Ravine Erosion and Livelihoods in Semi-arid India: Implications for Socioeconomic Development

Abstract

The ravines found along the Chambal River are among the most severe types of gully erosion found in semi-arid India. This paper estimates the extent and areal expansion of ravines over 40 years in the Lower Chambal Valley and provides a classification scheme to understand ravine characteristics in the region. To examine the implications of ravines on socioeconomic development and livelihoods of the people in the area, a mixed method approach has been followed. A combination of spatial and statistical tests has been run to examine the overall status of land degradation and its impact in the area concerned. Village-level socioeconomic data have been integrated with physical and environmental parameters in a GIS environment, which has been supplemented with findings from a qualitative survey in a few villages of the study region. The results show that there is a positive and significant relationship between indices of natural resources availability and socioeconomic development. A majority of villages within ravines were found to be very poor in development. In this fragile environment, people’s livelihoods are being adversely affected because of land degradation.

Keywords

Ravine erosion socioeconomic development Chambal badlands Semi-arid India land degradation ravine morphology

Introduction

Land degradation is considered to be one of the key global environmental challenges. Its magnitude and severity are significantly high in many developing countries including India.¹ Because of the intrinsic relation between topsoil loss and food production, it is considered to be an important challenge for achieving global food security (Scherr, 1999). Apart from that, land degradation affects the livelihoods of people in a number of ways and these impacts are considered to be far more serious in resource-poor and less developed regions (Scherr and Yadav, 2001). In a densely populated region like South Asia, the impact of land degradation on rural livelihoods and agriculture is an important dimension of the emerging patterns of environmental degradation. A large section of India’s population continues to live in rural areas and many of them are poor. The second important point is that there are large regional variations in India’s economy and in the context of recent growth of the Indian economy; some of the ecologically fragile regions are lagging behind the developed regions (Palmer-Jones and Sen, 2003).

Thus, environmental degradation in general and land degradation in particular have several implications for poverty reduction, agricultural productivity and rural livelihoods in India. Land degradation has been identified as one of the major environmental problems facing the country (GoI, 2009; Reddy, 2003; Sehgal and Abrol, 1994; Yedla and Peddi, 2007). It is not just that the extent of land degradation is a cause of concern, but also its expansion over time, which has been noted as a major environmental challenge, particularly in arid and semi-arid India (SAC, Indian Space Research Organisation (ISRO) 2007). Among the diverse types of land degradation in India, ravine is one of the severe forms of land degradation, where the loss of topsoil has major economic implications. Among the ravine-affected areas in India, the Chambal ravine is considered to be one of the major ravine-affected zones of India (Pani and Mohapatra, 2001; Sharma, 1968).

This paper attempts to study the extent and pattern of land degradation in one of most ravine-affected zones of India − the district of Morena in the Chambal Valley. Using remote sensing and other spatial datasets, along with field observation, the paper presents an estimate of the ravine-affected area in the study region. By examining the inter-temporal changes in used land cover, an estimate of the expansion of area affected by ravines has also been presented. Further, the interrelationship between socioeconomic development and land degradation has been examined using village-level data from population census. Finally, the livelihoods implications of land degradation have been studied on the basis of qualitative data collected from six villages in the affected region.

Aims and objectives

This paper aims at examining the implications of land degradation on socioeconomic development in a part of semi-arid India. The specific objectives of this paper are as follows:

to measure the extent of land degradation and to estimate the changes in its areal extent over a period of time in the study region;

to evaluate the geomorphic features of the study area and bring out the biophysical processes associated with the process of land degradation;

to examine the implications of land degradation for the socioeconomic development of the region through estimates of village-level composite indices of development;

to understand the livelihoods implications of land degradation through primary field research.

This paper is mainly focused on an analysis of physical environment in the study region and its change over 40 years and its implications. The geomorphology of the region has been described to understand the geomorphic units and its process of land degradation, focusing on ravine types and formation. The developmental impacts of such geomorphological processes need to be investigated to unravel the linkages between environment and the society and hence the paper also attempts to integrate geomorphic and socioeconomic analysis in a unified, multidisciplinary framework.

Study area

The standout ravine-affected region of the Lower Chambal Valley, the Morena district of Madhya Pradesh, has been considered as the present study area (Figure 1). The study area is located between the geographical coordinates of 26⁰17’15”N−26⁰52’22”N latitude, and 76028’30”E−78⁰32’55’’E longitude and covers an area of approximately 4989 km². The Chambal River, streaming in a SW−NE direction, controls the drainage of the area. River Kunwari, the prominent tributary of the River Chambal, flows south to north and north-east and finally meets the Chambal River on its right bank. Highly dissected and inaccessible areas with steep ridges, low-sloping hills, deep trenches and broad meanders are some of the significant characteristic features of the study area. Sandy loam and clayey loam are the two extensively major soil types in the area with low phosphorous and salt content (GoMP, 1996). Climatically the region experiences semi-arid and sub-humid types which include moderate rainfall with high temperature, dry summers and cold winters. The maximum and minimum temperatures vary between 48°C on summer and 3°C in winter, respectively, with an average annual rainfall of about 685 mm. It is imperative to note that the district headquarters of Morena is on the National Highway no. 3 that connects Bhopal, the state capital, with Delhi, the country’s capital. Yet, due to the physiographic set up it is still considered to be a rather ‘backward’ area.² Hence this area is appropriate for studying the implications of land degradation on socioeconomic development. Limited field-based research has been carried out in this area to understand the characteristics of ravines and their expansion due to the inaccessibility of the region and landscape conditions. However, it is felt that the region requires periodic observation and monitoring.

Figure 1.

Location map of Morena district, Madhya Pradesh.

Most parts of the ravenous area are without a decent vegetative cover other than thorny bushes and trees. The district has a forest cover of 14.63% as against the state average of 25.21%, according to the State of Forest Report 2011 (Forest Survey of India, 2011). Moderately dense forest accounts for 13.42% and open forest accounts for 86.58% of the total forest area, while there is no area under dense forest cover in the district (Forest Survey of India, 2011). As already expressed, land degradation by ravines and gullies is widespread in India but the most critical zone is the Chambal Valley. The area is densely populated and a substantial proportion of this population lives in the rural areas and is dependent on agriculture. The region has a long history of drought, periodic excessive downpours and food deficiencies (GoMP, 1996: 118−119). The high rate of soil loss because of topsoil erosion, encroachment of gullies and ravine formation is a serious threat to the overall development of the region.

Material and methods

Materials

Three different types of data have been used in the present study, such as (a) satellite data of different years/Survey of India topographic sheets, (b) District Census village boundary map/socioeconomic (Census data of 2001³) data and (c) qualitative information collected through field survey. The data used in the study along with their sources are listed below:

Base map prepared from topographical map of Survey of India.

Village boundary map prepared from District Census Village Boundary Map.

Geomorphology map derived from LANDSAT Image 8 (Sensor OLI), 2014.

Land use/land cover change and ravine expansion map from LANDSAT 1 (Sensor MSS) image, and LANDSAT 8 (Sensor OLI) images for the year 1975 and 2014 respectively.

Data on various socioeconomic variables have been taken from the Indian Population Census.

2001 (Primary Census Abstract and Village Directory).

Field data involving observations of agricultural practices and their impacts, extent of ravines, and coping mechanisms adopted, etc.

Research methods

The development of the villages in the study area has been analysed in an Arc-GIS environment, which is based on integrating both spatial and non-spatial data using various criteria. Initially a geo-database has been prepared consisting of various thematic maps such as land use, land cover, geomorphology, ravines, district boundary, village boundary, road network and railway line, etc. These thematic maps such as geomorphology, land use and land cover maps were prepared based on the onscreen visual interpretation techniques using different-year satellite images from 1975 and 2014. The different-years satellite images, Survey of India Topographic Sheets and existing published maps form the bases for spatial data creation, whereas the non-spatial data have been created from the district village census directory. The village map has been digitised from the district census map and all the development indicators (physical and social) were analysed and classified according to the facilities that are available in each village. All the spatial data of the study area are finally converted to a common reference system and the vector data were stored as shape files. The non-spatial data in the form of socioeconomic data, demographic data and the data pertaining to infrastructural facilities at village level were compiled and linked to the spatial data as their attributes. Village location and ID forms the common attribute in all tables of the integrated geo-database.

As, mentioned the study is based on Geo-Socio informatics, the development of the area/villages were considered on the basis of two sets of variables, viz. physical parameters, reflecting the availability of natural resources, and socioeconomic parameters. The physical parameters encompass geomorphological and ravine-related features of the area. Similarly, under socioeconomic parameters the variables include levels of literacy, availability of schools, banks, post and telegraph facilities, transport and communication, electricity, health/medical facility, average household size, area under cultivable waste land, per capita agricultural land, distance to road, total area under irrigation etc. Both these indices are constrained by the availability of reliable data at the village level. Weights have been given to each facility under the respective parameters in a 1 to 4 scale where 1 stands for the least and 4 for the highest. On the basis of the above logic all the individual index maps and their statistics were generated. The initial development maps were integrated parameter-wise and classified again on the same 1 to 4 points of scale combining the aggregate index of the facilities considered under those parameters. Hence, we have now two different village development maps based on the two indices mentioned above. Finally integration of the CVDI (Composite Village Development Index) based on parameters was attempted and a composite village development index map of the Morena district was prepared that shows four classes of the development as least developed, poorly developed, marginally developed and developed village. Various statistical operations, queries, buffer analysis and extractions have been operated in the Arc-GIS environment on the index maps to know the overall development and the reliability of the parameters concerned.

Natural Resource Availability Index (NRAI). Since geomorphology and slope form one of the major terrain attributes, the geomorphology, ravines and slope were considered under this parameter.⁴ A geomorphological map was prepared from the Indian Remote Sensing LISS III 1D digital satellite data and different units of geomorphology such as alluvial plain, structural hills and pediments are assigned different weights according to their perceived contribution to development on the basis of literature. A slope map of the area was prepared from ASTER data and was classified on a 1 to 4 scale giving weightage as discussed above. Ravines form one of the integral parts of this area and have a very strong influence on the development of the villages. Hence, a ravine map has been prepared from the satellite data. Ravines have been classified as severe and moderate on the basis of the severity of the ravines and weights were assigned accordingly.

Socioeconomic Development Index (SEDI). On the basis of the methodology described and the social parameters mentioned above the individual index maps were generated and integrated to form the Village Development Index (VDI) based on social parameters and their statistics. The choice of variables used in the index was limited by data constraints.

Composite Village Development Index (CVDI). Both the indices based on physical and social parameters were integrated and finally classified to form a CVDI based on composite parameters.

The village-level analysis was supplemented by a qualitative analysis of impacts of ravines on livelihoods by examining peoples’ perceptions and coping mechanisms. The information for this part of the analysis was collected through 10 focus group discussions (FGDs) with villagers in six villages of Morena district. Six FGDs were conducted with cultivators, senior villagers. During focus group discussions with different groups of villagers, they shared the problems that they face due to land loss caused by the headward erosion of ravines in their agricultural land. Such erosions on their productive land occur every year, mainly after the rainy season, and the land needs regular observation and maintenance to protect it from further damage. However, the availability of modern earth removers, tractors and other machinery in recent decades has helped farmers to expand their agricultural land to adjoining fields after levelling ravine land for agricultural use. Groups also reported that it is a costly affair for farmers to maintain the levelled land in the long run. This was supplemented with open-ended, in-depth interviews with key informants.

The results have been discussed in the results and discussion section below.⁵

Results and discussion

Geomorphology: Ravines and their expansion

The geomorphology of the area mainly comprises thick unconsolidated alluvial plains and ravines and some parts are occupied by structural hills, and residual hills which exist in a scattered manner mainly in south-western parts of the investigated area. The southern part of the Sabalgarh area comes under dissected plateau. The structural features observed in the area are in the form of lineaments. The other common features are mainly meander, and thick younger and older alluvial plains. Alluvial plains are used for agricultural purposes wherever they are flat. Agricultural land is found even in some parts of ravines. Channel bar and Point bar are also present in and adjoining the Chambal River where the river meanders. Most of the area in this region is covered by a highly dissected complex pattern of valley developed by ravine formation. The most striking geomorphic unit in the area is the ravines, which are extremely dissected landscapes and are generally agriculturally less productive (Figure 2). They extend on either side from each bank of Chambal River and its tributary Kunwari. They are characterized by a very fine drainage network and steep slopes with narrow interfluves. Ravines develop generally along the face or front of re-treading scarps. Ravines start from Chambal riverbanks and stretch to 2−2.5 km towards the south. Ravines are classified in three broad types as per their nature and intensity: highly degraded ravines and moderately degraded ravines; some of the ravine area is levelled and these ravines are classified as abolished ravines.⁶ This classification of ravines has been prepared in this study on the basis of severity of the ravine formation, its shape, size and cultivation practices. Three types of ravine-affected lands are observed here. The severely affected area is classified as deep ravine. Depth is more than 30 m, around 2−3 m narrow base width and high steep slope; these look V-shaped. The moderately affected area is classified as medium ravine, in which case the depth varies from 5 to 30 m, base width is around 20 m, slope varies from moderate to gentle, and these look U-shaped. The least affected areas are levelled and classified as abolished ravines, where they sometimes appear as rolling topography or develop terrace levelling in the adjoining agricultural land. It has been observed that if base widths are broad then this area accumulated by thick alluvium transported from the top of the ravine (Figure 3). Often such areas are suitable for agriculture.⁷ All the types of ravine exist together in a form of network of gullies.

Figure 2.

Geomorphology map of the study area.

Figure 3.

Types of ravines.

As per our estimate, nearly 23.97% of the total area of the district (around 1197 km²) is found to be under ravine in 2014 as per LANDSAT data (Figure 4). The two-point estimation suggests that, in 1974, the area under ravine was nearly 28% (around 1398.12 km²). Thus, the areal contraction of ravines has been in the magnitude of around 201 km² over the last 40 years (1974−2014) (Table 1). So far as changes in other land use classes are concerned, the major changes are: an increase in built-up area and agricultural land and decline in forest cover. However, ravine formation processes in the area are still active (Figure 2). The ravines of the study area are aggressively engulfing the agricultural land, roads and settlement during the rainy season every year. It was found during field investigation that due to this encroachment of ravines, people are forced to shift from one place to another (Pani and Mohapatra, 2001). Field investigation and interviews with local people and farmers suggest an increase in loss of agricultural land due to land degradation. Few other studies on the region support such findings.⁸ The decline in ravine land is higher in rate due to conversion of ravine land to agricultural land, mostly through heavy mechanised land levelling. Thus, the decline of total area under ravine is because of the higher rates of land levelling. It is important to note here that the levelled land generally has low productivity and requires constant refilling after every rainy season, making the land reclamation process highly cost-intensive. It has been noticed in other land-degraded affected countries like Spain, where subsidised olive farming is a common practice but with the practice of clean weeding, using fertilisers in the place of manure has accelerated the runoff on the slope. The rainfed olive plantations are often situated on steeper slopes and unsuitable land and cause further erosion (Graaff and Eppink, 1999). Even other studies also show that the practice of reclamation ultimately increases soil erosion, as it involves an expansion of uncovered surface area vulnerable to physical occurrences of erosion. Similarly, southern Italy also experienced prolonged degradation over the last century due to anthropogenic pressure mainly through an extensive agricultural practice which, over the last three decades, adopted reclamation of scrublands and badlands for durum wheat cultivation (Rendell, 1986).

Figure 4.

Land use land cover map of the study area (LANDSAT 2014).

Table 1.

Change in land use cover: 2014.

Feature	Area (km²)	Percentage distribution	Area (km²)	Percentage distribution	Change 1974−1975 to 2014
	1974−1975		2014
River	40.22	0.81	32.14	0.64	0.16
Sand bar	27.74	0.56	31.63	0.63	−0.08
Water body	21.59	0.43	24.75	0.50	−0.06
Ravine	1398.12	28.01	1196.88	23.97	4.03
Sparse vegetation	1038.92	20.81	973.64	19.50	1.31
Rocky terrain	114.81	2.30	87.35	1.75	0.55
Built-up area	6.82	0.14	33.70	0.68	−0.54
Agriculture	2343.95	46.95	2612.14	52.32	−5.37
Total	4992.17	100.00	4992.23	100.00	0.00

Source: Author’s calculation based on LANDSAT 1 and LANDSAT 8.

Causes of ravine development

The cause of ravine formation is very complex in this region. The exact cause of ravine formation is difficult to establish (Boardman, 2006). There are several reasons for the land degradation in terms of ravine formation in general. Due to the presence of sparse vegetation cover and/or intrinsic properties, the soil cannot withstand erosive forces, in such situations the topsoil is eroded and deep gullies develop (Gallart et al., 2002). Badlands can develop in any climate where loose sediments and less vegetation cover are present (Howard, 2009). The recent examples from all over the world suggest that land use change has a more serious impact on gully erosion than climate change (Valentin et al., 2005). In the study region, it is found that river-incision is very prominent, which may be another cause of ravine formation. The ravine depth also increased in the study area accordingly. This is linked with the rejuvenation of the river Chambal and its tributary which is probably the cause of ravine formation in the study region, a phenomenon that has been noted by earlier studies (Ahmad, 1973; Haigh, 1984). The probable causes of badland formation are due to the effect of Himalayan orogeny (Ahmad, 1968; Sharma, 1968; see also Ranga et al., 2016) and perhaps an increase in the southwest monsoon between 15−5 Ka (Gibling et al., 2005). Generally, the gulling processes are activated by increasing population, improper agricultural practices, and overgrazing, which is particularly evident in the study area. The study area is densely populated.⁹ Around 70% of rural people are engaged in agricultural practices and animal husbandry. The area also experienced relatively high population growth. The slope was levelled so that farming could cope with the demand for more land. The cultivation of steep slopes and clearing of vegetation has accelerated erosion in the high land (Bhan, 1988). In the six-village survey, it is noted that agriculture is taking place on the steep slopes, which leads to further soil erosion, aggravating the land degradation problem (Figure 5). A lowered groundwater table and water scarcity for cultivation were reported by many farmers. It has been noted in the literature that gully channels are developed mainly because of discontinuous gullies associated with sub-terrain concentration of flow in soil pipes (Ahmad, 1968; Jones, 1994; Sharma, 1968). Often local lowering of the water table raises the hydraulic gradient. This was also noticed in the field survey in the study area (Figure 6). It was expected that land use change such as deforestation, construction activities etc. would have a greater impact on gully systems. It was observed that stone and sand quarrying, forest-felling and construction activities have increased in the study region.

Figure 5.

Agriculture on a steep slope after reclaimed ravine land. Trees are in the background.

Figure 6.

Initiation of piping process. The initial depth of piping is around 1 m.

Land degradation and socioeconomic development

To examine the linkage between land degradation and socioeconomic development of the study area, three indices have been developed to examine the relationship. As explained in the methodology section, the villages in the study area have been clubbed into two groups: those that are within the ravines and are within a degraded area; and those outside the ravine area (Figure 8). It is found that of the total 766 villages,¹⁰ 343 villages are under the effect of ravines, and 423 villages are outside ravines in the study district. Out of the 343 ravine-affected villages, 109 villages are completely within the ravine. These are the villages most affected by ravines.

To find the implication and influence of ravines on development, tests were performed in three ways −three different types of composite indices were estimated and the distribution of villages according to levels of development has been presented in Tables 2 and 3. It is found that of all the villages, more than 52% are poorly developed as per physical parameters. The second model, where only socioeconomic indicators were used, the result suggests 45% of villages are poorly developed in the district. On the other hand, when both the indicators were included in the model, it is found that around 50% of villages are poorly developed in the district in terms of composite index of development (Table 2). Nearly 45% of villages that are within ravines are poorly developed, whereas near to 46% of villages outside ravines were developed. When the distribution of villages across size classes according to CVDI is presented separately for villages within and outside ravines, out of 353 ravine-affected villages around 71% villages are poorly developed, whereas 37% of villages outside ravines are poorly or least developed (Table 3).

Table 2.

Distribution of villages according to levels of development.

Levels of development	Natural Resource Availability Index (NRAI)	Socioeconomic Development Index (SEDI)	Composite Village Development Index (CVDI)
Least developed	60 (7.8)	29 (3.79)	25 (3.26)
Poorly developed	405 (52.87)	348 (45.43)	381 (49.74)
Marginally developed	63 (8.22)	322 (42.04)	282 (36.81)
Developed	238 (31.07)	67 (8.75)	78 (10.81)

Note: Figures within brackets refer to percentage of total villages.

Table 3.

Distribution of villages according to levels of development: Within and outside the ravines.

Levels of development	Distribution of villages according to Composite Village Development Index (CVDI)
	Villages within ravines	Villages outside ravines
Least developed	3 (0.87)	22 (5.20)
Poorly developed	245 (71.43)	136 (32.15)
Marginally developed	90 (26.24)	192 (45.39)
Developed	5 (1.46)	73 (17.26)
Total	343 (100)	423 (100)

Note: Figures within brackets refer to percentage of total villages.

To examine the interrelationship between physical and socioeconomic parameters we have cross-classified villages according to their scores in terms of these two indices (Table 4). Of the total 29 villages in the least developed category according to socioeconomic index, 16 villages (55.1%) are in the least developed or poor category as per the NRAI index. Similarly, of the 60 villages categorised as least developed according to physical parameters, as many as 78.4% of villages are either poor or least developed according to the socioeconomic index. On the other hand, none of the villages categorised as least developed in terms of NARI are in the highly developed category according to socioeconomic parameters. However, the relationship is far from uniform over all 238 villages as only 13% with the best physical index are in the highly developed category in terms of socioeconomic index; nearly 55% belong to the moderately developed category in on the socioeconomic index. Of the 67 villages in the highly developed category as per the socioeconomic index, 46% are in the highly developed category as per physical index; but it is important to note that 52% of such socioeconomically developed villages are also located in the poor category in terms of the physical index (Table 4).

Table 4.

Matrix of villages according to Socioeconomic Development and Natural Resource Availability Indices.

		Socioeconomic Development Index (SEDI)				Total
		Least developed	Poorly developed	Marginally developed	Developed
Natural Resource Availability Index (NRAI)	Lowest	1(1.7)[3.4]	46(76.7)[13.2]	1321.7)[4.0]	0(0.0)[0.0]	60(100.0)[7.8]
	Poor	15(3.7)[51.7]	208(51.4)[59.8]	147(36.3)[45.7]	35(8.6)[52.2]	405(100.0)[52.9]
	Moderate	5(7.9)[17.2]	27(42.9)[7.8]	30(47.6)[9.3]	1(1.6)[1.5]	63(100.0)[8.2]
	High	8(3.4)[27.6]	67(28.2)[19.3]	132(55.5)[41.0]	31(13.0)[46.3]	238(100.0)[31.1]
Total		29(3.8)[100]	348(45.4)[100]	322(42.0)[100]	67(8.7)[100]	766(100.0)[100]

Note: Parentheses refer to percentages to row totals; figures within square brackets refer to percentages to column totals.

Thus, while there is a strong relation between physical and socioeconomic development, there is no automatic and one-to-one correspondence between the two. The relationship may be mediated through other variables like population size, distance from urban centres (see Pani and Carling, 2013), proximity to highways or metallic roads or availability of alternative communication linkages through waterways etc.¹¹

In Table 5, the mean index scores for the degraded and non-degraded villages have been presented for three separate indices. In absolute terms, the mean difference is highest in the case of composite index of development and lowest in the index of socioeconomic development. The mean development indices of degraded villages are lower than those of the non-degraded villages in all three indices; however, the difference is not significant in the case of the socioeconomic index.

Table 5.

Mean score of indices.

	Natural Resource Availability Index	Socioeconomic Development Index	Composite Village Development Index
Non-degraded villages (N=423)	9.77	29.21	38.97
Degraded villages(N=343)	7.05	28.78	35.83
All villages(N=746)	8.55	29.01	37.56
t-value (for mean difference between degraded and non-degraded villages)	(30.585)**	(1.069)	(7.288)**

denotes t-test of mean difference between degraded and non-degraded villages significant at the 0.01 level (2-tailed).

It was expected that areas with better natural resource endowment would have better levels of socioeconomic development. The NRAI index and SEDI index are significantly and positively correlated (Table 6). Thus, there is a clear relationship between socioeconomic development and natural resource availability of the villages. However, many other factors influence the socioeconomic development of villages in the study region. For example, it was observed during the field survey that, in terms of severity of ravines, the banks of the Kunwari River are affected with a lower severity and much of the affected area where the depth is less than 3 m is reclaimable by levelling. (Figure 3c). Some of the villages are developed despite physical adversity − either these villages have better road communication facilities or they have alternative communication facilities like waterways.¹²

Table 6.

Zero-order correlation matrix.

	Natural Resource Availability Index (NRAI)	Socioeconomic Development Index (SEDI)	Composite Index Of Development (CID)
NRAI	1	0.187^**	0.465^**
SEDI		1	0.957^**
CID			1

Correlation is significant at the 0.01 level (2-tailed).

Land degradation and livelihoods: Results of qualitative analysis

Several key issues emerge from the qualitative analysis of linkages between livelihoods and land degradation in the study region. All the villages under study are predominantly agricultural − but they differ in terms of the levels of infrastructure development, accessibility, distance from urban centre and severity of land degradation. The agricultural system in the region, unlike many other parts of rural India, is not dominated by rice or wheat − the staple cereal crops of India. The main crops are bajra (pearl millet), mustard, and arhar (pigeon pea) along with wheat. The overall character of agriculture is determined by the availability of water. The Indira Gandhi canal provides water to a few of the villages, but there have been severe shortages in the past few years. It is interesting to note that while non-availability of enough water remains a key concern in all the villages (irrigated and non-irrigated), in villages affected by ravines, land degradation comes out as a major concern. In less affected villages, farmers are more concerned about the availability and price of agricultural inputs, particularly diesel and access to output markets.

In severely affected villages farmers generally talked about two types of impact of ravines: (a) loss of houses, homestead and kitchen gardens; and (b) loss of agricultural land, which affected their livelihoods. In some cases, farmers also talked about indirect effects such as loss of access to agricultural land, and changes in natural drainage patterns as a result of ravine formation. Ravines also affect public goods provisioning and village common property resources. We found instances of roads, primary schools and common grazing lands being affected as a result of ravines. While loss of individual property and livelihoods did create problems for individuals and their households, damage to village infrastructure and commons had long-term implications for all households (children walking to faraway schools; women going to fetch water; difficult access to health facilities).

Apart from these impacts farmers complained about decline in agricultural productivity in land located in the ravine zones. Although this interrelationship needs further investigation and more detailed analysis, loss of topsoil is cited as one of the prime reasons for low productivity in the areas affected by ravines. Farming practices, including cropping patterns have changed in some cases as a result of ravines. We noticed instances of a shift to less water-intensive crops (such as arhar or pigeon pea), decline in commercial wheat cultivation (which is water-intensive), cultivation of vegetables in lower valleys that were created as a part of ravine formation processes, crop holidays to cope with declining soil fertility and, above all, investment in levelling and abandonment of agricultural land.

It is interesting to note that farmers and villagers in general do not view ravines, locally called bihad, only as a curse though many of them complained about them as a problem for their survival. Bihads are also a source of fodder and fuel and act as a source of other minor forest products and sand. In one of the study villages, villagers bitterly complained about denial of access to a ravine forest zone as part of crocodile conservation efforts by government agencies. Bihads are a major source of fodder and the livestock economy of the villages is very dependent upon these lands.

The land affected by ravines is levelled and new agricultural land is often created. At times, villagers exchange or reorganise their agricultural land in response to damage caused by ravines. Government agencies have undertaken massive land-levelling exercises in some areas and such land has been distributed among the socially disadvantaged groups in the villages. However, these changes in agricultural land, when done by individual farmers, are often not recorded in official records and hence they can cause conflict.

The shifting of villages or dwelling units creates a huge livelihoods shock to families (Figure 7).¹³ Loss of ancestral homes and building new houses has led to severe financial burdens, often financed by high-interest loans and sale of productive assets. Disintegration of joint families and village communities has meant disintegration of social networks and support systems.

Figure 7.

Settlement encroached by ravines. Individual affected houses can be seen in the background.

Figure 8.

Composite village development index.

So far as coping mechanisms are concerned, people in the study villages have opted for both agriculture-based coping mechanisms and also some have tried to find livelihoods outside agriculture. As we have discussed above, agriculture-related coping mechanisms include levelling of land, construction of bunding and barricading land, shifting boundaries of agricultural plots, abandonment of some land and bringing new land under cultivation, changing cropping patterns, changes in agricultural practices. Coping strategies outside agriculture revolve around the spatial and occupational redistribution of labour. People have started to move to non-agricultural occupations and some have started going to nearby and faraway cities to work seasonally. Of course, all these occupational changes cannot be seen as responses to land degradation alone; there are multiple causes for such processes. However, the small and marginal farmer households, in particular, cited difficulties in carrying out agricultural operations and declining and inadequate agricultural income as key reasons for seasonal outmigration.

Conclusions

This study has brought out several key dimensions of the process of land degradation and its implications for socioeconomic development. Firstly, in terms of the estimates based on remote sensing data, it is found that ravine formation has affected a large chunk of land area in the district under study. The area under ravines has been found to be decreasing during 1974−2014 (Table 1). An analysis of the geomorphic features of the study area reveals that the dominant geomorphic features in the region are ravines. An attempt has been made to provide a classification of ravines on the basis of field observations. Secondly, the implication of land degradation for socioeconomic development was studied on the basis of three composite indices. This analysis suggests that a higher proportion of the villages located in ravine-affected areas are poorly developed in terms of socioeconomic development. Village-level infrastructure should not normally be affected by local environmental factors, as most of these are provided by the government. However, it was found that there is a close correlation between the index of availability of natural resources and that of socioeconomic development. Finally, qualitative information gathered through interviews and FGDs suggested the multifaceted linkages between land degradation and livelihoods in the study region. Perceptions of local people broadly match the evidence gathered through analysis of remote sensing and other spatial data. Major implications of ravine formation include loss of agricultural land, decline in agricultural productivity, shifting of villages, loss of livelihoods and impacts on village infrastructure. There is undoubtedly a need for closer monitoring and estimation of the loss caused by land degradation in the Chambal region. Effective policy intervention should take into account people’s perceptions of land degradation and its implications for their livelihoods.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

Author biography

Padmini Pani is an Assistant Professor of Geography at the Centre for the Study of Regional Development, Jawaharlal Nehru University, New Delhi. Her areas of research interests include Land Degradation, Water Balance, Climate Change, Environment and Development, and applications of Geo-informatics. She has done extensive field research in the Himalayas and semi-arid ravine-affected areas in India. She was awarded an ESRC Research Fellowship at the School of Geography and Environment, University of Southampton, UK, in 2010. Currently she is part of a DAAD Visiting Fellowship, at the Institute of Physical Geography, Goethe University, Frankfurt, Germany (2014-17). She has co-edited Geoinformatics for Natural Resource Management. New York: Nova Science Publishers, Inc. (2009).

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