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Soil moisture information has not been used extensively under PAN India mode operationally in the country due to sparse network of soil moisture measuring stations. Effort has been made to estimate the soil moisture using gridded rainfall data using soil water balance (SWB) model and subsequently to compare quantitatively with insitu soil moisture measured by gravimetric method. It is observed from the quantitative validation with ground observations that during monsoon season the accuracy with the observed was found to be fairly accurate from the early part of the July to the end of monsoon when the soil was almost recharged with the rainfall. One of the limiting factors is that during dry period and in the low rainfall areas accuracy is relatively low. Thus, the soil moisture information generated using gridded rainfall data can be used from the second month (July) of monsoon season to the end of the monsoon season on PAN India mode for irrigation scheduling and determination of sowing dates and for contingency crop planning etc. [ABSTRACT FROM AUTHOR]

A field experiment was conducted to study the effects of tillage and mulch on weed growth, soil moisture storage, productivity and profitability of upland rice during 2012-2013 at Lembucherra, India. Tillage treatments included CT-RI: conventional tillage with 100% residue incorporation and NT-RR: no-till with 100% residue retention. Mulches included rice straw (SM), Gliricidia (GM), brown manuring (BM) and none (NM). CT-RI registered the highest total weed density (89-168 weeds m−2) and biomass (9.6-183 g dry weight m−2) than those for the NT-RR (75-161 weed m−2 and 8-155 g dry weight m−2). In addition, NT-RR stored (122-172 mm) more soil moisture (0-40 cm soil depth) in comparison with that for the CT-RI treatment (110-161 mm) during crop growing season. Tillage treatments did not have the significant effect on yields. NT-RR reduced the cost of cultivation by 31.5% compared with that for the CT-RI. Thus, the net returns under NT-RR were more than those for the CT-RI. The BM recorded the lowest weed biomass and density as compared to that under other mulches. Therefore, cultivation of upland rice using NT along with BM mulching enhanced productivity and profitability of rice cultivation in India. [ABSTRACT FROM AUTHOR]

Groundwater aquifer vulnerability has been assessed by incorporating the major geological and hydrogeological factors that affect and control the groundwater contamination using GIS-based DRASTIC model along with solute transport modeling. This work demonstrates the potential of GIS to derive a vulnerability map by overlying various spatially referenced digital data layers (i.e., depth to water, net recharge, aquifer media, soil media, topography, the impact of vadose zone and hydraulic conductivity) that portrays cumulative aquifer sensitivity ratings in Kishangarh, Rajasthan. It provides a relative indication of groundwater aquifer vulnerability to contamination. The soil moisture flow and solute transport regimes of the vadose zone associated with specific hydrogeological conditions play a crucial role in pollution risk assessment of the underlying groundwater resources. An effort has been made to map the vulnerability of shallow groundwater to surface pollutants of thestudy area, using soil moisture flow and contaminant transport modeling. The classical advection-dispersion equation coupled with Richard’s equation is numerically simulated at different point locations for assessing the intrinsic vulnerability of the valley. The role of soil type, slope, and the land-use cover is considered for estimating the transient flux at the top boundary from daily precipitation and evapotranspiration data of the study area. The time required by the solute peak to travel from the surface to the groundwater table at the bottom of the soil profile is considered as an indicator of avulnerability index. Results show a high vulnerability in the southern region, whereas low vulnerability is observed in the northeast and northern parts. The results have recognized four aquifer vulnerability zones based on DRASTIC vulnerability index (DVI), which ranged from 45 to 178. It has been deduced that approximately 18, 25, 34, and 23% of the area lies in negligible, low, medium and high vulnerability zones, respectively. The study may assist in decision making related to theplanning of industrial locations and the sustainable water resources development of the selected semi-arid area. [ABSTRACT FROM AUTHOR]

This article presents a reconstruction of winter (November–March) drought by using the Standardized Precipitation Evapotranspiration Index (SPEI) based on the tree-ring width data of Pinus roxburghii (Chir pine) growing near Uttarkashi, Garhwal region, western Himalaya. This is based on a significant negative correlation between growth of Chir pine and SPEI of November–March (N-M) months. This relationship might be linked with the low rate of photosynthesis during low or freezing temperature when roots unable to take soil moisture, an analogous to drought situation as in the cold desert. The reconstructed winter SPEI record extends from 1767 to 2013 CE. It explains 30.5% of the variance for the calibration period (1903–2013 CE). The regression model was tested using Correlation Coefficient (r), Coefficient of Determination (R 2 ), Reduction of Error (RE), Coefficient of efficiency (CE) and Durbin-Watson test (DW). The extended SPEI time series has revealed several intervals of high and low intensity drought since the 17th century. There is also a linkage between (N-M) months SPEI and Western Disturbance (WD). This connection indicates that the WD may have a role in modulating droughts in the Indian region. [ABSTRACT FROM AUTHOR]

India received anomalously deficit southwest monsoon rainfall during 2014 and 2015, which resulted in consecutive droughts across the country. Reliable detection and monitoring of droughts are crucial for the reduction in drought vulnerability and associated socio-economic impacts. In this study, the potential of multiple high-resolution satellite datasets is examined using distinct drought indices over India for these two successive monsoon seasons. The satellite-derived precipitation, soil moisture and land surface temperature estimates are capable of depicting the anomalous drought conditions with some exceptions. A nonparametric multivariate standardized drought index, based on precipitation and soil moisture estimates is proven to be better in the detection of droughts when compared to conventional standardized drought indices. Overall, remote sensing satellite datasets provide immense opportunity to detect and monitor different kinds of droughts using a composite of indices. However, limited temporal records of these high-resolution satellite datasets restrain their applicability from the climatological perspective. [ABSTRACT FROM AUTHOR]

The objective of this study was to compare the performances of hydrological models that incorporate the Variable Source Area (VSA) mechanism of runoff generation with that of the Soil and Water Assessment Tool (SWAT), which uses the infiltration-excess mechanism. One of the VSA-based model used, SWAT--VSA, has been proposed as a re-conceptualization of the SWAT and uses a topography-based wetness index to identify source areas. In this study, the topography-based wetness index was replaced with a Modified Normalized Difference Water Index (MNDWI) derived from satellite imagery resulting in the SWAT--MNDWI model. Model performances were evaluated through their application in two humid tropical watersheds (Hemavathi - 2974 km²; Harangi - 538.8 km²) located in the Upper Cauvery River Basin, India. Using relevant data inputs, the three models were applied separately to both watersheds. Models were calibrated for the historical period 2000-2003 and validated for the period 2004-2006 using observed daily observed streamflow records at the watershed outlets. Overall, the SWAT--MNDWI model was the best one in simulating daily streamflow with Nash--Sutcliffe efficiency of 0.85, coefficient of determination of 0.88, percentage bias of 13.2% and root mean square error of 37.48 m³/s for the Hemavathi watershed and corresponding values of 0.88, 0.88, 1.09% and 16.67 m³/s for the Harangi watershed. The spatial patterns of surface runoff generation were similar for the SWAT--VSA and SWAT--MNDWI models, but completely different for the SWAT model. Overall results have demonstrated that models incorporating VSA hydrology, and in particular the proposed SWAT--MNDWI model, provide accurate and convenient tools for distributed hydrologic modelling in humid tropical watersheds. [ABSTRACT FROM AUTHOR]

In India, the production of turmeric is not even half compared to its potential. To analyze the possibilities for higher production in turmeric, this study was conducted at the BCKV, Gayeshpur, West Bengal, during 2011 and 2012, to evaluate the effect of irrigation scheduling (0.6, 0.9, and 1.2 irrigation water (IW)/cumulative pan evaporation (CPE) and rainfed) in main plots and nutrient management [100% inorganic, 75% inorganic + 25% FYM (Farm yard manure), and 50% inorganic + 25% FYM + 25% vermicompost] in subplots on soil moisture depletion and productivity of turmeric. The highest value of fresh rhizome yield (23.90 kg ha−1) and qualitative indices were obtained with irrigation schedule at 0.9 IW/CPE ratio water regimes and 50% inorganic + 25% FYM + 25% vermicompost. The correlation coefficients of water use and yield of turmeric were found at 0.943. The combination of 0.9 IW/CPE and 50% inorganic + 25% FYM + 25% vermicompost improved the overall performance of turmeric crop. [ABSTRACT FROM AUTHOR]

Understanding the relationship between gradually varying soil moisture (SM) conditions and monsoon rainfall anomalies is crucial for seasonal prediction. Though it is an important issue, very few studies in the past attempted to diagnose the linkages between the antecedent SM and Indian summer monsoon rainfall. This study examined the relationship between spring (April-May) SM and June rainfall using observed data during the period 1979-2010. The Empirical Orthogonal Function (EOF) analyses showed that the spring SM plays a significant role in June rainfall over the Central India (CI), South India (SI), and North East India (NEI) regions. The composite anomaly of the spring SM and June rainfall showed that excess (deficit) June rainfall over the CI was preceded by wet (dry) spring SM. The anomalies in surface-specific humidity, air temperature, and surface radiation fluxes also supported the existence of a positive SM-precipitation feedback over the CI. On the contrary, excess (deficit) June rainfall over the SI and NEI region were preceded by dry (wet) spring SM. The abnormal wet (dry) SM over the SI and NEI decreased (increased) the 2-m air temperature and increased (decreased) the surface pressure compared to the surrounding oceans which resulted in less (more) moisture transport from oceans to land (negative SM-precipitation feedback over the Indian monsoon region). [ABSTRACT FROM AUTHOR]

Change in soil moisture regime is highly relevant for agricultural drought, which can be best analyzed in terms of Soil Moisture Deficit Index (SMDI). A macroscale hydrological model Variable Infiltration Capacity (VIC) was used to simulate the hydroclimatological fluxes including evapotranspiration, runoff, and soil moisture storage to reconstruct the severity and duration of agricultural drought over semi-arid region of India. The simulations in VIC were performed at 0.25° spatial resolution by using a set of meteorological forcing data, soil parameters and Land Use Land Cover (LULC) and vegetation parameters. For calibration and validation, soil parameters obtained from National Bureau of Soil Survey and Land Use Planning (NBSSLUP) and ESA's Climate Change Initiative soil moisture (CCI-SM) data respectively. The analysis of results demonstrates that most of the study regions (> 80%) especially for central northern part are affected by drought condition. The year 2001, 2002, 2007, 2008 and 2009 was highly affected by agricultural drought. Due to high average and maximum temperature, we observed higher soil evaporation that reduces the surface soil moisture significantly as well as the high topographic variations; coarse soil texture and moderate to high wind speed enhanced the drying upper soil moisture layer that incorporate higher negative SMDI over the study area. These findings can also facilitate the archetype in terms of daily time step data, lengths of the simulation period, various hydro-climatological outputs and use of reasonable hydrological model. [ABSTRACT FROM AUTHOR]

ABSTRACT: India is very prone to heat waves during April–June. The intra‐annual variability of heat wave episodes over the east coast of India has been studied using 16‐year NCMRWF global forecast system (NGFS) retrospective data. The objective of this study is threefold: (1) identification of heat wave episodes over the east coast of India, (2) intra‐annual variability of heat wave episodes, and (3) which physical mechanism(s) is responsible for its occurrence and long‐lasting? A total of ten heat wave episodes (100 hot days) were obtained for the period 2000–2015. The intensity of heat wave is found to be maximum (minimum) for 2015 (2007) episode. The average duration of heat wave episodes was 10 days, with the longest episode lasting for 20 days in the year 2003. Moreover, an average duration of severe heat wave is 3.5 days longer than that of a normal heat wave. The common feature observed in all heat wave cases is the presence of anticyclone in the upper troposphere and associated persistence high. This can cause sinking motion, which leads to surface warming due to adiabatic compression. The lack of soil moisture (SM) induces a positive feedback between the surface and the air above it, which amplifies the sensible heating and thereby increases surface temperature. The prevailed westerly anomalies over the study region which reduce the land–sea breeze result in heat wave. The heat wave episodes exhibit a significant intra‐annual variability. Intensity of heat waves averaged over the east coast of India has shown an increase of 0.06 °C per heat wave. The geopotential height anomaly, vertical velocity, and SM exhibit significant intra‐annual variability between the episodes and become decisive parameters for the maintenance and variability. The correlation coefficient between the maximum temperature and SM is found to be −0.56, indicating the importance of SM regulating the intensity of heat waves. [ABSTRACT FROM AUTHOR]

India has witnessed some of the most severe historical droughts in the current decade, and severity, frequency, and areal extent of droughts have been increasing. As a large part of the population of India is dependent on agriculture, soil moisture drought affecting agricultural activities (crop yields) has significant impacts on socioeconomic conditions. Due to limited observations, soil moisture is generally simulated using land-surface hydrological models (LSMs); however, these LSM outputs have uncertainty due to many factors, including errors in forcing data and model parameterization. Here we reconstruct agricultural drought events over India during the period of 1951-2015 based on simulated soil moisture from three LSMs, the Variable Infiltration Capacity (VIC), the Noah, and the Community Land Model (CLM). Based on simulations from the three LSMs, we find that major drought events occurred in 1987, 2002, and 2015 during the monsoon season (June through September). During the Rabi season (November through February), major soil moisture droughts occurred in 1966, 1973, 2001, and 2003. Soil moisture droughts estimated from the three LSMs are comparable in terms of their spatial coverage; however, differences are found in drought severity. Moreover, we find a higher uncertainty in simulated drought characteristics over a large part of India during the major crop-growing season (Rabi season, November to February: NDJF) compared to those of the monsoon season (June to September: JJAS). Furthermore, uncertainty in drought estimates is higher for severe and localized droughts. Higher uncertainty in the soil moisture droughts is largely due to the difference in model parameterizations (especially soil depth), resulting in different persistence of soil moisture simulated by the three LSMs. Our study highlights the importance of accounting for the LSMs' uncertainty and consideration of the multi-model ensemble system for the real-time monitoring and prediction of drought over India. [ABSTRACT FROM AUTHOR]

Performance evaluation of Border irrigation method was carried out for cotton field in village Kirarkot, Sirsa (Haryana). Water application, storage and distribution efficiency were estimated using measurements of soil moisture (%), infiltration rate (cm/hr), water advance and recession time (minute) during different irrigation events. The advance time increased during the growing season due to increased infiltration rate and increased resistance to flow by the growing crops. The water application efficiency of cotton field was 100 per cent as average applied depth (8.26 cm for canal irrigation and 9.06 cm for tubewell irrigation) of irrigation was less than the average required depth (10.30 cm for canal irrigation and 10.98 cm for tubewell irrigation) throughout the field plots. The observed water storage efficiency in different cotton fields varied from 72.92 - 90.08 per cent indicating under irrigation. Water distribution efficiency of cotton fields (97.8 -99.2per cent) indicated a relatively high degree of uniformity of water application. Stratified soil profile (sandy loam: 0-30 cm and sandy clay loam: 30-120 cm) of the selected fields reduced the infiltration rate to relatively very low value after 10-15 minutes creating favourable condition for uniformity of water application under border irrigation. [ABSTRACT FROM AUTHOR]

Soil moisture is a key parameter in the prediction of southwest monsoon rainfall, hydrological modelling, and many other environmental studies. The studies on relationship between the soil moisture and rainfall in the Indian subcontinent are very limited; hence, the present study focuses the association between rainfall and soil moisture during different monsoon seasons. The soil moisture data used for this study are the ESA (European Space Agency) merged product derived from four passive and two active microwave sensors spanning over the period 1979-2013. The rainfall data used are India Meteorological Department gridded daily data. Both of these data sets are having a spatial resolution of 0.25° latitude-longitude grid. The study revealed that the soil moisture is higher during the southwest monsoon period similar to rainfall and during the pre-monsoon period, the soil moisture is lower. The annual cycle of both the soil moisture and rainfall has the similitude of monomodal variation with a peak during the month of August. The interannual variability of soil moisture and rainfall shows that they are linearly related with each other, even though they are not matched exactly for individual years. The study of extremes also exhibits the surplus amount of soil moisture during wet monsoon years and also the regions of surplus soil moisture are well coherent with the areas of high rainfall. [ABSTRACT FROM AUTHOR]

Indian monsoon depressions (MDs) are synoptic-scale cyclonic systems that propagate across peninsular India three or four times per monsoon season. They are responsible for the majority of rainfall in agrarian north India, so constraining precipitation estimates is of high importance. Here, a case study from August 2014 is used to explore the relationship between varying soil moisture and the resulting track and structure of an incident MD using the Met Office Unified Model. This case study is chosen with the view to increasing understanding of the general impact of soil moisture perturbations on monsoon depressions. It is found that increasing soil moisture in the monsoon trough region results in deeper inland penetration and a more developed structure-for example, a warmer core in the midtroposphere and a stronger bimodal potential vorticity core in the mid-to-lower troposphere-with more precipitation, and a structure that in general more closely resembles that found in depressions over the ocean, indicating that soil moisture may enhance the convective mechanism that drives depressions over land. This experiment also shows that these changes are most significant when the depression is deep and negligible when it is weakening. Increasing soil moisture in the sub-Himalayan arable zone, a region with large irrigation coverage, also caused deeper inland penetration and some feature enhancement in the upper troposphere, but no significant changes were found in the track heading or lower-tropospheric structure. [ABSTRACT FROM AUTHOR]

In North-Western India, wheat is normally irrigated at an IW: CPE of 0.9, with 75 mm depth of irrigation water (conventional irrigation practice, CP) resulting in wastage of water. An effective irrigation strategy is required that will save irrigation water without compromising yield penalty. So, an experiment was conducted at Punjab Agricultural University, Ludhiana during 2014–15 and 2015–16 in split plot design, keeping four sowing dates {25th October (D 1 ), 10th November (D 2 ), 25th November (D 3 ) and 10th December (D 4 )} in the main plots and five irrigation schedules {irrigation at 15 (FC 15 ), 25 (FC 25 ), 35 (FC 35 ) and 45 (FC 45 )% depletion of soil moisture from field capacity (FC) and a conventional practice} in sub plots. The objectives of the study were to evaluate the effect of drip irrigation amounts on field water balance, yield and water productivity of wheat. The results revealed that mean grain yield decreased by 8.3 & 8.7, 10.7 & 10.6 and 13.1 & 13.4% from D 1 to D 2 , D 2 to D 3 and D 3 to D 4 during 2014-15 and 2015-16, respectively. Pooled grain yield decreased by 29% with delay in sowing from D 1 to D 4. Reduction in ETc was 10% in D 4 as compared to D 1 during 2014-15 and 24% during 2015-16. The highest grain yield was obtained with irrigation applied at 15% depletion from FC. The pooled grain yield decreased by 30%, ETc by 21% and water productivity by 29% in FC 45 as compared to FC 15 . The water saving in drip irrigation during 2014-15 was 62, 70, 77 and 83% in FC 15 , FC 25 , FC 35 and FC 45 respectively as compared to CP. The respective values during 2015-16 were 38, 44, 54 and 60%. The results demonstrate that irrigating wheat at 15% depletion of FC using drip method of irrigation as a novel concept that saves irrigation water in addition to higher grain yield. [ABSTRACT FROM AUTHOR]

Conventional agricultural practices that use excessive chemical fertilizers and pesticides come at a great price with respect to soil health, a key component to achieve agricultural sustainability. Organic farming could serve as an alternative agricultural system and solve the problems associated with the usage of agro-chemicals by sustainable use of soil resources. A study was carried out to evaluate the impact of organic vs. conventional cultivations of basmati rice on soil health during Kharif (rainy) season of 2011 at Kaithal district of Haryana, India, under farmers' participatory mode. Long-term application of organic residues in certified organic farms was found to improve physical, chemical, and biological indicators of soil health. Greater organic matter buildup as indicated by higher soil organic carbon content in organic fields was critical to increase soil aggregate stability by increasing water holding capacity and reducing bulk density. Proper supplementation of nutrients (both major and micro nutrients) through organic residue addition favored biologically available nutrients in organic systems. Further, the prevalence of organic substrates stimulated soil microorganisms to produce enzymes responsible for the conversion of unavailable nutrients to plant available forms. Most importantly, a closer look at the relationship between physicochemical and biological indicators of soil health evidenced the significance of organic matter to enzyme activities suggesting enhanced nutrient cycling in systems receiving organic amendments. Enzyme activities were very sensitive to short-term (one growing season) effects of organic vs. conventional nutrient management. Soil chemical indicators (organic matter and nutrient contents) were also changed in the short-term, but the response was secondary to the biochemical indicators. Taken together, this study indicates that organic farming practices foster biotic and abiotic interactions in the soil which may facilitate in moving towards a sustainable food future. [ABSTRACT FROM AUTHOR]

Rainfall over Madhya Pradesh (MP) in central India has large intra-seasonal variability causing droughts and floods in many years. In this study, rainfall variability in daily and monthly scale over central India has been examined using observed data. Consistency among various datasets such as rainfall, surface temperature, soil moisture and evapotranspiration has been examined. These parameters are from various different sources and critical for drought monitoring and prediction. It is found that during weak phases of monsoon, central India receives deficit rainfall with weaker monsoon circulation. This phase is characterized by an anticyclonic circulation at 850 hPa centered on MP. The EOF analysis of daily rainfall suggests that the two leading modes explain about 23-24% of rainfall variability in intraseasonal timescale. These two modes represent drought/flood conditions over MP. Relationship of weak phases of rainfall over central India with real-time multivariate (RMM) indices of Madden Julian Oscillation (MJO) has been examined. It is found that RMM-6, RMM-7, RMM-1 and RMM-2 describe the weak monsoon conditions over central India. However, frequency of drought occurrence over MP is more during RMM-7 phase. Surface temperature increases by about 0.5°-1° during weak phases of rainfall over this region. Soil moisture and evapotranspiration gradually reduce when rainfall reduces over the study region. Soil moisture and evapotranspiration anomalies have positive pattern during good rainfall events over central India and gradually reduce and become negative anomalies during weak phases. [ABSTRACT FROM AUTHOR]

Early vigour had been a target trait for developing wheat varieties tolerant to moisture stress. Manifestation of this trait depends on the relative efficiency of a genotype to utilize the residual soil moisture and dew precipitation, thereby developing a good canopy in lesser time after emergence. Lack of proper quantification system had always prevented the use of early vigour as a dependable selection parameter under field conditions. Digital imaging intervention has facilitated phenotyping this parameter in the form of early ground cover (EGC). Utilizing this phenotyping strategy, we have identified a quantitative trait locus for EGC located on the chromosome 6A (short arm) with a significant additive component under moisture stress in the north western plain zone of India. [ABSTRACT FROM AUTHOR]

The main objective of this study is to evaluate suitability of shrink-swell soils for surface irrigation system based upon a parametric evaluation system in low irrigation potential (7%) of cotton growing Yavatmal district, Maharashtra, India. The thirty three shrink-swell soil series on basaltic landforms were identified from reconnaissance soil survey on 1:50,000 scale and evaluated for surface irrigation methods using Geographic Information System (GIS). The standard weekwise rainfall data showed that the rainfall is less than 20% of total precipitation during September and December, the top A horizon reaches to wilting point and needs supplementary protective irrigation to cotton based cropping systems . It was estimated that ten soil mapping units (1.8 Mha and 13.89%) of shrink-swell soils on moderate slopes (5 to 8%) were evaluated as suitable for surface methods and calculated the irrigation intervals that vary from 8.61±1.35 days for cotton to 8.9±1.4 days for wheat and 10±1.64 days for sugar cane. The study emphasized the utility of soil resource maps helps to delineate the soils with large PAWC(>200mm) with slight yield advantage and will serve as benchmark sites to monitor the interrelationships of soil water dynamics with respect to climate and cotton yields. [ABSTRACT FROM AUTHOR]

The assessment of land use land cover (LULC) and climate change over the hydrology of a catchment has become inevitable and is an essential aspect to understand the water resources-related problems within the catchment. For large catchments, mesoscale models such as variable infiltration capacity (VIC) model are required for appropriate hydrological assessment. In this study, Ashti Catchment (sub-catchment of Godavari Basin in India) is considered as a case study to evaluate the impacts of LULC changes and rainfall trends on the hydrological variables using VIC model. The land cover data and rainfall trends for 40 years (1971-2010) were used as driving input parameters to simulate the hydrological changes over the Ashti Catchment and the results are compared with observed runoff. The good agreement between observed and simulated streamflows emphasises that the VIC model is able to evaluate the hydrological changes within the major catchment, satisfactorily. Further, the study shows that evapotranspiration is predominantly governed by the vegetation classes. Evapotranspiration is higher for the forest cover as compared to the evapotranspiration for shrubland/grassland, as the trees with deeper roots draws the soil moisture from the deeper soil layers. The results show that the spatial extent of change in rainfall trends is small as compared to the total catchment. The hydrological response of the catchment shows that small changes in monsoon rainfall predominantly contribute to runoff, which results in higher changes in runoff as the potential evapotranspiration within the catchments is achieved. The study also emphasises that the hydrological implications of climate change are not very significant on the Ashti Catchment, during the last 40 years (1971-2010). [ABSTRACT FROM AUTHOR]

• Evaluated the performance of SWAT in reproducing daily-scale reservoir inflow. • HEC-ResSim derived reservoir outflow estimates are reliable for baseline scenario. • Proposed 10-daily scale E-flow estimation approach is highly reliable. • EPRC and SPRC scenarios based rule curves have more practical implications. • Proposed SWAT-HEC-ResSim-GA approach could effectively govern reservoir operation. The complex hydrological connectivity of integrated river-reservoir catchment command regions in conjunction with abrupt societal development and population growth impose adverse water availability scenario in the global reservoirs. In this context, to formulate optimal reservoir operation policies, numerous reservoir simulation and optimization models are currently on board. However, lack of combined hydrologic and hydraulic conceptualizations in the existing reservoir operation framework fetches considerable uncertainty; thereby leading to formulation of erroneous reservoir operation rule. This study proposed an integrated Soil and Water Assessment Tool (SWAT) based hydrologic, HEC-ResSim based hydraulic, and genetic algorithm (GA) based optimization framework (SWAT-HEC-ResSim-GA) for formulating the optimal reservoir operation rule of the Kangsabati reservoir located in the eastern India. Unlike the existing reservoir operation rules, the present study incorporates a 10-daily-scale environmental flow estimation approach to quantify the water demand. The proposed reservoir operation framework generated rule curve based HEC-ResSim simulation revealed improved reservoir performance with reservoir time reliability, volume reliability, and resiliency magnitudes of 0.631, 0.736, and 0.591, respectively. Finally, this study endorses to use the developed methodology for supply–demand management, and subsequent, reservoir operation in any global reservoir catchment-command regions with utmost accuracy. [ABSTRACT FROM AUTHOR]

Due to depleting water supplies and the cultivation of high water-demanding crops like rice, water deficit in crop production has become a major concern, especially in semi-arid regions of South Asia. Soybean has been considered a possible substitution for high-water-demand crops with improved water productivity and nutrient quality. However, due to inefficient and injudicious water and fertilizer management, the overall productivity and profitability of soybean is quite low. Hence, a three-year field investigation was carried out using strip-strip plot design with three replications to study the individual and combined effects of tillage, irrigation, and fertilizer levels on crop yield and quality, soil moisture and soil microbial dynamics. Results revealed that zero tilled-flat beds (ZTFB) and conventional tilled-raised beds (CTRB) reduced the irrigation water requirement by 5.15–5.45 and 3.12–3.49 cm ha−1, respectively, compared to conventional tilled-flat beds (CTFB). Moreover, CTRB enhanced seed yield by 8.1–31.5 %, biomass yield by 6.5–34.1 %, crop water productivity (CWP) by 27.2–30.9 %, and irrigation water productivity (IWP) by 55.2–57.5 % over CTFB. Similarly, in 2016 and 2017, CTRB had higher SPAD-chlorophyll content (34.3 and 33.2 in the top leaves) and normalized difference vegetation index (NDVI) (0.51 and 0.71) values than CTFB and ZTFB. At 0.0–0.30 m soil depth, ZTFB showed the highest soil moisture content of 11.2 % and 22.5 %, respectively, leading to the highest relative water content (RWC) of 76.7–78.7 % in soybean leaves. As a result, ZTFB took 4–8 days longer to mature than CTFB, delaying the sowing of the following wheat crop. During the 2016–2018 growing seasons, irrigation applied at the depletion of available soil moisture (DASM) by 25 % and 100 % rate of recommended fertilizer (RRF) achieved significantly higher crop, biomass yields, protein yield, SPAD, NDVI, and CWP than irrigation at lower levels. Interaction effects revealed that combinations of CTRB and ZTFB + 25 % DASM + 100 % RRF strategies generated significantly (P ≤ 0.05) higher seed yield, biomass yield, and CWP. At the same time, ZTFB had significantly higher alkaline and acid phosphatase activity than CTRB, whereas the latter had significantly higher soil microbial biomass carbon. In comparison to individual use of these crop management methods, the results of this study showed planning soybean either in CTRB or ZTFB, irrigating at 25 % DASM, and fertilizing crops with 100 % RRF could help achieve higher crop and water productivity, thus sustaining soybean production in India and adjoining regions with similar agro-ecology. • Tillage, irrigation and fertilizer rates on soybean growth were studied in three years. • CTRB+DASM 25 % + 100 % fertilizer rate enhanced soybean yield and resource use efficiency. • Due to higher soil moisture content, a soybean grown in ZT-flat beds matures later. [ABSTRACT FROM AUTHOR]

The present study has developed the time series database surface soil moisture over India, for June, July and August months for the period of 20 years from 1991 to 2010, using data products generated under Climate Change Initiative Programme of European Space Agency. These three months represent the crop sowing period in the prime cropping season in the country and the soil moisture data during this period is highly useful to detect the drought conditions and assess the drought impact. The time series soil moisture data which is in 0.25 degree spatial resolution was analyzed to generate different indicators. Rainfall data of same spatial resolution for the same period, generated by India Meteorological Department was also procured and analyzed. Geospatial analysis of soil moisture and rainfall derived indicators was carried out to study (1) inter annual variability of soil moisture and rainfall, (2) soil moisture deviations from normal during prominent drought years, (3) soil moisture and rainfall correlations and (4) drought exposure based on soil moisture and rainfall variability. The study has successfully demonstrated the potential of these soil moisture time series data sets for generating regional drought surveillance information products, drought hazard mapping, drought exposure analysis and detection of drought sensitive areas in the crop planting period. [ABSTRACT FROM AUTHOR]

Surface level soil moisture from two gridded datasets over India are evaluated in this study. The first one is the UK Met Office (UKMO) soil moisture analysis produced by a land data assimilation system based on Extended Kalman Filter method (EKF), which make use of satellite observation of Advanced Scatterometer (ASCAT) soil wetness index as well as the screen level meteorological observations. Second dataset is a satellite soil moisture product, produced by National Remote Sensing Centre (NRSC) using passive microwave Advanced Microwave Scanning Radiometer 2 measurements. In-situ observations of soil moisture from India Meteorological Department (IMD) are used for the validation of the gridded soil moisture products. The difference between these datasets over India is minimum in the non-monsoon months and over agricultural regions. It is seen that the NRSC data is slightly drier (0.05%) and UKMO soil moisture analysis is relatively wet during southwest monsoon season. Standard AMSR-2 satellite soil moisture product is used to compare the NRSC and UKMO products. The standard AMSR-2 and UKMO values are closer in monsoon season and AMSR-2 soil moisture is higher than UKMO in all seasons. NRSC and AMSR-2 showed a correlation of 0.83 (significant at 0.01 level). The probability distribution of IMD soil moisture observation peaks at 0.25 m/m, NRSC at 0.15 m/m, AMSR-2 at 0.25 m/m and UKMO at 0.35 m/m during June-September period. Validation results show UKMO analysis has better correlation with in-situ observations compared to the NRSC and AMSR-2 datasets. The seasonal variation in soil moisture is better represented in UKMO analysis. Underestimation of soil moisture during monsoon season over India in NRSC data suggests the necessity of incorporating the actual vegetation for a better soil moisture retrieval using passive microwave sensors. Both products have good agreement over bare soil, shrubs and grassland compared to needle leaf tree, broad leaf tree and urban land cover types. [ABSTRACT FROM AUTHOR]

Many soils in the region of Kanpur, North India, are heavily affected by the leather industry and its upstream supplier sector, as indicated by elevated chromium (Cr) contents. Under reducing conditions—for instance, at water saturation after monsoon rain or flood irrigation—the dynamic and species distribution of Cr may be affected due to changes in redox potential (EH). In this study, the influence of EH on the speciation and release of Cr from a contaminated agricultural soil was investigated. A soil sample that was affected by hyperalkaline leachate from chromite ore processing residue, was taken and packed in soil columns, and subjected to a saturation–drainage–saturation cycle. After initial water saturation, the EH dropped slowly to minimum values of around ‒100 mV (calculated to pH 7), while EH was controlled by CrO4 2-/Cr2O3(s), or CrO4 2-/(Fe,Cr)OOH redox couples. Soil drainage resulted in a quick return to oxidizing conditions; i.e., EH > 300 mV. The Cr species distribution and release showed a clear trend with EH. At the beginning of the experiment, under oxidizing and weakly reducing conditions (EH range from >100 to 300 mV), Cr(VI) was released in particular. However, under moderately reducing conditions (EH range from 100 to –100 mV), Cr was gradually immobilized and irreversible sequestered via reductive precipitation. The results presented in this study provide an improved understanding of the mobility of Cr(VI) in contaminated soils at varying water contents, which is essential for the evaluation of environmental risks in this region. [ABSTRACT FROM AUTHOR]

The direct impact of high resolution land surface initialization on the forecast bias in a regional climate model in recent years over Indian summer monsoon region is investigated. Two sets of regional climate model simulations are performed, one with a coarse resolution land surface initial conditions and second one used a high resolution land surface data for initial condition. The results show that all monsoon years respond differently to the high resolution land surface initialization. The drought monsoon year 2009 and extended break periods were more sensitive to the high resolution land surface initialization. These results suggest that the drought monsoon year predictions can be improved with high resolution land surface initialization. Result also shows that there are differences in the response to the land surface initialization within the monsoon season. Case studies of heat wave and a monsoon depression simulation show that, the model biases were also improved with high resolution land surface initialization. These results show the need for a better land surface initialization strategy in high resolution regional models for monsoon forecasting. [ABSTRACT FROM AUTHOR]

Indian mustard [ Brassica juncea (L.) Czern & Coss] is the predominant oilseed crop in semi-arid India, conventionally grown by repeated plowings during the rainy seasons to conserve soil moisture in fallow fields. To evaluate the effect of establishment methods on productivity, soil health and economics of mustard under various cropping systems, a field experiment was conducted for four years from 2009–2010 to 2012–2013 at the Directorate of Rapeseed-Mustard Research, Bharatpur, India. Conventional tillage (CT), reduced tillage (RT), zero tillage (ZT), and permanent furrow irrigated raised beds (FIRB) treatments were evaluated for five mustard-based cropping systems, viz., fallow–mustard, green manure–mustard, brown manure–mustard, cluster bean–mustard, and pearl millet–mustard, in split-plot design with three replications. The variable tillage practices significantly affected seed, stover, and biological yields, production efficiency, and the economics of mustard along with the bulk density and soil organic carbon dynamics. After four years of the experimentation, the highest mustard seed yield was obtained under FIRB (2765 kg ha −1 ) which was 23.6% higher over CT. The seed yield obtained under ZT (2533 kg ha −1 ) was 17.5% higher over CT. The seed yield recorded under RT was found similar with ZT, but significantly higher over CT due to higher dry matter accumulation, higher translocation efficiency, and greater sink/source potential at the seed filling stage. Among the cropping systems, highest yield was obtained under the green manure-mustard system followed by the cluster bean–mustard system. The seed yield enhancement with the green manure–mustard cropping system was 13.9% over the fallow-mustard system. The highest assimilate supply (0.33 g siliqua −1 ) was recorded under ZT. Sustainability parameters, including harvest index (0.29), sustainability yield index (0.85), and production efficiency (16.1 kg ha −1 day −1 ) were also found highest under ZT after four years of the experiment. Soil organic carbon increased to 0.39% and 0.36% in ZT and FIRB, respectively, from 0.26% in CT. A higher mass of soil organic carbon and carbon sequestration potential rate was recorded under ZT. The bulk density under ZT and FIRB decreased over CT. The soil organic carbon, the mass of soil organic carbon, and the carbon sequestration potential rate were highest in the green manure–mustard system. These parameters were similar between the pearl millet–mustard system and fallow-mustard system, indicating that an additional pearl millet crop can be successfully grown without exhausting the soil organic carbon. The net returns, profitability, and the benefit-cost ratio were highest under FIRB, followed by ZT. [ABSTRACT FROM AUTHOR]

In 2013, Indian summer monsoon witnessed a very heavy rainfall event (>30 cm/day) over Uttarakhand in north India, claiming more than 5000 lives and property damage worth approximately 40 billion USD. This event was associated with the interaction of two synoptic systems, i.e., intensified subtropical westerly trough over north India and north-westward moving monsoon depression formed over the Bay of Bengal. The event had occurred over highly variable terrain and land surface characteristics. Although global models predicted the large scale event, they failed to predict realistic location, timing, amount, intensity and distribution of rainfall over the region. The goal of this study is to assess the impact of land state conditions in simulating this severe event using a high resolution mesoscale model. The land conditions such as multi-layer soil moisture and soil temperature fields were generated from High Resolution Land Data Assimilation (HRLDAS) modelling system. Two experiments were conducted namely, (1) CNTL (Control, without land data assimilation) and (2) LDAS, with land data assimilation (i.e., with HRLDAS-based soil moisture and temperature fields) using Weather Research and Forecasting (WRF) modelling system. Initial soil moisture correlation and root mean square error for LDAS is 0.73 and 0.05, whereas for CNTL it is 0.63 and 0.053 respectively, with a stronger heat low in LDAS. The differences in wind and moisture transport in LDAS favoured increased moisture transport from Arabian Sea through a convectively unstable region embedded within two low pressure centers over Arabian Sea and Bay of Bengal. The improvement in rainfall is significantly correlated to the persistent generation of potential vorticity (PV) in LDAS. Further, PV tendency analysis confirmed that the increased generation of PV is due to the enhanced horizontal PV advection component rather than the diabatic heating terms due to modified flow fields. These results suggest that, two different synoptic systems merged by the strong interaction of moving PV columns resulted in the strengthening and further amplification of the system over the region in LDAS. This study highlights the importance of better representation of the land surface fields for improved prediction of localized anomalous weather event over India. [ABSTRACT FROM AUTHOR]

Construction of big dams on rivers develops artificial lakes or water reservoirs which conceive alterations in soil properties of the upstream catchment area. An undulating topography and freckly soil properties cause ups and downs in tree diversity, composition and distribution. The study aimed to evaluate the effect of Gobind Sagar reservoir on soil properties relative to the distance from it and aßsess its effect on tree diversity, evenness and their distribution in tropical and subtropical forests. Based on data analysis it was found that the soil moisture and organic carbon decreased along with increasing distance from the reservoir. It played a significant role in varying tree diversity. The sites distributed within 0-2 km showed significantly higher a and β-diversity indices. Tree species richness and diversity indices showed a strong correlation ( p < 0.05) with soil moisture and organic carbon content. Simpson's and McIntosh evenness indices showed a strong negative correlation with soil bulk density. Indirect Detrended Correspondence Analysis (DCA) identified soil moisture and soil organic carbon as two major environmental gradients that influenced tree diversity and their distribution in five tropical and four subtropical forests in an upstream catchment of the reservoir. Mixed forests inhabited moist sites and Acacia-Pinus forests showed an inclination to dry areas. Canonical Correspondence Analysis (CCA) revealed that the tree species in tropical forests were mainly affected by driving forces such as soil moisture, organic carbon and bulk density whereas, in subtropical forest tree species were influenced by elevation, soil pH, EC and clay content. [ABSTRACT FROM AUTHOR]

Cereal cropping productivity in the Indo-Gangetic Plain ( IGP) of India is declining, which may be overcome by diversification, alternate crop establishment methods and mulching. This study was conducted to determine whether no-till flat ( NTF), permanent raised beds ( PRB) and nontraditional ex situ mulching would improve crop and water productivity, economic profitability and soil biological properties in an irrigated maize ( Zea mays)-wheat ( Triticum aestivum) system ( MWS). NTF systems produced 10% higher economic net returns compared with PRBs. Non-traditional mulching ( Sesbania, Jatropha and Brassica) increased yields by >10% and net returns by >12% compared with no-mulch. The water saving in PRBs compared with NTF systems was 79, 94 and 173 mm/ha in maize, wheat and MWS, respectively. PRBs saved 29.2% of irrigation water and improved the MWS irrigation water productivity ( WPI) by 24.5% over NTF. On average, mulching saved 23.8 mm/ha irrigation water over no-mulch and improved WPI by 12.0%. PRBs with ex situ mulching produced wheat and maize equivalent system yields lower than NTF but improved WPI and soil biological properties. Jatropha and Sesbania mulching improved yield, water saving, WPI and system profitability. In limited irrigation and no crop residue availability conditions, Sesbania, Jatropha and Brassica vegetation material have potential applications for ex situ mulching under PRBs for water saving and NTF for productivity. [ABSTRACT FROM AUTHOR]

Accurate soil moisture data, critical for many applications such as agriculture and estimation of ground water, is limited worldwide, and particularly over India, by the absence of sustained multisite observations. A long-term sustained soil moisture observation at four vertical levels (5, 15, 50, and 100 cm) is now available at several locations over India under a multi-institutional program Climate Observations and Modeling Network (COMoN) led by CSIR, India. At the same time, a high resolution (0.1^\circ\times 0.1^\circ ) daily (moving 5-day mean) surface relative soil moisture data set has now become available from the Advanced Scatterometer (ASCAT) . However, there is a need to compare remotely sensed data and in situ observations to ensure consistency and quantify uncertainties. This is particularly true for India characterized by diverse climatic zones. We present a comparative analysis of gridded ASCAT soil moisture data and in situ COMoN station data over six locations in India during the period 2010–2013. A multiscale analysis is carried out involving daily, weekly, monthly, and seasonal timescales at different geographical locations. Analyses show that the two data sets are generally consistent, although there are seasonalities in the agreement; the correlation coefficient is higher for the wet season (summer, autumn), and moderate for dry season (winter, spring) . The correlation coefficients are ranged from 0.73 to 0.91 and above 99% significance level. The results quantify the reliability and robustness of ASCAT soil moisture over different climatic regions in India; the results also identify certain differences between the two data sets. [ABSTRACT FROM PUBLISHER]

• Soils from three agro-climatic zones were classified using MSCC and Nix. • Soil OC was predicted using MSCC and Nix in different combinations. • Both non– standardized and MSCC-standardized Nix values were used. • Results indicated the reproducibility and potential accuracy of the Nix sensor. • Nix + MSCC produced satisfactory surface OC prediction. Optimal soil management depends on rapid and frequent monitoring of key soil properties, which are conventionally measured in the laboratory using laborious wet-chemistry protocols. The Nix color sensor has recently exhibited promise for predicting several soil properties using soil color. This study evaluated the relationship between the Munsell Soil Color Chart (MSCC) color values of dry and ground surface soil samples to those reported by the Nix color sensor with (Nix STD) and without MSCC standardization (Nix NON-STD) to classify 371 samples collected from three contrasting soil types, collected from three agro-climatic zones (coastal saline zone, red and laterite zone, and Gangetic alluvial zone) and to predict soil organic carbon (OC) using different multivariate data mining algorithms. Comparing the CIEL*a*b* color values reported by the MSCC and the Nix STD , an acceptable mean color difference (ΔE* ab) value of 5.20 was obtained, indicating the potential accuracy of the Nix sensor. Principal component analysis efficiently clustered the soil types using the RGB variables extracted from the MSCC color chips in tandem with the Nix STD /Nix NON-STD data. Both classification tree and linear support vector machine algorithms perfectly classified all three contrasting soil types using Nix NON-STD data alone. Besides, the combination of the MSCC and the Nix NON-STD datasets produced the best OC prediction (R2 = 0.66) via random forest (RF) algorithm and indicated the potential of Nix in digital soil morphometrics. In most of the RF models, redness (a*), yellowness (b*), and yellow (Y) variables appeared influential, presumably because of their negative correlation with OC in red and laterite soils. More research is warranted to measure the impacts of variable soil moisture and other confounding soil morphological features on the soil classification and OC prediction performance to extend the approach for classifying soil types and predicting OC in-situ. [ABSTRACT FROM AUTHOR]

• Evaluation of precipitation from downscaled SM using SM2RAIN bottom-up approach. • Optical based SM downscaling method is used to downscale SMOS and ESA CCI SM. • Indirect validation of downscaled SM. • The framework is evaluated in Ganga Basin, India. Soil moisture (SM) and precipitation play an essential part in land surface and atmospheric processes. Availability of high-resolution SM and precipitation data are quintessential for regional and global studies in hydro climatology. There exists a strong interconnection between the varying amounts of SM and the precipitation over a given area, giving rise to the bottom-up approach of estimating precipitation from SM2RAIN. This study examines precipitation derived from SM, downscaled using a unique cognation of land surface temperature (LST), vegetation index (VI), and SM. For this work, MODIS optical data having one km spatial resolution has been used to downscale the SMOS (25 km) and ESA CCI (25 km) SM data to generate four fine-resolution SM products SMOS-LST-NDVI, SMOS-LST-EVI, ESA CCI-LST-NDVI, and ESA CCI-LST-EVI, respectively. In this study, the Ganga basin in India is used as a case study area to assess the bottom-up SM2RAIN approach. The correlation analysis of SM products with LST, NDVI, and EVI, shows that LST has a robust negative correlation, whereas NDVI and EVI have a significant positive correlation. Results obtained from the SM2RAIN simulation from downscaled SM managed to capture the spatial variation of the high precipitation event. Validation with IMERG GPM precipitation data shows that the SMOS-LST-NDVI precipitation product best captures the spatial variation of observed precipitation. The present study results provide convincing evidence that high-resolution precipitation can be estimated using satellite-derived SM data at basin level, as long as better calibration and validation data are available. [ABSTRACT FROM AUTHOR]

• Spatiotemporal dependence between soil moisture (SM) and precipitation (P) over India investigated using Tail Dependence and Event Coincidence Analysis. • The precursor coincidence rate quantifies the fraction of P extreme events happening after SM has already attained extreme state. • Basin-scale analysis of temporal evolution of precursor coincidence revealed distinct patterns for major river basins over India. • Higher SM anomalies triggering P extremes is explored using trigger coincidence rate. Anthropogenic climate change has impacted almost all phases of the global water cycle. Growing consensus asserts that extreme precipitation events will only rise in the years to come. However, an increase in extreme precipitation events does not necessarily correspond to higher flood risk. Much onus lies on the antecedent conditions before the storm events. Despite the importance of Soil Moisture (SM) – Precipitation (P) dependence in runoff generation, relatively few studies have unraveled the SM – P dependence. Previous studies were constrained by the direct trivial relationship existing between SM and P, and hence there is a need to understand direction and dynamical interdependency. We employed Event Coincidence Analysis (ECA) to identify and quantify the preconditioning of P extremes by soil moisture (SM) anomalies. High precursor coincidence rate (greater than45%) was obtained for traditional flash flood-prone areas over India - Ganga river basin, West-flowing rivers of Kutch and Saurashtra including Luni, inland drainage of Rajasthan and Narmada river basin, indicating the robustness of the approach. The trigger coincidence rate reveals strong SM-P coupling over central India. Our results indicate the applicability of ECA in characterizing the spatiotemporal patterns of SM-P dependence over India. [ABSTRACT FROM AUTHOR]

Previous studies on the response of the South Asian summer monsoon to the direct radiative forcing caused by anthropogenic absorbing aerosols have emphasized the role of premonsoonal aerosol forcing. This study examines the roles of aerosol forcing in both pre- and postonset periods using the Community Earth System Model, version 1.0.4, with the Community Atmosphere Model, version 4. Simulations were perturbed by model-derived radiative forcing applied (i) only during the premonsoonal period (May-June), (ii) only during the monsoonal period (July-August), and (iii) throughout both periods. Soil water storage is found to retain the effects of premonsoonal forcing into succeeding months, resulting in monsoonal central India drying. Monsoonal forcing is found to dry all of India through local responses. Large-scale responses, such as the meridional rotation of monsoon jet during June and its weakening during July-August, are significant only when aerosol forcing is present throughout both premonsoonal and monsoonal periods. Monsoon responses to premonsoonal forcing by the model-derived 'realistic' distribution versus a uniform wide-area distribution were compared. Both simulations exhibit central India drying in June. June precipitation over northwestern India (increase) and southwestern India (decrease) is significantly changed under realistic but not under wide-area forcing. Finally, the same aerosol forcing is found to dry or moisten the July-August period following the warm or cool phase of the simulations' ENSO-like internal variability. The selection of years used for analysis may affect the precipitation response obtained, but the overall effect seems to be an increase in rainfall variance over northwest and southwest India. [ABSTRACT FROM AUTHOR]

The present experiment was carried out to assess influence and inter-relationships of soil properties in grasslands of three national parks in Madhya Pradesh, Central India. Above ground biomass samples of grass and soil samples were collected during different seasons based on specified measurement protocol by the state forest department. Aboveground biomass of grass showed a characteristic growth pattern throughout the year, increased and achieved maximum biomass at the end of rainy season (September), while started decreasing and attained minimum biomass during pre-summer (March) season. Mean aboveground biomass in the study regions varied from 2.03 (Bandhavgadh National Park) to 5.44 Mg/ha (Kanha National Park) with an average biomass of 3.37 Mg/ha. Biomass showed strong correlation with soil moisture (r=0.69), organic carbon (r=0.77) and electric conductivity (r=0.80) at p=0.05. Correlation between six soil properties showed significant correlation (r=0.90; p=0.01). From this analysis it can be conclude that variation in soil moisture, electric conductivity and organic carbon have direct effect on biophysical properties of grass. [ABSTRACT FROM AUTHOR]

Soil temperature and moisture are important initial conditions in weather and climate models. Owing to the sparsity of observations, surface and subsurface soil temperature andmoisture are usually generated using land-surface models (LSMs). Hence, it is important to test the performance of LSMs in predicting these parameters. In the present study, the simulation skill of the three-dimensional Noah LSM is evaluated with respect to soil temperature and moisture at two sites in India, Kharagpur and Ranchi. The model-simulated soil temperature and soil moisture are compared with site observations for a period of 2 years, 2009-2010, at both sites. Soil moisture is reasonably well simulated by the model at all depths and at all time scales in both these sites, showing a dry bias in the monsoon and a wet bias in spring and winter. Soil temperature is usually over-predicted by the model except in the monsoon. It appears that the model has a slower infiltration rate and higher evaporation rate than the actual values. [ABSTRACT FROM AUTHOR]

The current study presents an algorithm to retrieve surface Soil Moisture (SM) from multi-temporal Synthetic Aperture Radar (SAR) data. The developed algorithm is based on the Cumulative Density Function (CDF) transformation of multi-temporal RADARSAT-2 backscatter coefficient (BC) to obtain relative SM values, and then converts relative SM values into absolute SM values using soil information. The algorithm is tested in a semi-arid tropical region in South India using 30 satellite images of RADARSAT-2, SMOS L2 SM products, and 1262 SM field measurements in 50 plots spanning over 4 years. The validation with the field data showed the ability of the developed algorithm to retrieve SM with RMSE ranging from 0.02 to 0.06m3=m3 for the majority of plots. Comparison with the SMOS SM showed a good temporal behaviour with RMSE of approximately 0.05 m3=m3 and a correlation coefficient of approximately 0.9. The developed model is compared and found to be better than the change detection and delta index model. The approach does not require calibration of any parameter to obtain relative SM and hence can easily be extended to any region having time series of SAR data available. [ABSTRACT FROM AUTHOR]

Understanding changes in monsoon variability over a decade requires thorough knowledge of the seasonal and inter-annual variability in surface energy flux and its forcing parameters (land surface and meteorology) in response to climate change. In the present study, the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua climate model gridded global products (0.05° × 0.05° spatial resolution) of land surface temperature (LST;Ts), normalized difference vegetation index (NDVI), and surface albedo (α) were used to generate seasonal (June–September) and inter-annual (2003–2012) variation in surface energy flux and its forcing parameters over different agro-climatic regions (ACRs) of India. Energy fluxes were retrieved using a single-source surface energy balance model (here vegetation and soil is considered as a single unit). Energy flux observations over different ACRs allowed comparison of the seasonal transition of latent heat flux (LE), net radiation (Rn), soil heat flux (G), available energy (Q = Rn – G), and evaporative fraction (EF) as terrestrial links to the atmosphere. The seasonal and inter-annual variation in EF was investigated by plotting against the soil moisture information retrieved from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) global monthly data product (1° × 1° spatial resolution). Decadal and seasonal analysis showed that energy fluxes vary widely in time and space due to variability in surface radiation parameters (Ts,α), vegetation cover, soil moisture, and air temperature (Ta), which influence the seasonal transition of monsoon through LE and EF. Among the ACRs, LE and EF were found lowest in the Western Dry Region (WDR) and highest in the Western Himalayan Region (WHR). The spatiotemporal depiction of MODIS LE and MODIS EF over a span of 10 years can identify the hotspots and monsoon intensity over different ACRs. Climatic parameters that are susceptible to changes resulting from climate change are thoroughly studied in the present analysis. [ABSTRACT FROM AUTHOR]

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Since the dawn of the industrial revolution, mankind has been introducing numerous hazardous compounds into the environment at an exponential rate. These hazardous pollutants consist of a variety of organic compounds and heavy metals (Cu, Pb, Cd, Ni, Fe, Mn, and Zn), which increasingly pose serious risks to human health. Heavy metal contamination is of special concern due to widespread reports emanating both from India and abroad about various diseases and disorders observed both in human and livestocks due to metal toxicity. The pollution of environment particularly from hazardous heavy metals is also considered as a vital societal problem. Thus, understanding the existing heavy metal pollution in India required a special attention for remediation through eco-friendly approach by using plants called phyto-remediation. In this review, we have highlighted the major research outcomes by Indian researchers working in the area of technologies like phytoextraction, phytoaccumulation, rhizofiltration and phytostabilization. Finding the suitable hyperaccumultor plant species is of first and foremost step for successful application of this economic and useful technology. This review attempts to address the major works done in India and will give readers a vivid idea of scope of phytoremediation with its possible benefits on agriculture. This technique hold a great promise for decontamination of heavy metals from soil and water bodies with successful intervention of interdisciplinary researchers, but challenges remain before commercialization and field scale application. Phytoremediation, a new-generation technology for both agricultural and environmental sustainability also widens up many new areas of researches for generations to come. [ABSTRACT FROM AUTHOR]

We investigated the composition of tropical dry forest woody species at adult, sapling, and seedling stages, in terms of plant diversity, distribution, and importance value index (IVI), and identified the dominant and ubiquitous species in the five study sites having variable edaphic properties. Species varied markedly in the composition and IVI at different sites. The semi-evergreen species,Shorea robusta, was dominant at the wettest site at all the three growth stages; at the driest site, highly deciduous speciesLannea coromandelicawas the dominant adult species andNyctanthis arbortrististhe dominant sapling and seedling species. Soil moisture content (SMC) altered the distribution of about 8% of the adult species. ANOVA indicated significant site-wise differences in the Shannon-Wiener index, Whittaker’s evenness, Margalef’s species richness, and β-diversity for the woody species at all the three stages. The Shannon-Wiener index, Whittaker’s evenness, Margalef’s species richness, and β-diversity were greater in seedlings as compared to adult and saplings of tree species. These variations in species composition and distribution are evidently on account of different levels of SMC as well as habitat heterogeneity as indicated by β-diversity which was independent of SMC. [ABSTRACT FROM AUTHOR]

In an incubation experiment with flooded rice soil fertilized with different N amounts and sampled at different rice stages, the methane (CH4) and carbon dioxide (CO2) production in relation to soil labile carbon (C) pools under two temperature (35°C and 45°C) and moisture (aerobic and submerged) regimes were investigated. The field treatments imposed in the wet season included unfertilized control and 40, 80 and 120 kg ha−1 N fertilization. The production of CH4was significantly higher (27%) under submerged compared to aerobic conditions, whereas CO2production was significantly increased under aerobic by 21% compared to submerged conditions. The average labile C pools were significantly increased by 21% at the highest dose of N (120 kg ha−1) compared to control and was found highest at rice panicle initiation stage. But the grain yield had significantly responded only up to 80 kg ha−1 N, although soil labile C as well as gaseous C emission was noticed to be highest at 120 kg ha−1 N. Hence, 80 kg N ha−1is a better option in the wet season at low land tropical flooded rice in eastern India for sustaining grain yield and minimizing potential emission of CO2and CH4. [ABSTRACT FROM PUBLISHER]

Space-time variability of soil moisture (SM) and ground water plays a fundamental role in shaping hydrology of terrestrial ecosystem, best represented as the Critical Zone (CZ), which extends from top of vegetation canopy to the bottom of groundwater table. In several parts of the world, a network of instrumented sites, known as Critical Zone Observatories (CZOs), have been set up to understand the hydrodynamics of soil-water system in particular reference to natural and anthropogenic forcings. Here, we employed the empirical orthogonal function (EOF), random combination, and temporal stability approach to understand the in-situ space-time dynamics of SM and depth to groundwater table (DTGT) over an agriculture-dominated CZO in the Ganga basin. Our results showed that both the components exhibit a constant temporal coefficient of variation, suggesting a consistent seasonal changing pattern. Around 91 % of the observed DTGT spatial variation are explained by first two spatial EOFs while the first five EOFs explain only 67 % of the total SM variability. On an annual basis, the spatial patterns of SM and DTGT are driven by topography and soil texture (% clay) while monsoon rainfall and post-monsoon crop cycle appear to be the leading factors for temporal variability of both components. Furthermore, we have demonstrated that randomly selected four sampling locations and three monitoring wells within the CZO could capture the mean spatial variability of SM (RMSE = 3 % vol/vol) and DTGT (RMSE = 0.7 mgbl) respectively. In addition, temporal stability analysis indicates that four representative sites and a single monitoring well can provide robust catchment mean with an absolute error of ±2 % vol/vol and 0.36 mgbl respectively. Overall, this study provides an insight to the hydrodynamics and controls of SM and groundwater in an agricultural landscape with significant implications for upscaling and efficient water resource management in such regions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Investigation of spatio-temporal variability of column-averaged dry-air mole fraction of CO 2 (XCO 2) over the Indian region using remote sensing satellite measurements is of interest due to the sparseness of ground-based observations. In this study, we utilized OCO-2 satellite retrievals in conjunction with an atmospheric chemistry-transport model (ACTM) simulations for a set of known (bottom-up) and optimized (top-down) flux for the period September 2014 to December 2018. Results showed the highest XCO 2 during the pre-monsoon season, due to prevailing seasonal-high temperatures and drier soil conditions that resulted in increased respiration and suppressed photosynthesis. In contrast, a reduction in XCO 2 during the monsoon season is found as precipitation increased soil moisture and moderated the air temperature, driving vegetation growth by which photosynthesis exceeded respiration by the land biosphere. Model - observation differences of XCO 2 have shown the overestimation (underestimation) during monsoon (pre-monsoon) especially over the central India region, which might be due to underestimation of the modeled peak-to-trough biospheric fluxes. Analyses of the latitudinal distribution of XCO 2 averaged over Indian landmass shows a clear increasing trend and seasonality. An enormous increase in XCO 2 of about ~12 ppm during 2015–2018 is estimated from OCO-2, which is in good agreement with model-simulated XCO 2 (optimized flux case) and consistent with the global growth rate from surface observations. The time series and seasonal cycle of XCO 2 have also been examined using model simulations over different parts of the Indian region and agreed well with those from OCO-2. Over the northern regions, especially over the Indo Gangetic Plain, the peak-to-trough seasonal cycle amplitudes of 2–3 ppm are twice than those in the southern and oceanic regions,~1–1.5 ppm. An annual total CO 2 flux of −397 ± 99 TgC/yr is estimated by the inversion and that is consistent with the XCO 2 measurements. • Study investigated the seasonality and variability of XCO 2 using satellite observations and model simulations over India. • Highest XCO 2 noted during the pre-monsoon season, likely due to increased respiration and suppressed photosynthesis. • Strong Seasonal Cycle Amplitude (SCA) is found over the IGP region, while SCAs are lower over southern and oceanic regions. • An annual total CO 2 flux of -397 ± 99 TgC/yr is estimated by the inversion and it is consistent with the XCO 2 measurements. [ABSTRACT FROM AUTHOR]

• Agroclimatic onset of crop season was determined using SWB, depth and MZ methods. • Identified suitable method based on crop sown status, false onset & undefined years. • Rainfall, wet/dry-spell and dry-spell search period-based combinations identified. • MTC onset dates were validated with SWB output to identify appropriate threshold. • Evaluation of rainfall thresholds are more critical in arid and semi-arid regions. Success of rainfed crop production is highly dependent on timely sowing/planting decisions. Variability in sowing/planting dates between years affect crop planning and thus could decrease farm profitability. Therefore, information on the optimum crop sowing window for the season will facilitate crop planning by farmers and other stakeholders. To determine optimum sowing window over 19 Agro-Ecological Regions (AER) of India, three methods viz. , Soil Water Balance (SWB), Depth and modified Morris & Zandesta methods were evaluated to identify the most suitable method for working out the onset dates of the crop growing season. The onset dates of growing season determined by three methods were found to be similar over northeastern (hot sub-humid and warm per-humid eco-region), west coast (hot humid to per-humid), cold and hot arid eco-regions in India. However, differences in onset dates of the crop growing season were observed over hot semi-arid to sub-humid eco-region. SWB method was found to be the most suitable based on validating with observed crop sowing dates, false start and number of undefined onset years criteria. However, as SWB method is data-intensive, onset was determined using an alternative Modified Threshold Combination (MTC) method comprising 40 combinations of threshold values viz. rainfall amount, wet spell duration, dry spell duration and dry spell search period. The onset dates determined by MTC and SWB methods were validated and subsequently, appropriate threshold values were identified to work out onset dates in 19 AERs of India. This study revealed that the onset is not influenced by threshold combinations in per-humid, humid and sub-humid regions. However, in semi-arid and arid regions, critical evaluation of criteria for determining onset is vital to avoid false starts and undefined onset years. Information on agroclimatic onset dates for each AER is useful for improving practical utility/decision making, especially in the semi-arid and arid regions of India. [ABSTRACT FROM AUTHOR]

An optimal nutrient prescription along with favorable water management through mulching is key to high horticultural productivity, efficient water use, and minimizing soil nutrient loss. A field experiment was conducted in the Balindi Research Complex, Bidhan Chandra Krishi Viswavidyalaya in the Indo-Gangetic Plains of India, to evaluate the impact of mulching and balanced fertilization on actual evapotranspiration (ETa), crop coefficients (Kc), yield and yield attributes of cabbage (Brassica oleracea var. capitata L. cv. Green Express) during the winter seasons of 2018–2019 and 2019–2020 in the cabbage-fallow upland system under surface irrigated conditions. The experiment was laid out in a factorial strip plot design where no mulch (M1), live mulch [M2, Egyptian clover (Trifolium alexandrinum L.)], and paddy straw mulch (M3) were in strips with cabbage. Each treatment contained nutrient levels of 75% (N1), 100% (N2), and 125% (N3) of the recommended dose of an NPK fertilizer (RDF) with 200 N:100 P 2 O 5 :100 K 2 O. Higher soil water conservation under M3 incited 60% and 46% lower profile water change than M1 and M2 treatments, respectively. Paddy straw mulch produced 10.1% and 22.3% more yield and achieved 29.5% and 15.1% higher water productivity (WP) as compared to M1 and M2, respectively. Treatment N3 produced the highest yield and the least partial factor productivity of fertilizer (PFP f) compared to N2 and N1 treatments. Maximum ETa loss was from the M1N3 treatment (226.30 mm) and the highest yield (25,695 kg ha−1), yield attributes, and WP (120.1 kg ha−1 mm−1) were obtained from the M3N3 combination. The average estimated Kc values were 0.5 for initial, 1.0 for crop development, and 1.2 for mid-season, and 0.6 for maturity stages. The results suggest that the application of straw mulch with 125% RDF of chemical fertilizer under surface irrigated conditions improved cabbage yield, water productivity and soil fertility, however, living mulch achieved a higher economic return to the Indo-Gangetic alluvial clay loam Inceptisol of India. • Soil moisture storage under different mulched materials (straw and living) were different. • No mulch obtained higher ETa of cabbage irrespective of nutrient doses. • Higher doses of NPK and paddy straw produced higher yield and water use efficiency. • Nutrient management and mulch in finer soils affected soil moisture-nutrient retention and release. • Crop coefficients obtained from field water balance are comparable to FAO-56 due to soil and climatic variability. [ABSTRACT FROM AUTHOR]

In India, chickpea (Cicer arietinum L.) is mostly cultivated in post-rice residual soil water on marginal lands. Low crop productivity due to terminal water and heat stress during reproductive stages, is a major concern, especially in the rice-fallows of lower Gangetic plains of India. In this backdrop, we examined the effect of different tillage (CT and ZT) and irrigation management (I 0 – no irrigation; I F – irrigation at the initiation of the flowering stage; I PF – irrigation at the initiation of pod formation stage, I F+PF – irrigation at both initiation of flowering and pod formation stage) on the performance of chickpea concerning dynamics of soil and crop water stress affecting various physiological characteristics, yield and water productivity (WP) on an Aeric Haplaquept, clay loam soil in rice-fallows of lower Gangetic plain of India during 2017–18 and 2018–19. ZT with standing rice stubbles modified the hydrothermal regime of the soil by lowering the evaporative loss and vertical movement of soil water within the compacted puddled rice soil and significantly altered the stress intensity faced by chickpea at the critical growth stages. On average, 35.0%, 23.5%, and 15.5% higher soil water storage under ZT as compared to CT during vegetative, flowering, and pod formation stages, significantly alters the plant water status as affirmed by higher relative leaf water content, leaf area index, leaf chlorophyll content, stomatal conductance, and transpiration rate and lowering of proline content and canopy temperature. Application of irrigation at the critical growth stages had a positive priming effect on plant water availability under both the tillage practices. Higher yield (1984 kg ha−1), and WP (13.6 kg ha−1mm−1) under ZT-I F treatment combination proved it to be the best, from the perspective of mitigating terminal soil water stress as well as enhancing the productivity of chickpea in the rice-fallows of lower Gangetic plains of India. • Adoption of ZT improves soil water availability and minimizes the stress intensity. • Supplemental irrigation application can bridge the yield gap of chickpea. • CWSI as a soil moisture stress indicator, has been assessed. • Relation between soil moisture storage and physiological attributes has been established. • An integrated tillage and irrigation management strategy for chickpea has been developed. [ABSTRACT FROM AUTHOR]

Spring sweet corn as a short duration cash crop is gaining popularity in northern India owing to increasing demand in urban and peri-urban regions. Under hot dry climate and minimal rainfall, irrigation is the major yield contributing factor for attaining superior quality cobs and higher economic returns. The study aimed at examining the effect of irrigation scheduling (I) (IW/CPE 1.0, 1.2, 1.4), sowing methods (S) (flat and furrow) and moisture conservation practices (M) (no-residue, rice straw mulch 6.0 t ha−1 and rice straw biochar 3.0 t ha−1) on spring sown sweet corn yield, quality, profitability and water use efficiency in the Tarai region (sandy loam soil texture) of Uttarakhand, India. The experiment was conducted in split factorial design (Main I x S, Sub M) with 18 treatment combinations and three replications. Results indicated that the combination IW/CPE 1.4 +furrow+mulch being at par with IW/CPE 1.4 +furrow+biochar were superior in terms of dehusked cob yield which was ~42% higher over IW/CPE 1.0 +flat+control. Application of biochar 6 t ha−1 and straw mulch 3 t ha−1 increased dehusked cob yield of sweet corn by ~6–9% over control (no-residue) during both years. Among irrigation schedules, IW/CPE 1.0 obtained highest irrigation water use efficiency (IWUE) followed by IW/CPE 1.2. Mulch and biochar being on par recorded 7–10% higher IWUE over no-residue control. Likewise, furrow sowing increased IWUE by 39–44% over flat method with ~25% higher water savings. Average soil moisture content under mulch and biochar was 25% and 12% higher respectively over no-residue. Maximum net returns was obtained under the combination IW/CPE 1.4 +furrow+mulch (1672 USD ha−1) which was 69% higher over IW/CPE 1.0 +flat+no-residue. Sweet corn quality parameters viz., total soluble solids and non-reducing sugar was significantly higher under IW/CPE 1.0 and 1.2 in comparison to 1.4, as well as under furrow sowing over flat sowing. Therefore, although maximum yield and profitability of sweet corn was obtained under irrigation schedule IW/CPE 1.4, the treatment combination of IW/CPE 1.2 with furrow sowing and mulch/biochar application may be adopted for attaining superior quality parameters and improved water use efficiency of sweet corn. • Irrigation scheduled at IW/CPE 1.4 & 1.2 increased sweet corn yield over IW/CPE 1.0. • IW/CPE 1.2 improved irrigation water use efficiency (IWUE) by 7% over IW/CPE 1.4. • Furrow sowing had 4–8% and 39–44% higher cob yield and IWUE resp. than flat sowing. • Mulch 6 t ha−1 & biochar 3 t ha−1 observed 7–10% higher IWUE of sweet corn over control. • Virtual water of sweet corn was lowest with IW/CPE 1.0, furrow and mulch. [ABSTRACT FROM AUTHOR]