Sikkim is one of the constituent states of India, endowed with huge water resources. However, due to steep terrain and non availability of a groundwater aquifer, water conservation is a challenge. The water received as rainfall drains away through the steep terrain in the deep valleys, thereby creating a water stress after withdrawal of the monsoon. To overcome such a situation, a study was undertaken to design a suitable rain water harvesting system for the state. To design a suitable water harvesting system, we estimated the water demand of the end users, assessed the water availability during the non-rainy period, and designed the volume of storage structure. The study revealed that more than 80% of the respondents experienced water stress during the period from December to March. The average daily water demand of individual households was observed to be around 400 litres. The rainfall pattern indicated that 90% of the rainfall is concentrated during 6 rainy months. On average, 24 consecutive dry days were observed in the state. The volume of storage structure obtained, based on water availability and demand, was 5 m3 per household. It is felt that this volume can take care of the domestic water demand.

INTRODUCTION

Water is a lifeline for the sustenance of any society. There is a growing perception that due to various anthropogenic activities and climate change natural resources, particularly water, are at profound risk (IPCC 2007). The change in landscape characteristics and deforestation has altered the hydrological regimes, leading to declining water availability in the natural sources, that is, the springs and streams. Looking to the present trend of a declining water availability scenario, it is necessary to explore the possibility of harnessing easily accessible sources such as rain (Postel 1992; Reid & Schipper 2014). Rain water is the most easy to use and accessible sustainable water resource, which has very high potential for both domestic and agricultural use in future (Helmreich & Horn 2009; Lange et al. 2012). Rain water harvesting (RWH) systems are drawing global attention as an important component in attaining water security (Rygaard et al. 2011). In urbanized locations experiencing severe scarcity, there is unanimity regarding rain water harvesting, that is, roof top harvesting (Abdulla & Al-Shareef 2009; Srinivasan et al. 2010).

The concept of roof top rain water harvesting (RRWH) is not new, but its adoption has been sluggish. In the present scenario, due to the drying up of existing natural sources and the inability of water infrastructure to meet the growing demand, special attention has been drawn to RWH. A typical RRWH system comprises three basic subsystems – a catchment system (roof), a delivery system (filters and gutters), and a storage system (Kahinda et al. 2007). The RRWH can augment the main source and can be effectively used for non-potable purposes (Appan 2000; Handia et al. 2003; Jones & Hunt 2010; Umapathi et al. 2013). Efforts have been made to devise appropriate planning strategies for the RRWH system to make it a viable option. One of them is sizing of the storage system. In one such effort, Liaw & Tsai (2004) conducted a study in Taiwan to estimate the most cost effective combination of roof area and storage capacity that best supplies a specific volume of water. They claimed that the procedures developed constitute an effective tool for preliminarily estimating the most satisfactory storage capacity of any specific roof area and for determining the rational reliability of a corresponding water supply. Ward et al. (2010), in another study in the UK, recommended a simulation model for design of RRWH. They observed that actual tanks were over size for a given demand and roof size compared to those designed as per the simulation model. Vieritz et al. (2015) listed a number of parameters to be considered for design of RWH tanks that includes the time step, simulation length, processes to include in the model, order of calculations used within the model and outputs required. Shreeve et al. (2016) performed multi criteria analysis to illustrate that the traditional RWH configurations are not necessarily the optimum solutions when broader criteria are considered. From their study, they suggested alterations in the existing RWH technologies to address the effect of storm water.

The benefits of RWH have been investigated in many large cities in Japan (Zaizen et al. 1999), London (England) (Hills et al. 2001) and in Melbourne, Australia (Imteaz et al. 2011). The reliability and feasibility of any RWH system is another aspect that needs to be ascertained for large scale adoption. RWHs have been reported to be significantly reliable and feasible in both urban (high water consumption) as well as in rural areas (low water consumption) (Imteaz et al. 2012, 2014; Karim et al. 2015). Haq (2006) states that RRWH is free from contamination of arsenic, and it has been able to augment 11.5 million litres of water in the year 2002 in Bangladesh. The RRWH is an important source in areas where surface water is contaminated by faecal pathogens and the scope for developing groundwater is negligible, or it is contaminated by chemicals, such as arsenic in Bangladesh (Chakraborti et al. 2010). The RWH system can be used for both potable and non-potable applications. Examples exist of systems that provide water for domestic, commercial, institutional and industrial purposes as well as agriculture, livestock, groundwater recharge, flood control, process water and as an emergency supply for fire fighting.

Although the benefits of the RWH system have been enumerated by many earlier researchers, its adoption has been slow. Ward et al. (2010) listed some reasons such as uncertainty about the financial viability of RWH systems; lack of experience and the absence of well-run demonstration sites are other reasons. Thomas (1998) also mentioned that considering the wage level in most of the tropical countries, for a domestic RWH system to be viable the capital cost of creating a storage structure should be less than $15 per m3. In a study conducted by Gurung & Sharma (2014), estimates were made for a communal RWH system in Australia. Their study reported that the capital cost constitutes 70%, followed by maintenance (10–15%), operation (3–5%) and the replacement of components (1–10%). However, they reported that a change in the topographical slope is bound to influence the cost.

The RRWH is not only a necessity for urban societies but also in mountain ecosystems, particularly of the middle Himalayas, which consist of steep slopes where the natural watersheds do not provide scope to harness sufficient water resources (Tambe et al. 2012; Vaidya 2015). In these locations, habitations are scattered and are at higher elevations. In these locations, the creation of a traditional water supply system consisting of a pipe network is very costly. Small scale local storage options such as RRWH provide a bright opportunity to build community resilience. This article is intended to understand the perception of water stress of the people of South Sikkim, located in the middle Himalayas, assess the rain water resources, and design an appropriate tank size to enhance the coping strategies of the local inhabitants of the district.

DESCRIPTION OF THE STUDY AREA

Sikkim is one of the constituent states of India, located in the Eastern Himalayan ranges. The state is placed between the latitudes of 27 ° 5′ N to 20 ° 9′ N and longitudes of 87 ° 59′ E to 88 ° 56′ E. It is characterized by highly undulating terrain, with elevations ranging from 300 to more than 8,000 m. Administratively, the state is divided into four districts, that is, East, West, North and South. The population of the state as per the 2011 census is 6.11 lakhs. Although the North district is the largest, it is thinly populated due to the extreme terrain and weather conditions. The state is endowed with huge water resources, but it is still subjected to mild to severe water stress. The state receives a good amount of rainfall, but its distribution is erratic and uncertain. Most of the rainfall is concentrated in the rainy months that span April to September. Thus, after the withdrawal of the rainy months, there exists a severe water shortage in the state. The water stress situation in the state has resulted in events such as non-availability of drinking water, forest fires, incidences of pests and diseases, drops in productivity and so on, which have a direct impact on the economy of the state. The increasing population and changing climatic pattern are also attributed to such water stress (Tambe et al. 2011).

The state is characterized by steep slopes, thereby creating constraints for water conservation through conventional measures. Further, the isolated habitats and small clusters of households make a pipeline system economically unviable. The habitation pattern of the state consists of people living at higher elevations, as the very narrow, deep valleys are not suitable for settlements. For this reason, it is very difficult for any households to fetch water from the perennial streams sources flowing in the deep and narrow valleys. It has been reported that 80% of the households are dependent on the springs as a source of water, or diversions from nearby small streams that are seasonal in nature. With the changes in climatic patterns and land use, drying of springs has been reported in the state (Tambe et al. 2012).

METHODOLOGY

The methodology adopted in the present study can be broadly categorized in three steps:

  • (i) Water demand analysis

  • (ii) Water availability analysis

  • (iii) Design of an RWH system.

The methodology adopted in the present study is shown as a flow chart in Figure 1 and is described in detail below.
Figure 1

Flow chart of the methodology used.

Figure 1

Flow chart of the methodology used.

Water demand analysis

To assess the water demand, we conducted a questionnaire survey in five gram panchayats (villages) in the East and South districts of the state. Questionnaires were drafted and tested at local level before visiting the villages. A total of 142 villagers were administrated from five gram panchayat units (GPU) with the questionnaire to get their response about the demand for water for various activities (Table 1). GPUs are the smallest administrative units of Sikkim. Each GPU consist of a number of wards. It was found that on average the family size in the state consists of six members that decide the demand for water for individual households. As the households in the state are isolated and sparse, we assumed that the sample is representative for coming to some conclusion.

Table 1

The details of the sample size for the questionnaire survey

Sl noName of GPUParticipantsNo of wards represented
Mellidara 25 
Namphing 37 
Phongla 32 
Turuk 26 
Rumtek 22 
  142 13 
Sl noName of GPUParticipantsNo of wards represented
Mellidara 25 
Namphing 37 
Phongla 32 
Turuk 26 
Rumtek 22 
  142 13 

The major emphasis in the questionnaire survey was perception of the water stress, water requirements for different household activities, priority demand and willingness to contribute financially to any suitable water harvesting system.

The perception of water stress was obtained by understanding the peoples' view about water availability during various months of the year. The hydrological year was classified into five groups, that is, June–September, October–November, December–January, February–March and April–May. The responses were obtained in terms of surplus, nominal, stressful or very scarce conditions.

The water requirements of each household were categorized as cooking, cloth washing, toilet, bathing and cleaning. The responses were obtained from the villagers in terms of the number of buckets (assuming 20 litres as an average volume) they require. The respondents were asked to reply in terms of priority of water demand if the availability is limited. Further, the respondents were asked about their willingness to contribute financially to creating water harvesting infrastructure. The purpose of administrating the willingness was to understand the sustainability issues if such infrastructures are created under any government schemes.

Water availability analysis

As rainfall is the main source for roof top harvesting, we analysed the rainfall pattern of the state. The state lacks a systematic network for long term rainfall data. Long term data are available only in Gangtok station. However, being in the hilly zone, there is significant variation in spatial distribution in rainfall with the East district receiving comparatively higher rainfall. Further, the habitation is mostly concentrated in the East, West and South districts only. The North district, with its hostile and inhospitable terrain, has much lower population distribution and was not considered for rainfall analysis. The data on rainfall are available for 12 automatic weather stations (AWS) installed under the MOSDAC (Meteorological and Oceanographic Satellite Data Archival Centre) program of the Government of India. The parameters recorded by each AWS are rainfall, maximum and minimum temperature, humidity and wind speed. During the analysis, four stations were ignored due to inconsistent data. Incidentally, all the stations considered in the study were concentrated in the East and South districts only. The data period for the eight stations varied from 3 to 5 years. As our interest was in the design of an RWH system, we assumed that the data period was normal and was considered appropriate for our study. The locations of these stations are shown in Figure 2.
Figure 2

Map of Sikkim showing districts and the rainfall stations.

Figure 2

Map of Sikkim showing districts and the rainfall stations.

The rainfall pattern is distinct, with 6 rainy months (April–September), referred to as the peak season in the following text and 6 non-rainy months (October–March), referred to as the lean season in this paper. The rainfall analysis was conducted in terms of rainfall pattern, average number of rainy days, average number of dry days and consecutive dry days, rainfall characterization, spatial and temporal distribution of rainfall. These analyses were conducted for both peak and lean season but we concentrated only to lean season as demand for water is higher during this period.

The rainfall pattern included the distribution of rainfall during each month and its distribution during the peak and lean season. From the rainfall data, we analysed the average number of rainy days and dry days. Further, we analysed the consecutive dry days when no rainfall was recorded. We categorized the consecutive dry days in eight broad categories, that is, 1–2, 3–5, 6–8, 9–11, 12–15, 16–20, 21–30 and more than 30 dry days. The rainfall characterization was made on the type of rainfall events in terms of depth of rainfall. In the characterization, we categorized rainfall into eight groups, that is, ≤2 mm, 3–5 mm, 6–8 mm, 9–11 mm, 12–15 mm, 16–20 mm, 21–30 mm and >30 mm.

We also attempted to map the spatial distribution of rainfall in the state. For mapping of rainfall patterns, the ArcGIS platform was used. The isohyetal map was generated by interpolating the contour.

Design of the water harvesting system

After assessing the water availability and demand, we attempted to design a suitable RWH system for domestic consumption. For designing the system we attempted to estimate the average roof sizes, the materials used for construction of the roof, the type of roof and its collection efficiency.

The roof size was estimated by finding the area of average houses in Sikkim scattered over the entire district through Google Earth. A total of 53 houses were considered and the roof sizes were calculated. The roof types and materials of the roof were obtained from the questionnaire survey. The roof types were categorized as sloping or flat roofed, and the roof materials was categorized as reinforced cement concrete (RCC), asbestos, galvanized iron (GI) sheet, plastic and others.

Estimation of RWH potential

The RWH potential was estimated by the method suggested by Farreny et al. (2011) and is shown in Equation (1). 
formula
1
where rain water harvesting (RWH) potential (in L/year) of a roof, P is the local precipitation (P, in mm/year), A is the catchment area (in m2) and the runoff coefficient is RC (non-dimensional). The values of runoff coefficient for different types of roofs are given by Farreny et al. (2011).

Design of average tank size for Sikkim

For design of a suitable tank size, we modified the methods as suggested by the Environment Agency EA (2008). EA (2008) suggested a method to size a tank based on a user-defined percentage of the average annual rainfall or demand (whichever is the lower). The equation for this approach takes the form: 
formula
2
where S is the storage capacity; P is the user-defined percentage of average rainfall or demand, whichever is lower (current best practise recommends 5%, i.e. 0.05); Cf is the runoff coefficient; F is the system filter efficiency and R is the rainfall in volume units (R would be replaced by D if the annual demand was the lower of the two). In the present study, the values of P, F and Cf were clubbed to include the initial abstractions, runoff coefficient and other losses.

RESULTS AND DISCUSSION

The results of the study indicated are presented in the following sequence:

  • (i) Water demand analysis

  • (ii) Water availability analysis

  • (iii) Design capacity of a suitable harvesting structure.

Water demand analysis

Water stress perception of the stakeholders

The analysis of the questionnaire survey indicated that there exists a severe water stress situation, particularly during the non-rainy period (Table 2). The table indicates that more than 90% of the respondents expressed stressed water availability during December to March. It is during this period the rainfall availability is negligible. Traditionally the habitants of hills in general and Sikkim in particular are dependent on spring as a source of water for both domestic and agricultural purposes (Negi & Joshi 2002, 2004; Tambe et al. 2012). However it have been reported that the spring sources are experiencing declining discharges and even drying up during the period of December to March (Tambe et al. 2012). The reason for drying up of springs has been attributed to developmental activities such as construction of infrastructural facilities and climate change (Tambe et al. 2012; Barua et al. 2014).

Table 2

Perception of water availability and stress situation on a temporal scale (in %) in the state

 Months
Availability categorizationJun-SepOct-NovDec-JanFeb-MarchApril-May
Surplus 26.90 5.28 0.76 2.17 12.72 
Normal 51.28 53.93 18.94 14.90 29.09 
Stressed 8.34 18.94 27.18 23.14 18.66 
Very scarce 13.48 21.83 53.12 59.78 44.73 
 Months
Availability categorizationJun-SepOct-NovDec-JanFeb-MarchApril-May
Surplus 26.90 5.28 0.76 2.17 12.72 
Normal 51.28 53.93 18.94 14.90 29.09 
Stressed 8.34 18.94 27.18 23.14 18.66 
Very scarce 13.48 21.83 53.12 59.78 44.73 

Water demand analysis

The water demand of the stakeholders was collected by administrating the questionnaires. The results of water demand for various activities are shown in Table 3. The analysis indicated most of the water is utilized for washing (100 litres) purpose. The demand of water for other purpose is bathing, toilet and cleaning purposes (80 litres each activities). The analysis indicates that an average household requires around 400 litres of water daily for various activities.

Table 3

Average water requirement for the different activities of a family

ActivitiesAverage number of bucketsAverage volume of water demand (L)Percentage of water demand
Cooking 3.5 70.0 17.0 
Washing 4.8 95.0 23.1 
Bathing 4.0 80.0 19.6 
Toilet 4.3 85.0 20.7 
Cleaning 4.0 80.0 19.6 
Total 20.6 410.0 100 
ActivitiesAverage number of bucketsAverage volume of water demand (L)Percentage of water demand
Cooking 3.5 70.0 17.0 
Washing 4.8 95.0 23.1 
Bathing 4.0 80.0 19.6 
Toilet 4.3 85.0 20.7 
Cleaning 4.0 80.0 19.6 
Total 20.6 410.0 100 

Priority demand

In the study, an effort was made to explore an alternate demand situation if limited water was made available. The stakeholders were asked to submit their views about the priority demand. It was observed that the highest priority was accorded for toilet and washing purposes and minimum priority was accorded for cooking purposes (Table 4).

Table 4

Priority demand of water for various domestic activities

 Priority (%)
Domestic activities1st2nd3rd4th5th
Cooking 11.36 6.42 5.31 5.83 51.07 
Washing 35.99 23.54 16.87 15.59 8.00 
Bathing 7.41 21.09 29.33 37.65 3.01 
Toilet 35.84 28.79 24.11 10.74 0.52 
Cleaning 25.98 24.36 23.38 18.50 7.73 
 Priority (%)
Domestic activities1st2nd3rd4th5th
Cooking 11.36 6.42 5.31 5.83 51.07 
Washing 35.99 23.54 16.87 15.59 8.00 
Bathing 7.41 21.09 29.33 37.65 3.01 
Toilet 35.84 28.79 24.11 10.74 0.52 
Cleaning 25.98 24.36 23.38 18.50 7.73 

Willingness of the stakeholders to invest in a water harvesting system

In the questionnaire survey, the stakeholders were asked about their view on willingness to invest in a water harvesting system if supported by governmental agencies. It was interesting to find that 95% of the respondents affirmed that they would make a contribution of different amounts (Table 5). The variation in the willingness to pay for water infrastructure is attributed to the aspect on which these GPUs are located. The Mellidara GPU, which is located in the southern part of the district and is in a rain shadow area, experiences the most scarcity. Such information is important for the sustainability of any system if provided to the stakeholders.

Table 5

Willingness of the respondent to contribute to water resources infrastructure ($ 1 = Rs 65.00)

Number of respondents (%) from selected GPUs
Sl no.Amount of money (Rs.) in monthNamphingPonglaMellidara
<100 
100–300 97.22 81.25 23.52 
300–500 2.78 18.75 17.65 
>500 58.82 
Number of respondents (%) from selected GPUs
Sl no.Amount of money (Rs.) in monthNamphingPonglaMellidara
<100 
100–300 97.22 81.25 23.52 
300–500 2.78 18.75 17.65 
>500 58.82 

Water availability analysis

Average annual rainfall pattern

The average annual rainfall pattern in the selected stations shows that more than 90% of the total is concentrated during the months of April–September. Further, there is variation in the spatial distribution of rainfall recorded at different stations ranging from 804 mm for Duga to 2,395 mm at Kabi station. Similar variation was also observed during the non-rainy season, with rainfall ranging from 70 mm at Melli station to 324 mm at Kabi. The spatial variation of the rainfall pattern is shown in Figure 3.
Figure 3

Spatial rainfall distribution during non-rainy and rainy season.

Figure 3

Spatial rainfall distribution during non-rainy and rainy season.

Average number of rainy days

The rainfall mentioned in the previous section states its temporal and spatial distribution. However, this rainfall occurs during a certain number of days in a year. Therefore the present analysis was made to analyze the number of rainy days recorded in the state. The monthly rainfall days, as recorded in each station, are shown in Table 6. The table shows that 70–85% of the rainy days are concentrated during April to September, whereas the remaining 15–30% of the rainy days are observed during the non-rainy period of October to March. The spatial distribution of the number of rainy days is shown in Figure 4.
Table 6

Station wise distribution of rainy days in each rainfall observation station in Sikkim

Average no. of rainy days in each months
Sl no.StationJanFebMarchAprilMayJuneJulyAugustSeptOctNovDec
Ranipool 11 19 25 28 31 29 20 
Melli 15 13 21 28 24 25 
Rhegu 15 19 25 30 13 
Pakyong 10 14 19 25 29 26 19 
Temi 10  12 30 25 17  11 
Duga 10 19 20 26 19 17 10 
Kabi 16 24 25 27 25 22 27 13 14 
SIRD_Karfacter 11 17 21 27 21 16 
Average no. of rainy days in each months
Sl no.StationJanFebMarchAprilMayJuneJulyAugustSeptOctNovDec
Ranipool 11 19 25 28 31 29 20 
Melli 15 13 21 28 24 25 
Rhegu 15 19 25 30 13 
Pakyong 10 14 19 25 29 26 19 
Temi 10  12 30 25 17  11 
Duga 10 19 20 26 19 17 10 
Kabi 16 24 25 27 25 22 27 13 14 
SIRD_Karfacter 11 17 21 27 21 16 
Figure 4

Distribution of rainy days during non-rainy and rainy season.

Figure 4

Distribution of rainy days during non-rainy and rainy season.

Rainfall characterization

The type of rainfall event has significant impact on RWH potential. Therefore characterization was done of the rainfall distribution for Sikkim. The results of the characterization are shown in Table 7. Generally, a rainfall amount greater than 8 mm has significance in stream water harvesting (Zerizghy et al. 2012). The analysis revealed that most of the rainfall (40–50% for different stations) occurring during the lean season is less than 2 mm. Further, the analysis showed that 65–80% of the rainfall events have a rainfall amount less than 8 mm. This indicates the limited harvesting potential in streams. Therefore, roof top harvesting is expected to play a significant role in Sikkim.

Table 7

Rainfall characterization for different stations in Sikkim

 Number of rainfall days with rainfall quantity (mm)
 
Station≤ 23–56–89–1112–1516–2021–30> 30Total days
Ranipool 13 32 
Melli 14 
Rhegu 14 26 
Pakyong 20 
Temi 15 32 
Duga 16 
Kabi 22 48 
SIRD_karfacter 12 22 
 Number of rainfall days with rainfall quantity (mm)
 
Station≤ 23–56–89–1112–1516–2021–30> 30Total days
Ranipool 13 32 
Melli 14 
Rhegu 14 26 
Pakyong 20 
Temi 15 32 
Duga 16 
Kabi 22 48 
SIRD_karfacter 12 22 

Average dry days between two rainfall events

The dry days between two consecutive rainfall events were estimated for the available rainfall records during the lean season. It is observed that the average maximum dry days between two rainfall events are 24 days. The highest dry days (59 days) between two rainfall events was recorded in SIRD Karfactor station in South Sikkim district. The numbers of dry days recorded between two events is shown in Table 8.

Table 8

Number of consecutive dry days for each station for the peak period

 Number of consecutive dry days
 
Station0–23–56–89–1516–30> 30Maximum dry days
Ranipool 72 
Melli 38 17 21 
Rhegu 15 12 
Pakyong 49 11 40 
Temi 20 12 
Duga 39 12 17 
Kabi 34 22 14 
SIRD_karfacter 26 36 12 11 59 
      Average 24 days 
 Number of consecutive dry days
 
Station0–23–56–89–1516–30> 30Maximum dry days
Ranipool 72 
Melli 38 17 21 
Rhegu 15 12 
Pakyong 49 11 40 
Temi 20 12 
Duga 39 12 17 
Kabi 34 22 14 
SIRD_karfacter 26 36 12 11 59 
      Average 24 days 

While planning the RWH system, a suitable amount need to be stored. The storage capacity of the storage system should be able to cater for the demand for water of the average household.

Design capacity of RWH system

For designing the roof top system, analysis was done for the roof top area and the materials of construction of the roof. It was observed that the average roof size was 93 m2. The roof type indicated that 85% have sloping roofs and 81% of the roofs are made of GI sheets. The roof type and roof materials have bearing on the harvesting ability of the system.

The next step adopted was to estimate the volume of harvestable water. The events when the rainfall depth recorded was 2 mm or more was considered. A rainfall amount of 2 mm or more is effective for harvesting purposes. Table 9 indicates the effective harvestable water volume.

Table 9

Effective harvestable water volumes under different types of rainfall events

Sl no.Rainfall amount (mm)Average number of daysAverage depth of rain received (mm)Volume of effective harvestable water (m3)Practicable collectable water considering the losses
3–5 5.5 22 2.05 1.53 
6–8 3.25 22.75 2.12 1.59 
9–11 1.5 15 1.40 1.05 
12–15 1.375 18.56 1.73 1.29 
16–20 1.625 29.25 2.72 2.04 
21–30 0.75 18.75 1.74 1.31 
>30 0.625 18.75 1.74 1.31 
   145.06 13.49 10.12 
Sl no.Rainfall amount (mm)Average number of daysAverage depth of rain received (mm)Volume of effective harvestable water (m3)Practicable collectable water considering the losses
3–5 5.5 22 2.05 1.53 
6–8 3.25 22.75 2.12 1.59 
9–11 1.5 15 1.40 1.05 
12–15 1.375 18.56 1.73 1.29 
16–20 1.625 29.25 2.72 2.04 
21–30 0.75 18.75 1.74 1.31 
>30 0.625 18.75 1.74 1.31 
   145.06 13.49 10.12 

From Table 10, it can be seen that the total volume of water that can be harvested is 10.12 m3. We also analysed the monthly harvestable volume of rain water during the lean season (Table 10). This indicates that the water harvested in October is 4.86 m3. Two scenarios can be planned, considering that the entire volume is captured or augmenting the volume of harvested water with occasional rainfall in the lean season. So one approach may be to have 10 m3 storage structures and the second alternative can be for a 5 m3 structure. The period for which the harvested water can be used under different demand scenarios is also estimated and presented in Table 11.

Table 10

Estimated harvesting potential for rural household of Sikkim in lean period

Sl no.MonthsQuantity (m3)Effective volume in m3 (after considering loss)
October 4.86 3.64 
November 2.02 1.52 
December 0.15 0.11 
January 0.77 0.58 
February 1.80 1.35 
March 3.74 2.81 
 Total 13.35 10.01 
Sl no.MonthsQuantity (m3)Effective volume in m3 (after considering loss)
October 4.86 3.64 
November 2.02 1.52 
December 0.15 0.11 
January 0.77 0.58 
February 1.80 1.35 
March 3.74 2.81 
 Total 13.35 10.01 
Table 11

Number of days the harvested water can augment the existing source used under different scenarios

Sl noScenarioDaily demand (lit)Tank of 5 m3Tank of 10 m3
All demand 400.00 12.50 25.00 
Cooking, washing, bathing and toilet 320.00 15.63 31.25 
Washing, bathing and toilet 260.00 19.23 38.46 
Washing and toilet 180.00 27.78 55.56 
Sl noScenarioDaily demand (lit)Tank of 5 m3Tank of 10 m3
All demand 400.00 12.50 25.00 
Cooking, washing, bathing and toilet 320.00 15.63 31.25 
Washing, bathing and toilet 260.00 19.23 38.46 
Washing and toilet 180.00 27.78 55.56 

However, in terms of cost, a 10 m3 structure will be costly compared to a 5 m3 structure, and may lead to the generation of grey water, causing health concerns. In a report from the Government of India (GOI 1999) it has been pointed out that due to lack of space for natural water storage and the scattered population pattern in hilly regions, the cost of creating conventional water harvesting infrastructure such as conveyance systems and the energy cost for lifting of water is high. In such regions, independent roof water harvesting system could be encouraged by providing subsidies (Kumar 2004). Secondly, the quality aspects of water are also important. Thomas (1988) in a study on a domestic water harvesting system reported that a tank size of 5–10 m3 is adequate for most conditions including favourable climatic conditions. Further, in that study, the recommended treatment for water is an approach such as boiling if used for consumption purposes. Similarly, in an effort in Germany, emphasis was given more to alternate uses other than consumption. However, in the study area, construction of structures of 5 or 10 m3 may be difficult due to the steep slope. To overcome the constraint of the paucity of space due to the terrain condition, a series of smaller size tanks (say 2 m3 or 1 m3 capacity) can also be suggested.

CONCLUSION

The present study indicates the state of Sikkim, although rich in water resources, faces a significant stress condition during the non-rainy season. The stressful situation results in a number of socio economic impacts. It has been found that a roof top water harvesting system augments the total water demand of each household. This augmentation can help in reducing water stress to a considerable level. The specific outcomes of the study are as follows:

  • (i) There exists a severe water stress situation during December to March when rainfall is almost negligible.

  • (ii) More than 90% of the respondents have indicated water stress and the need for a suitable water harvesting system.

  • (iii) The rainfall pattern indicates that an average of 24 consecutive dry days have been experienced in the state in last 3 years.

  • (iv) A total of 10 m3 of water can be harvested during the non-rainy season.

  • (v) A tank of 5 m3 capacity can store water to meet the priority demand of individual households.

  • (iv) The tanks can be installed in series, as on hilly terrain many times the available space does not support larger size tanks. The houses in rural Sikkim are in a cluster of small structures that can be interconnected and can be used for storing water for useful purposes.

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