Improper practices of land use and land cover (LULC) including deforestation, expansion of agriculture and infrastructure development are deteriorating watershed conditions. Here, we have utilized remote sensing and GIS tools to study LULC dynamics using Cellular Automata (CA)-Markov model and predicted the future LULC scenario, in terms of magnitude and direction, based on past trend in a hydrological unit, Choudwar watershed, India. By analyzing the LULC pattern during 1972, 1990, 1999 and 2005 using satellite-derived maps, we observed that the biophysical and socioeconomic drivers including residential/industrial development, road-rail and settlement proximity have influenced the spatial pattern of the watershed LULC, leading to an accretive linear growth of agricultural and settlement areas. The annual rate of increase from 1972 to 2004 in agriculture land, settlement was observed to be 181.96, 9.89 ha/year, respectively, while decrease in forest, wetland and marshy land were 91.22, 27.56 and 39.52 ha/year, respectively. Transition probability and transition area matrix derived using inputs of (i) residential/industrial development and (ii) proximity to transportation network as the major causes. The predicted LULC scenario for the year 2014, with reasonably good accuracy would provide useful inputs to the LULC planners for effective management of the watershed. The study is a maiden attempt that revealed agricultural expansion is the main driving force for loss of forest, wetland and marshy land in the Choudwar watershed and has the potential to continue in future. The forest in lower slopes has been converted to agricultural land and may soon take a call on forests occurring on higher slopes. Our study utilizes three time period changes to better account for the trend and the modelling exercise; thereby advocates for better agricultural practices with additional energy subsidy to arrest further forest loss and LULC alternations.
Artificial groundwater recharge plays a vital role in sustainable management of groundwater resources. The present study was carried out to identify the artificial groundwater recharge zones in Bist Doab basin of Indian Punjab using remote sensing and geographical information system (GIS) for augmenting groundwater resources. The study area has been facing severe water scarcity due to intensive agriculture for the past few years. The thematic layers considered in the present study are: geomorphology (2004), geology (2004), land use/land cover (2008), drainage density, slope, soil texture (2000), aquifer transmissivity, and specific yield. Different themes and related features were assigned proper weights based on their relative contribution to groundwater recharge. Normalized weights were computed using the Saaty's analytic hierarchy process. Thematic layers were integrated in ArcGIS for delineation of artificial groundwater recharge zones. The recharge map thus obtained was divided into four zones (poor, moderate, good, and very good) based on their influence to groundwater recharge. Results indicate that 15, 18, 37, and 30 % of the study area falls under "poor," "moderate," "good," and "very good" groundwater recharge zones, respectively. The highest recharge potential area is located towards western and parts of middle region because of high infiltration rates caused due to the distribution of flood plains, alluvial plain, and agricultural land. The least effective recharge potential is in the eastern and middle parts of the study area due to low infiltration rate. The results of the study can be used to formulate an efficient groundwater management plan for sustainable utilization of limited groundwater resources.
Optimal resources allocation strategies for a canal command in the semiarid region of Indian Punjab are developed in a stochastic regime, considering the competition of the crops in a season, both for irrigation water and area of cultivation. The proposed strategies are divided into two modules using a multilevel approach. The first module determines the optimal seasonal allocation of water as well as optimal cropping pattern. This module is subdivided into two stages. The first stage is a single crop intraseasonal model that employs a stochastic dynamic programming algorithm. The stochastic variables are weekly canal releases and evapotranspiration of the crop that are fitted to different probability distribution functions to determine the expected values at various risk levels. The second stage is a deterministic dynamic programming model that takes into account the multicrop situation. An exponential seasonal crop-water production function is used in this stage. The second module is a single crop stochastic dynamic programming intraseasonal model that takes the output of the first module and gives the optimal weekly irrigation allocations for each crop by considering the stress sensitivity factors of crops.
The Balasore coastal groundwater basin in Orissa, India is under a serious threat of overdraft and seawater intrusion. The overexploitation resulted in abandoning many shallow tubewells in the basin. The main intent of this study is the development of a 2-D groundwater flow and transport model of the basin using the Visual MODFLOW package for analyzing the aquifer response to various pumping strategies. The simulation model was calibrated and validated satisfactorily. Using the validated model, the groundwater response to five pumping scenarios under existing cropping conditions was simulated. The results of the sensitivity analysis indicated that the Balasore aquifer system is more susceptible to the river seepage, recharge from rainfall and interflow than the horizontal and vertical hydraulic conductivities and specific storage. Finally, based on the modeling results, salient management strategies are suggested for the long-term sustainability of vital groundwater resources of the Balasore groundwater basin. The most promising management strategy for the Balasore basin could be: a reduction in the pumpage from the second aquifer by 50% in the downstream region and an increase in the pumpage to 150% from the first and second aquifer at potential locations.
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