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Many global climate models, including the Climate Forecast System version 2 (CFSv2), have a biased representation of subseasonal modes of variability of the Indian summer monsoon. For instance, they simulate a weaker summer mean monsoon low‐pressure systems (LPS) climatology, faster than observed northward propagation of monsoon intraseasonal oscillations (MISOs), and a systematic dry bias over Indian landmass. The Bay of Bengal (BoB), with its shallow mixed layers and unique thermal stratification, significantly modulates the convective activity in this region at subseasonal‐to‐seasonal timescales through modulation of sea surface temperature. The highly stratified upper ocean in the BoB is due to the enormous freshwater it receives from rains and rivers. A river routing model is coupled to the CFSv2 to account for the riverine freshwater and the improvements in modelling the upper‐ocean structure are analysed. Model simulations indicate that inclusion of temporally varying riverine freshwater improves the upper‐ocean state in the BoB and the observed mixed‐layer temperature gradients in the Bay are simulated reasonably after incorporating the time varying river runoff. This resulted in increased LPS lifetime and track density, and enhanced rainfall over central India. Better representation of the upper‐ocean stratification in the model leads to larger post‐convection shoaling of mixed layers at intraseasonal timescales, thereby forming thick barrier layers. Enhanced air–sea interactions restricted to the shallow mixed layer are associated with stronger vorticity, specific humidity and low‐level convergence to the north of the intraseasonal convection band. This enhanced low‐level moisture convergence north of the convection centre results in realistic northward propagation of MISO and aids LPS activity. It is demonstrated that better simulation of the upper‐ocean structure in coupled climate models can improve the representation of subseasonal modes of monsoon variability. These results bear important implications for operational forecasting. [ABSTRACT FROM AUTHOR]

Wetlands are dynamic ecosystems that require continuous monitoring and assessment of degradation status to design strategies for their sustainable management. While hydrology provides the primary functional control for the wetland ecosystem, the loss of landscape connectivity influences wetland degradation in a major way as it leads to fragmentation. This article aims to integrate hydrogeomorphic and ecological concepts for the assessment of degradation status and its causal factors for a large wetland in the western Ganga plains, India, the Haiderpur, using a wetlandscape approach. We have used a remote‐sensing‐based approach, which offers a powerful tool for assessing and linking cross‐scale structures, functions, and controls in a wetlandscape. The Haiderpur, a Ramsar site since December 2021, is an artificial wetland located on the right bank of the Ganga River wherein the inflows are controlled by a barrage constructed on the Ganga River apart from smaller tributaries flowing in from the north. A novel aspect of this work is the integration of river dynamics and its connectivity to the wetlandscape to understand the spatiotemporal variability in the waterspread area in the wetland. In this work, we have developed an integrated wetlandscape assessment approach by evaluating wetland's geomorphic and hydrological connectivity status for the period 1993–2019 (25 years) across three different spatial scales – regional, catchment, and wetland. We have highlighted the ecological implications of connectivity and patch dynamics for developing sustainable wetland management plans. [ABSTRACT FROM AUTHOR]

Despite the remarkable improvements in skillful weather forecasts, their uses in irrigation water management at a farm scale are still limited. This is attributable to the scale mismatch between weather and hydrologic models as well complexities in farmscale ecohydrological processes. Here, we have developed a simulation‐optimization algorithm for minimizing irrigation water application using short to medium range forecasts by determining the conditional probability density functions of the rainfall and subsequently the soil moisture for the days in forecast range. With the forecasted soil moisture information, the model ensures that the probability of crops undergoing water stress is less than a prescribed threshold. The optimization model includes a farmscale ecohydrological model, which computes daily evapotranspiration, runoff, and leakage based on a probabilistic description of rainfall through Monte‐Carlo simulations. After calibrating and validating the ecohydrological model with past data obtained from the farmers, this proposed optimization framework was employed to test the outcome for two pilot sites in Nashik, Maharashtra, India. We found that using the proposed framework, irrigation water use can be reduced by 10%–30% as compared to that resulting from the conventional strategies used by the farmers, without significant loss in crop yields, by almost always maintaining the soil moisture at or above the prescribed threshold. Considering that irrigation accounts for over 80% of the total water use worldwide, the value of such an approach as a decision‐support tool for irrigation optimization is self‐evident. We also posit that the co‐production of this tool with the farmers increases its usability and credibility. Plain Language Summary: A competent irrigation water management should minimize water application, avoid water stress in plants, and stabilize crop productivity and revenues. As there are substantial monetary investments and water use for irrigation, planned management is essential for sustainable use of water, without a loss in yield or economic benefit, especially considering the uncertainties in climatic drivers. To deliver a suitable scheme, we adopt a probabilistic approach based on the probability density function (pdf) of soil moisture at a farm scale. A stochastic ecohydrological model simulates the probabilistic soil moisture considering irrigation and rainfall input. The model uses the conditional probability of rainfall, given past forecasts, and hence, takes care of uncertainties and errors therein. The stochastic modeling is represented by Monte‐Carlo simulations, which are inbuilt within the optimization model. The model's objective function is to minimize the irrigation amount with a constraint that on a specific day, given a forecast, the probability of water stress is less than a user‐defined value. The framework thus co‐developed with the farmers is found to have considerable potential for reducing irrigation water use compared to the farmers' approach over the chosen test sites. The usability of the tool is enhanced by the farmers' involvement from the beginning. Key Points: Use of weather/climate forecasts for analytically deriving irrigation requirements at farm‐scaleDevelopment of water use management strategy at farm‐scale addressing uncertainty in weather forecastsReducing water use for irrigation with weather forecasts and stochastic ecohydrological model at farm‐scale [ABSTRACT FROM AUTHOR]

Accurate estimation of ET0, and determination of its trend/variability and sensitivity to changes in climate variables is essential at regional scale for different applications. These are attempted for India by considering 18 homogeneous ET0 regions formed in companion paper. Food and Agriculture Organization (FAO) recommends Penman–Monteith (PM) equation for ET0 estimation, which requires information on several climate variables. The equation cannot be used in data‐sparse areas where information/forecasts on one or more required climate variables is unavailable/unreliable. To address this, relevance vector regression (RVR) relationships are developed in this paper for the 18 homogeneous regions to arrive at FAO‐PM estimate of ET0 from subsets of its predictor climate variables, which could be typically expected in data‐sparse areas. The developed relationships are shown to be better in arriving at ET0 estimates when compared to multiple linear regression (MLR) relationships and three widely used empirical equations (Hargreaves, Mcguinness–Bordne, Priestly–Taylor). Regional trend analysis revealed that ET0 is significantly decreasing (increasing) in most regions located in north (south) India. Sensitivity of ET0 and surface runoff to changes in their predictor climate variables is determined for each region by considering third‐order Taylor series approximation of their functional relationships. Key climate variable(s) that govern ET0 changes in each region are identified. Results indicate that at annual scale solar radiation and relative humidity govern ET0 changes in regions located in south and north‐east India, whereas wind speed followed by relative humidity mostly influence the ET0 changes over other regions. Existence of evaporation paradox in four regions and validity of Bouchet's complementary relationship between ET0, actual evapotranspiration (ETa), and precipitation in 11 regions is also established. Significant divergence in trend of ET0 and ETa was evident in north‐east India. [ABSTRACT FROM AUTHOR]

Delineation of homogeneous reference evapotranspiration (ET0) regions is essential for different applications in hydro‐meteorology. In conventional regionalization approaches, lumped (time‐invariant) statistics such as mean, median or interquartile range of different hydrometeorological variables are often considered as attributes to delineate regions. Information on temporal dynamics of those variables is not utilized (as it is lost in lumped statistics), which if accounted could yield better regions. To address this, a new regionalization approach is presented in fuzzy framework in this Part 1 of a two‐part series. In the proposed approach, information on temporal dynamics of predictor climate variables influencing ET0 is used for regionalization, and the delineated regions are subsequently validated for homogeneity using the predictand (ET0) related information. Effectiveness of the approach is demonstrated through a case study on India, which yielded 18 regions. They are shown to be statistically more homogeneous in ET0 when compared to the existing agro‐ecological zones and regions formed using global fuzzy c‐means clustering method. The homogeneous ET0 regions were found to be different from homogeneous actual evapotranspiration (ETa) regions delineated over India using the fuzzy dynamic clustering approach. Various applications of the homogeneous ET0 regions formed using the proposed approach are presented in Part 2 of this series. [ABSTRACT FROM AUTHOR]

Urban lakes in many places around the world are rapidly becoming vulnerable because of such factors as urbanization, climate change, anthropogenic pollutant inputs, etc. The influence of such forcing factors on lakes hydrology must be correctly recognized and addressed in order to protect them over the long term. Facing similar challenges, Sukhna Lake, an urban lake in northern India, has apparently dried up frequently in the recent past. Numerous hypotheses were subsequently proposed to isolate the possible factors affecting the lake and its water budget, including the potential impacts of land use changes, climate change, anthropogenic activities and other natural processes. Using meteorological data, lake‐catchment information and a hydrologic model, these hypotheses were comprehensively analysed. Relevant data on rainfall, wind, temperature, lake inflows, groundwater, lake physical characteristics, catchment land uses, soil texture, etc., were gathered for the analysis. A temporal trend analysis of factors relevant to these hypotheses was undertaken to identify critical drivers of hydrological changes. A sensitivity analysis also was performed, using the lake water budget, to determine and prioritize the predominant factors affecting the lake, leading to the creation of an annual lake water budget for the period from 1971 to 2013, highlighting the lake inflows and outflows. The lake annual inflow (catchment run‐off) was computed by adopting a rainfall–run‐off model based on the SCS‐curve number. Lacking any anthropogenic water withdrawals, the outflow was quantified by estimating the evaporation loss (using the FAO‐based Penman–Monteith Equation). The results of the present study  indicate that the process of siltation and the construction of check dams in the catchment, rather than urbanization and climate change, were the dominating reasons contributing to changes in the lake hydrology, and affecting the lake most in recent years. [ABSTRACT FROM AUTHOR]

A paired watershed approach was used to quantifying the effects of staggered contour trenching (SCT) densities on runoff and soil loss from a long-term field experiment. Four adjacent physiographical similar ravine watersheds were selected. After 2-year calibration period, three of the four watersheds were treated with different SCT densities and leaving one watershed as untreated control (WC). The SCT densities of 139, 278 and 417 trenches ha−1 were determined based on the targeted 25, 50 and 75% runoff trapping potential of the WT1, WT2 and WT3 treatment watersheds, respectively. Runoff and soil loss were recorded for a period of 11 years including 2 years of calibration period. The calibration and treatment prediction equations for the treatment watershed with respect to untreated control watershed were developed by the simple linear regression. F-test and t-test ( p < 0·0001) suggested that calibration predictions were highly significant and treatment prediction equations differ significantly. Results showed mean runoff reductions of 86·1, 60·5 and 37·7% in the WT3, WT2 and WT1 treatment watershed over the control, respectively. Similar trends as the runoff were also recorded in soil loss reduction by 124·9, 77·1 and 40·0% for the WT3, WT2 and WT1 over Wc, respectively. Paired t-test ( p < 0·001) indicated that the means of the treatment effects on runoff and soil loss in treatment watersheds differ significantly with control watershed. It was concluded that 417 staggered contour trenches ha−1 is an optimum trenching density for supporting the horti-pastoral land use system in ravine lands of India. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

We present a sociohydrological model that can help us to better understand the system dynamics of a smallholder farmer. It couples the dynamics of the six main assets of a typical smallholder farmer: water storage capacity, capital, livestock, soil fertility, grazing access, and labor. The hydroclimatic variability, which is a main driver and source of uncertainty of the smallholder system, is accounted for at subannual scale. The model incorporates rule-based adaptation mechanisms of smallholders (for example, adjusting expenditures on food and fertilizers and selling livestocks) when farmers face adverse sociohydrological conditions, such as low annual rainfall, occurrence of dry spells, or variability of input or commodity prices. We have applied the model to analyze the sociohydrology of a cash crop producing smallholder in Maharashtra, India, in a semisynthetic case study setting. Of late, this region has witnessed many suicides of farmers who could not extricate themselves out of the debt trap. These farmers lacked irrigation and were susceptible to fluctuating commodity prices and climatic variability. We studied the sensitivity of a smallholder's capital, an indicator of smallholder well-being, to two types of cash crops (cotton and sugarcane), water storage capacity, availability of irrigation, initial capital that a smallholder starts with, prevalent wage rates, and access to grazing. We found that (i) smallholders with low water storage capacities and no irrigation are most susceptible to distress, (ii) a smallholder's well-being is low at low wage rates, (iii) wage rate is more important than absolution of debt, (iv) well-being is sensitive to water storage capacity up to a certain level, and (v) well-being increases with increasing area available for livestock grazing. Our results indicate that government intervention to absolve the debt of farmers or to invest in local storage to buffer rainfall variability may not be enough. In addition, alternative sources of income may need to be provided, for instance by ensuring minimum wages or by providing more access to grazing areas. [ABSTRACT FROM AUTHOR]

Balancing the health and sustainable use of water bodies with human needs and social benefits [ABSTRACT FROM AUTHOR]

Geostationary satellites provide measurements over a wider geographical area with high temporal sampling, while microwave measurements are more accurate but sparse. For continuous monitoring of the Indian monsoon, geostationary platform would be ideal. In this study, INSAT ( Indian National Satellite) Multi-spectral Rainfall Algorithm ( IMSRA) has been used for the estimation of rainfall from Kalpana-1 very high resolution radiometer ( VHRR) measurements. IMSRA benefits from the relative advantages of infrared and microwave sensors and is operational at the India Meteorological Department ( IMD). In this paper, rainfall is estimated over India at meteorological sub-divisional scale during the south-west monsoon season of 2009 using Kalpana-1 satellite measurements. This is the first experimental attempt to generate meteorological sub-divisional scale rainfall maps using Kalpana-1 satellite measurements. The rainfall maps for the south-west monsoon season over the Indian land region are successfully utilised as a space input for the drought monitoring of the year 2009. The results have been compared with the IMD gauge-based accumulated rainfall maps at monthly and seasonal time scales. The qualitative comparison suggests that rainfall maps generated using the present methodology is in good agreement with the IMD rainfall maps. The quantitative comparison of the sub-divisional monthly accumulated rainfall shows a correlation of 0.77 and standard error of 71 mm over the non-orographic regions, whereas a correlation of 0.60 and standard error of 117 mm is observed over the orographic regions. The present study shows that Kalpana-1 satellite-based rainfall estimates ( IMSRA technique) can act as a complementary tool for the monsoon monitoring over the Indian meteorological sub-divisions and can be used for various meteorological and hydrological applications. [ABSTRACT FROM AUTHOR]

In climate-change studies, a macroscale hydrologic model (MHM) operating over large scales can be an important tool in developing consistent hydrological variability estimates over large basins. MHMs, which can operate at coarse grid resolutions of about 1° latitude by longitude, have been used previously to study climate change impacts on the hydrology of continental scale or global river basins. They can provide a connection between global atmospheric models and water resource systems on large spatial scales and long timescales. In this study, the variable infiltration capacity (VIC) MHM is used to study large scale hydrologic impacts of climate change for Indian river basins. Large-scale changes in runoff, evapotranspiration and soil moisture for India, as well as station-scale changes in discharges for three major river basins with distinct climatic and geographic characteristics are examined in this study. Climate model projections for meteorological variables (precipitation, temperature and wind speed) from three general circulation models (GCMs) and three emissions scenarios are used to drive the VIC MHM. GCM projections are first interpolated to a 1° by 1° hydrologic model grid and then bias-corrected using a quantile-quantile mapping. The VIC model is able to reproduce observed statistics for discharges in the Ganga, Narmada and Krishna basins reasonably well, even at the coarse grid resolution employed using a calibration period for years 1965-1970 and testing period from 1971-1973/1974. An increasing trend is projected for summer monsoon surface runoff, evapotranspiration and soil moisture in most central Indian river basins, whereas a decrease in runoff and soil moisture is projected for some regions in southern India, with important differences arising from GCM and scenario variability. Discharge statistics show increases in mid-flow and low flow at Farakka station on Ganga River, increased high flows at Jamtara station upstream of Narmada, and increased high, mid-flow and low flow for Vijayawada station on Krishna River in the future. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

With the urbanisation drive comes steady growth in urban water demand. Although in the past this new demand could often be met by tapping unclaimed water sources, this option is increasingly untenable in many regions where little if any unclaimed water remains. The result is that urban water capture, and the appropriation of associated physical and institutional infrastructure, now often implies conflict with other existing uses and users. While the urbanisation process has been studied in great depth, the processes and, critically, impacts of urban water capture and appropriation are not well researched or understood. This paper undertakes a critical examination of the specific case of Hyderabad, one of India's fastest growing cities, to shed light more generally on the process of water capture by cities and the resultant impacts on pre-existing claims, particularly agriculture. It does this by examining the history and institutional response to Hyderabad's urban–rural water contest; how the results of that contest are reflected in surface and groundwater hydrology; and the eventual impacts on agriculture. The findings show that the magnitude, and sometimes even direction, of impact from urban water transfer vary in space and time and depend on location-specific rainfall patterns, the nature of existing water infrastructure and institutions, and farmers' adaptive capacities and options, notably recourse to groundwater. Broader consideration of the specific findings provides insights into policy mechanisms to reduce the possible negative impacts from the global, and seemingly inexorable, flow of water to the world's growing cities. [ABSTRACT FROM AUTHOR]

The article presents a case study on hydrological modelling of the Kangsabati river under changed climate scenario in India. The study is committed towards the planning, management and development of water resources of the river through presenting detailed future scenarios of the river basin. Included in the findings are soil water content, potential evapotranspiration and lateral flow to reach.

The article discusses a study about the impact of choice of clustering algorithm on the overall performance of a fuzzy-based hydrologic model. An overview of the Takagi-Sugeno (TS) fuzzy model is presented, along with a brief discussion about identification of the TS fuzzy model including the optimal number of fuzzy partitions. The study is based on a research about developing a TS fuzzy model for reservoir inflow forecasting in the Narmada basin, India. Key findings suggest that the choice of the clustering algorithm may not have a significant impact on the model performance if the forecast needed at 1 hour in advance.

The article investigates the water quality of the River Yamuna in the Delhi stretch in India, through the identification of changes in the concentration levels of 19 physico-chemical parameters. The research indicate that vegetation plays a significant role in acting as a biological sink for mineral nutrients, thereby restoring the water quality. The restoration of the inundation pattern of floodplains may help in the reaeration of the overlying water and re-absorption of pollutants through mud/water exchanges.

The article reports on the study of the historical climate variations and climate change in the Brahmaputra basin such as Tibetan plateau (TP), Himalayan belt and the floodplains (FP). The study analyses the historical trends in temperature and precipitation of the TP, FP, and Himalayan belt through a global 100 year monthly high resolution dataset. It shows that precipitation in the basin is determined by the strength by the monsoons. It expresses that El Niño Southern Oscillation teleconnection does not have an important role in the changes in monsoon precipitation. The study also demonstrates the relationship among air temperature, FP, TP, and the strength of the monsoon.

The daily variations of the horizontal wind shear at the 850 hPa level between a southern region (5-15°N, 40-80 °E: Zone I ) and a northern region (20-30°N, 70-90 °E: Zone 2) during the period 1979-2002 were investigated. Investigations revealed that the changes of this wind shear on a daily basis are directly related to the large-scale rainfall over the Indian region during the monsoon season. The wind shear of zonal wind together with Zone 2 is useful for determining active, weak and break periods of the Indian summer monsoon (ISM). Thus, the Horizontal Wind Shear can be used as a dynamical circulation Index (HWSI) for studying ISM variability. [ABSTRACT FROM AUTHOR]

Growing salt-tolerant under-explored crops utilizing saline ground water can provide for an economic use of abandoned semiarid lands. Field trials were conducted between 1999 and 2003 on a calcareous soil in a semiarid region of northwest India. Woody perennials were planted at the sill of furrows and irrigated with water of high salinity (EC 10–28 dS m-¹), low salinity (EC 5–9 dS m-¹) and alternately with these two waters. Woody species included Azadirachta indica, Cordia rothii, Salvadora persica, Jatropha curcas, J. gossipifolia, Ricinus communis, Catharanthus roseus, Adhatoda vasica and Aloe barbadensis. Most of these could be grown successfully but S. persica—a highly salt-tolerant halophyte—though it produced huge biomass, could not yield mature fruit due to frost injury. The salinity build up in the soil was greater during low-rainfall years, but a good rainfall year, e.g. 714 mm in 2001, helped to leach out the accumulated salts. The uptake of Na+ in plants was greater when irrigated with water of high salinity, while K+ accumulation was greater with water of low salinity. Na+ accumulation was higher in roots as compared to other parts except in Jatropha and Salvadora, while K+ accumulation was greater in leaves. There was a negative correlation between Na+ and K+ accumulation and a positive correlation between Ca²+ and Mg²+. Thus, saline water (ECiw 12 dS m-¹) can successfully be used for growing several under-explored crops of high economic value. [ABSTRACT FROM AUTHOR]

Increasing production of wheat from a limited water supply can result from efficient irrigation and nutrient management. A 3-year field experiment was conducted at the Indian Institute of Soil Science, Bhopal, to study the growth, yield, seasonal evapotranspiration (ET) and water use efficiency (WUE), and the water–yield relationship of wheat in a soybean–wheat cropping system on vertisols. Three levels of irrigation, viz. I0, no post-sowing irrigation; I1, two irrigations [crown root initiation (CRI) and flowering stage]; and I2, three irrigations (CRI, maximum tillering and flowering stage) and three nutrient management treatments, viz. F0, control (without fertilizer/manure); F1, 100 % NPK (100–21.5–24.9 kg ha−1); and F2, 100 % NPK + farmyard manure (FYM-10 t ha−1) were tested in a split-plot design with three replication. It has been established (through anova) that the year effect was rather negligible and the interaction effects of irrigation and nutrient management on the growth parameters, ET, yield components, yield and WUE were significant. Plant height, progressive leaf area index, dry matter accumulation and crop growth rate were higher in I2F2, and I2F1 and I1F2 were statistically at par. The seasonal ET increased significantly with the increase in water supply in every nutrient treatment and it was highest in I2F2 and lowest in I0F0. The highest grain yield was obtained in I2F2; and a similar yield was recorded in I3F1 and I2F2. This shows a strong interaction effect between irrigation and nutrients. Yield components, viz. number of ears m−2, number of grains ear−1 and 1000-grain weight were significant. The higher number of ears m−2 containing greater number of grains with relatively heavier weights appeared to have contributed to the higher yield in I1F2, I2F1 and I2F2. The highest WUE obtained in I0F2 did not correspond to the highest yield and maximum ET, but a WUE of 10.43 kg ha−1 mm−1 in the I2F2 combination corresponded with the highest yield and the seasonal ET requirement was 391.8, which was 137 % greater than the water use at maximum WUE. The ET–grain yield relationship was linear, with a lowest regression slope (i.e. marginal WUE) and elasticity of water production (Ewp) in F0 and a considerably higher slope and Ewp in F1 and F2. As the Ewp is positive and close to one in 100 % NPK treatment, the scope of improving WUE and yield with only inorganic fertilizer is very little, and relatively greater scope exists in the integrated management of organic manure and inorganic fertilizer. The results suggest that integrated nutrient management (100 % NPK + FYM) in conjunction with three irrigations maximized yield of wheat with concomitant improvement in ET and WUE under limited water availability. [ABSTRACT FROM AUTHOR]