Variability Of Water Resources Research Articles

Identifying hydro-climatic and socioeconomic forces of water scarcity through structural decomposition analysis: A case study of Beijing city

Water scarcity has become a serious problem in many parts of the world. While many previous studies have recognized that the changing water scarcity levels were attributed to population growth, economic development and climate change, effects of different factors on variations of water scarcity were rarely disentangled and quantified based on historical data. This study develops an analytical framework, based on the structural decomposition analysis, to decompose temporal water scarcity changes into effects of a number of hydro-climatic and socioeconomic factors. The methodology is applied to water scarcity analysis in Beijing, China, which has long been under severe water scarcity. Results from Beijing show that the population-driven water scarcity tends to increase, whereas the demand-driven water scarcity presents a slightly declining trend. The declining trend of demand-driven water scarcity is mainly attributed to industrial structure upgrade, improved water use efficiency, reclaimed and transferred water uses, and domestic water saving. In contrast, the economic development, population growth and increased ecological water use contribute to aggravating Beijing's water scarcity. High randomness in Beijing's water scarcity is mainly attributed to variability of available water resources. The results provide an in-depth understanding of dynamics in water demand and supply, and help develop policies towards sustainable water resources planning and management.

Water use indicators at farm scale – An agro-hydrological software solution

The challenge to sustainably intensify agricultural production in farming systems in face of the increasing variability in regional water resources requires concerted action from many stakeholders, locally, regionally and globally. Models, such as the AgroHyd Farmmodel presented here, can provide information on how farm management decisions affect local water resources at various scales for use in multiple assessment frameworks. It is a stand-alone web-based software that connects agricultural and water-related systems, including all water flows related to farming systems. Results from a case study of the production of 12 crops with rainfed and supplemental irrigation on a farm in northeastern Germany are described here. Indicators that relate the water use to plant production on the farm such as water intensity or water productivity are compared in detail for three consecutive years with greatly varying annual rainfall amounts (from 373 to 790 mm) to highlight the effect of local variability on water flows and indicator values. The discussion illustrates how information on the effect of management decisions, such as crop type, seeding date, crop rotation, cultivation and irrigation on water use can be processed into indicators to help farmers make more effective decisions.

Coupling the maximum overlap discrete wavelet transform and long short-term memory networks for irrigation flow forecasting

Many countries are suffering from water resource constraints due to rising demands from different water-consuming sectors and a changing climate. In some countries, such as Spain, operators of agricultural irrigation are under increasing pressure to improve efficiency. Accordingly, accurate forecasts of water demand are a pre-requisite for the successful implementation of water resources planning and management tools in irrigated areas. However, forecasting approaches based on traditional neural networks have challenges to capture temporal dependencies that generally characterize irrigation flow time series. In this study, for the first time, a recurrent long short-term memory network (LSTM) was coupled with the maximum overlap discrete wavelet transformation (MODWT) and bootstrap techniques, for accurate and robust irrigation flow forecasting. For comparative purposes, the study also explored the ability of an Artificial Neural Network (ANN), a Least Squares Support Vector Regression (LSSVR), an Extreme Learning Machine (ELM) and a Multi Linear Regression (MLR), to forecast irrigation flow in Palos de la Frontera, an irrigation district located in Huelva (southern Spain), for a one-day lead time. The autocorrelation function and partial autocorrelation function determined the most significant lagged time series of irrigation flow to be used as model inputs. The wavelet-LSTM (W-LSTM) and waveletbootstrap-ANN models (WB-ANN) had the most accurate forecasts, as measured by statistical metrics including the root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (r2), mean relative error (MRE), mean absolute relative error (MARE), Willmott’s index, and Nash-Sutcliffe efficiency index (NASH). In this study, the capabilities of LSTMs, along with the MODWT transform analysis and bootstrap techniques, were benchmarked and could be further explored for forecasting other water resources variables in different climatic regions and for multi-step lead time forecasting.

Impacts of future climate change on water resource availability of eastern Australia: A case study of the Manning River basin

Hydrological responses of catchments to climate change require detailed examination to ensure sustainable management of both water resources and natural ecosystems. This study evaluated the impacts of climate change on water resource availability of a catchment in eastern Australia (i.e. the Manning River catchment) and analyzed climate-hydrology relationships. For this evaluation, the Xinanjiang (XAJ) model was used and validated to simulate monthly rainfall-runoff relationships of the catchment. Statistically downscaled climate data based on 28 global climate models (GCMs) under RCP8.5 scenarios were used to assess the impacts of climate changes on the Manning River catchment. Our results showed that the XAJ model was able to reproduce observed monthly rainfall-runoff relationships with an R2 ≥ 0.94 and a Nash-Sutcliffe Efficiency ≥0.92. The median estimates from the ensemble of downscaled GCM projections showed a slight decrease in annual rainfall and runoff for the period 2021–2060 and an increase for the period 2061–2100. Annual actual evapotranspiration was projected to increase slightly, while annual soil moisture content was predicted to decrease in the future. Our results also demonstrated that future changes in seasonal and annual runoff, actual evapotranspiration and soil moisture are largely dominated by changes in rainfall, with a smaller influence arising from changes in temperature. An increase in the values of high runoffs and a decrease in the values of low runoffs predicted from the ensemble of the 28 GCMs suggest increased variability of water resources at monthly and seasonal time-scales in the future. A trend of decreasing values in winter runoff and soil moisture content in the future is likely to aggravate possible future reductions in water availability in eastern Australia. These results contribute to the development of adaptive strategies and future policy options for the sustainable management of water resources in eastern Australia.

Quantifying the probabilistic divergences related to time-space scales for inferences in water resource management

Studies focusing on time-space scaling issues have not yet established guidelines for choosing a time-space scale for water resources management. This study attempts to develop a methodology to understand the deviations induced by the scaling framework on water resource variables. The study addresses eight variables: streamflow, groundwater level, precipitation, air temperature, soil moisture, solar radiation, wind speed, and relative humidity. For each variable, a 10-year (2001 to 2010) daily time-series data were retrieved from weather and hydrologic stations selected across Oklahoma. The methodology entailed three phases, including a variable rescaling, a probability analysis, and a divergence quantification. Hence, daily time-series of the selected variables were rescaled to weekly, biweekly, monthly, bimonthly, and trimonthly scales. To derive the probability density function of each variable, a kernel density estimator was applied to the rescaled time-series. The Kullback–Leibler divergence was used to evaluate the deviations pertaining to the time-space scaling. Results showed meaningful divergences that were a consequence of time-space scale variations. However, the sensitivity of variables to the scaling framework differed. For instance, air temperature was less sensitive to time-space scaling, while wind speed, soil moisture, and precipitation were highly sensitive. Correlation analysis showed that correlations tended to gradually increase with the increase in scale, even though the strength of the relation varied, depending on the variable involved. The methodology was tested via a case study where data obtained from a location outside of the study region were used to address the scaling effect on the Normalized Difference Vegetation Index’s response to precipitation and soil moisture. It was concluded that understanding the divergences associated with time-space scales was critical for interpreting results in water resource studies.

A framework to quantify impacts of elevated CO2 concentration, global warming and leaf area changes on seasonal variations of water resources on a river basin scale

With concerns about future catastrophic disasters, elevated CO2 concentration (eCO2), global warming and vegetation changes have received much attention globally. In recent years, studies have suggested controlling climate change should be based on regional impacts. However, regional quantitative assessments of respective and combination influences of CO2, temperature and vegetation variations on water resources remain limited. To address this issue, a comprehensive framework is developed. This framework integrates a dynamic vegetation simulation approach, a biosphere hydrological model and a variance-based sensitivity analysis approach which enables identification of predominant influential factors including their combinations. A medium-sized river basin in northeast China is used to illustrate the application based on different CO2 concentration and temperature rise assumptions. Validation using MODIS products shows the proposed approach can simulate Leaf Area Index (LAI) changes well. Results show sum of the influences of LAI and temperature variations on transpiration are more than 1.6 times higher than physiological effects of eCO2 in growing seasons, which implies more water could be transpired than conserved with eCO2, global warming and LAI changes. Results also show runoff increases with eCO2 and decreases with increasing temperatures, but LAI changes play a dominate role in runoff decrease in hot summer. Therefore, considering LAI changes is of utmost importance in projections of future water resources, and severity of future water shortage could be underestimated if LAI changes are neglected. This research is useful in gaining insights into the complicated impacts of eCO2, global warming and LAI changes on regional water security and sustainability.

Anthropocene and streamflow: Long-term perspective of streamflow variability and water rights

Since 1981, water allocation in Chile has been based on a water use rights (WURs) market, with limited regulatory and supervisory mechanisms. The volume to be granted as permanent and eventual WURs is calculated from streamflow records, if stream gauge data are available, or from hydrologic parameter transfer from gauged to ungauged catchments, usually with less than 50 years of record. To test the performance of this allocation system, while analyzing the long-term natural variability in water resources, we investigated a 400 year-long (1590–2015) tree-ring reconstruction of runoff and historical water rights for Perquilauquén at Quella catchment, a tributary to the Maule River in Central Chile (35°S–36°30S). Furthermore, we assess how the current legislation would perform under a projected climate scenario, based on historical climate simulations of runoff calibrated against observed data, and future projections. Our analyses indicate that the allocation methodology currently applied by the Water Authority in Chile is very sensitive to the time window of data used, which leads to an underestimation of variability and long-term trends. According to the WURs database provided by the Chilean Water Directorate, WURs at Perquilauquén at Quella are already over-allocated. Considering regional climate projections, this condition will be exacerbated in the future. Furthermore, serious problems regarding the access and quality of information on already-granted WURs and actual water usage have been diagnosed, which further encumber environmental strategies to deal with and adapt to climate change. We emphasize the urgent need for a review and revision of current water allocation methodologies and water law in Chile, which are not concordant with the dynamics and non-stationarity of hydrological processes. Water scarcity and water governance are two of the key issues to be faced by Chile in the Anthropocene.

Impact assessment of land use and cover changes on water resources using RS and GIS Techniques in watershed area

Management, assessment and simulation of different water resource variables are important at watershed scale to understand their interactions for appropriate water resource planning and management. The advent and recent development of RS and GIS techniques has facilitated the generation of spatially temporally distributed information very accurately, precisely and in an very time efficient manner that makes it possible to apply physically based hydrologic models for water resource variables simulation in a simply and realistically manner as possible. In present study, the effect of land use and land cover changes in the hydrologic response of a watershed is assessed for different rainfall events on surface, sub-surface and groundwater recharge, along with infiltration and evapotranspiration losses using widely recognised SWAT model in a watershed with limited gauges and data availability. Two different years of land use maps representing a 12 years of period, in which the area underwent a significant land use transition, were applied to the SWAT hydrological model to see the effect of land use change on hydrological response in the watershed. The SWAT model was calibrated and validated during the period of 2009–2010 and 2011–2012, respectively. The higher runoff rate and volume produced during validation period by SWAT with LISS-III is due to increased agricultural land and decreased forest land, whereas SWAT with LANDSAT ETM+ model shows that the same event could have produced lower runoff compared to runoff obtained in 2011–2012. Based on different performance indices, it was found that SWAT model coupled with the capabilities of RS and GIS performs good during both calibration and validation periods in Limkheda watershed.

Long-term dynamics of water resources variability in the Ural River basin (within the Republic of Bashkortostan)

Long-term dynamics of water resources variability in the Ural River basin (within the Republic of Bashkortostan)

Global Warming and Water Resources Variability in the Maritime Region of Togo (West Africa)

One of the most important climatic phenomena of our planet on the threshold of this third millennium is undoubtedly that of global warming. This phenomenon, whose impact on the global environment is disastrous, has been attracting the attention of the international community since the end of the last century. Global warming can be observed on a global scale, but with regional and local signatures. In Togo, the Maritime region which houses the bulk of industrial activities (90%) and densely populated (40% of the national population), would be more exposed to the effects of global warming than all the other regions of the country. The current study uses meteorological and hydrological data to calculate statistical indexes which show the evolution of temperatures and water resources variability. The aim is to detect the signs of global warming and the variability of water resources in order to envisage better adaptation strategies. The results of the analysis of climate data for a long enough period (30 to 50 years) demonstrated a change on rain distribution after 1960 which is prejudicial to rainfall agriculture practiced by about 90% of Togolese crop growers, and an augmentation of the average temperature about 2.2 degree celsius for Lomé and 1.7 degree celsius for Tabligbo.

The potential of global reanalysis datasets in identifying flood events in Southern Africa

Abstract. Sufficient and accurate hydro-meteorological data are essential to manage water resources. Recently developed global reanalysis datasets have significant potential in providing these data, especially in regions such as Southern Africa that are both vulnerable and data poor. These global reanalysis datasets have, however, not yet been exhaustively validated and it is thus unclear to what extent these are able to adequately capture the climatic variability of water resources, in particular for extreme events such as floods. This article critically assesses the potential of a recently developed global Water Resources Reanalysis (WRR) dataset developed in the European Union's Seventh Framework Programme (EU-FP7) eartH2Observe (E2O) project for identifying floods, focussing on the occurrence of floods in the Limpopo River basin in Southern Africa. The discharge outputs of seven global models and ensemble mean of those models as available in the WRR dataset are analysed and compared against two benchmarks of flood events in the Limpopo River basin. The first benchmark is based on observations from the available stations, while the second is developed based on flood events that have led to damages as reported in global databases of damaging flood events. Results show that, while the WRR dataset provides useful data for detecting the occurrence of flood events in the Limpopo River basin, variation exists amongst the global models regarding their capability to identify the magnitude of those events. The study also reveals that the models are better able to capture flood events at stations with a large upstream catchment area. Improved performance for most models is found for the 0.25° resolution global model, when compared to the lower-resolution 0.5° models, thus underlining the added value of increased-resolution global models. The skill of the global hydrological models (GHMs) in identifying the severity of flood events in poorly gauged basins such as the Limpopo can be used to estimate the impacts of those events using the benchmark of reported damaging flood events developed at the basin level, though this could be improved if further details on location and impacts are included in disaster databases. Large-scale models such as those included in the WRR dataset are used by both global and continental forecasting systems, and this study sheds light on the potential these have in providing information useful for local-scale flood risk management. In conclusion, this study offers valuable insights in the applicability of global reanalysis data for identifying impacting flood events in data-sparse regions.

Addressing Barriers of Rural Development under Drought

Purpose - Several models of rural development have been proposed but they have failed to adequately explain why development stagnates in certain regions. To fill this knowledge gap, this qualitative research was conducted. Design/methodology/approach- Based on focus group interviews with farmers and semi-structured interviews with rural managers and experts from two sub-counties in Kherameh, Fars province, the barriers of rural development under drought were investigated. Finding- Various adaptation strategies, such as changing cropping pattern, developing greenhouses and rising mushroom, quail and ostrich, have been applied by farmers in order to reduce the negative impacts of drought and water scarcity. However, different barriers including climate variability, quantitative and qualitative reduction of water resources, unemployment and lack of sustainable job opportunities, limitation of financial resources and investment, inefficiency of institutional supporting policies, limitation of budgets and loans, and uncertainty about future of agriculture have prevented rural areas from development. Practical implications - Continuous monitoring of drought and developing early warning systems, consensus about distribution of common water resources, water conveyance from other regions and considering water subsides, local participation in development planning, encouraging research institutes to focus their research on investigating and producing water resistance crops, improving drought management information through effective extension services and linking urban-based businesses with small-scale crop producers are offered to improve rural development in this drought prone area. Originality/value- Given that a similar study has not been conducted about rural development traps under drought, the findings of this study can be used by rural development planners and practitioners.

Resilience, Decision‐making, and Environmental Water Releases

AbstractTensions between delivering water for human uses versus environmental benefits are increasing in many arid and semiarid regions, potentially causing irreversible environmental consequences. The issue of how to balance these competing uses of water is of fundamental importance, especially with projected increases in the variability of water resources due to climate change. In response, a stochastic resilience optimization model is developed to assist decision‐makers to optimally determine water releases from storages for environmental purposes and to measure the resilience of a system for given risk tolerances. The model, with sensitivity analyses, provides a valuable tool for water planners to minimize the risk of irreversible consequences and to optimize for resilience taking into account weather uncertainty, existing environmental conditions, and water storage levels. A calibration of the model to the Murray‐Darling Basin and also the Goulburn‐Broken catchment region in Australia highlights its potential to improve decision‐making at multiple spatial scales and over time.

Preface: Understanding spatio-temporal variability of water resources and the implications for IWRM in semi-arid eastern and southern Africa

Preface: Understanding spatio-temporal variability of water resources and the implications for IWRM in semi-arid eastern and southern Africa

Assessment of the impact of climate change on spatiotemporal variability of blue and green water resources under CMIP3 and CMIP5 models in a highly mountainous watershed

The variability and uncertainty of water resources associated with climate change are critical issues in arid and semi-arid regions. In this study, we used the soil and water assessment tool (SWAT) to evaluate the impact of climate change on the spatial and temporal variability of water resources in the Bazoft watershed, Iran. The analysis was based on changes of blue water flow, green water flow, and green water storage for a future period (2010–2099) compared to a historical period (1992–2008). The r-factor, p-factor, R2, and Nash–Sutcliff coefficients for discharge were 1.02, 0.89, 0.80, and 0.80 for the calibration period and 1.03, 0.76, 0.57, and 0.59 for the validation period, respectively. General circulation models (GCMs) under 18 emission scenarios from the IPCC’s Fourth (AR4) and Fifth (AR5) Assessment Reports were fed into the SWAT model. At the sub-basin level, blue water tended to decrease, while green water flow tended to increase in the future scenario, and green water storage was predicted to continue its historical trend into the future. At the monthly time scale, the 95% prediction uncertainty bands (95PPUs) of blue and green water flows varied widely in the watershed. A large number (18) of climate change scenarios fell within the estimated uncertainty band of the historical period. The large differences among scenarios indicated high levels of uncertainty in the watershed. Our results reveal that the spatial patterns of water resource components and their uncertainties in the context of climate change are notably different between IPCC AR4 and AR5 in the Bazoft watershed. This study provides a strong basis for water supply-demand analyses, and the general analytical framework can be applied to other study areas with similar challenges.

Performance of a RBSN under the RCP Scenarios: A Case Study in South Korea

According to the Intergovernmental Panel on Climate Change’s (IPCC) Fifth Assessment Report, the amount of precipitation in South Korea would increase regardless of the reduction of Greenhouse Gas (GHG) emissions. However, at the same time, it is expected that the temporal and spatial rainfall variation would also increase. Due to the impact from typhoons, 90% of the annual precipitation in Korea occurs in July, August, and September. Moreover, the Representative Concentration Pathways (RCP) scenario projected that the average precipitation in this period is expected to increase markedly, especially over the next 100 years. These predictions imply an increased variability of available water resources. In this study, we assessed a RBSN (rain barrel sharing network) as an efficient way to respond to the future climate change projections under the RCP scenarios when compared to the historical data. We proposed an evaluation procedure for the reliability, resilience, and vulnerability of RBSN based on a storage-reliability-yield (SRY) relationship. The result shows that the reliability and resiliency of a RBSN will improve but be more vulnerable compared to the results from the historical rainfall data. However, even in the climate change condition, the results showed that a RBSN still contributes to reduce vulnerability. The results of this study imply that a RBSN is an effective and alternative measure that can deal with the impacts of climate change in the future.

厄瓜多尔水资源时空分布及变化规律

厄瓜多尔水资源时空分布及变化规律

The Impact of Precipitation Deficit and Urbanization on Variations in Water Storage in the Beijing-Tianjin-Hebei Urban Agglomeration

Depletion of water resources has threatened water security in the Beijing-Tianjin-Hebei urban agglomeration, China. However, the relative importance of precipitation and urbanization to water storage change has not been sufficiently studied. In this study, both terrestrial water storage (TWS) and groundwater storage (GWS) change in Jing-Jin-Ji from 1979 to the 2010s were investigated, based on the global land data assimilation system (GLDAS) and the EartH2Observe (E2O) outputs, and we used a night light index as an index of urbanization. The results showed that TWS anomaly varied in three stages: significant increase from 1981 to 1996, rapid decrease from 1996 to 2002 and increase from 2002 to the 2010s. Simultaneously, GWS has decreased with about 41.5 cm (500% of GWS in 1979). Both urbanization and precipitation change influenced urban water resource variability. Urbanization was a relatively important factor to the depletion of TWS (explains 83%) and GWS (explains 94%) since the 1980s and the precipitation deficit explains 72% and 64% of TWS and GWS variabilities. It indicates that urbanization coupled with precipitation deficit has been a more important factor that impacted depletion of both TWS and GWS than climate change only, in the Jing-Jin-Ji region. Moreover, we suggested that the cumulative effect should be considered when discussing the relationship between influence factors and water storage change.

An integrated hydrological modeling approach for detection and attribution of climatic and human impacts on coastal water resources

Water resources in coastal areas can be profoundly influenced by both climate change and human activities. These climatic and human impacts are usually intertwined and difficult to isolate. This study developed an integrated model-based approach for detection and attribution of climatic and human impacts and applied this approach to the Luanhe Plain, a typical coastal area in northern China. An integrated surface water-groundwater model was developed for the study area using GSFLOW (coupled groundwater and surface-water flow). Model calibration and validation were performed for background years between 1975 and 2000. The variation in water resources between the 1980s and 1990s was then quantitatively attributed to climate variability, groundwater pumping and changes in upstream inflow. Climate scenarios for future years (2075–2100) were also developed by downscaling the projections in CMIP5. Potential water resource responses to climate change, as well as their uncertainty, were then investigated through integrated modeling. The study results demonstrated the feasibility and value of the integrated modeling-based analysis for water resource management in areas with complex surface water-groundwater interaction. Specific findings for the Luanhe Plain included the following: (1) During the historical period, upstream inflow had the most significant impact on river outflow to the sea, followed by climate variability, whereas groundwater pumping was the least influential. (2) The increase in groundwater pumping had a dominant influence on the decline in groundwater change, followed by climate variability. (3) Synergetic and counteractive effects among different impacting factors, while identified, were not significant, which implied that the interaction among different factors was not very strong in this case. (4) It is highly probable that future climate change will accelerate groundwater depletion in the study area, implying that strict regulations for groundwater pumping are imperative for adaptation.

Quantitative analysis of the water-energy-climate nexus in Shanxi Province, China

Water and energy security are major challenges for sustainable development in China. This study focuses on the local impact of future climate change and human activities on water resources in Shanxi Province, which contains the largest coal energy base in China. Climate change and water resource variations from 2010‒2050 are investigated using the Coupled Land surface and Hydrology Model System, applying three different IPCC AR5 emission scenarios. The capacity of water resources to support mid-21st century development is discussed with reference to current national policy. The water demand of Shanxi’s energy bases will continue to grow as resource pressure intensifies.