Hydroclimatic Information Research Articles

Construction and testing of a low-cost device for the collection of rainfall samples destined for stable isotope analysis

Oxygen- and hydrogen-isotope ratios in rainfall provide important hydroclimatic information, yet despite a global network of rainfall isotope measurements, significant geographical gaps exist in data coverage, with only three long-term stations spanning the southern African region. Project-based, ad hoc collections of rainfall for isotope analysis can improve this coverage. However, all rainfall samples that are destined for stable isotope analysis must be collected in such a way to avoid evaporation and resultant isotope fractionation. While such rainwater collectors are available commercially, both the product and shipping are prohibitively costly. We describe the construction of a simple rainfall collector using a design from the literature and materials that are readily available in South African hardware stores. Our rainwater collector can be constructed for the much lower cost of just under ZAR820 in comparison with the cost of ZAR9300 inclusive of shipping from commercial outlets (2022 prices). Our design modifications have the added advantage of portability, with the rainwater collector housed in a bucket with a handle. The device was tested by comparing its performance, in terms of evaporative water loss and isotopic fractionation, with that of an open bottle, using tap water in both cases. Testing confirmed that the collector prevented evaporation over a one-week period, indicating that it is suitable for weekly or more frequent sampling of rainfall. Although the design described was based on materials procured in South Africa, it could easily be adapted for construction elsewhere. Significance: Hydrogen and oxygen isotope composition of rainfall provides valuable climatic information. Rainwater collectors for stable isotope samples must prevent evaporation, as evaporation will alter the isotopic signature. We describe the construction and testing of a bespoke, low-cost and portable device that can be used to collect rainfall samples destined for oxygen- and hydrogen-isotope analysis without significant evaporation.

Hydrological Web Services for Operational Flood Risk Monitoring and Forecasting at Local Scale in Niger

Emerging hydrological services provide stakeholders and political authorities with useful and reliable information to support the decision-making process and develop flood risk management strategies. Most of these services adopt the paradigm of open data and standard web services, paving the way to increase distributed hydrometeorological services’ interoperability. Moreover, sharing of data, models, information, and the use of open-source software, greatly contributes to expanding the knowledge on flood risk and to increasing flood preparedness. Nevertheless, services’ interoperability and open data are not common in local systems implemented in developing countries. This paper presents the web platform and related services developed for the Local Flood Early Warning System of the Sirba River in Niger (SLAPIS) to tailor hydroclimatic information to the user’s needs, both in content and format. Building upon open-source software components and interoperable web services, we created a software framework covering data capture and storage, data flow management procedures from several data providers, real-time web publication, and service-based information dissemination. The geospatial infrastructure and web services respond to the actual and local decision-making context to improve the usability and usefulness of information derived from hydrometeorological forecasts, hydraulic models, and real-time observations. This paper presents also the results of the three years of operational campaigns for flood early warning on the Sirba River in Niger. Semiautomatic flood warnings tailored and provided to end users bridge the gap between available technology and local users’ needs for adaptation, mitigation, and flood risk management, and make progress toward the sustainable development goals.

Multi-Criteria Performance Evaluation of Gridded Precipitation and Temperature Products in Data-Sparse Regions

Inadequate climate data stations often make hydrological modelling a rather challenging task in data-sparse regions. Gridded climate data can be used as an alternative; however, their accuracy in replicating the climatology of the region of interest with low levels of uncertainty is important to water resource planning. This study utilised several performance metrics and multi-criteria decision making to assess the performance of the widely used gridded precipitation and temperature data against quality-controlled observed station records in the Lake Chad basin. The study’s findings reveal that the products differ in their quality across the selected performance metrics, although they are especially promising with regards to temperature. However, there are some inherent weaknesses in replicating the observed station data. Princeton University Global Meteorological Forcing precipitation showed the worst performance, with Kling–Gupta efficiency of 0.13–0.50, a mean modified index of agreement of 0.68, and a similarity coefficient SU = 0.365, relative to other products with satisfactory performance across all stations. There were varying degrees of mismatch in unidirectional precipitation and temperature trends, although they were satisfactory in replicating the hydro-climatic information with a low level of uncertainty. Assessment based on multi-criteria decision making revealed that the Climate Research Unit, Global Precipitation Climatology Centre, and Climate Prediction Centre precipitation data and the Climate Research Unit and Princeton University Global Meteorological Forcing temperature data exhibit better performance in terms of similarity, and are recommended for application in hydrological impact studies—especially in the quantification of projected climate hazards and vulnerabilities for better water policy decision making in the Lake Chad basin.

Combining satellite-based rainfall data with rainfall - runoff modelling to simulate low flows in a Southern Andean catchment

Since 2010, Chile has been affected by a long-term drought, often referred to as the Mega-Drought. To adapt to future drought events, we need reliable hydro-climatic information based on robust observations and models. However, reliable hydro-climatic data needed for hydrological modelling of remote Andean catchments are rarely available. Our objective was therefore to identify the most suitable combination of different rainfall estimates with two rainfall-runoff models of varying complexity to reliably simulate low flows related to drought.We forced the widely used SWAT and HBV-light models with four satellite-based rainfall estimates (SREs) (CHIRPSv2, MSWEPv1.2, MSWEPv2.0, TMPA 3B42v7) and inverse distance weighted (IDW) precipitation observations for the main headwater catchment of the Imperial River basin (Araucania, 38°N). Sobol global sensitivity analysis and calibration were carried out using the hydroPSO R package, using two objective functions focused on the performance of low flows (logNSE and low flows KGE).Despite the differing amount and temporal distribution of water, for all four SREs, the Sobol sensitivity analysis resulted in robust identification of key model parameters for all SWAT optimisation runs, with most sensitivity for parameters related to deep groundwater recharge, lateral flow travel time and the SCS runoff curve number. For the HBV-light model, only parameters related to snow-melt and deep groundwater recharge were robustly identified for the wetter SRE products. For both models and the two objective functions, the best efficiencies were obtained with the wetter SREs (MSWEP v1.2 and CHIRPSv2) as well as with IDW.We found that SREs combined with rainfall-runoff modelling provide a valuable instrument to simulate daily discharges for the Upper Imperial River Basin. The resulting models are hence suitable to project low flows and water availability; information that is requested by local decision makers needed to design irrigation systems for the agricultural downstream area and the secure water supply of settlements in the context of future droughts.

Modelación hidrológica para medir el impacto del cambio climático en la cuenca del río Yaqui

Objective: To model and analyze the behavior of surface runoff in the Yaqui river basin under climate change scenarios. Methodology: Representative concentration pathways (RCP) of three sub-basins (La Angostura, El Novillo and El Oviachic) were shown using hydrologic modeling with SWAT, where the simulated variable was surface runoff. Results: A change in water availability of -67 % is expected in La Angostura for the period 2021-2040 (RCP2.6) and an increase of 60 % from 2041-2060 (RCP8.5), in El Novillo a decrease of 65 % is predicted for the period 2061-2080 (RCP4. 5) and a 42 % increase from 2061-2080 (RCP2.6), and in El Oviachic a 63 % decrease is predicted for the period 2041-2060 (RCP2.6 and 4.5) and a 47 % increase from 2041-2060 (RCP4.5). Limitations: Veracity and impact of basins studies depend on quality hydro-climatic information of unrestricted availability. Originality: The impact of climate change on the availability of water for agricultural use in the Yaqui River basin was projected. In addition, there is a technological platform for planning processes. Conclusions: The data collected can be used to generate adaptation and mitigation strategies for efficient water use in the basin and to propose long-term sustainable management alternatives.

Hydroclimatic Information Needs of Smallholder Farmers in the Lower Bengal Delta, Bangladesh

Hydroclimatic information services are vital for sustainable agricultural practices in deltas. They advance adaptation practices of farmers that lead to better economic benefit through increased yields, reduced production costs, and minimized crop damage. This research explores the hydroclimatic information needs of farmers by addressing (1) what kind of information is needed by the periurban delta farmers, and (2) whether information needs have any temporal dimension that changes with time following capacity building during coproduction of information services. Results reveal that the attributes of weather and water-related forecasts most affecting the farmers are rainfall, temperature, water, and soil salinity, along with extreme events such as cyclone and storm surges. The majority of the male farmers prefer one- to two-week lead-time forecasts for strategic and tactical decision-making; while female farmers prefer short-time forecasts with one-day to a week lead time that suggests the difference of purpose of the forecasts between male and female farmers. Contrarily, there is little preference for monthly, seasonal, and real-time forecasts. Information communication through a smartphone app is preferred mostly because of its easy accessibility and visualization. Farmers foresee that capacity building on acquiring hydroclimatic information is vital for agricultural decision-making. We conclude that a demand-driven coproduction of a hydroclimatic information service created through iterative interaction with and for farmers will enable the farmers to understand their information needs more explicitly.

Role of Information in Farmers’ Response to Weather and Water Related Stresses in the Lower Bengal Delta, Bangladesh

Farmers in the lower Bengal Delta around the city of Khulna, Bangladesh, are particularly vulnerable to hydro-climatic variability. Phenomena such as heavy rain, drought and salt intrusion increasingly affect their crop production, with far-reaching socio-economic and environmental impacts. Reliable hydro-climatic information service received in a timely manner could help farmers improve their responses to hydro-climatic variability, thus improving their agricultural decision-making. However, significant challenges persist regarding information uptake and the role of information from the available sources. We designed an explorative research framework combining different participatory methods and analysis of climate data. Our aim was to examine three key research questions: (i) what information is currently available to farmers for agricultural practices and decision-making? (ii) what is the perceived quality of the available hydro-climatic information in response to water and weather related stresses? (iii) how does the available information influence farmers’ decision-making? We found that farmers had access to information from five main sources: informal contacts, formal contacts, education and training programs, traditional media (like television) and modern ICT tools/social media. However, informal contacts, particularly with peer farmers and private input suppliers, were the farmers’ main source, in addition to their own previous experiences. Farmers perceived hydro-climatic variability as high and the quality of available hydro-climatic information as poor. They indicated a need for more accurate, time-specific, trusted and actionable information for improving agricultural decision-making. We conclude that there is high potential and need for hydro-climatic information services tailored for farmers in the study area.

Runoff reconstruction and climatic influence with tree rings, in the Mayo river basin, Sonora, Mexico

Abstract: Dendrochronological series are reliable sources of information to analyze past hydrological and climatological variation that provides useful information for the management of water resources within basins. We analyzed dendrochronological series obtained from the upper Mayo River Basin using principal components analysis to determine a common climatic signal. Although the complete series extended for over 350 years, the representative period common to all series was from 1750 to 2014 (265 years) with an expressed population signal of over 0.85. Climate data (precipitation and temperature) were collected from the North American Land Data Assimilation System 2 model of the Land Data Assimilation System and hydrometrics records were obtained from the National Commission of Water in Mexico. The results of the response function showed an association of mean monthly temperature with the ring width series for the months of December of the previous year, May and October of the year of growth, and seasonally from January to July (r = -0.75, n = 36, p < 0.05). A significant response to rainfall of earlywood growth was observed for June, November, and December of the previous year, January and February of the growth year, and seasonally, from October of previous year to May of the current growth year (r = 0.70, n = 35, p < 0.05). Significant association also was found between earlywood and the accumulated runoff from October of the previous year to May of the growth year, which was used for reconstruction of the runoff flow between 1750 and 2014, which showed evidence of decadal drought. Significant correlation was found between the reconstructed runoff series, and the Southern Oscillation index (r = -0.42, n = 228, p < 0.05), but not significant with the Pacific Decadal Oscillation index (r = 0.16, n = 115, p < 0.05). We also observed significant (p < 0.05) associations with the drought indices Palmer Drought Severity Index and Standardized Precipitation Evapotranspiration Index (r = 0.56, r = 0.41, respectively). Our study demonstrated the potential of assimilated data for dendroclimatic reconstructions and the feasibility of generating hydroclimatic information of extreme events that have not been recorded in the available climatic and hydrological instrumental records.

The Critical Role of Communities of Practice and Peer Learning in Scaling Hydroclimatic Information Adoption

Abstract Significant effort has been put into advancing the use and usability of information products to support adaptation to drought and climate variability, particularly for the water supply sector. Evidence and experience show that advancing the usability of information through processes such as coproduction is time consuming for both providers and users of information. One challenge for boundary organizations and researchers interested in enhancing the usability of their information is how such processes might “scale” to all the potential organizations and individual managers that might possibly be able to benefit from improved climate information. This paper examines information use preferences and practices specifically among managers of small water systems in the Upper Colorado River basin, with an eye toward identifying new opportunities to effectively scale information usability and uptake among all water managers—regardless of location or capacity—in a resource-constrained world. We find that boundary organizations and other usable science efforts would benefit from capitalizing on the communities of practice that bind water managers together. Specifically, strategic engagement with larger, well-respected water systems as early adopters, supporting dissemination of successes and experiences with new information products among a broader community of water managers, and increasing well-respected water systems’ capacity to engage directly with rural systems may all serve as useful strategies to promote widespread distribution, access, and adoption of information.

Evaluation of hydroclimatic variables for maize yield estimation using crop model and remotely sensed data assimilation

We used the Decision Support System for Agro-technology Transfer-Cropping System Model (DSSAT) and data assimilation scheme (DSSAT-DA) to estimate maize (i.e., corn) yield and to evaluate the sensitivity of maize yield to hydroclimatic variables (i.e., precipitation, air temperatures, solar radiation, soil water). The remotely sensed soil moisture products, which includes Advanced Microwave Scanning Radiometer and the Soil Moisture and Ocean Salinity, were assimilated to DSSAT model by using the Ensemble Kalman Filtering approach. It was observed that both DSSAT and DSSAT-DA models can able to capture the annual trend of maize yield, although they overestimate the observed maize yield. The DSSAT-DA scheme assimilated with remotely sensed products slightly improves the model performance. The antecedent hydroclimatic information can influence the subsequent maize yield. The maize yield is sensitive to the soil water availability and precipitation amount, especially at the antecedent 1 month time to sowing and the subsequent second and third month’s growing period.

Verification of Seasonal Climate Forecast toward Hydroclimatic Information Needs of Rice Farmers in Northern Ghana

Abstract Farmers in sub-Saharan Africa face many difficulties when making farming decisions due to unexpected changes in weather and climate. Access to hydroclimatic information can potentially assist farmers to adapt. This study explores the extent to which seasonal climate forecasts can meet hydroclimatic information needs of rice farmers in northern Ghana. First, 62 rice farmers across 12 communities were interviewed about their information needs. Results showed that importance of hydroclimatic information depends on the frequency of use and farming type (rain-fed, irrigated, or both). Generally, farmers perceived rainfall distribution, dam water level, and temperature as very important information, followed by total rainfall amount and onset ranked as important. These findings informed our skills assessment of rainfall (Prcp), minimum temperature (Tmin), and maximum temperature (Tmax) from the European Centre for Medium-Range Weather Forecasts (ECMWF-S4) and at lead times of 0 to 2 months. Forecast bias, correlation, and skills for all variables vary with season and location but are generally unsystematic and relatively constant with forecast lead time. Making it possible to meet farmers’ needs at their most preferred lead time of 1 month before the farming season. ECMWF-S4 exhibited skill in Prcp, Tmin, and Tmax in northern Ghana except for a few grid cells in MAM for Prcp and SON for Tmin and Tmax. Tmin and Tmax forecasts were more skillful than Prcp. We conclude that the participatory coproduction approach used in this study provides better insight for understanding demand-driven climate information services and that the ECMWF-S4 seasonal forecast system has the potential to provide actionable hydroclimatic information that may support farmers’ decisions.

Diagnosing the potential of hydro-climatic information services to support rice farming in northern Ghana

Hydro-climatic information has a potential to improve agricultural productivity under climate variability. Recent developments in information sharing platforms (Environmental Virtual Observatories, EVOs) could make information provisioning more actionable. Here we present the results of a diagnostic study for the development of a hydro-climatic EVO that enables rice farmers in Northern Ghana to deal with climate variability and water shortage. The hydro-climatic EVO aims to combine data from scientific and indigenous forecast systems, facilitating information exchange using two-way interaction with stakeholders to co-produce knowledge. Data was collected through informal interviews with field practitioners, through focus group discussions with farmers and content analysis of documents. Results show that both the biophysical and socio-institutional circumstances need be taken into account for the development of the EVO. Existing governance and information exchange arrangements and lack of collaboration between actors were found to limit current hydro-climatic information flow, interpretation, and use. Our study reveals existing models of information exchange and their limitations in the study area. We discuss the proposed design of a hydro-climatic EVO from a responsible innovation perspective, considering possible future eventualities in a process that aims to be anticipatory, inclusive, reflexive and responsive. We conclude that such a hydro-climatic EVO has a potential to contribute to rice farmers’ adaptive decision-making in Northern Ghana, but there are challenges that need to be considered. The diagnostic study has helped to refine these challenges and offers concrete suggestions to improve both the design and implementation of the proposed platform in a responsible way.

Governance arrangements and adaptive decision-making in rice farming systems in Northern Ghana

Climate variability has consequences on water availability in rice farming systems. In Ghana, rice farmers in the Northern Savannah are amongst the most vulnerable to long periods of drought and erratic rainfall conditions. Within the Kumbungu district, farmers engaged in both rain-fed and irrigated rice farming are no exception. Coping with uncertain water availability conditions requires adaptive decision-making for sustained productivity in rice cropping. From an adaptive governance perspective, the extent to which formal and traditional governance arrangements enable adaptive decisions amongst rice farmers remains a key question. Using an exploratory research design, the study investigates three key questions; what water-dependent decisions rice farmers take and how these are adaptive to changing water availability conditions; what formal and informal governance arrangements rice cropping decisions are embedded in; and how existing governance arrangements enable or constrain adaptive decision-making. Rice farmers in twelve communities around the Bontanga Irrigation Scheme in the Kumbungu District in the Northern region were engaged through individual interviews and focus group discussions. The study reveals that farmers take six major water-dependent decisions throughout the cropping season; decision to or not to plant rice, land preparation, planting, weed control, fertilizer application and harvesting. Farmer decisions are most adaptive to water availability conditions during planting and fertilizer application. Both formal and traditional governance arrangements influence the extent to which farmers are able to adapt to changes in water availability conditions. The paper also reflects on the potential of hydro-climatic information and the place of Environmental Virtual Observatories (EVOs) in adaptive governance and decision-making.

Quantification of Rotavirus Diarrheal Risk Due to Hydroclimatic Extremes Over South Asia: Prospects of Satellite-Based Observations in Detecting Outbreaks.

Rotavirus is the most common cause of diarrheal disease among children under 5. Especially in South Asia, rotavirus remains the leading cause of mortality in children due to diarrhea. As climatic extremes and safe water availability significantly influence diarrheal disease impacts in human populations, hydroclimatic information can be a potential tool for disease preparedness. In this study, we conducted a multivariate temporal and spatial assessment of 34 climate indices calculated from ground and satellite Earth observations to examine the role of temperature and rainfall extremes on the seasonality of rotavirus transmission in Bangladesh. We extracted rainfall data from the Global Precipitation Measurement and temperature data from the Moderate Resolution Imaging Spectroradiometer sensors to validate the analyses and explore the potential of a satellite‐based seasonal forecasting model. Our analyses found that the number of rainy days and nighttime temperature range from 16°C to 21°C are particularly influential on the winter transmission cycle of rotavirus. The lower number of wet days with suitable cold temperatures for an extended time accelerates the onset and intensity of the outbreaks. Temporal analysis over Dhaka also suggested that water logging during monsoon precipitation influences rotavirus outbreaks during a summer transmission cycle. The proposed model shows lag components, which allowed us to forecast the disease outbreaks 1 to 2 months in advance. The satellite data‐driven forecasts also effectively captured the increased vulnerability of dry‐cold regions of the country, compared to the wet‐warm regions.

Tree-ring δ18O, a tool to crack the paleo-hydroclimatic code in subtropical China

Tree ring plays an important role in deciphering the paleoclimatic signals. Although tree-ring width (TRW) has obvious advantages in studying the hydroclimatic history in the middle-high latitudes, it has certain limitation in hydroclimatic signal extraction in the tropical to subtropical areas, which greatly limits our fully understanding about the hydroclimatic history in these areas. In this work, tree-ring δ18O (δ18Otree) records from five independent tree-ring cores were measured and a composite δ18Otree record (1939–2014) was developed in Guilin, subtropical southwest China. No “juvenile effect” existed in this δ18Otree record and no relationship was found between δ18Otree and TRW. Correlation analysis with the climatic parameters demonstrated that the δ18Otree record significantly (p < 0.01) and negatively correlated with all the hydroclimatic parameters during the growing season (e.g. April–October precipitation, August–October relative humidity and April–November standardized precipitation–evapotranspiration index), while it only positively correlated with the August–September mean temperature (p < 0.05). At high frequency, the above relationships were greatly strengthened. Compared with the temperature-limited TRW in Guilin and other areas of subtropical China, δ18Otree was a better choice for hydroclimatic reconstruction. Moreover, the δ18Otree record in Guilin showed high consistency with other moisture-sensitive δ18Otree records in a large area of central-southeastern China. Analysis revealed that both large-scale circulation system (e.g. Indian summer monsoon, ENSO, westerlies) and local weather system significantly influenced the growing-season hydroclimatic variation in the study area. This study provides great potential for extracting hydroclimatic information from longer-living trees in subtropical China.

Adaptive Capacity of Water Governance: Cases From the Alps and the Andes

The Alps and the Andes are both considered water towers in their respective continents and are thus significant not only for their own water needs but also for those of lowland regions farther downstream. As climate change impacts on the hydrology of mountain regions are increasingly observed, attention is turning to the adaptive capacity of the water governance regimes in mountain communities. This paper explores the adaptive capacity of two contrasting water governance regimes in the Swiss Alps and the Chilean Andes. It assesses adaptive capacity by analyzing a set of governance-related adaptive capacity indicators in the context of recent extreme events, which serve as proxies for future climate change. Across these highly contrasted governance contexts, analysis reveals both similar and distinct institutional challenges for developing and mobilizing adaptive capacity in relation to climatic uncertainty and change. It also identifies emergent tensions related to temporal and spatial scales. Conclusions point to the need to focus on challenges relating to trust, integration of hydroclimatic information, and flexibility and iterativity of rules and plans across governance scales to better manage the exacerbating impacts of both climate variability and climate change.

Improving Groundwater Predictions Utilizing Seasonal Precipitation Forecasts from General Circulation Models Forced with Sea Surface Temperature Forecasts

Recent studies have found a significant association between climatic variability and basin hydroclimatology, particularly groundwater levels, over the southeast United States. The research reported in this paper evaluates the potential in developing 6-month-ahead groundwater-level forecasts based on the precipitation forecasts from ECHAM 4.5 General Circulation Model Forced with Sea Surface Temperature forecasts. Ten groundwater wells and nine streamgauges from the USGS Groundwater Climate Response Network and Hydro-Climatic Data Network were selected to represent groundwater and surface water flows, respectively, having minimal anthropogenic influences within the Flint River Basin in Georgia, United States. The writers employ two low-dimensional models [principle component regression (PCR) and canonical correlation analysis (CCA)] for predicting groundwater and streamflow at both seasonal and monthly timescales. Three modeling schemes are considered at the beginning of January to predict winter (January, February, and March) and spring (April, May, and June) streamflow and groundwater for the selected sites within the Flint River Basin. The first scheme (model 1) is a null model and is developed using PCR for every streamflow and groundwater site using previous 3-month observations (October, November, and December) available at that particular site as predictors. Modeling schemes 2 and 3 are developed using PCR and CCA, respectively, to evaluate the role of precipitation forecasts in improving monthly and seasonal groundwater predictions. Modeling scheme 3, which employs a CCA approach, is developed for each site by considering observed groundwater levels from nearby sites as predictands. The performance of these three schemes is evaluated using two metrics (correlation coefficient and relative RMS error) by developing groundwater-level forecasts based on leave-five-out cross-validation. Results from the research reported in this paper show that using precipitation forecasts in climate models improves the ability to predict the interannual variability of winter and spring streamflow and groundwater levels over the basin. However, significant conditional bias exists in all the three modeling schemes, which indicates the need to consider improved modeling schemes as well as the availability of longer time-series of observed hydroclimatic information over the basin.

Seasonal and centennial cycles of carbonate mineralisation during the past 2500 years from varved sediment in Lake Shira, South Siberia

Shira Lake is a good representative object for detail weather–climate modeling due to its local hydroclimatic information and annually laminated bottom sediments. Carbonate biochemical mineralization in Shira Lake shows not only seasonal but also centennial pulses over each 450–500 years. An age–depth model has been built by layer counting combined with 137Cs and 14C isotopic dates. Thermodynamic estimation of the rock-water multisystem in conformity with local conditions and source matter provides grounds for interpretation of measured geochemical parameters in sediments including environmental indicators such as temperature, salinity, and pH. Scanning X-ray fluorescence for sub-millimeter microstratigraphic study of varves connects geochemical oscillations of microelement content (Rb, Ti, Ca, Sr, Br, XRD) with seasonality, as well as revealing centennial pulses of environmental change. Quantitative environmental reconstruction using multiple regression for precipitation calibrated by hydrometeorological time series year by year was carried out for the lake over the last 2500 years.

Detection of long-term change in hydroelectric reservoir inflows: Bridging theory and practise

We studied long-term monotonic trend in inflow volume to 20 reservoirs, plus a measure of system-wide hydroelectric power potentially available for generation, in British Columbia, Canada. The primary analysis involved application of a linear method with explicit signal-to-noise ratio (S:N) estimation to monthly and annual mean inflows over the period of record common to all basins, providing a broad and convenient overview of changes across the hydroelectric system. Additional analyses then investigated the sensitivity of the results to methodological choices, focussing on annual inflow volume for eight indicator basins and system power. In these auxiliary analyses, alternative data selection and processing schemes were explored: full period of record for each indicator basin; residual after Pacific Decadal Oscillation signal removal; and data from streamgauges on catchments within or near each indicator basin. Alternative analysis techniques were also applied: nonparametric Spearman rank correlation with adjustment for serial dependence; change point detection using Mann–Whitney sliding window analysis; and visual assessment of data low-pass filtered using polynomial fits of various orders. Finally, we studied changes in year-to-year water supply variability, employing a split-sample approach implemented using a standard F-test; a nonparametric Ansari–Bradley test; and a novel Monte Carlo-based test on the Shannon entropy, a measure of hydroclimatic information content. The results provided no substantial evidence for decreased annual water supply and pointed to some increases; seasonal inflow pattern shifts were also detected for many basins, in particular a wintertime flow increase. The split-sample tests yielded no evidence for shifts in the volatility and predictability of annual inflow. One of the more intriguing and perhaps broadly important findings was that methodological choices ultimately made little difference to final outcomes.

Coupled Regional Hydroclimate Model and Its Application to the Tigris-Euphrates Basin

To establish a basinwide water management plan for the Tigris-Euphrates (TE) watershed, it is necessary to perform rigorous water balance studies of the whole watershed—at least for critical historical drought and flood conditions and under various water resources development scenarios. Water-balance studies over the watershed require climatic and hydrologic data sets, corresponding to historical critical flood and drought periods, at fine time and spatial grid resolutions provide the necessary hydroclimatic information. The Regional Hydroclimate Model of the Tigris-Euphrates (RegHCM-TE) and the associated geographic information system (GIS) were developed to downscale large-scale atmospheric data sets over the TE watershed and to reconstruct the aforementioned climatic and land hydrologic data sets at fine spatial and time increments. In RegHCM-TE, the earth system over the TE watershed is modeled as a fully coupled system of atmospheric processes aloft coupled with the atmospheric boundary layer, land-surface processes, surface and subsurface hydrologic processes, and the interactions among the various hydrologic and atmospheric processes. The parameters of the model are estimated by using existing global and local GIS data. By using the large-scale global historical atmospheric databases as its initial and boundary conditions, RegHCM-TE has been used to reconstruct historical hydroclimate data at a grid size of 15 km over the TE watershed, for which only very sparse hydrologic observations were available. RegHCM-TE and its model validation are described in this paper.