Bharat mein 1990-1999 ke dauraan shushkata visangatiyon ka kshetreey avem saamayik vishleshan

Aridity Anomaly Index (AAI), based on Thornthwaite’s water balance technique, has been used to identify the extent and persistence of aridity anomalies over 33 sub-divisions of India during a period of 10 years from 1990 to 1999. Regional and temporal analysis has been carried out to identify the areas and periods of intense and prolonged persistence. This study has shown that 1992 was worst hit by the aridity conditions, which emerged in 5 or more fortnights. All sub-divisions of north India were affected by moderate aridity during 1990, 1992-94 and 1999. Similarly, all sub-divisions of peninsular India were influenced by moderate aridity during 1991, 1993 and 1999. Severe aridity appeared in all sub-divisions of peninsular India during 1990. The duration of severe aridity was less than that of moderate aridity during all years. Moderate and severe aridity appeared simultaneously in 5 or more fortnights in maximum 9 sub-divisions in 1992 and occurred during maximum 5 years in Madhya Maharashtra. Moderate aridity in 5 or more fortnights emerged each year during 1990 to 1999 in coastal Andhra Pradesh. In 1991, maximum 55% sub-divisions were affected by severe aridity in 9th fortnight, whereas Saurashtra & Kutch was affected in 1996 and north Interior Karnataka in 1999 during maximum 7 fortnights. In the year 1992, maximum number of sub-divisions under moderate and severe persistence was 70% and 24% respectively. In north India, moderate persistence appeared in east Rajasthan in all nine years except 1996, with its longest duration of 8 fortnights in 1995. West Madhya Pradesh, in peninsular India, was affected by moderate aridity during 7 fortnights in each year during the period of study from 1990 to 1999.

Allowing the Actual Evapotranspiration Uncertainty in Hydrological Models: Coupling of Interval-Based Water Balance and METRIC Models

Against the paramount role of actual evapotranspiration (ET) in hydrological modeling, determining its values is mixed with different sources of uncertainties. In addition, estimation of ET with energy-based methods (e.g., METRIC) leads to different results with various acceptable initial and boundary conditions (such as land use and cold/hot pixels). The aim of the current research is to allow the uncertainty effects of ET as an interval-based input variable in hydrological modeling. The goal is achieved via feeding the uncertainty of computed ET values to the developed Interval-Based Water Balance (IBWB) model in terms of gray values. To this purpose, the comprehensive monthly water balance model (including surface and groundwater modules) has been revised to a new interval-based form. Moreover, the METRIC model has been used 20 times in each month of computational period to calculate the ET patterns with different hot/cold pixels to provide monthly ensemble ET values. For a comprehensive assessment, the selected water balance model has been calibrated with ensemble means of the computed ET with its classical type. The study area is a mountainous sub-basin of the Sefidrood watershed, Ghorveh-Dehgolan basin, with three alluvial aquifers in the North of Iran. Not only the paradigm shift from determinist to interval-based hydrologic structure improved the statistical metrics of the models’ responses, but also it decreased the uncertainty of the simulated streamflow and groundwater levels.

The Water Yield Pattern for Annual and Monthly Scales Through a Unifying Catchment Water Balance Model

Long-term scheduling and short-term decision-making for water resources management often require understanding the relationship of water yield pattern between the annual and monthly scales. As the water yield pattern mainly depends on land cover/use and climate, a unifying catchment water balance model with factors has been adopted to derive a theoretical water yield pattern with annual and monthly scales. Two critical values at the parameters ε=1-√2/2 and ϕ=1.0 are identified. The parameter ε referring to the water storage (land use/cover) and evaporation (climate) changes can make more contribution than ϕ for water yield when ϕ>1.0, especially with ε<1-√2/2. But there is less contribution made by ε when ϕ<1.0. The derived theoretical water yield patterns have also been validated by the observed data or the simulated data through the hydrological model. Due to the bias of the soil moisture data, a lot of the estimated parameter ε values are over its theoretical range, especially for the monthly scale in humid basins. The performance of the derived theoretical water yield pattern at annual scale is much better than that at monthly scale while there are only a few data sets from the arid basin at every months fall within their theoretical ranges. Even the relative contributions of ε is found to be bigger than those of ϕ due to ε<1-√2/2 and ϕ>1.0, there are no significant linear relationships between annual and monthly parameters ε and ϕ. Our results not only validate the derived theoretical water yield pattern with the estimated parameter directly by the observed or simulated data rather than the calibrated parameter, but also can guide for further understanding physical of water balance to conversion time scales for the combing long-term and short-term water resources management.

A Daily Water Balance Model Based on the Distribution Function Unifying Probability Distributed Model and the SCS Curve Number Method

A new daily water balance model is developed and tested in this paper. The new model has a similar model structure to the existing probability distributed rainfall runoff models (PDM), such as HyMOD. However, the model utilizes a new distribution function for soil water storage capacity, which leads to the SCS (Soil Conservation Service) curve number (CN) method when the initial soil water storage is set to zero. Therefore, the developed model is a unification of the PDM and CN methods and is called the PDM–CN model in this paper. Besides runoff modeling, the calculation of daily evaporation in the model is also dependent on the distribution function, since the spatial variability of soil water storage affects the catchment-scale evaporation. The generated runoff is partitioned into direct runoff and groundwater recharge, which are then routed through quick and slow storage tanks, respectively. Total discharge is the summation of quick flow from the quick storage tank and base flow from the slow storage tank. The new model with 5 parameters is applied to 92 catchments for simulating daily streamflow and evaporation and compared with AWMB, SACRAMENTO, and SIMHYD models. The performance of the model is slightly better than HyMOD but is not better compared with the 14-parameter model (SACRAMENTO) in the calibration, and does not perform as well in the validation period as the 7-parameter model (SIMHYD) in some areas, based on the NSE values. The linkage between the PDM–CN model and long-term water balance model is also presented, and a two-parameter mean annual water balance equation is derived from the proposed PDM–CN model.

Integrated Water Balance and Water Quality Management Under Future Climate Change and Population Growth: A Case Study of Upper Litani Basin, Lebanon

The impacts of the growing population at Lebanon including Lebanese, Palestinian and Syrian refugees, associated with the changing climate parameters such that the precipitation are putting the Bekaa Valley’s water resources in a stymie situation. The water resources are under significant stress limiting the water availability and deteriorating the water quality at the Upper Litani River Basin (ULRB) within the Bekaa Valley region. These impacts are assessed by Water Evaluation And Planning model to assure the water balance and quality at baseline scenario in 2013, and future scenarios reaching 2095, serving by the Watershed Modeling System to get the flow throughout the Litani River’s ungauged zones. Moreover, a General Circulation Model is used to predict the future climate up to 2100 under several emissions scenarios which shows a critical situation at the high emission scenario where the precipitation will be reduced about 87 mm from 2013 to 2095. The aim of this research is to reduce the water pollution that limits the availability of usable water, and to minimize the gap between the demand and supply of water within the ULRB in order to maintain water resources sustainability, and preserves its quality, even after 80 years. In particular, this may be achieved by removing encroachments on the river, by adding waste water treatment plants, by reducing the amount of lost water in damaged water network, and by avoiding the overconsumption of groundwater.

How well are we able to close the water budget at the global scale?

The water budget equation describes the exchange of water between the land, ocean, and atmosphere. Being able to adequately close the water budget gives confidence in our ability to model and/or observe the spatio-temporal variations in the water cycle and its components. Due to advances in observation techniques, satellite sensors, and modelling, a number of data products are available that represent the components of water budget in both space and time. Despite these advances, closure of the water budget at the global scale has been elusive. In this study, we attempt to close the global water budget using precipitation, evapotranspiration, and runoff data at the catchment scale. The large number of recent state-of-the-art datasets provides a new evaluation of well-used datasets. These estimates are compared to terrestrial water storage (TWS) changes as measured by the Gravity Recovery And Climate Experiment (GRACE) satellite mission. We investigated 189 river basins covering more than 90 % of the continental land area. TWS changes derived from the water balance equation were compared against GRACE data using two metrics: the Nash–Sutcliffe efficiency (NSE) and the cyclostationary NSE. These metrics were used to assess the performance of more than 1600 combinations of the various datasets considered. We found a positive NSE and cyclostationary NSE in 99 % and 62 % of the basins examined respectively. This means that TWS changes reconstructed from the water balance equation were more accurate than the long-term (NSE) and monthly (cyclostationary NSE) mean of GRACE time series in the corresponding basins. By analysing different combinations of the datasets that make up the water balance, we identified data products that performed well in certain regions based on, for example, climatic zone. We identified that some of the good results were obtained due to the cancellation of errors in poor estimates of water budget components. Therefore, we used coefficients of variation to determine the relative quality of a data product, which helped us to identify bad combinations giving us good results. In general, water budget components from ERA5-Land and the Catchment Land Surface Model (CLSM) performed better than other products for most climatic zones. Conversely, the latest version of CLSM, v2.2, performed poorly for evapotranspiration in snow-dominated catchments compared, for example, with its predecessor and other datasets available. Thus, the nature of the catchment dynamics and balance between components affects the optimum combination of datasets. For regional studies, the combination of datasets that provides the most realistic TWS for a basin will depend on its climatic conditions and factors that cannot be determined a priori. We believe that the results of this study provide a road map for studying the water budget at catchment scale.

Probabilistic Minimum Night Flow Estimation in Water Distribution Networks and Comparison with the Water Balance Approach: Large-Scale Application to the City Center of Patras in Western Greece

Quantification of water losses (WL) in water distribution networks (WDNs) is a crucial task towards the development of proper strategies to reduce them. Currently, WL estimation methods rely on semi-empirical assumptions and different implementation strategies that increase the uncertainty of the obtained estimates. In this work, we compare the effectiveness and robustness of two widely applied WL estimation approaches found in the international literature: (a) the water balance, or top-down, approach introduced by the International Water Association (IWA), and (b) the bottom-up or minimum night flow (MNF) approach, based on a recently proposed probabilistic MNF estimation method. In doing so, we use users’ consumption and flow-pressure data from the 4 largest pressure management areas (PMAs) of the WDN of the city of Patras (the third largest city in Greece), which consist of more than 200 km of pipeline, cover the entire city center of Patras, and serve approximately 58,000 consumers. The obtained results show that: (a) when MNF estimation is done in a rigorous statistical setting from high resolution flow-pressure timeseries, and (b) there is sufficient understanding of the consumption types and patterns during day and night hours, the two approaches effectively converge, allowing for more reliable estimation of the individual WL components. In addition, when high resolution flow-pressure timeseries are available at the inlets of PMAs, the suggested version of the bottom-up approach with probabilistic estimation of MNF should be preferred as less sensitive, while allowing for confidence interval estimation of the individual components of water losses and development of proper strategies to reduce them.