for eleven locations in or around the Río Salado Basin and the period 1950-present. Stations to be considered include: (1) Reconquista Aero, (2) Sauce Viejo Aero, (3) Ceres Aero, (4) Villa María, (5) Resistencia Aero, (6) Corrientes Aero, (7) Paraná Aero, (8) INTA Bella Vista, (9) INTA Paraná, (10) INTA Rafaela, and (11) INTA Presidente R. S. Peña. These data will be used to “train” stochastic weather generators,

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calibrate hydrologic models, and compute indices that require long records (e.g., the Standardized Precipitation Index).

Real-time Climate Data: Data collected at the locations listed above will be continuously updated throughout the span of the project (probably on a monthly basis) to provide context on recent climate conditions. A network of 30 automated stations to monitor most of the meteorological and hydrological variables will be deployed by the Province of Santa Fe in early 2006, coinciding with the start of this project. This mesoscale network will enhance significantly the volume of near-real-time information available to this project in the Salado Basin. As data from this network becomes available, it may allow us to validate interpolation procedures developed for the coarser historical network and output from numerical models (see below).

Real-time Climate Model Output and Forecasts: We will arrange for access to the output produced by regional mesoscale Eta model runs over the Río de la Plata Basin, including our target area. The model is being run routinely by Dr. Hugo Berbery, Univ. of Maryland (http://www.atmos.umd.edu/~berbery/).

Seasonal Climate Forecasts : Seasonal climate forecasts from operational agencies can range from the prediction of an El Niño or a La Niña event (that in turn influence regional climate conditions) to probabilistic statements about the likelihood of regional precipitation or temperature falling within certain categories (e.g., “above normal”, “below normal”). Temperature and precipitation forecasts for the study region will be obtained for the International research Institute for Climate Prediction (IRI), regional agencies (e.g., Brazil’s CPTEC) and Regional Climate Outlook Fora, periodically held in the region (Buizer et al., 2000).

Plausible Decadal Climate Scenarios: The marked increase since the 1970s in spring-summer precipitation in central-eastern Argentina has contributed to significant changes in land use patterns (Castañeda & Barros 1994; Viglizzo et al 1995, 1997; Satorre 2001). Although, at present, predictions of decadal variability have very little skill, we will define various plausible scenarios (we stress these are not predictions) to explore interesting situations. For example, we may “run the climate movie backwards,” simulating gradual or abrupt returns to a drier epoch (e.g., pre-1970s) in the Pampas, and explore the hydrological and agricultural outcomes of drier conditions.

Río Salado Streamflow and Other Hydrological Measurements: The present hydrologic monitoring network in the Salado Basin in the Province of Santa Fe is constituted by seven water-level stations, six of which have relatively short records. The longest record available at the State Road No. 70 gauging station starts in water year 1952/1953. A Master Thesis that is underway at Universidad del Litoral (UNL) on hydrologic monitoring for the Province of Santa Fe will add some instrumentation to selected current groundwater level monitoring locations, including precipitation, soil moisture, and soil and air temperature. The data will be available for this project. Data from the planned automated observation network (see above) also will augment the volume of available hydrological data.

3.2.2 Translating prognostic climate information into relevant hydrological information

Prognostic climate information in the Salado Basin is available on two main temporal scales. On one hand, agencies such as CPC, IRI, or ECMWF routinely issue large-scale climate forecasts on a seasonal or monthly time-scale. On the other hand, weather forecasts produced from experimental regional models are available for shorter time scales (say, up to a week into the future). Each of these types of prognostic information may assist in different types of decisions, but both sources require a process of “translation” into usable scenarios before they can be used in conjunction with process models (e.g., a watershed model) to produce relevant hydrological products.

Seasonal forecasts typically are probabilistic and categorical. Rainfall is often forecast as the chance of being ‘above normal’, ‘below normal’ or ‘near normal’. Each of these categories corresponds to a tercile of the distribution (terciles include 1/3 of the sorted historical distribution of precipitation totals for a

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given period). For example, a hypothetical forecast for Oct-Dec precipitation in the Salado Basin may assign probabilities of 0.45, 0.35, and 0.20 to precipitation totals in the lower, middle, and upper terciles, respectively. Because the probability of rainfall in the lower tercile is 0.45 (as opposed to the climatological 0.33), this forecast implies that dry conditions are more likely than normal or wet conditions, although the latter two also may occur. This probabilistic nature needs to be emphasized so that users do not assume it to be a deterministic prediction that is wrong when the actual climate is not as forecast (Ziervogel and Calder, 2003).

We also will have access to real-time forecasts of precipitation, temperature and circulation fields from regional Eta model runs for most of the Plata Basin produced by Dr. Hugo Berbery at the University of Maryland (http://www.atmos.umd.edu/~berbery/). The Eta model is driven by NCEP’s (National Centers for Environmental Prediction) global climate model (GCM) forecast to provide improved regional forecasts. Dr. Berbery has applied the Eta model to simulate/forecast meteorology over river basins in both North and South America, and found that spatial correlations between the model forecast and observed precipitation over the Plata Basin are almost as high as those obtained for the Mississippi River basin using forecasts of the NCEP operational Eta model (Berbery and Collini, 2000).

Seasonal forecasts typically are issued for areas that have sizes of the order of hundreds of square kilometers (see Buizer et al., 2000, for examples of forecasts). Similarly, output from the regional Eta model, while improving upon the coarse spatial resolution of the GCMs, still provides results on a grid larger than the point-scale required to drive watershed models. The key issue for both types of forecasts, therefore, is how coarse forecast information can be translated into weather scenarios at observation points in the basin and, subsequently, into hydrologic (i.e., streamflow attributes) scenarios that can be used in water resources management.

3.2.2.1 Generating synthetic daily weather sequences consistent with seasonal climate scenarios

This section describes how we plan to generate ensembles of synthetic daily weather scenarios conditioned on a large-scale seasonal climate forecast using stochastic weather generators. Weather scenarios are generated using stochastic weather generators and these are used routinely in water, agricultural, and erosion control management (Skidmore and Tatarko, 1990; Wilks, 1997; Dubrovsky et al., 2000). Most approaches are based on parametric or semi-parametric schemes (i.e., underlying distributions are assumed and described via parameters estimated from historical data). Recent developments of stochastic nonparametric weather generators and their successful applications (Rajagopalan and Lall, 1999; Yates et al., 2003; Clark et al., 2003) are an attractive alternative to traditional parametric approaches. The nonparametric methods avoid subjective judgments about appropriate model forms and probability distributions (rarely tested formally). Furthermore, as data-driven methods, they can capture deviations from theoretical probability distributions and nonlinearities in the associations between variables (Wilks and Wilby, 1999; Rajagopalan and Lall, 1999). The number of parameters to be estimated increases significantly with the number of weather variables and desired periods (weeks, months, etc.); with short historical records, this can lead to unstable models. In contrast, non-parametric methods are more parsimonious.

We will adapt the nonparametric weather generator based on the K-nearest neighbor (K-NN) framework (Lall and Sharma, 1996; Rajagopalan and Lall 1999; Yates et al. 2003). In this approach, all weather variables are considered simultaneously as members of a feature vector for day t. The algorithm selects the next day t+1 starting from day t from a set of potential nearest neighbors in the historical record. The simulated weather sequences will reproduce all the statistical properties (i.e. probability density function, PDF) of the historical data. This unconditional weather generator has been applied and tested at several locations in the USA (Yates et al., 2003; Rajagopalan and Lall, 1999) and also in the Pampas region by the PIs.

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The K-NN framework can be modified to generate weather sequences conditioned on categorical forecasts such as those issued by IRI. Let us consider the hypothetical tercile forecast for Oct-Dec precipitation in the Río Salado del Norte Basin as described earlier—0.45, 0.35, and 0.20 for below normal, normal, and above normal categories. In order to generate weather scenarios conditioned on the above forecast, we first divide the historical rainfall records of the Oct-Dec season into 3 categories; wet, normal and dry based on the tercile. Then, the years falling into the three categories are given weights equal to the categorical forecasts - in this example, the historical years with rainfall in the lower tercile (dry years) are given a weight of 0.4, those in the middle tercile (normal years), 0.35 and the wet years, 0.20. A small random noise, a random number between (0, 0.001), is added to the weights of each year so that the weights are different from one another and possible ties are broken. The years are then ranked from the highest to lowest weights – clearly in this example, the dry years will be at the top and the wet years at the bottom. We then preferentially select a year, say using the criterion proposed by Clark et al. (2004):

(1)

where is a uniform random number between (0,1), is a weighting parameter, is a selection parameter, N is the number of years in the historical record, and INT is the integer operator. Clark et al. (2004) suggest typical values of =5.55 and =1.106, however, these can be changed and tested for the basin. We select N years from the above equation – of course, some of the years will be selected multiple times. The selected N years and the associated observed data can be considered as the “historical” record and to this record we apply the unconditional weather generator described earlier. The idea here is to generate weather sequences based on the forecast, thus some years are given less weight than others. In the unconditional weather generation all years are given equal weight – this is the key difference. Clark et al. (2004) successfully demonstrated the application of this procedure for generating weather sequences over Arizona. Furthermore, this entire framework was applied recently for quantifying and managing delays in highway construction due to weather. The PIs have extensive experience with development of the weather generator and also its application to several locations and sectors. Given this, the testing and validation of the stochastic weather generator in the Salado Basin will be done in short order.

3.2.2.2 Translating short-term forecasts into hydroclimate scenariosThe methodology described in the preceding section can be adapted to produce weather scenarios at observation points in the basin which can, subsequently, be converted into hydrologic (i.e., streamflow) attributes. The K-NN weather generator described above can be easily modified to translate Eta model output into weather scenarios conditioned on the regional model output and downscaled to observation points in the basin.

The required modification of the K-NN algorithm was developed and successfully demonstrated on two climatologically different basins in the US by Gangopadhyay et al. (2005). In this approach, they downscaled the NCEP (1998) medium range forecast (MRF) model output to point-scale weather scenarios. The algorithm queries days similar to a given feature vector (i.e., the vector of output from the RM) in the archive, and using EOF (Empirical Orthogonal Functions) analysis identifies a subset of days (K) similar to the feature day.  These K days are then weighted using a bi-square weight function, and randomly sampled to generate ensembles.  The feature vector could be precipitation output at the grids or circulation variables (winds, pressures etc.), because the models are generally good at capturing the circulation fields compared to precipitation. Gangopadhyay et al. (2005) show very good skill from this downscaling approach. The PI (R. Balaji) was involved in developing this approach. We will apply this approach to the Salado Basin.

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3.2.2.3 Translating synthetic daily weather into hydrological scenariosThe stochastic weather sequences will drive a watershed model system to generate ensembles of streamflow and other hydrologic conditions in the basin, thus, providing their probability distributions. The Universidad Nacional del Litoral (UNL, Santa Fe) is collaborating with other institutions in a project called FLAGS whose objective is to get a better understanding of the surface and ground water dynamics and their interaction in the Lower Basin of the Salado. As part of FLAGS, a watershed model system is being developed that consists of a hydrodynamic model of surface water coupled with a groundwater model (running in parallel on a cluster of 16 PCs). This system is currently being calibrated by groundwater level data monitored at six locations and precipitation from 15-20 stations.

The groundwater flow model has been developed based on the standard MODFLOW model developed by the US Geological Survey (Mc Donald and Harbaugh, 1988) and supported by the GMS graphical user interphase (GMS, 2005). MODFLOW can provide the spatial distribution of water table elevations across the basin at different times. Input to the model includes the aquifer system properties, i.e., stratigraphy, hydraulic conductivity and storativity; evapotranspiration losses; recharge from precipitation and any other source being natural or artificial; groundwater abstractions through wells; stream/aquifer interactions characteristics. All input data and initial parameter values already have been developed for the Salado Basin using GMS (Giampieri et al. 2003). The calibration of the groundwater model is accomplished by tuning the model parameters to obtain a good fit (in statistical terms) between observed and simulated hydraulic heads or water table elevations across the basin. The calibration process of the Salado Basin groundwater flow model is underway at the UNL and is expected to be completed in the next few months.

Stream/aquifer interactions play a key role on the basin hydrodynamics. The groundwater flow model is complemented with another model for flood routing and computation of water surface profiles along the main channels of the drainage network, based on the model HEC-RAS developed by the US Army Corps of Engineers (USACE 2002). Basic geometric data for the model consist of the connectivity of the stream system, stream cross sections, reach lengths, energy loss coefficients, stream junction information, and hydraulic structures data. The UNL group has completed the calibration of this model on one of the sub-basin and work is underway for the other two sub-basins. We hope to have the calibration done in the next few months.

The coupling between MODFLOW and HEC-RAS, intended to improve the simulation of the stream/aquifer interaction process, will be undertaken once both models are calibrated separately. The concurrent use of MODFLOW and HEC-RAS has been successfully demonstrated in another application by Cello and Rodríguez (2002). Additional experience has been gained with a shallow water computational code (TELEMAC 2004) to assess the major flood of Santa Fe City in 2003 due to heavy rains on the Salado Basin (Vionnet et al. 2005) – which will be incorporated in this effort.

The integrated watershed model system will be completely implemented and calibrated during the first year of this project. Output from the watershed model system will include ensembles of streamflow at several locations, water depths, potential flooding, soil moisture in the basin etc. All of these variables form a rich array of decision inputs that can be used by decision makers (described in the following section).

3.2.3 Producing relevant hydrological products3.2.3.1 Products derived from prognostic climate informationRuns of the integrated hydrologic model with multiple ensembles of different weather scenarios produced by resampling procedures described above will yield probability distributions of various hydrological quantities. The products we currently envision include: Flood risk, including flood persistence;

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Soil moisture; and Depth of the water table.

Soil moisture and depth of the water table will be direct outputs of the model. Flood risk will be expressed as inundation maps for different recurrences (1 time every N years), which will be obtained by constructing the envelope of maximum flow height during a flood wave passage for a series of stations along the stream (Re et al., 2004). Flood persistence, in turn, will be calculated for each station as the time interval during which the flow height stays above a predefined threshold; the flood persistence map will be built as contour lines for the flood persistence.For urban areas, flood risk maps will be useful as a base to establish land use regulations and, eventually, define structural protection measures. This information should be used by municipalities as part of urban planning and land zoning, and by the Provincial government when defining big defense works.

For rural zones, flood risk maps will be useful to evaluate possible losses of agricultural areas during wet periods. Because the topography of the study area is very flat, floods tend to persist for long periods; estimates of flood persistence will assist farmers to plan their activities (e.g., the need to move animals to new grazing areas). Projections of soil moisture, together with the real-time soil moisture maps derived from diagnostic climate data, will provide the basis to predict expected crop yields. This information will be relevant not only to individual farmers but also to traders and the transportation sector. Soil conditions at harvest time may imply unexpected costs, such as the more expensive use of machines capable of harvesting in wet soils, or additional transportation costs because of longer alternative routes to market as a consequence of flooded roads.

Maps of the depth of the water table at regional scale will allow an estimation of the buffering capacity of the unsaturated zone for the precipitation scenarios to be considered in the project. In addition, the Provincial government should benefit from all this information, required to determine when extraordinary fiscal measures (e.g., tax exemptions) have to be taken due to emergency environmental situations such as floods or protracted drought.

3.2.3.2 Products derived from diagnostic climate informationIn previous work (Ferreyra et al., 2002), we have shown that diagnostic climate information (i.e., information about conditions in the recent past, say, the last 1-6 months) is useful and relevant to decision-making. Diagnostic information provides useful context for the interpretation of prognostic climate information: for example, it is not the same to receive a seasonal forecast of dry conditions if the soil is already dry or, alternatively, if there is sufficient water stored in the soil. We will implement and adapt various hydrological products derived from climate conditions in the recent past, assessed from either in situ observations or high-resolution regional model output.

Standardized Precipitation Index (SPI): This index was developed by McKee et al. (1993, 1995) to determine the onset and duration of droughts. Its utility for this purpose was illustrated by monitoring the development of the severe 1996 drought in the southern plains and southwestern US (Hayes et al., 1999). Seiler et al. (2002) showed that the SPI also can be used as an indicator of soil-saturation conditions leading to flood situations. A fundamental strength of the SPI is that it can be calculated for a variety of time scales; this versatility allows the index to monitor both short-term water supplies such as soil moisture, important for agricultural production, and longer-term water resources such as groundwater supplies and streamflows (Hayes et al., 1999). So far, the SPI has not been routinely produced in Argentina, but we are collaborating with the Argentine Met Service in its implementation and testing. We will compute the index for several locations in the Salado Basin, and will disseminate the values through the Met Service’s WWW page. The SPI is routinely produced for many important agricultural regions in the world (e.g., the US Corn Belt). US farmers familiar with this product might be able to monitor growing conditions in the Pampas, a main competitor in the production of global agricultural commodities.

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Soil Moisture Fields. Simulated values of water content generated by the 1-D water balance model component will be compared with field data to be collected at a selected number of locations where water content will be monitored at three different depths: 15 cm, 30 cm and 60 cm. This calibration procedure will contribute to gain confidence on model predictions, and therefore in the generation of water content maps at regional scale to be produced as one of the by-products of the integrated model under different precipitation scenarios.

3.2.4 Understanding and Monitoring Information Use 3.2.4.1 Mapping the decision-making landscapeAdaptive responses to climate information require that a range of options exist. Therefore, as a first step towards assessing the scope for adaptation, we will construct in collaboration with stakeholders decision maps and calendars to identify “entry points” for climate information (Pulwarty and Melis, 2001). The maps will characterize (a) flood- or drought-related decisions, (b) their timing, and (c) realistic options and constraints for each decision. The decision maps/calendars are based on similar tools used in agroclimate and other studies, where timing of activities depends on seasonal transitions and their impact on physical and biological systems. One must understand the nature of these climatological transitions and changes, and their relevance to management activities and decision needs (Pulwarty and Melis, 2001).

We will use influence diagrams (Morgan et al 2002) to build a conceptual model of climate-related risks and other context factors, as well as the multiple objectives influencing drought/flood control and mitigation decisions. Influence diagrams show associations between variables or factors (e.g., “A influences B”) and provide a very effective participatory mechanism to develop a consensus description of the target system, as most people intuitively understand “bubbles and arrows” diagrams. This exercise will yield a detailed recording of group learning, and will help to build a shared, consensus mental model of the target system. Simple models have advantages for addressing complex systems initially, as they make assumptions transparent and uncertainty more traceable (often not the case for larger, unwieldy models). Simple initial descriptions can evolve into increasingly complex models.

As a way of triangulating the appropriateness of the decision maps/calendars and the conceptual model of the context of decision-making, we propose a series of role-playing exercises in which stakeholders will be asked to make specific decisions in the light of hypothetical diagnostic and prognostic information. For example, farmers may be given various scenarios of soil moisture and predicted seasonal conditions, and asked to make realistic decisions (e.g., what kind of crop varieties to plant to avoid anticipated water stresses, when to harvest). Public administrators may be asked to explore the consequences of various flood scenarios on the road infrastructure needed to transport massive volumes of harvested soybean to port. In both cases, process models (crop growth models, our hydrological model) will provide stakeholders with immediate feedback on the results of their decisions, facilitating adaptive learning.

3.2.4.2 Characterization of the institutional structures that facilitate/impede the flow of climate information

Because of the prominent role of governmental agencies in water management and emergency drought/flood relief provisioning, we will identify relevant public institutions at various jurisdictional levels (national, provincial, and municipal) and their role in managing climate variability. In most cases, these institutions lack the expertise and resources to satisfy the increasing demand for information to address climate-related policy issues. Further, institutions or networks currently in place may inadvertently have an incomplete focus. For example, we learned that stakeholders in climatically marginal locations have particular interest on information about favorable conditions in order to maximize potential benefits. In contrast, existing early warning systems may be focused mainly towards disaster management or drought warnings, so they may not address user needs entirely (Ziervogel and Downing, 2004).

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Through open-ended interviews with key personnel, we will characterize the candidate institutions’ current capabilities for the generation, dissemination, and use of credible and salient climate information. We gained experience in assessing institutional structures and information flows during a project sponsored by NOAA-OGP to characterize Argentine institutions involved in producing and using climate information relevant to agriculture. These institutions were surveyed in the context of a comparative framework that included, among other considerations, their functions as “boundary organizations” (convening, translation, collaboration and mediation) and the characteristics of the information they produce (salience, credibility, and legitimacy) (Cash et al., 2003; Cash et al., in review). A similar approach will be used in this project.

We had argued above that a mismatch still exists between the capabilities and communication abilities of producers of climate information, and the expectations, needs and beliefs of potential users of such information. Overcoming the mismatch requires a mutual learning process by producers and users. In our ongoing study of boundary organizations we found that a promising approach to facilitate such learning involves fostering strategic institutional partnerships (e.g., a partnership between the Met Service and farmers’ groups focused on extension). We will identify (and hopefully facilitate) such critical institutional linkages.

We will survey in detail the Ministerio de Asuntos Hídricos (Ministry of Water Affairs, MAH). This is a state-level governmental organization responsible for the enforcement of different national and state laws regarding water resources use within Santa Fe. MAH oversees ground and surface water exploitation. For many years, MAH actions related to surface water focused on the construction of hundreds of miles of artificial channels to evacuate excess water from farmlands. Most of these constructions, built in a mostly unplanned manner, responded to direct pressure from farmers, which has increased in recent years due to more humid conditions. A positive side of this process has been the organization of farmers into what are called “Comités de Cuenca” (basin committees). Even though the jurisdiction associated with these committees does not really follow basin boundaries but rather district boundaries, these organizations have proved to be efficient and helped to decentralize many local and regional decisions, maintaining a fluid dialogue with the State Water. These committees constitute an excellent communication channel between project researchers and water end-users.

We will not only work with governmental and official institutions, but will also focus on non-governmental organizations and individual decision-makers (e.g., farmers). We have initiated contacts with CODETEA, Commission for the Agricultural Technological Development of Las Colonias County, State of Santa Fe (see attached letter of support) This commission involves various stakeholders’ associations, farmers’ organizations, agrotechnical schools from an area with high strategic value for the state economy, the National Institute for Agricultural Technology (INTA) and research groups from the Dept. of Agricultural Science of UNL. Also, we will continue our ongoing collaboration with a national-level farmer organization, the Asociación Argentina de Consorcios Regionales de Experimentación Agrícola (AACREA, http://www.aacrea.org.ar), a non-profit farmers’ organization. AACREA has a leading role in agricultural technology dissemination because budgetary problems have weakened significantly the governmental agricultural extension system. AACREA farmers and technical advisors are actively collaborating with project investigators on other projects (sponsored by NOAA-OGP and NSF), and have participated willingly in several research activities led by the project investigators.

3.2.4.3 Monitoring diffusion of hydroclimate information productsAs stated above, this project will develop and implement a series of hydroclimate products that so far have not been widely available (if at all!) to the user community. This offers unique opportunities not only to design the products in a collaborative mode to ensure relevance and usefulness, but also to monitor the process of diffusion of these new products. Innovation diffusion (Rogers, 1995; Wejnert, 2002) is a useful way to frame the problem of climate information dissemination. This approach, however, has not been used very extensively in this context. Agrawala and Broad (2002) suggest different

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models of technology transfer as a tool for situating the state of seasonal forecast dissemination and adoption. Ziervogel and Downing (2004) have studied networks of stakeholders involved in the diffusion of seasonal climate forecasts.

We will work with stakeholders in NGOs to monitor periodically awareness and use of the various products to be implemented as part of the project. Short surveys will be administered a few times a year through stakeholder groups. Regular monthly meetings of AACREA farmers provide ready-made occasions to conduct these surveys. Results will be used to quantify awareness and adoption rates. In some cases, immediate feedback on products will be requested from users. For example, buttons in the same WWW pages where the SPI values will be displayed by the Met Service will allow users to rate the usefulness of the product.

3.2.4.3 Towards a decision support system After the catastrophic flooding of the Salado River in 2003, the Santa Fe MAH seriously started to plan for a Flood Forecasting System for the basin. A first step in this direction is a 30-station monitoring network expected to become operative by early 2006. To facilitate progress towards that goal, we have asked Dr. E. Zagona to join this project. Dr. Zagona is an expert on Water Resources Decision Support System and also the director of the Center for Decision Support for Water and Environmental Systems (CADSWES, http://cadswes.colorado.edu), sponsored by the USBR. CADSWES has developed DSS tools for water management that are widely used by water managers, USBR, municipalities and a variety of stakeholders. Furthermore, these tools have enabled stakeholder participation in decision making in the Western US – which is a significant step in the participatory decision making.

We feel that developing a DSS on the Río Salado del Norte Basin would be the culmination of the process of incorporating climate information and stakeholder participation. Given the restricted scope of the proposed research we plan to initiate discussions and potential collaborations between CADSWES/USBR and the water managers on Río Salado as part of this project. We hope that these initial efforts will provide a platform for significant and fruitful collaborations in future. To this end, CADSWES has agreed to host the graduate student (hopefully from Argentina) that will be working on this project, which will enable close collaboration and development of lasting professional ties.

3.2.5 Outreach Efforts One of the main design criteria for this project is to foster tangible progress towards operational (or at least quasi operational) use of the information and products to be implemented. Special emphasis thus will be placed on the transfer of knowledge to administrators and technicians in governmental agencies such as the MAH, and to individual users. Users who are educated in the meaning and significance of climate information will probably make greater and better use of this information. The introduction of new products will be accompanied by training materials designed in collaboration with stakeholders. These materials will address knowledge gaps, wrong beliefs, and misconceptions about climate variability and flood and drought risks. On the other hand, materials may focus on specific products, such as a tutorial on the use and interpretation of the SPI. Outreach materials for the general public will be published in diverse venues, such as AACREA’s monthly magazine or Met Service bulletins

Participating investigators at the UNL maintain close links with several agrotechnical schools (high schools focusing on agricultural training) disseminated over the Salado Basin. These schools have a crucial role on the communication of technical innovations in their region, as most of the students come from farming families. Moreover, these schools also collect valuable meteorological information very useful for this project’s needs. Four of these schools are about to join the US-sponsored GLOBE program.

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4. SYNERGIES WITH ONGOING EFFORTSThe work proposed will provide an opportunity to test, on a relatively small scale, various approaches that can subsequently be transplanted to the larger Plata Basin. Given the economic significance of the Plata Basin for South America, regional experts recently have been developing the project “A Framework Program for Sustainable Water Resources Management in the la Plata Basin, with Respect to the Hydrological Effects of Climatic Variability and Change” to be supported by the Global Environmental Fund (GEF). We have agreed to collaborate with administrators (see letter of support) and scientists involved in this effort. One of the PIs in this proposal [Menéndez] is member of the Science Steering Committee to develop a Science Plan for the Plata Basin.

The tools to be used in this research, particularly, the weather generators and downscaling techniques were developed with NOAA-OGP funding (especially, the Western Water Assessment, WWA). Outcomes from this project will provide useful experience to the water management efforts in the Western US. The project also will benefit significantly from interactions with an OGP-sponsored project that, although focused on agriculture, is exploring existing mental models of climate variability in the study region, as well as existing institutional structures for production and dissemination of climate information. Further, investigators in this team are participating in NSF-sponsored projects exploring adaptive management in complex natural/human systems and decision-making under climate uncertainty. Results from the multiple perspectives offered by these complementary projects will provide rich insights.

5. PROJECT MANAGEMENTThis proposal is being simultaneously submitted by the University of Colorado (Dr. Balaji Rajagopalan, PI) and the University of Miami (Guillermo Podestá, PI). Drs. Rajagopalan and Podestá will share overall responsibility for project completion. Table 1 shows the major groups of tasks and the investigators who will lead each component.

Table 1. Project work plan, indicating major groups of tasks, responsibilities, and timing of each task.

RESEARCH COMPONENTS Year 1

Year 2

Year 3

Data Preparation and watershed model: testing/calibration of watershed model (Menendez/Rodriguez/Vionnet); data compilation (entire team)Synthetic daily series of hydroclimatic variables (stochastic weather generators) conditioned upon large-scale climate forecasts (Balaji, Podesta) – testing and validation on the data in the basin Translation of climate forecasts: Hydrologic scenarios generation by the watershed model drive with hydroclimatic scenarios conditioned on large-scale seasonal forecasts - testing/validation/skill assessment (Menendez, Balaji, Podesta)Hydroclimate products: Diagnostic, prognostic and management tools such as wetness/dryness indices, flood risk estimates etc. – these will be derived from data and watershed model (Menendez, Rodriguez,Vionnet,Balaji)Water Resources Management (Menendez, Podesta, Balaji)Social System Study (Podesta, regional social scientists)

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Rajagopalan and Podestá will collaborate on the translation of climate forecasts into hydrologic scenarios generation by the watershed model drive, including tests and validation. The Argentine co-PIs (Menéndez, Rodríguez and Vionnet) will be responsible for local data compilation (in collaboration with the Argentine Met Service) and the calibration and final integration of the hydrological model. All investigators will participate in the generation of hydroclimatic products. The development of decision maps and the institutional survey will be coordinated by G. Podestá, with the participation of a group of local social scientists to be recruited (two groups have been approached and agreed to collaborate). A graduate student from the study region will be recruited to complete a degree (MS or PhD) at the University of Colorado under the supervision of Dr. Rajagopalan.

6. RELEVANCE OF PROPOSED RESULTS The major outcomes of this project are twofold. First, we will demonstrate the potential for learning and change that will accelerate and expand the use of climate research outcomes and products in water management. The ability to integrate new information should facilitate learning and increase adaptive capacity, which is particularly important if climate variability increases in the future. An increase in adaptive capacity is critical in contributing to future resilience and sustainability of water systems. Second, we will develop experiences and insights, guiding principles, and “best practices” about the provision of climate information and services that can be transferred to other contexts and institutions elsewhere, particularly the United States. The proposed work, therefore, is highly relevant to NOAA’s strategic goal of understanding climate variability and change to enhance society’s ability to plan and respond. Because of strategic partnerships with foreign governmental institutions, academic and stakeholder-driven NGOs, this work will advance NOAA’s priority of fostering international collaboration and cooperation.

The proposed research activities will build on almost a decade of investment by NOAA and other funding agencies in the region, and will consolidate enhanced adaptive capacity to deal with climate variability in water resources management, an important and prevalent sector. The project will yield innovative products that will help bridge the gap between climate research insights and products, and water management decision needs. Several elements of this project should be highlighted: The design, production, and collaborative refinement of climate information products that reflect

stakeholders’ needs, are understandable to users, will be available at the times and places they are needed, and will be accessible through channels available to the user community.

The adaptation and assembly of existing tools to support adaptive decision-making and learning by exploring outcomes from alternative actions in response to plausible climate scenarios on inter-annual and inter-decadal scales;

An interdisciplinary approach, required to address problems in a real-world complex natural/human system;

A diverse and well-balanced team of investigators that draws equally from the social and natural sciences;

The active involvement of users of climate information that will ensure the relevance of the research and stakeholders’ ownership of the process, ultimately amplifying the project’s impact; and

The opportunity to test approaches and products in a relatively small basin, that subsequently may be applicable to the larger Plata Basin, the target of several ongoing and planned research efforts.

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Figure 1. Average annual streamflow of the Salado River, 1954-2002. The mean streamflow increases significantly after 1972 (vertical bar in the plot). The Qavg values indicated on either side of the vertical bar indicate annual streamflow averages for the 1954-1971 and 1972-2002 periods. Source: PROCIFE-Programa Institucional frente a la Emergencia (2003). Contribución al documento diagnóstico de la crecida del Río Salado presentado a Naciones Unidas. Coordinadores Generales: H. Arrillaga, C. Paoli y B. Frischi.

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Figure 2. Schematic description of the proposed research.

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García, N. O., and W. M. Vargas, 1998: The temporal climatic variability in the Río de La Plata basin displayed by the river discharges. Climatic Change, 38, 359-379. 

Genta, J., G. Perez-Iribarren, and C. Mechoso. 1998: A recent increasing trend in the streamflow of rivers in southeastern South America. Journal of Climate 11: 2858-2862.

Giampieri R., L. Rodríguez y C. Vionnet. Análisis de las condiciones de borde de un modelo de agua subterránea a escala regional en el centro-oeste de Santa Fe. III Congreso Nacional de Hidrogeología. Rosario, Set/03.

Giampieri R.C., P.A. Tassi, L.B. Rodríguez, y C.A. Vionnet. 2004. Simulacion Numérica de la Crecida Extraordinaria del Río Salado en la Ciudad de Santa Fe. Revista Internacional de Desastres Naturales, Accidentes e Infraestructura Civil, Puerto Rico. ISSN 1535-0088. 4: 85-102.

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Interannual Climate Predictions. International Journal of Climatology 21: 1111-1152.González M. and V. Barros. 1996. Aspectos estadísticos del ciclo anual de precipitación y sus anomalías en Argentina

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Niña events. Journal of Climate 13: 35-58.Grondona, M.O., G.P. Podestá, M. Bidegain, M. Marino, and H. Hordij. 2000. A stochastic precipitation generator conditioned

on ENSO phase: A case study in southeastern South America. Journal of Climate 13: 2973-2986.Hayes, M.J., M.D. Svoboda, D.A. Wilhite, and O.V. Vanyarkho. 1999. Monitoring the 1996 drought using the Standardized

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115.Lall, U., and A. Sharma, A nearest neighbor bootstrap for time series resampling, Water Resour. Res., 32(3), 679–693, 1996.Lemos, M.C., T.J. Finan, R.W. Fox, D.R. Nelson, and J. Tucker. 2002. The use of seasonal climate forecasting in policymaking:

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Pulwarty, R.S. and T.S. Melis. 2001. Climate extremes and adaptive management on the Colorado River: Lessons from the 1997–1998 ENSO event. Journal of Environmental Management 63: 307–324.

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Oscillation. Journal of Climate 2: 268-284.Rusticucci, M., and O. Penalba. 2000. Interdecadal changes in the precipitation seasonal cycle over Southern South America and

their relationships with surface temperature. Climate Research 16: 1-15.Rusticucci, M., and W. Vargas. 2002. Cold and warm events over Argentina and their relationships with the ENSO phases: Risk

evaluation analysis. International Journal of Climatology 22: 467-483.Satorre, E.H. 2001. Production Systems in the Argentine Pampas and their Ecological Impact. In: Solbrig, O., R. Paalberg and F.

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2002, User Manual.VAMOS Scientific Study Group. 2001. Climatology and Hydrology of the La Plata Basin. Available at:

http://www.atmos.umd.edu/~berbery/lpb/index.html.Vargas, W., O.C. Penalba, and J.L. Minetti. 1999. Las precipitaciones mensuales en zonas de la Argentina y el ENOS. Un

enfoque hacia problemas de decisión. Meteorológica 24: 3-22.Viglizzo, E.F., Z.E. Roberto, M.C. Filippin and A.J. Pordomingo. 1995. Climate variability and agroecological change in the

Central Pampas of Argentina. Agriculture, Ecosystems and Environment 55: 7-16.Viglizzo, E.F., Z.E. Roberto, F. Lértora, E. Lopez Gay and J. Bernardos. 1997. Climate and land use change in field crop

ecosystems of Argentina. Agriculture, Ecosystems and Environment 66: 61-70.Wernstedt, K. and R. Hersh. 2002. Flood planning and climate forecasts at the local level. Resources for The Future, Discussion

Paper 02-07.Wejnert, B. 2002. Integrating models of diffusion of innovations: A conceptual framework. Annual Review of Sociology 28:

297-326.Wilks, D. Forecast value in prescriptive decision studies, in Economic Value of Weather and Climate Forecasts, edited by R. W.

Katz and A. H. Murphy, pp. 109– 145, Cambridge Univ. Press, New York, 1997.Wilks, D., and R. Wilby. 1999. The weather generation game: a review of stochastic weather models. Progress in Physical

Geography. 23: 329-357.Yates, D., S. Gangopadhyay, B. Rajagopalan, and K. Strzepek, A technique for generating regional climate scenarios using a

nearest neighbor algorithm: Water Resour. Research, 39(7), 1199, doi:10.1029/2002WR001769, 2003.Ziervogel, G. 2004. Targeting seasonal climate forecasts for integration into household level decisions: the case of smallholder

farmers in Lesotho. The Geographical Journal 170: 6-21.Ziervogel, G. and T. Downing. 2004.Stakeholder networks: improving seasonal climate forecasts. Climatic Change65: 73-101.Ziervogel, G. and R. Calder. 2003. Climate variability and rural livelihoods: assessing the impact of climate forecasts in Lesotho.

Area 35: 403-417.

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E. University of Colorado’s Budget and Budget Justification

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University of Colorado’s Budget Discussion

We note that the budget is somewhat high in large part due to out of state tuition for the graduate student for all the three years. We plan to have a student from Argentina, preferably working with the Co-PIs there. The student will be in the graduate program of Department of Civil Environmental and Architectural Engineering at University of Colorado, Boulder and will work on this proposed research. This will enable close collaboration, effective technical transfer and capacity building. The student will be supervised by the PIs, R. Balaji and G. Podesta. If we are unable to get a student from Argentina then we will recruit a student locally and this can reduce the budget by about $50~60K.

Dr. Edith Zagona, Co-PI, is budgeted for 0.25 month per year for the first two years. Dr. Zagona is an expert on Water Resources Decision Support System and also is the director of Center for Decision Support for Water and Environmental Systems (CADSWES, http://cadswes.colorado.edu). This center is supported by the USBR. Dr. Zagona will meet with the water managers on the The Río Salado del Norte Basin to introduce them to DSS tools and experiences from the Western US water management and, explore opportunities for developing a DSS on the Río Salado. While development of a DSS tool is not an explicit part of the proposal we feel her involvement at essentially no cost can foster greater collaboration between the Federal agencies of US and Argentina. To this end, funds for one trip to Argentina in the first year by the PI and Co-PI, Edith Zagona is requested. Also, the student will be hosted by CADSWES, thus, enabling interactions to develop a DSS.

Leveraging funds from other projects that address somewhat related topics (for example, an NSF Biocomplexity project focused on adaptive responses to climate in the agriculture sector), only half a summer month each year is budgeted for the PI, R. Balaji.

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F. Supporting Documentation

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F. Investigators’ VitaeBiographical Sketch

RAJAGOPALAN BALAJI

PROFESSIONAL PREPARATION Kurukshetra University, India, B. Tech. (with honors) in Civil Engineering, 1989

Indian Statistical, Calcutta, India, M. Tech. (with honors) in Operations Research and Quality Reliability, 1991

Utah State University, Logan, UT, USA, PhD in Civil Engineering (Stochastic Hydroclimatology), 1995

APPOINTMENTS

2000 (Aug) - present Assistant Professor, Department of Civil, Environmental and Architectural Engineering, University of Colorado at Boulder.

2001 (June) – present Fellow, Co-operative Institute for Research in Environmental Sciences (CIRES, University of Colorado, Boulder, CO.

2000 (Aug) – present Adjunct Associate Research Scientist, International Research Institute (IRI), Lamont-Doherty Earth Observatory (LDEO), Columbia University, NY

1999 (July) – 2000 (August) Associate Research Scientist, International Research Institute (IRI), Lamont-Doherty Earth Observatory (LDEO), Columbia University, NY

1997 (July) – 1999 (June) Associate Research Scientist, Lamont-Doherty Earth Observatory (LDEO), Columbia University, NY

1995 (April) – 1997(June) Post-Doctoral Research Scientist, Lamont-Doherty Earth Observatory (LDEO), Columbia University, NY

1991 (Oct) – 1995 (April) Graduate Research Assistant, Utah Water Research Laboratory, Utah State University, Logan, UT

HONORS AND AWARDSDistinguished Utah State University Dissertation in Engineering: 1993-1995. Utah State University nomination for

the Council of Graduate Schools Distinguished Dissertation Award.Honorable mention, 1996 Award for the Outstanding Water Resources Dissertation in the field of Engineering and

Physical Sciences,The Universities Council on Water Resources.Nominated for the 1996 Lorenz G. Straub award for the most meritorious thesis in hydraulics and hydrology and

finished in the top three.Young Researcher award: 2003. Department of Civil Environmental and Architectural, University of Colorado,

Boulder, CO.Participated in the 15th Annual Beckman Frontiers of Science Symposium, National Academy of Sciences, Irvine,

CA, Nov 6 – 8, 2003.

RESEARCH INTERESTSStochastic Hydrology and Hydroclimatology; Nonparametric functional estimation techniques (probability density Functions, regression, scenarios generation, forecasting); Understanding low frequency climate variability and its signatures on regional hydrology; Incorporating climate information in water resources/hydrologic decision making; Understanding spatio-temporal variability in Indian summer monsoon; Stochastic modeling of hurricane tracks; Nonlinear Dynamics - recovering dynamics from data; Bayesian techniques for optimal combination of information from multiple sources and decision making.

PUBLICATIONS(i) Publications most closely related to the proposed projectRajagopalan, B., U. Lall, and M. A. Cane, Anomalous ENSO occurrences: an alternate view, Journal of Climate,

10(9), 2351-2357,1997.

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Rajagopalan, B., and U. Lall, Nearest Neighbor Local Polynomial Estimation of Spatial Surfaces, Spatial Interpolation Comparison Contest 1997, Journal of Geographic Information and Decision Analysis, 2(2), 48-57, 1998.

Rajagopalan, B., and U. Lall, A Nearest Neighbor Bootstrap Resampling Scheme for Resampling Daily Precipitation and other Weather Variables,Water Resources Research, 35(10), 3089-3101, 1999.

Rajagopalan, B., U. Lall, and S. Zebiak, Optimal Categorical Climate Forecasts through Multiple GCM Ensemble Combination and Regularization, Monthly Weather Review, 130, 1792 – 1811, 2002

Clark, M., S. Gangopadhyay, D. Brandon, K. Werner, L. Hayes, B. Rajagopalan and D. Yates, A Resampling procedure for generating conditioned daily weather sequences Water Resources Research, 40, W04304, 2004.

(ii) Other significant publicationsKrishnaKumar, K., B. Rajagopalan, and M.A. Cane, On the weakening relationship between the monsoon and

ENSO, Science, 284, 2156-2159, 1999.Rajagopalan, B., E. Cook, U. Lall, B. Ray, Temporal Variability of ENSO-drought association in the South West

US, Journal of Climate, 13, 4244-4255, 2000.Tourre, Y., B. Rajagopalan, and Y. Kushnir, Dominant patterns of climate variability in the Atlantic ocean region

during the last 136 years, Journal of Climate, 12, 2285-2289,1999.Phillips, J., B. Rajagopalan, M. Cane, and C. Rosenzweig, The Role of ENSO in determining climate and maize

yield variability in the US cornbelt, International Journal of Climatology, 19, 877-888,1999.Rajagopalan, B., M. E. Mann and U. Lall, A multivariate frequency-domain approach to long-lead climatic

forecasting, Weather and Forecasting, 13(1), 58-74, 1998.

SYNERGISTIC ACTIVITIESAssociate Editor, Geophysical Research Letters and ASCE - Journal of Hydrologic EngineeringMember, The American Geophysical UnionMember, Precipitation Committee, AGU Hydrology section.Reviewer, Water Resources Research, Science, Geophysical Research Letters, Journal of Hydrologic Engineering, Journal of Climate, Tellus, NSF, NOAA and NASA proposals.Organized a session titled Low frequency climate variability signatures on regional hy drometeorological variables - implications to hydrologic forecasting and planning at the Spring meeting of AGU, Boston, May, 1998.Organized a session titled “Incorporating climate variability information in water resources decision making”, at the Fall AGU, San Fransisco, Dec 2002.

COLLABORATORS & OTHER AFFILIATIONS(i) CollaboratorsClark, M., CIRES/Univ. of Colorado at Boulder; Kushnir, Y., Columbia Univ. at NYC; K. Krishna Kumar, Indian Institute of Tropical Meteorology, Pune, India; Lall U., Columbia Univ. at NYC; Hoerling, M, Pulwarty, R., CDC-NOAA/Univ. of Colorado at Boulder; Katz, R., NCAR, Boulder; Podesta, G., Univ. of Miami, Miami; Zagona, E., CADWES/Univ. of Colorado at Boulder; Zebiak, S., IRI/Columbia Univ. at NYC;

(ii) Graduate and Postdoctoral AdvisorsUpmanu Lall, Columbia University, NY, Mark Cane, Columbia University, NY.

(iii) Theses Advised (at University of Colorado, Boulder) MS David Newmann; James Prairie; Katrina Grantz; Nkrintra Singhrattna; AdamHobson and J. D. EmmertPhD Yeonsang Hwang (iv)Advisors for Research AssociatesDr. Subhrendu Gangopadhyay, University of Colorado, Boulder, CO, 2002 - Dr. Krishna Kumar, Visiting Fellow, CIRES/University of Colorado, Boulder, CO 2003-2004

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Biographical SketchEDITH A. ZAGONA, Ph.D., P.E.

DirectorCenter for Advanced Decision Support for Water and Environmental Systems (CADSWES)

Department of Civil, Environmental and Architectural EngineeringCampus Box 421, University of Colorado at Boulder, Boulder, Colorado 80309-0421

(303) 492-2189, E-mail:zagona@cadswes.colorado.edu

Academic DegreesPh.D., Civil Engineering, University of Colorado, 1992 Thesis: “Model-Predictive Control of Automated Canals” M.S.C.E., Hydraulics, Colorado State University, 1983B.S., Civil Engineering, University of Arizona,1978 B.A., Philosophy and Mathematics, University of Arizona, 1975

AppointmentsSince March 2001 Interim Director, CADSWES.

Since September 1992: Research Associate, CADSWES. Principal Investigator of Research and development of RiverWareTM since 1993.

January 1988 - August 1992: Professional Research Assistant, CADSWES. PI of research grants with Imperial Irrigation District associated with doctoral research.

February 1986 - March 1987: Design and Planning Coordinator for the Central Arizona Project, U.S. Bureau of Reclamation, Arizona Projects Office, Phoenix, Arizona, 1985-87.

July 1978 - February 1984: Hydraulic Engineer, Water Conveyance Branch, U.S. Bureau of Reclamation Engineering and Research Center, Denver, Colorado, 1978-1984.

Recent Research and Development ActivitiesPrincipal Investigator for research and development of RiverWareTM, a river basin simulation and optimization model licensed internationally by the University Technology Corporation. Since 1993, grants totaling approximately $12 million with Tennessee Valley Authority, Electric Power Research Institute, U.S. Bureau of Reclamation and U.S. Army Corps of Engineers. Lead team of 15 to 20 professional researchers, water resources engineers, software developers and student assistants.

Recent PublicationsNeumann, D., B. Rajagopalan, and E. Zagona, " A regression model for daily maximum stream temperature" (accepted) ASCE Journal of Environmental Engineering, July 2003.

Wheeler, K., T.M. Magee, T. Fulp, and E. Zagona, " Alternative Policies on the Colorado River," Proceedings of University of Colorado Natural Resources Law Center Conference: Allocating and Managing Water for a Sustainable Future: Lessons From Around the World, Boulder, Colorado, June 2002.

Zagona, E.A., Fulp, T.J., Shane, R., Magee, T. and Goranflo, H.M. “RiverWare: A Generalized tool For Complex River Basin Modeling,” Journal of American Water Resources Association, August 2001.

Magee, T, Zagona, E. and Frevert D., "Operational Policy Expression and Analysis in the RiverWare Modeling Tool," to appear in Environmental and Water Resources Institute’s (EWRI’s) World Water & Environmental Resource Congress, ASCE New York, NY, 2001.

Eschenbach, E., Magee, T., Zagona, E., Goranflo, M. and Shane, R. “Multiobjective Daily Operations of Reservoir Systems via Goal Programming,” ASCE Journal of Water Resources Planning and Management, March 2001.

Zagona, E. and Magee, T., “Modeling Hydropower in RiverWare,” in “Waterpower ‘99, Proceedings of the International Conference on Hydropower, ASCE New York, NY, 1999.

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Current and Pending Support for RAJAGOPALAN BALAJI

NSF(current)

The role of tropical Asian landcover changes in altering large-scale atmospheric circulations : interaction with ENSO and the Asian summer monsoon (with PI Tom Chase)

$222,365 12/1/04 – 11/30/06

1 month summer

AWWARF(tentatively

awarded – pending official intimation)

Decision tool to help utilities develop simultaneous compliance strategies(Macolm Pirnie, CU Boulder and Stratus Consuting)

$400,000CU portion

$90,000

9/1/05 – 8/31/08 1 month summer

USBR(current)

Stochastic hydrology study of Colorado river flow and salinity

$25,000 09/04 - 03/06 1 month summer

NSF(pending)

Integrated Framework for Modeling Climate Impact on Transportation Network Reliability

$475,407 10/05 – 09/08 1 month summer

NSF(pending)

Integrated Framework for Modeling the Impact of Climate and Weather on Transportation Infrastructure Performance (with Y. Xi, Co-PI)

$441,989 01/06 – 12/08 1 month summer

NOAA(pending)

Transforming climate information into usable knowledge to enhance decision-making in water resources management of the Río Salado del Norte Basin, Argentina(with PI, G. Podesta)

$402,930CU portion$206,481

3/1/06 – 8/31/08 0.5 month summer

NATIONAL ENVIRONMENTAL POLICY ACT STATEMENT

The research activities that will be carried out in this project is analysis and synthesis of observed climate and hydrological data. These datasets are readily available to the PIs. This work will be carried out at the University of Colorado at Boulder, Rosenstiel School campus of the University of Miami and, at the collaborating institutions in Argentina. The work will make no impact on species or habitat. It includes no construction activities. There are no environmental concerns.

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SOURCE PROJECT TITLE AWARD AMOUNT

DURATION TIMECOMMITTED

NOAA(current)

Understanding the spatio-temporal variability of the North American Monsoon: Implications to Water Resources Management in the South Western US (with E. Zagona, M. Clark, S. Gangopadhyay and A. Ray Co-PI)

$213,427 9/1/03 - 8/31/06 1.0 month summer

NSF(current)BE/CNH(current)

Understanding and Modeling the scope for adaptive management in agroecosystems in the Pampas in response to interannual and decadal climate variabilty and other risk factors (with PI, G. Podesta, Co-PI, R. Katz, E. Weber, W. Easterling)

$1,600,000CU portion$190,000

9/1/04 – 8/31/07 0.6 month summer