Impact of forest cover and human intervention on crop water footprint

Water is necessary for the survival of living beings and the production of non-living beings. The concept of a water footprint (WF) was first introduced by Hoekstra in 2002 (2003). The available water is getting stressed globally due to the high consumption to fulfil the demand of the increasing population (Chapagain & Hoekstra 2008). WF is a good indicator for analysing the impact of human intervention (Rao et al. 2019). Green WF (WF_green) is the quantity of consumed water from green water resources i.e., rainfall, and blue WF (WF_blue) is the consumption of water from blue water resources i.e., groundwater and surface water (Chapagain & Hoekstra 2008; Hoekstra et al. 2011; Luan et al. 2018). There is a great need to calculate regional WF to understand the present scenario of available water and to manage unnecessary water consumption in that region. Many researchers have shown various ways to calculate WF in their studies, namely, through empirical formulae (Hoekstra et al. 2011) and using machine learning algorithm with the climate change impact (Mokhtar et al. 2021). The most feasible and easy way to find this is through empirical formulae, as machine learning algorithms are very complex and need great skill to execute the calculation. WF depends upon the consumed water of a crop and the yield of that crop in a particular area (Hoekstra & Mekonnen 2012); and the water consumption of a crop is majorly influenced by evapotranspiration (ET), which depends on meteorological parameters such as effective rainfall, speed of wind, and minimum and maximum temperatures (Huang et al. 2019). ET can be obtained through models such as Crop Water and Irrigation Requirements Program of FAO (Cropwat), Cropping Systems simulator (CropSyst) (Mekonnen & Hoekstra 2011; Sun et al. 2013a; Bocchiola 2015), and Soil and Water Assessment Tool (SWAT). (Luan et al. 2018) and through the statistical method depending upon regional water balance (Zhao et al. 2009; Sun et al. 2013b). The extensively used Cropwat 8.0 model gives accurate results and lessens the calculation time (Abdullahi et al. 2021; Pawar et al. 2021). Many scientists use it to assess crop ET, crop water requirements (CWR), and irrigation scheduling, especially net irrigation requirements (Babu et al. 2014; Singh et al. 2019; Roja et al. 2020). The recommendations from irrigation scheduling are based on specific locations depending upon soil types and agroclimatic and agroecological conditions (Karanja 2006; Ewaid et al. 2019; Surendran et al. 2019; Tewabe & Dessie 2020; Balan & Joseph 2021; Khaydar et al. 2021).

Evaluation of crop WF is needed to estimate agricultural water use efficiency, which plays a crucial role in food security and sustainable water conservation (Hai et al. 2020). The highest consumer of global water is agricultural activity and a quarter portion of global WF is for food trade (Hoekstra & Mekonnen 2012). Many studies have been conducted to understand the consumption of water with the help of WF of rice over various regions (Wu et al. 2021). Rice is a majorly produced cereal in the world and it also consumes global freshwater in a great quantity. So, there is a need to measure water consumption properly to preserve available water and provide the major staple food in a region. For achieving a great quantity of rice yield, precipitation and temperature play key roles, and these natural phenomena also affect the WF of rice (Saravanakumar et al. 2022). The crop WF depends upon regional differences along with local conditions, climate change, and human consumption (Dourte et al. 2014; Sun et al. 2016; Sidhu et al. 2021; Wang et al. 2023). The urbanized WF analysis helps the officials in the economic aspect of the urban regions (Vanham & Bidoglio 2014; Paterson et al. 2015). The forest areas also show significant variation in WF due to climatic conditions, tree management, and choices of methodological models (Launiainen et al. 2014; Raluy et al. 2022). There is a great need to conduct such a study of rice WF estimation in unexplored regions, such as Jharkhand, which has great potential in terms of minerals, is preserved by dense forests, and is a culturally rich state in India. This state of forest-loving people is majorly hilly with some plateau regions with less soil water conservation practices and rapid runoff.

Analysing the above flaws of the region and considering the future scope to enhance the socioeconomic condition of the state and gross domestic product of the nation, the present study aims to understand the impact of forest cover and human intervention on a major crop WF in the state of Jharkhand of India from 2000 to 2017, and the study has been conducted for rice as it is the major yielding crop of Jharkhand.

The region consists of major and minor river systems, namely, Koel, Damodar, Barakar, and their tributaries. Paddy (rice) is the most yielded cereal crop in the whole of Jharkhand (SAMETI Jharkhand 2021–2022). The cultivation period of this crop in this region is in the Kharif season, from June to November/December (PMFBY 2018). The average annual actual rainfall for Ranchi is 1,131.60 mm, in Dhanbad it is 1,328.10 mm, in Hazaribagh, 1,194.70 mm, and in Palamu, 945.1 mm (India-WRIS, 2019; https://indiawris.gov.in/wris/#/rainfall).

The input data, provided in Table 1, are used to simulate CWRs and irrigation scheduling of rice through the Cropwat 8.0 model, a computer programme that is a Windows-based decision support system used to estimate ET over the study area by using the Penman–Monteith equation, and this obtained ET helps to calculate CWRs and irrigation scheduling of a crop depending upon the soil, crop, and meteorological data (Allen et al. 1998).

This study shows an increasing trend of WFs (green, blue, consumptive, and white) with forest cover and a decreasing trend of WFs with effective rainfall. The results express the highest values of every type of WF in Palamu, followed by Hazaribagh; these are the two forest-covered regions. The two urban districts show comparatively lower WFs during the study period than these two forest cover districts. Generally forests are the receivers of good rainfall, but still Palamu had the maximum average WF_blue of 972 m³/ton, and the urban district Ranchi experienced the minimum average WF_blue of 167 m³/ton. WF_green depends on precipitation and WF_blue is based on surface or groundwater and irrigation. This means the CWR for rice cultivation is not fulfilled only by rainfall despite having great rainfall over the study region, especially the forest region. The contradictory results of this study show the necessity of understanding and considering all the influencing conditions in WF calculation (Li et al. 2022). The abrupt change of WFs with forest cover and P_e strengthens the concept of change in WF according to regional differences.

Furthermore, the three districts Ranchi, Dhanbad, and Hazaribagh are in the same agroclimatic region ‘Central and North-Eastern plateau region’ except Palamu, which is in the western plateau region. The results show the major changes in WFs according to the agroclimatic region, as Palamu experienced the highest variation in WF during the period. Hazaribagh also received a high variation of WFs apart from the two urban districts, Dhanbad and Ranchi, situated under the same agroclimatic region. It justifies the study regarding the change in crop WF along with crop water productivity in the same climatic zones (Brauman et al. 2013).

This study showed some contradictory results between many climatic factors and WF. In the years between 2000 and 2017, the average range of temperature in the Kharif season was 20–35 °C over the study period, whereas it became 23–45 °C in 2022, which has a critical role in climatic factors, especially ET and it variates’ yield of the crop along with WF consecutively. There were six heatwave conditions in India between 2000 and 2010 from March to May, except in 2003 when it lasted 26 days from 18 May to 18 June (Indian Meteorological Department Report, 2023). This study was done from June to November/December (PMFBY 2018) throughout the study period avoiding heatwave conditions. Ranchi might experience heatwaves due to its presence near the Tropic of Cancer, but there was no valid relationship between heatwave and WF. A detailed study about this aspect in the recent scenario is needed owing to the increase of heatwave incidents due to climate change.

Another influencing factor for WF, especially for crop yield, is the soil profile of the region. The growth of the crop, water use, and crop yield depend on the soil acidity and micronutrients present in the soil. The majorly distributed soil in the study region is strongly acidic; Dhanbad (41.2% of total gross area [TGA]), Ranchi (96.4% of TGA), Hazaribagh (88.2% of TGA), and Palamu (47.8% of TGA). According to the Food and Agriculture Organization of the United Nations (FAO)'s soil map report, the soil of Dhanbad is composed of chromic cambisols, lithosols, ferric luvisols, and eutric nitosols; Ranchi has the composition of lithosols, ferric luvisols, distric nitosols, and eutric nitosols; Hazaribagh has chromic cambisols, lithosols, ferric luvisols, distric nitosols, and eutric nitosols; and Palamu has chromic cambisols, eutric cambisols, lithosols, calcaric fluvisols, ferric luvisols, and orthic luvisols (https://www.sameti.org/Soil_Inventory/); almost all soil types have accumulation of clay except lithosols. The simulation for rice in the Cropwat 8.0 model was done with clay soil, as rice is grown in clay due to its high water retention capacity. The micronutrients that play a great role in crop production such as organic carbon (C), nitrogen, phosphorus, potassium, boron (B), sulphur (S), iron (Fe), and manganese (Mn) are accumulated mostly in these four districts according to district soil report, as Dhanbad (high C-83.4% of TGA, medium N-74.2%, low P-68.8%, low K-48.4%, sufficient S, Fe, Mn, B), Ranchi (high C-43.8%, medium N-67.2%, medium P-56.2%, medium K-57.1%, low S-36.7%, sufficient Fe, Mn, B), Hazaribagh (high C-64.5%, medium N-69.4%, low P-57.8%, medium K-48.2%, low S-33.8%, sufficient Fe, Mn, B), and Palamu (high C-42.6%, medium N-68.3%, low P-46.8%, medium K-55.9%, high S-48.9%, sufficient Fe, Mn, deficient in B-67.7%). Jharkhand has majorly acidic soil, which can be treated using agro-forestry such as a rice–pea cropped system, mild alkalization using carbonates, and oxide components of Ca and Mg (Zade et al. 2021). The infiltration rate of the soil depends upon the texture of the soil, elevation profile, fewer voids of the soil, and so on. The forest-covered areas of Palamu have dominantly red sandy soils, and the rest of the region is covered with tertiary laterite and alluvium soil, whereas Hazaribagh consists of steep sloped hill and forest soils, red yellow and light grey soil, and Pale yellow, yellow, and pinkish deep soil consisting highly of micaceous schists (Central Ground Water Board (CGWB) district wise report, 2013). Palamu district is elevated in the range of 360–1,110 msl with a highly rugged hilly landscape, whereas Hazaribagh has an average 600 m of elevation, consisting of three parts, central plateau, lower plateau, and Damodar valley region. The urban district Ranchi has hillocks and forests with an altitude in the range of 500–700 msl, the district largely consists of alluvial soil, red and yellow soil, lateritic soil, and stony and gravely soil. The urbanized Dhanbad has clayey soil, loamy soil, sandy soils, and stony and gravelly soil with much lower altitude, the lowest elevation of this district is in Chirkunda at 133 msl and the highest is in Parasnath hills, at 745 msl. The geomorphological features and soil profile of the study region show the variation of WFs majorly depends on these features despite having great forest cover or urbanization. This research work recommends that a more detailed study should be considered on any region considering its physiographic features and soil profile. The results in this study show that despite having good forest cover, good rainfall, and alluvium soil, Palamu experiences highest WFs due to its rugged hilly landscape, which helps to get great runoff and low soil moisture. Due to the geomorphological advantage, the highly urban district of Dhanbad experienced the lowest WF_consumptive and WF_{white .} This study helps other researchers implement the findings of this study in other regions with similar local conditions anywhere in the world.

The two developed areas, Ranchi and Dhanbad, showed a decrease in rice's consumptive crop WF in 2017 about 2000 at 39.92 and 48.29%, respectively. The two forest-covered districts Palamu and Hazaribagh showed comparatively lower decreases in the same context with 24.12 and 23.42%, respectively. As the two majorly urbanized districts Ranchi and Dhanbad experienced the lowest crop WF of rice, especially WF_blue, the study suggests cultivating it in these districts in the Kharif season. The WF_green of rice in Ranchi over this period was high, WF_blue was lowest, the white WF was moderate to low, and rainfall was also good, so the study recommends cultivating rice here by eliminating irrigation requirement and its loss through rainfed agriculture. The other three districts are also recommended to use less water from nearby lakes, river systems, canals, and groundwater to lessen the quantity of water for irrigation and maintain the available water, as the groundwater recharge in Jharkhand is very low and the storage is declining (Ashwini et al. 2023). The results showed a decrease in all types of WF in all four districts, which is very beneficial to storing available water, reducing over-consumption, and achieving sustainable water management.

There were some assumptions and uncertainties in estimating crop WF in this study region due to the unavailability of data considering the local atmosphere and situation. This study leads future scope on this emerging topic with a proper dataset (climatic factors, crop yield, soil data, land-use pattern) considering a broader scale with regional, national, and global importance.

This study helps environmentalists, policy makers, and government officials understand the implementation of a proper plan or scheme to cultivate a crop in a forest area or industrialized area considering local conditions by achieving sustainable water management and food security at the regional and global levels.

The present study suggests the cultivation of a rice crop in the kharif season in Ranchi district due to a high value for WF_green (which shows there was a sufficient amount of rainfall in the kharif season for paddy production) and a low value for WF_blue (and therefore less requirement for irrigation water). All four districts are recommended to use agroforestry and mild alkalization to improve soil health and reduce soil acidity. The study shows that climatic factors such as temperature, rainfall, wind speed, ENSO effect, and crop yield are the influencing factors of the significant results of this study. This study showed the variation of WFs majorly influenced by different agroclimatic regions, geomorphological features, and soil profiles despite the change in forest cover and urbanization. The results show an increasing trend of WF_green, WF_blue, and WF_consumptive regarding forest coverage. The maximum declination of WF_consumptive from 2000 to 2017 occurred in Dhanbad with 48.29%, followed by Ranchi with 39.92 and 24.12% in Palamu and 23.42% in Hazaribagh. The white WF also decreased in 2017 with respect to 2000; with a maximum decrease in Dhanbad (33.91%), followed by Ranchi (22.92%), Palamu (21.22%), and Hazaribagh (8.43%). The results of this study showed a decrease in WF in all four districts, which is very beneficial to store available water and reduce over-consumption. The study suggests making a proper database system with global and regional datasets to reduce irrigation loss, and calculating regional WF with high precision considering all local influencing conditions. There are many influencing factors discussed in this study, but the more intense factor is the yield of the crop; many contradictory results are achieved in this study. This study suggests increasing the crop yield to lessen the quantity of WF and attain sustainable water management. This study would be significant to the environmentalists, policymakers, and government officials for executing a proper plan or scheme to cultivate a crop in a forest area or industrialized area considering local conditions to achieve sustainable water management and food security at the regional level along with global aspects.

The author(s) did not receive any type of financial support for this research.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict of interest.