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A field experiment was conducted at Crop Research Centre, G.B. Pant University of Agriculture and Technology, Pantnagar, during kharif 2019 to study the effect of integrated use of organic manures and chemical fertilizers under STCR approach on physico-chemical, biological properties of soil and yield of maize crop in a Mollisol. The experiment comprised of 9 treatments replicated thrice. The treatment details were Control (no fertilizers), RDF, STCR (inorganic mode), STCR INM mode, 75% STCR dose of N (inorganic mode) + Green manure, 50% STCR dose of N (inorganic mode) + Green Manure, 75% RDN + Green Manure, 50% RDN + Green Manure and FYM + Green Manure + Intercropping with urd. The lowest yield and soil properties were observed under control. The highest water holding capacity (63.20%), available N (183.98 kg ha-1), available P (28.94 kg ha-1), microbial biomass carbon (335.35 µg/g soil) and urease enzyme activity (30.06 µg urea/g soil/h) was observed under T4 (STCR INM mode). The highest organic carbon (0.99%), available K (200.85 kg ha-1) and dehydrogenase activity (223.60 µgTPF/gsoil/day) was observed under T5 (75% STCR dose of N (inorganic mode) + Green manure). The highest maize yield was observed under T4 (STCR INM mode). Therefore, the present investigation clearly reveals the significance of balanced and efficient utilization of resources under STCR approach on soil and crop productivity of maize crop.

Water is a very important part of life circle, due to which life flourishes in Earth. In today’s scenario water scarcity is becoming the major problem so there is an urgent need to conserve it. In order to manage the scare water resources efficiently estimation of runoff in a watershed is very important factor. In India the availability of accurate runoff information is rare where most of the watersheds are ungauged, which poses a serious challenge for hydrologists. Number of mathematical models is available to quantify runoff. Soil Conservation Services-Curve Number method (SCS-CN) is used for computing the runoff depth based on the rainfall depth.In the present study SCS-CN method has been applied to estimate the runoff depth in Maniari watershed in Lormi block of Mungeli District Chhattisgarh state. This method is based on one parameter i.e. curve number which is basically a coefficient that is used to estimate runoff due to rainfall. layers has been prepared namely base map, soil map, land use map and other maps of the study area using GIS and remote sensing data. Based on the rainfall data of the study area, daily runoff depth has been estimated. Integration of GIS with the SCS-CN method is used for estimating runoff from the un-gauged watersheds for better watershed management and conservation purposes.

In this study, a comparative analysis of three satellite precipitation products including the Tropical Rainfall Measuring Mission (TRMM-3B43 V7), the Precipitation Estimation from Remotely Sensed I...

Drought hazard mapping and its trend analysis has become indispensable due to the aggravated impact of drought in the era of climate change. Sparse observational networks with minimal maintenance limit the spatio-temporal coverage of precipitation data, which has been a major constraint in the effective drought monitoring. In this study, high-resolution satellite-derived Climate Hazards Group Infrared Precipitation with Station (CHIRPS) data has been used for computation of Standardized Precipitation Index (SPI). The study was carried out in Bundelkhand region of Uttar Pradesh, India, known for its substantial drought occurrences with poor drought management plans and lack of effective preparedness. Very limited studies have been carried out in assessing the spatio-temporal drought in this region. This study aims to identify district-wide drought and its trend characterization from 1981 to 2018. The run theory was applied for quantitative drought assessment; whereas, the Mann-Kendall (MK) test was performed for trend analysis at seasonal and annual time steps. Results indicated an average of nine severe drought events in all the districts in the last 38 years, and the most intense drought was recorded for the Jalaun district (1983–1985). A significant decreasing trend is observed for the SPI1 (at 95% confidence level) during the post-monsoon season, with the magnitude varying from −0.16 to −0.33 mm/month. This indicates the increasing severity of meteorological drought in the area. Moreover, a non-significant falling trend for short-term drought (SPI1 and SPI3) annually and short- and medium-term drought (SPI1, SPI3, and SPI6) in winter months have been also observed for all the districts. The output of the current study would be utilized in better understanding of the drought condition through elaborate trend analysis of the SPI pattern and thus helps the policy makers to devise a drought management plan to handle the water crisis, food security, and in turn the betterment of the inhabitants.

The soil moisture level effectively estimates the extremity of irrigation demand, and thus acts as a significant indicator of irrigation water management. In recent time due to increase in population, demand for freshwater in all competing sectors is being a constraint for irrigation that raises the need to optimise utilisation of irrigation water with its high efficiency. Therefore, an accurate and precise assessment of soil moisture content (SMC) is required for optimal allocation and management of water in agriculture. Owing to this, the current study aims to simulate SMC from water balance–based macro-scale Variable Infiltration Capacity (VIC) hydrological model for various applications in irrigation water management. The current study was carried out in the Bundelkhand region of Uttar Pradesh, India, for a period of 5 years (2010–14). The simulated SMC was validated with ESA Climate Change Initiative soil moisture (CCI-SM) indicated high R2 value ranging from 0.73 to 0.90 and low RMSE value ranging from 0.03 to 0.05 m3m−3. The dataset of simulated and CCI-SM content values was close to the 1:1 scale line for approximately all the periods. Additionally, the Soil Moisture Deficit Index (SMDI), a dryness index, was computed for estimating irrigation demand from VIC-derived SMC for Kharif season (July–October) from 2010 to 2014; this shows more irrigation water demand in 2014 and sowing period of 2010 and 2012.

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 hydro-climatological 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.

Analysis of spatial and temporal changes of long-term precipitation and extreme precipitation distribution at a local scale is very important for the prevention and mitigation of water-related disasters. In the present study, we have analyzed the long-term trend of 116 years (1901–2016) of precipitation and distribution of extreme precipitation index over the Kosi River Basin (KRB), which is one of the frequent flooding rivers of India, using the 0.25° × 0.25° resolution gridded precipitation datasets obtained from the Indian Meteorological Department (IMD), India. The non-parametric Mann–Kendall trend test together with Sen’s slope estimator was employed to determine the trend and the magnitude of the trend of the precipitation time series. The annual and monsoon seasons revealed decreasing trends with Sen’s slope values of −1.88 and −0.408, respectively. For the extreme indices viz. R10 and R20 days, a decreasing trend from the northeastern to the southwest part of the basin can be observed, whereas, in the case of highest one-day precipitation (RX1 day), no clear trend was found. The information provided through this study can be useful for policymakers and may play an important role in flood management, runoff, and understanding related to the hydrological process of the basin. This will contribute to a better understanding of the potential risk of changing rainfall patterns, especially the extreme rainfall events due to climatic variations.

Drought is an intricate phenomenon assessed by analyzing several hydro-meteorological factors such as rainfall, soil moisture, temperature, evapotranspiration, vegetation cover, etc. For effective drought hazard management and preparedness, the monitoring of drought requires the evaluation of influencing factors via the Drought Hazard Inventory (DHI). The main objective of this study is to compare spatial occurrences of drought hazard with the help of microwave and Optical/Infrared datasets obtained from multiple satellites. The long-term climatology of the Tropical Rainfall Measuring Mission (TRMM) Rainfall, Climate Change Initiative soil moisture (CCI-SM) and Moderate Resolution Imaging Spectroradiometer (MODIS) derived Land Surface Temperature (LST), Evapotranspiration (ET) and Normalized Difference Vegetation Index (NDVI) were used in this study for drought hazard assessment. This study was carried out in the Bundelkhand region of Uttar Pradesh, considered as one of the most frequent and dominant drought-prone areas of India. The current study includes the Analytical Hierarchy Process (AHP) technique based on Multi-Criteria Decision Making Analysis (MCDM) for weighting assignment and decision making, while the geospatial platform was used for data layer standardization, integration, and drought assessment. The results indicate that a large percentage of area (38.05% and 27.54%, respectively) lying in the central part of Bundelkhand region is under high to extreme drought conditions, where precautionary measures are needed. To demonstrate the robustness of our results, we compare them with the long-term in-situ ground water depletion as a proxy. Finally, based on the findings of this study, we recommend the methodology for drought assessment at a larger scale, as well as in the remote areas where ground based measurements are limited.

Remote sensing and GIS techniques are being extensively used since quite some time in watershed related studies as very effective tools in determination of the basin geometry i.e, morphometric analysis or quantitative description of watershed morphologic characteristics. In the present study, an attempt has been made to use the capabilities of GIS (ArcGIS 10.4) to quantify the morphology of the Maniari watershed. The watershed was studied for its size and shape, drainage and relief characteristics to develop a thorough understanding of the watershed for future planning to avert the land degradation. Twenty three morphometric parameters of the Maniari watersheds situated in Lormi block of Mungeli District (Chhattisgarh), have been quantified. They comprise: Stream Order, Stream Length (Lu), Mean stream length (Lsm), Stream Length ratio (RL), Bifurcation ratio (Rb), Mean bifurcation ratio (Rbm), Drainage Density (Dd), Length of overland flow (Lg), Basin length (Lb), Basin perimeter (P), Basin/drainage area (A), Compactness constant (Cc), Stream frequency (Fs), Circulatory ratio (Rc), Elongation ratio (Re), Form Factor (Rf), Watershed shape factor (Ws), Drainage Texture (Rt), Total relief (H), Relief ratio (Rh), Relative relief (Rp) and Ruggedness number (Rn). On the basis of the morphometric studies it was concluded that the hydrologic response of the Maniari watershed is dependent on surface characteristics significantly due to its being a “Fan Shaped” one. The watershed is in active stage of degradation. Its quantification is being done based on the field measurements and recording of soil erosion. The result suggests that the ratio between cumulative stream length and stream order is constant throughout the successive orders of the basin.

Soil moisture estimation has paramount importance for hydrological land surface processes and their management. Taking into consideration the importance of its application in monitoring of extreme hydrologic events such as drought and flood, runoff modeling, numerical weather prediction, landslide monitoring, vegetation monitoring, agricultural monitoring, epidemiological prediction, GHG budget, climate studies, groundwater modeling, and so forth, the benefits of the various available data sets for soil moisture are expected to be vast. In this chapter, we explore the various available data sets for soil moisture monitoring and measurements. This chapter is a comprehensive study of all the possible established and emerging facilities that retrieve soil moisture data from in situ (field method) to remote sensing methods.

Drought is a recurrent phenomenon in the semiarid regions of India that significantly affects the regional social, economic, and environmental conditions. Drought monitoring and assessment are challenging especially for regions that have sparse or very limited rain gauge observation networks. In this study, a comparative analysis was performed between satellite precipitation products including Tropical Rainfall Measuring Mission (TRMM-3B42), Climate Hazards Group InfraRed Precipitation (CHIRP) and ground-measured Indian Meteorological Department (IMD) precipitation data over the Bundelkhand region of Uttar Pradesh, India to assess the meteorological drought in this region. The district wise study was done to determine the regional differences among these satellite precipitation products and to statistically verify their performance in estimating the degree and spatial pattern over the study area. The Standardized Precipitation Index (SPI) was computed using the open-source DRINC software. The IMD derived SPI was found more correlated with TRMM compared to CHIRP for SPI-1, 3 and 12 with r values 0.74, 0.81 and 0.65 respectively. However, SPI-6 shows low positive and negative and correlation for both TRMM and CHIRP data. The current case study highlights the outperformance of TRMM data that enables real-time drought assessment owing to better accuracy and higher spatiotemporal resolution.