Soil-Water, Agriculture, and Climate Change

Melt water from the glaciers and snow over the Himalayan mountainous range plays a vital role in the river hydrology where more than 200 million of people consume this water for domestic and agricultural purposes. The hydrology of this high-altitude glaciated range is quite complex and from a water resources management perspective a comprehensive hydrometeorological modeling system is mandatory to project the hydrological changes in response to climate change. Climate change has an impact on the basic components that control the formation and melting of glaciers and snow cover, consequently impacting the livelihood, hydropower generation, and agricultural practices. Several hydrological models from lumped to fully distributed, have been developed to understand the complex hydrological behavior of the Himalayan region, however, the impacts of climate change on the hydrology of the Himalayan region are still ambiguous. Some researchers agree with glaciers expansion while others showed a glacier retreat. Such contradictory views in the climate and glaciers threaten future water management and sustainability of water resources. The choice of hydrological models is purely dependent on the availability of the datasets and the goals to be achieved. Lack of in-situ meteorological datasets is one of the biggest challenges that researchers must face while estimating the hydrological variables. Satellite-based meteorological products, to some extent, provide a reasonable replacement of in-situ data but cascade the uncertainties in the final outputs. This chapter aims to demonstrate the complexity and understanding of the hydrology of Himalayan regions, and the challenges to developing the hydrological models in the Himalayan region.

Hillslope-stream-groundwater interactions has been identified as one of the major unsolved scientific problems in hydrology. Research studies to understand hillslope response processes involves time, effort, and resources. Therefore, hydrological models prefer to eliminate the minor details from hillslope responses in aggregation approach to watershed scale. Such approaches are unsuitable for regions where hillslope processes are dominant. Bur there are not many hydrological models to address hillslope concepts. This paper presents a process-based semi-distributed rainfall-runoff model (Hilly Watershed Hydrologic Model, HWHM) for hilly watersheds to address the aggregation of hillslope response to watershed scale for a Himalayan River Basin. The prime objective of HWHM is to support the water management in this region by modelling the runoff response and water storage. HWHM operates by dividing the river basin into small grids (≈1km²), each grid representing a micro-watershed and assumed to be made up of several hillslopes. The emphasis of HWHM is to mimic the runoff generation in hillslopes in space and time which includes runoff from both surface and subsurface. The surface runoff partition and water balance are conceptualized by the influence of three-layer soil matrix (A-, B-, and C- layer) and vertical macropore distribution in subsurface system. The A-layer depth (root zone) and macropore distribution is characterized by MODIS land use/land cover product, deduced from several sample dye-tracer experiments. Model parameterization includes the response controlling variables for surface (threshold for surface runoff generation (T_sur), and gradient of runoff generation rate (S)), and sub-surface (bedrock topography factor (a), saturated hydraulic conductivity (K_sat), and aquifer thickness (D_p)). The variability of T_sur in space is determined in the range of (T_sur ± 25%) defined by vegetation fraction, whereas variability in time depends upon the antecedent moisture condition in A-layer. S is standardized between a lower and higher limit as per the antecedent moisture condition in top soil layer. The combined volumetric variability in A-layer depth and macropore distribution influence variable surface runoff generation. The subsurface is assumed to contain aquifer above bedrock with a maximum limit of aquifer thickness D_p and its ability to contribute as baseflow defined by K_sat. However, due to assumed dominance of preferential pathways, a high order factor of 10^a is multiplied with K_sat, where a is a standardized value between a range according to antecedent moisture condition of B-layer between its field capacity and wilting point. The standardization schemes for S and a helps to address the variation of runoff response in wet and dry seasons in surface and sub-surface respectively. With the help of satellite-based hydrometeorological inputs (CHIRPS precipitation, and FLDAS evapotranspiration) and modelled land surface variables (field capacity, wilting point, and K_sat from SOILGRIDS), HWHM is used to parameterize the spatio-temporal response of micro-watersheds, by calibration with the observed daily flow volume at the outlet. The controlling variables were simulated in combinations within stipulated ranges to find the best values (T_sur = 1 ± 0.25 cm; S = 0.7–0.1; K_sat ≈ 10⁵–10¹⁰ times original K_sat; and D_p ≤ 1 m) in calibration. Simulations from 2001–2007 produced a decent result of (RMSE = 60 MCM and R² = 0.72). The value of resulting K_sat was found to be of several times higher order than original K_sat (10⁵–10¹⁰ times). This confirmed major domination of preferential pathways in runoff generation process at watershed scale. HWHM could be used for studies to further understand the influence of hillslope processes on water budget components at large scale watersheds with macropore dominated hilly regions.

A coupled Artificial Neural Network (ANN) and Soil Conservation Service (SCS) based method was developed for rainfall-runoff simulation in Pagladiya River Basin. Pagladiya River, a major northern sub-catchment of the Brahmaputra River Basin, significantly contributes to the mainstream Brahmaputra River. Because of this, the watershed is prone to both flood and erosion. In this study, runoff at different sub-catchments of the Pagladiya River Basin was simulated using the SCS-CN based approach. The Land Use Land Classification (LULC) was classified in ArcGIS using a supervised classification technique and a maximum likelihood classifier algorithm to estimate the curve number. Taking the runoffs at different sub-catchments as the inputs, an ANN model was developed in MATLAB for runoff simulation at the main outlet of Pagladiya. The ANN model's time series analysis employed the nonlinear autoregressive with exogenous inputs (NARX) method. The model efficiency was satisfactory with a coefficient of correlation (R), 0.91 for training, 0.88 validation, and 0.87 testings period. The overall value of R (0.90) indicates the utility of this ANN-SCS based coupled model for rainfall-runoff simulation.

Water erosion poses serious problems by inducing the degradation and mobilization of soils and the silting up of dam reservoirs. The mapping of the vulnerability of land to erosion has been the subject of several studies in northern Morocco. This work is based on the RUSLE model (Revised Universal Soil Loss Equation) coupled with a Geographic Information System (GIS) to quantify soil loss rate. The study concerns the Mohamed Ben Abdelkrim El Khattabi (MBAK) watershed. It covers an area of 779 km² with land with sparse vegetation cover, friable substrates, and very rugged topography. The integration of the five factors of erosion in a GIS environment shows the susceptibility of this basin to the risk of water erosion. The average annual rate of soil loss is 6.44 t/ha/year. These results could assist decision-makers and planners in any decision to preserve and restore heavily eroded areas in the Mohamed Ben Abdelkrim El Khattabi Dam watershed.

Rivers are important for domestic, industrial, agricultural, and geopolitical purposes. Within the tropics, rivers are fed by rainfall and underground recharge. Understanding the contribution of rainfall to the dynamics of river is necessary for several reasons. In this study, the best fit marginal probability distribution function for rainfall and river discharge from among Gamma, Beta, Gaussian, Student T, and Uniform were considered. Furthermore, the dependence between rainfall and river discharge was investigated using three copula functions: Gumbel, Clayton and Frank. Results obtained suggests that the Student T’s distribution was best suited for rainfall and river discharge at Lokoja. It was also found that using the Akaike Information Criteria, that the Frank copula provides the best model for dependence between rainfall and river discharge. These results are important for an effective integrated water resources planning and management.

Drought is an inevitable consequence of climate change. Therefore, newer crop varieties are required which are resilient to drought stress. Though there are extensive breeding programs for numerous crops, traditional breeding process is slow. Phenotyping crops for physiological and morphological traits could be used as proxies for drought tolerance traits. However, extensive in-situ field data collection is constrained by time and resources. Remote data collection and machine learning techniques for analysis offer a high-throughput phenotyping (HTP) alternative to manual measurements that could help breeding for stress tolerance. In this chapter we would discuss recent advances and future of HTP techniques that could help in faster selection of desired genotypes. These techniques could be further extended to aid in variable rate input application such as irrigation and be a step towards precision agriculture. In this chapter we advocate for the use of newer technologies such as remote sensing, machine learning, and computer vision in plant breeding and agronomic decision making.

Water is considered the most critical resource for sustainable agricultural development worldwide. Irrigated areas will increase in forthcoming years, while fresh water supplies will be diverted from agriculture to meet the increasing demand for domestic use and industry. Furthermore, the efficiency of irrigation is very low, since less than two third of the applied water is actually used by the crops. The sustainable use of irrigation water is a priority for agriculture in arid areas. So, under scarcity conditions and climate change, considerable effort has been devoted over time to introducing policies aiming to increase water efficiency based on the assertion that more can be achieved with less water through better management. Better management usually refers to the improvement of water allocation and/or irrigation water efficiency. Looking at current and future trends of agricultural production worldwide, it is clear that irrigation is essential to meet current food demand and that irrigation will have to increase in the future. The use of large amounts of water by crops is dictated by the evaporative demand of the environment and is tightly associated with biomass production and yield. Increases in potential biomass production per unit of water transpired during the next 10–20 years will be small despite promises from biotechnology. Breeding for yield potential will also provide a small contribution in the near future, so the real opportunity to increase the productivity of water resides in closing the current large gap between actual and potential yields. To increase the effectiveness of irrigation in a sustained fashion, without detrimental impacts on the environment, a number of measures need to be considered, particularly: improving water management at farm and district levels and reforming institutions to allow for user participation.

Nearly 70% of the global renewable water resources are annually used for irrigation. It is projected that the demand for irrigation will continuously increase over time due to increasing climatic variability, reduction in water quantity and quality, increasing competition for freshwater resources from other sectors of the economy, and changes in water policy. Water use in agriculture is interconnected with soil, weather, land use pattern and allocation of available water resources. For sustainable agriculture, efficient water use and productivity with implication on socioeconomic aspects needs to be discussed thoroughly. This chapter discusses the concepts and rationale of deficit irrigation (DI), different popular DI approaches in the world, and discusses the challenges and limitations of each one. Furthermore, the chapter will discuss different practical tools and resources required for the successful implementation of DI and discuss the physiological and biochemical basis of DI.

The increasing technological and scientific development to cater the anthropogenic needs has caused a substantial increase of Emerging Contaminants (ECs) in the environment, posing threats to the ecosystem due to their hazardous nature. A successful treatment system for the removal is still not developed because of diversity in the physico-chemical nature of ECs and cost constraints. The mathematical model serves as a good alternative in predicting the transport and fate of the contaminants in the environment. The output of the models may serve as a risk assessment tool and shall be utilized for policy making and control of emerging contaminants in the environment. The paper discusses the processes of transport, fate, and distribution of the ECs in the environment. Also, several models currently in practice have been discussed highlighting their limitations to give clarity of the model to be used for a specific category of contaminant. The paper aims to ease the selection of models for a specific category of EC, scenario, and requirement of the user. The identified limitations will serve a medium for future researchers to easily select a suitable model by applying suitable modifications and performing risk assessment studies.

Auto-mechanic workshops in developing countries such as Nigeria are a major source of potentially toxic substances which can leach into the water table and contaminate groundwater. Several physical and chemical methods have been employed to remediate pollutants in oil-contaminated soils, some of these methods are simply a transfer of contaminants from one place to another, which may also require additional treatments. A combination of treatments consisting of the application of NPK (nitrogen, phosphorous, and potassium) fertilizer, sawdust, horse manure and exposure to oxygen was evaluated in situ during 70 days for the remediation of cadmium, chromium, lead and total petroleum hydrocarbon in used engine oil-contaminated soils. The soils received 447.6 kg of horse manure, 48 kg of sawdust and 4.2 kg of NPK fertilizer per 2 m² of surface area. The total heterotrophic bacteria count at the start-up of the experiment was 0.018 × 10⁶ CFU/g in the contaminated soil and thus increased to 80.5 × 10⁶ CFU/g during the 70 days treatment. In addition, the combined treatment showed 87% total petroleum hydrocarbon degradation, 71% Cd and 62% Pb reduction. Hence, the results of this study showed that nutrient enhanced bioremediation can achieve the degradation of petroleum hydrocarbon and heavy metals in oil-contaminated soils under the prevailing tropical conditions of Nigeria.

Petroleum hydrocarbons are a severe environmental problem globally due to their persistence and toxicity to soil and human health. This research aims to analyze the impact of diesel and its blends on root zone microbial communities using a small-scale Vigna radiata L. growth assessment experiment. Five plate setups were prepared with organic soils and spilled with diesel, neat biodiesel, two blends of diesel (B5 and B20), and a control. Straight-chain saturated hydrocarbons, n-alkanes persisting in the blended diesel contaminated soil samples were analyzed using gas chromatography-mass spectrometry (GC–MS). A 16S rRNA gene amplicon sequencing was performed to identify the microbial communities and their abundance. Results showed that concentrations of C₈, C₁₀, C_30, and C₃₂ hydrocarbons were higher in diesel contaminated tray than biodiesel and its blend spilled trays. Proteobacteria benefited bacteria due to the addition of carbon sources and thus dominated in contaminated soils. Acidobacteria was prevalent in soil samples prior to contamination, decreasing significantly after contamination. No significant change was observed for Chlamydiae, Planctomycetes, Verrucomicrobia, and Dependentiae in all soil samples, in the relative abundance, before and after contamination. Plant growth index was 1.22% in case of neat biofuel containing try, with a more significant growth percentage than control tray, i.e., 1%. This indicates the positive impact of neat biofuel as a substrate or plant stimulator. We conclude that neat biofuel application in soil improves proteobacterial communities to take care of hydrocarbon-polluted soils.

Non-contaminated water or sustaining each sector of fresh water is essential for the survival of all living beings in current and upcoming generations. However, the degradation of freshwater qualities is a significant concern in developing countries (India). The need for clean water is increasing sharply to meet rising human demands constantly. River water is rich in ecological community and plays a vital role in surviving all living beings. Still, presently it is the most threatened ecosystem due to various human-made activities. Hence, meticulous monitoring of river water qualities (RWQs), assessment of numerous variables (physicochemical, bacteriological, pathogenic), and heavy metals content are imperative indicators for finding out the actual health of river water ecosystems. Upsetting the concentration of multiple RWQ variables and metals content leads to deteriorating the RWQ and ultimately affects human well-being. Simultaneously, applying a multivariate statistical approach and computing water quality index (WQI) and comprehensive pollution index (CPI) is also a vital role in understanding the actual status of RWQ. This comprehensive study is focused on various processes, causes, and sources of river water pollution in India. It provides extensive information and better understanding to enable policymakers, preservationists, and environmentalists to develop strategies to mitigate river pollution and strengthen aquatic ecosystems rejuvenation.

As water plays a vital role in the life support system of the planet, the issue of water scarcity creates an insecurity which need to be overcome for the enhancement of socio-economic balance. Such condition affects more than billion people globally, and most of them live in the semi-arid regions where the available water resources are under threat. As per Food and Agriculture Organization (FAO), 12.2% of total global land is semi-arid zone. Based on the projected climate change, millions more people will be living under such conditions in the coming decades. However, various attention has been given to the eradication of water scarcity problems over this region, only few changes are remarkable in terms of field application. The water governance policies made by the local or national authorities must keep an eye to distinguish properly between various extreme events such as interannual droughts, continuous dry spells and long-term climate aridification. In general, few common contrasting situations are observed to cope with different water-scarcity dilemmas. The most vulnerable countries or region should adapt their water policy in order to sharpen the water shortage condition. The developing countries should take the decisions wisely to pursue the win–win approaches by selecting the most advantageous measures. In this chapter, various adaptive measures taken in the recent past in arid and semi-arid regions of Australia, Brazil, India and other south Asian countries are discussed. The basic fundamental approach for adaptive management for climate change will be providing social learning to the stakeholders to recognize their inter dependence as well as differences. The rethinking will be always required between local governance and stakeholders in order to manage the water for the most common uses such as irrigation, crop processing, domestic, industrial and other environmental uses. However, the large-scale adaption to global change is only possible by integrated river basin management (IRBM) plan by defining the medium- and long-term goals. Various adapting methods for water stress condition are discussed and also domain specific advance technology can play a vital role in such conditions. The aim of this chapter is to discuss various measures taken by the society or stakeholders to adapt the changing trend of water availability due climate extremes in the semi-arid zones of the world.

Latin America is currently home to approximately 700 million people, a population that is expected to grow even more. In addition, we can see the growth of cities, industries and agriculture, facts that have raised concerns about water security, an agenda that is highlighted in all countries, considering the available quantity and quality. Despite concentrating a significant portion of the world's freshwater reserve, due to the expansion of agriculture and especially the pollution of many rivers and lakes, today practically all countries face some kind of difficulty regarding the supply of drinking water or sanitation to the population. In addition, some countries have become a world reference in the extraction of ores such as gold, copper and iron. Currently, mining and deforestation for illegal logging and possible expansion of agricultural areas have contributed to the degradation of surface water and aquifers. In this worrying scenario, it is also worth mentioning the lack of enforcement of environmental legislation and the existence of few agreements and policies between nations aimed at strengthening integrated river basin management plans. Actually, studies evaluating the issue of water security in Latin America in an integrated way, with basin-scale planning, with the interaction of different nations, in addition to the exchange of experiences and establishment of cooperation agreements are topic that still lacks clarification and intense scientific debate, comparing realities, identifying the biggest challenges and proposing solutions. Thus, the present text seeks to contribute to the analyze of water security in Latin America in a comprehensive way, basing the main current aspects most relevant in relation to the conservation and preservation of this important natural resource that is the water. For this, the main challenges to be faced in this century in Latin America were listed and discussed, which are the impacts of megacities, climate change, lack of policies and implementation of laws, expansion of agriculture and deforestation, increased industrialization, expansion of activities mining, sewage treatment and the lack of transboundary watershed management programs.

Since the end of the last century, climate change has generated qualified pluviometric events favoring the triggering of flash floods characterized by very high speeds and fairly short rise times. These floods caused extensive damage and paralyzed all activities in the flooded regions, as was the case during the last event in November 2014 which left behind a significant body of human and material damage in the different regions of Morocco. The Wadi Tamlest watershed located north of the Agadir city is a good example of areas affected by floods. The FHI (Flood Hazard Index) method was applied to study these extreme phenomena and to determine their lateral extensions using six factors influencing the floods (accumulation of flow, distance from the main wadis, drainage density, land use, slope, and permeability). This method made it possible to map with great precision the areas vulnerable to flooding throughout the Wadi Tamlest watershed. Finally, the application of the FHI method is more advantageous in basins not equipped with hydrometric stations but seems less precise in terms of defining the water heights downstream of the basin.

The Niger basin plays a critical role in the achievement of Nigeria’s agricultural targets through irrigation, dry season farming, and fish habitats. The seasonality of the river discharge along the lower Niger River creates the possibility of two extremes—drought and flood. The risk of flood has not been adequately monitored on the continent. In this study, the possibility of remotely sensing flood incidences along the lower Niger River was considered. Sentinel-1 imagery was incorporated within the Google Earth Engine infrastructure to map the region before and after the flood event of 20th September 2020 using a change detection approach. This is done by dividing the after-flood mosaic by the before-flood mosaic, resulting in a raster layer showing the degree of change per pixel. The impact of the flood event on the human and socio-economic livelihoods within the region was also evaluated. The flood event was found to affect about 108,587 people, 9,123 ha of cropland, and 2,056 ha of the urban area. The possibility of assessing flood extent, risk, and impact using remotely sensed data will help in humanitarian services, disaster planning and mitigation, and environmental evaluation for policy formulation.

Since the end of the last century, climate change has generated extreme pluviometric events favoring the triggering of flash floods, characterized by very high velocity and short rise times. These floods cause a lot of damage and thus, modified the activities in the flooded regions. Watershed of the Taguenit Wadi in the Western Anti-Atlas is a better example to study the effects of these extreme phenomena such as the last event in November 2014. The latter have indeed caused a lot of human and material damage, as well as the destruction of infrastructure and loss of soil. In this paper, a Flood Hazard Index (FHI) method was applied to study these extreme phenomena and determine their lateral extensions. Moreover, this method made it possible to map with great precision the areas vulnerable to flooding throughout the Taguenit Wadi basin. The FHI method is more advantageous in the basins, which are poorly gauged but seem to be less precise in terms of defining the water levels downstream of the basin.