Bhaskar R. Nikam

Assessment of the effect of slope on runoff potential of a watershed using NRCS-CN method

The rainfall-runoff is a very complex hydrological phenomenon, as this process is highly non-linear, time-varying and spatially distributed. The average slope within the watershed together with the overall length and retardance of overland flow are considered to be the main factors which govern the runoff process. The natural resources conservation service curve number (NRCS-CN), formerly known as soil conservation services curve number, is the most widely used method to estimate direct runoff from rainfall, due to its simplicity and the use of the single CN parameter. However, the NRCS-CN method has been developed for limited watershed area and slope. In the present study, the modified NRCS-CN method for slope and CN conversion have been investigated to determine runoff potential of a watershed in geo-spatial environment. Solani watershed, which is a sub-watershed of Ganga basin located partly in Uttarakhand and Uttar Pradesh states of India; has been considered for analysis. The daily rainfall-runoff study has been carried out for year 2006. It was found that slope factor effects runoff estimation significantly.

Using satellite-based soil moisture to detect and monitor spatiotemporal traces of agricultural drought over Bundelkhand region of India

Detection and monitoring of seasonal agricultural drought at sub-regional scale is a complex theme due to inefficient spatiotemporal indicators. This study presents a new time-based function of spaceborne soil moisture as an efficient indicator. Bundelkhand of Central India, a frequently agricultural drought affected region, was used as the study area. Rabi agricultural season (October–May) being the dominant agricultural return period, was chosen as the study period. Coarse resolution soil moisture (SMc) obtained from European space agency under climate change initiative program was spatially downscaled (SMd) to meet spatial scale at sub-regional level with overall root-mean-square error under 0.065 cm3/cm3. Indirect validation of SMd was done using temporal impact of rainfall/dry spell on SMd and spatiotemporal impact of SMd on vegetation condition. SMd was found to agree with phenomenon as expected in natural processes and hence it was assumed to be validated. The time-based function derived from spatiotemporal SMd (FSMs) was found to be better related with fluctuations in seasonal crop yield (Ys) at district level as compared to a similar function (FVCIs) derived using vegetation condition index (VCI) from Moderate Resolution Imaging Spectroradiometer. FSMs outperformed FVCIs having better correlation coefficient (R ≥0.8) and Nash–Sutcliffe efficiency coefficient (NSE) than FVCIs for most of the districts. Unlike FVCIs, it also efficiently detected the lowest and highest Ys for majority of the districts representing better association with agricultural drought. Subsequently, frequent soil moisture deficit areas were mapped by using FSMs to visualize the spatiotemporal severity of agricultural drought in the region during Rabi season.

Hydrological Modelling in North Western Himalaya

The Himalayas are one of the largest reservoirs of freshwater in the form of glaciers and snow outside the Polar region (Mani 1981). There are around 32,392 glaciers, covering an area of about 71,182 km2 in the Indian part of the Himalaya (SAC 2011). Among all, North Western Himalaya (NWH) has the largest area under seasonal and perennial snow cover. This snow/glacier melt contributes significantly to perennial rivers like the Ganga and the Indus during lean time. The Indus Basin is comprised of Chennab, Jhelum, Rawi, Satluj and Beas River subbasins, whereas Upper Ganga Basin is comprised of Bhagirathi, Alaknanda, Mandakini, Dhauliganga and Pindar subbasins. Moreover, these basins have huge hydropower potential, which is a matter of concern during lean period (Kasturirangan et al. 2013).

Hydrometeorological Hazards Mapping, Monitoring and Modelling

Northwest Himalaya (NWH) has unique topographical and climate settings which makes this area prone to various types of hydrometeorological hazards such as flash floods, hail storms, glacier lake outburst floods, avalanches and mudflows. These hazards have high probability of turning into natural disasters if proper planning of natural resources, infrastructure and man-made structures is not done. Floods of June 2013 in Uttarakhand (Dobhal et al. 2013; Thakur et al. 2014) and 2014 floods of Srinagar (Bhatt et al. 2016) are prime examples of such hazards turning into the major disasters. Northwest Himalayan states in the last few years have experienced large number of hydrometeorological disasters such as high-intensity precipitation, cloud burst and subsequent flash flooding in downstream areas, snow avalanches, glacier lake outburst floods (GLOF), hail storms, drought and rainfall-induced mudflows (Kumar et al. 2015; Gupta et al. 2013; Kumar et al. 2012; Rana et al. 2012). This chapter gives an overview of various hydrometeorological hazards which are reoccurring in NWH and provides insights in few such hazards by providing some actual case studies related to such hazards.

Cryosphere Studies in Northwest Himalaya

Himalaya is also known as the “third pole” of the Earth due to the presence of the largest area and volume of seasonal snow and glacier ice outside the polar regions. Most visible effects of climate change are found in this region (Immerzeel et al. 2010; IPCC-5 2014 WGII AR5 Section 28.3). The Indian states of Uttarakhand (UK), Himachal Pradesh (HP) and Jammu and Kashmir (JK National Remote Sensing Centre 2013). This chapter highlights remote sensing (RS) and geographical information system (GIS)-based studies of major components of NWH cryosphere such as seasonal SC, GI, GL and permafrost. This also includes subsections for mapping, monitoring and quantification of SC, GI in NWH along with retrieval and modelling of snowpack properties, snowmelt and glacier mass balance.